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1. Toward enhancing the autonomy of a telepresence mobile robot for remote home care assistance

Author

François Ferland, François Michaud, Dominic Létourneau, Sebastien Laniel, Mathieu Labbé, and Francois Grondin

Subjects
mobile robot assistant, Technology, 0209 industrial biotechnology, voice tracking, Computer science, Cognitive Neuroscience, media_common.quotation_subject, 05 social sciences, Mobile robot, 02 engineering and technology, Human-Computer Interaction, Behavioral Neuroscience, assisted telepresence, 020901 industrial engineering & automation, Developmental Neuroscience, robot control architecture, evaluation in home settings, Artificial Intelligence, Human–computer interaction, 0501 psychology and cognitive sciences, autonomous navigation, 050107 human factors, Autonomy, media_common
Abstract

In health care, a telepresence robot could be used to have a clinician or a caregiver assist seniors in their homes, without having to travel to these locations. However, the usability of these platforms for such applications requires that they can navigate and interact with a certain level of autonomy. For instance, robots should be able to go to their charging station in case of low energy level or telecommunication failure. The remote operator could be assisted by the robot’s capabilities to navigate safely at home and to follow and track people with whom to interact. This requires the integration of autonomous decision-making capabilities on a platform equipped with appropriate sensing and action modalities, which are validated out in the laboratory and in real homes. To document and study these translational issues, this article presents such integration on a Beam telepresence platform using three open-source libraries for integrated robot control architecture, autonomous navigation and sound processing, developed with real-time, limited processing and robustness requirements, so that they can work in real-life settings. Validation of the resulting platform, named SAM, is presented based on the trials carried out in 10 homes. Observations made provide guidance on what to improve and will help identify interaction scenarios for the upcoming usability studies with seniors, clinicians and caregivers.

Published
2021
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2. Lightweight and optimized sound source localization and tracking methods for open and closed microphone array configurations

Author

Francois Grondin and François Michaud

Subjects
FOS: Computer and information sciences, Sound (cs.SD), 0209 industrial biotechnology, Microphone array, Computer science, Microphone, General Mathematics, 02 engineering and technology, Computer Science - Sound, 03 medical and health sciences, 020901 industrial engineering & automation, 0302 clinical medicine, Audio and Speech Processing (eess.AS), FOS: Electrical engineering, electronic engineering, information engineering, Computer vision, Signal processing, business.industry, Acoustic source localization, Filter (signal processing), Computer Science Applications, Noise, Control and Systems Engineering, 030220 oncology & carcinogenesis, Artificial intelligence, business, Software, Electrical Engineering and Systems Science - Audio and Speech Processing
Abstract

Human–robot interaction in natural settings requires filtering out the different sources of sounds from the environment. Such ability usually involves the use of microphone arrays to localize, track and separate sound sources online. Multi-microphone signal processing techniques can improve robustness to noise but the processing cost increases with the number of microphones used, limiting response time and widespread use on different types of mobile robots. Since sound source localization methods are the most expensive in terms of computing resources as they involve scanning a large 3D space, minimizing the amount of computations required would facilitate their implementation and use on robots. The robot’s shape also brings constraints on the microphone array geometry and configurations. In addition, sound source localization methods usually return noisy features that need to be smoothed and filtered by tracking the sound sources. This paper presents a novel sound source localization method, called SRP-PHAT-HSDA, that scans space with coarse and fine resolution grids to reduce the number of memory lookups. A microphone directivity model is used to reduce the number of directions to scan and ignore non significant pairs of microphones. A configuration method is also introduced to automatically set parameters that are normally empirically tuned according to the shape of the microphone array. For sound source tracking, this paper presents a modified 3D Kalman (M3K) method capable of simultaneously tracking in 3D the directions of sound sources. Using a 16-microphone array and low cost hardware, results show that SRP-PHAT-HSDA and M3K perform at least as well as other sound source localization and tracking methods while using up to 4 and 30 times less computing resources respectively.

Published
2019
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3. ECAPA-TDNN Embeddings for Speaker Diarization

Author

Brecht Desplanques, Mirco Ravanelli, Nauman Dawalatabad, Hwidong Na, Francois Grondin, and Jenthe Thienpondt

Subjects
Scheme (programming language), spectral clustering, Technology and Engineering, Time delay neural network, Computer science, Speech recognition, SIGNAL (programming language), Domain (software engineering), Speaker diarisation, Discriminative model, Robustness (computer science), Audio and Speech Processing (eess.AS), Component (UML), FOS: Electrical engineering, electronic engineering, information engineering, speaker embedding, speaker diarization, computer, data augmentation, computer.programming_language, Electrical Engineering and Systems Science - Audio and Speech Processing
Abstract

Learning robust speaker embeddings is a crucial step in speaker diarization. Deep neural networks can accurately capture speaker discriminative characteristics and popular deep embeddings such as x-vectors are nowadays a fundamental component of modern diarization systems. Recently, some improvements over the standard TDNN architecture used for x-vectors have been proposed. The ECAPA-TDNN model, for instance, has shown impressive performance in the speaker verification domain, thanks to a carefully designed neural model. In this work, we extend, for the first time, the use of the ECAPA-TDNN model to speaker diarization. Moreover, we improved its robustness with a powerful augmentation scheme that concatenates several contaminated versions of the same signal within the same training batch. The ECAPA-TDNN model turned out to provide robust speaker embeddings under both close-talking and distant-talking conditions. Our results on the popular AMI meeting corpus show that our system significantly outperforms recently proposed approaches.

Published
2021

4. Audio scene monitoring using redundant ad-hoc microphone array networks

Author

Chaitanya Patil, Peter Gerstoft, Francois Grondin, Michael J. Bianco, Yoav Freund, Yihan Hu, and Ardel Alegre

Subjects
FOS: Computer and information sciences, Computer Science - Machine Learning, Microphone array, Sound (cs.SD), Computer Networks and Communications, Microphone, Computer science, Computer Science - Sound, Machine Learning (cs.LG), Circular buffer, Audio and Speech Processing (eess.AS), FOS: Electrical engineering, electronic engineering, information engineering, Computer vision, Rectangle, Fusion center, Communications Technologies, business.industry, Direction of arrival, sound localization, Ad hoc circular microphone arrays, Computer Science Applications, smart homes, Hardware and Architecture, Signal Processing, Principal component analysis, Affine transformation, Artificial intelligence, business, Distributed Computing, Electrical Engineering and Systems Science - Audio and Speech Processing, Information Systems
Abstract

We present a system for localizing sound sources in a room with several ad-hoc microphone arrays. Each circular array performs direction of arrival (DOA) estimation independently using commercial software. The DOAs are fed to a fusion center, concatenated, and used to perform the localization based on two proposed methods, which require only few labeled source locations (anchor points) for training. The first proposed method is based on principal component analysis (PCA) of the observed DOA and does not require any knowledge of anchor points. The array cluster can then perform localization on a manifold defined by the PCA of concatenated DOAs over time. The second proposed method performs localization using an affine transformation between the DOA vectors and the room manifold. The PCA has fewer requirements on the training sequence, but is less robust to missing DOAs from one of the arrays. The methods are demonstrated with five IoT 8-microphone circular arrays, placed at unspecified fixed locations in an office. Both the PCA and the affine method can easily map out a rectangle based on a few anchor points with similar accuracy. The proposed methods provide a step towards monitoring activities in a smart home and require little installation effort as the array locations are not needed., Comment: IN press, IEEE Internet of Things Journal

Published
2021

5. Learning Filterbanks for End-to-End Acoustic Beamforming

Author

Samuele Cornell, Manuel Pariente, Francois Grondin, and Stefano Squartini

Subjects
Signal Processing (eess.SP), FOS: Computer and information sciences, Computer Science - Machine Learning, Sound (cs.SD), Audio and Speech Processing (eess.AS), FOS: Electrical engineering, electronic engineering, information engineering, Electrical Engineering and Systems Science - Signal Processing, Computer Science - Sound, Electrical Engineering and Systems Science - Audio and Speech Processing, Machine Learning (cs.LG)
Abstract

Recent work on monaural source separation has shown that performance can be increased by using fully learned filterbanks with short windows. On the other hand it is widely known that, for conventional beamforming techniques, performance increases with long analysis windows. This applies also to most hybrid neural beamforming methods which rely on a deep neural network (DNN) to estimate the spatial covariance matrices. In this work we try to bridge the gap between these two worlds and explore fully end-to-end hybrid neural beamforming in which, instead of using the Short-Time-Fourier Transform, also the analysis and synthesis filterbanks are learnt jointly with the DNN. In detail, we explore two different types of learned filterbanks: fully learned and analytic. We perform a detailed analysis using the recent Clarity Challenge data and show that by using learnt filterbanks it is possible to surpass oracle-mask based beamforming for short windows., Comment: accepted at ICASSP 2022

Published
2021
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6. Neural Network Based Lidar Gesture Recognition for Realtime Robot Teleoperation

Author

Jack Collier, Francois Grondin, and Simon Chamorro

Subjects
FOS: Computer and information sciences, Modality (human–computer interaction), Artificial neural network, business.industry, Computer science, Computer Vision and Pattern Recognition (cs.CV), Image and Video Processing (eess.IV), Computer Science - Computer Vision and Pattern Recognition, ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION, Electrical Engineering and Systems Science - Image and Video Processing, Convolutional neural network, Computer Science - Robotics, Gesture recognition, Robustness (computer science), FOS: Electrical engineering, electronic engineering, information engineering, Robot, Computer vision, Artificial intelligence, business, Pose, Robotics (cs.RO), Gesture
Abstract

We propose a novel low-complexity lidar gesture recognition system for mobile robot control robust to gesture variation. Our system uses a modular approach, consisting of a pose estimation module and a gesture classifier. Pose estimates are predicted from lidar scans using a Convolutional Neural Network trained using an existing stereo-based pose estimation system. Gesture classification is accomplished using a Long Short-Term Memory network and uses a sequence of estimated body poses as input to predict a gesture. Breaking down the pipeline into two modules reduces the dimensionality of the input, which could be lidar scans, stereo imagery, or any other modality from which body keypoints can be extracted, making our system lightweight and suitable for mobile robot control with limited computing power. The use of lidar contributes to the robustness of the system, allowing it to operate in most outdoor conditions, to be independent of lighting conditions, and for input to be detected 360 degrees around the robot. The lidar-based pose estimator and gesture classifier use data augmentation and automated labeling techniques, requiring a minimal amount of data collection and avoiding the need for manual labeling. We report experimental results for each module of our system and demonstrate its effectiveness by testing it in a real-world robot teleoperation setting.

Published
2021
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7. Coupled Electro-Thermal-Aging Battery Pack Modeling—Part 1: Cell Level

Author

Hadi Pasdarshahri, Émile Veilleux, William Mooney, Luc G. Fréchette, François Grondin, and David Rancourt

Subjects
Li-ion batteries, semi-empirical model, aging, capacity fade, Production of electric energy or power. Powerplants. Central stations, TK1001-1841, Industrial electrochemistry, TP250-261
Abstract

This paper presents a modeling approach to capture the coupled effects of electrical–thermal aging in Li-ion batteries at the cell level. The proposed semi-empirical method allows for a relatively high accuracy and low computational cost compared to expensive computer simulations. This is something current models often lack but is essential for system level simulations, relevant for electric vehicle manufacturers. The aging analysis includes both cycling and calendar effects across the lifetime of the cell and reversible and irreversible heat in a lumped-mass model to capture the temperature evolution of the cell in operation. The Thévenin equivalent circuit model with capacitance used to simulate the electrical behavior of the cell was experimentally validated, showing a high correlation with the proposed model during the charging and discharging phases. A maximum error of 3% on the voltage reading was identified during discharge with the complete model. This model was also designed to be used as a stepping stone for a comprehensive model at the module and vehicle levels that can later be used by designers.

Published
2024
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8. GEV Beamforming Supported by DOA-Based Masks Generated on Pairs of Microphones

Author

François Michaud, Jean-Samuel Lauzon, Francois Grondin, and Jonathan Vincent

Subjects
Beamforming, Noise, Microphone array, Artificial neural network, Audio and Speech Processing (eess.AS), Computer science, Acoustics, FOS: Electrical engineering, electronic engineering, information engineering, Direction of arrival, Speech processing, Cocktail party effect, Signal, Electrical Engineering and Systems Science - Audio and Speech Processing
Abstract

Distant speech processing is a challenging task, especially when dealing with the cocktail party effect. Sound source separation is thus often required as a preprocessing step prior to speech recognition to improve the signal to distortion ratio (SDR). Recently, a combination of beamforming and speech separation networks have been proposed to improve the target source quality in the direction of arrival of interest. However, with this type of approach, the neural network needs to be trained in advance for a specific microphone array geometry, which limits versatility when adding/removing microphones, or changing the shape of the array. The solution presented in this paper is to train a neural network on pairs of microphones with different spacing and acoustic environmental conditions, and then use this network to estimate a time-frequency mask from all the pairs of microphones forming the array with an arbitrary shape. Using this mask, the target and noise covariance matrices can be estimated, and then used to perform generalized eigenvalue (GEV) beamforming. Results show that the proposed approach improves the SDR from 4.78 dB to 7.69 dB on average, for various microphone array geometries that correspond to commercially available hardware.

Published
2020
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9. Dynamic Object Tracking and Masking for Visual SLAM

Author

Mathieu Labbé, Jonathan Vincent, Francois Grondin, Jean-Samuel Lauzon, Pier-Marc Comtois-Rivet, and François Michaud

Subjects
FOS: Computer and information sciences, Masking (art), 0209 industrial biotechnology, Computer science, Computer Vision and Pattern Recognition (cs.CV), Computer Science - Computer Vision and Pattern Recognition, 02 engineering and technology, Simultaneous localization and mapping, computer.software_genre, 020901 industrial engineering & automation, FOS: Electrical engineering, electronic engineering, information engineering, 0202 electrical engineering, electronic engineering, information engineering, Computer vision, business.industry, Image and Video Processing (eess.IV), Location awareness, Kalman filter, Electrical Engineering and Systems Science - Image and Video Processing, Pipeline (software), Visualization, Video tracking, Robot, 020201 artificial intelligence & image processing, Artificial intelligence, business, computer
Abstract

In dynamic environments, performance of visual SLAM techniques can be impaired by visual features taken from moving objects. One solution is to identify those objects so that their visual features can be removed for localization and mapping. This paper presents a simple and fast pipeline that uses deep neural networks, extended Kalman filters and visual SLAM to improve both localization and mapping in dynamic environments (around 14 fps on a GTX 1080). Results on the dynamic sequences from the TUM dataset using RTAB-Map as visual SLAM suggest that the approach achieves similar localization performance compared to other state-of-the-art methods, while also providing the position of the tracked dynamic objects, a 3D map free of those dynamic objects, better loop closure detection with the whole pipeline able to run on a robot moving at moderate speed.

Published
2020
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10. Audio-Visual Calibration with Polynomial Regression for 2-D Projection Using SVD-PHAT

Author

Hao Tang, James Glass, and Francois Grondin

Subjects
Signal Processing (eess.SP), FOS: Computer and information sciences, Sound (cs.SD), Microphone array, Computer science, Microphone, ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION, 02 engineering and technology, Computer Science - Sound, 030507 speech-language pathology & audiology, 03 medical and health sciences, Audio and Speech Processing (eess.AS), Distortion, Singular value decomposition, FOS: Electrical engineering, electronic engineering, information engineering, 0202 electrical engineering, electronic engineering, information engineering, Computer vision, Electrical Engineering and Systems Science - Signal Processing, Projection (set theory), Polynomial regression, business.industry, Acoustic source localization, Visual field, Computer Science::Sound, Computer Science::Computer Vision and Pattern Recognition, 020201 artificial intelligence & image processing, Artificial intelligence, 0305 other medical science, business, Electrical Engineering and Systems Science - Audio and Speech Processing
Abstract

This paper proposes a straightforward 2-D method to spatially calibrate the visual field of a camera with the auditory field of an array microphone by generating and overlaying an acoustic image over an optical image. Using a low-cost microphone array and an off-the-shelf camera, we show that polynomial regression can deal efficiently with non-linear camera distortion, and that a recently proposed sound source localization method for real-time processing, SVD-PHAT, can be adapted for this task.

Published
2020
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11. 3D Localization of a Sound Source Using Mobile Microphone Arrays Referenced by SLAM

Author

Samuel Faucher, Dominic Létourneau, François Michaud, François Ferland, Simon Michaud, Mathieu Labbé, Francois Grondin, and Jean-Samuel Lauzon

Subjects
FOS: Computer and information sciences, 0209 industrial biotechnology, Microphone array, geography, Sound (cs.SD), geography.geographical_feature_category, Microphone, Computer science, business.industry, 02 engineering and technology, Simultaneous localization and mapping, Computer Science - Sound, 030507 speech-language pathology & audiology, 03 medical and health sciences, 020901 industrial engineering & automation, Audio and Speech Processing (eess.AS), FOS: Electrical engineering, electronic engineering, information engineering, Computer vision, Artificial intelligence, 0305 other medical science, business, Sound (geography), Electrical Engineering and Systems Science - Audio and Speech Processing
Abstract

A microphone array can provide a mobile robot with the capability of localizing, tracking and separating distant sound sources in 2D, i.e., estimating their relative elevation and azimuth. To combine acoustic data with visual information in real world settings, spatial correlation must be established. The approach explored in this paper consists of having two robots, each equipped with a microphone array, localizing themselves in a shared reference map using SLAM. Based on their locations, data from the microphone arrays are used to triangulate in 3D the location of a sound source in relation to the same map. This strategy results in a novel cooperative sound mapping approach using mobile microphone arrays. Trials are conducted using two mobile robots localizing a static or a moving sound source to examine in which conditions this is possible. Results suggest that errors under 0.3 m are observed when the relative angle between the two robots are above 30 degrees for a static sound source, while errors under 0.3 m for angles between 40 degrees and 140 degrees are observed with a moving sound source.

Published
2020
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12. Fast and Robust 3-D Sound Source Localization with DSVD-PHAT

Author

James Glass and Francois Grondin

Subjects
FOS: Computer and information sciences, Sound (cs.SD), 0209 industrial biotechnology, Computer science, Planar array, 02 engineering and technology, Acoustic source localization, Computer Science - Sound, 020901 industrial engineering & automation, Audio and Speech Processing (eess.AS), Robustness (computer science), Singular value decomposition, FOS: Electrical engineering, electronic engineering, information engineering, 0202 electrical engineering, electronic engineering, information engineering, Robot, 020201 artificial intelligence & image processing, Generalized singular value decomposition, Algorithm, Electrical Engineering and Systems Science - Audio and Speech Processing
Abstract

This paper introduces a variant of the Singular Value Decomposition with Phase Transform (SVD-PHAT), named Difference SVD-PHAT (DSVD-PHAT), to achieve robust Sound Source Localization (SSL) in noisy conditions. Experiments are performed on a Baxter robot with a four-microphone planar array mounted on its head. Results show that this method offers similar robustness to noise as the state-of-the-art Multiple Signal Classification based on Generalized Singular Value Decomposition (GSVD-MUSIC) method, and considerably reduces the computational load by a factor of 250. This performance gain thus makes DSVD-PHAT appealing for real-time application on robots with limited on-board computing power.

Published
2019
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13. State-of-the-Art Speaker Recognition for Telephone and Video Speech: The JHU-MIT Submission for NIST SRE18

Author

David Snyder, Leibny Paola Garcia-Perera, Pedro A. Torres-Carrasquillo, Jonas Borgstrom, Sanjeev Khudanpur, Gregory Sell, Fred Richardson, Daniel Garcia-Romero, Nanxin Chen, Daniel Povey, Francois Grondin, Alan V. McCree, Najim Dehak, Réda Dehak, Jesús Villalba, and Suwon Shon

Subjects
Computer science, Speech recognition, NIST, State (computer science), Speaker recognition
Published
2019
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14. Multiple Sound Source Localization with SVD-PHAT

Author

James Glass and Francois Grondin

Subjects
Signal Processing (eess.SP), Mean squared error, Computer science, Phase (waves), Acoustic source localization, Space (mathematics), Linear subspace, Reduction (complexity), Audio and Speech Processing (eess.AS), Singular value decomposition, FOS: Electrical engineering, electronic engineering, information engineering, Electrical Engineering and Systems Science - Signal Processing, Projection (set theory), Algorithm, Electrical Engineering and Systems Science - Audio and Speech Processing
Abstract

This paper introduces a modification of phase transform on singular value decomposition (SVD-PHAT) to localize multiple sound sources. This work aims to improve localization accuracy and keeps the algorithm complexity low for real-time applications. This method relies on multiple scans of the search space, with projection of each low-dimensional observation onto orthogonal subspaces. We show that this method localizes multiple sound sources more accurately than discrete SRP-PHAT, with a reduction in the Root Mean Square Error up to 0.0395 radians.

Published
2019
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16. Sound Event Localization and Detection Using CRNN on Pairs of Microphones

Author

François Glass, Mark D. Plumbley, Iwona Sobieraj, Francois Grondin, Mandel, Michael, Salamon, Justin, and Ellis, Daniel P. W.

Subjects
FOS: Computer and information sciences, Microphone array, Sound (cs.SD), Computer science, 02 engineering and technology, Computer Science - Sound, 030507 speech-language pathology & audiology, 03 medical and health sciences, Audio and Speech Processing (eess.AS), 0202 electrical engineering, electronic engineering, information engineering, FOS: Electrical engineering, electronic engineering, information engineering, Sound (geography), Event (probability theory), geography, geography.geographical_feature_category, business.industry, Direction of arrival, 020206 networking & telecommunications, Pattern recognition, Multilateration, Sound event detection, Recurrent neural network, Baseline system, Artificial intelligence, 0305 other medical science, business, Electrical Engineering and Systems Science - Audio and Speech Processing
Abstract

This paper proposes sound event localization and detection methods from multichannel recording. The proposed system is based on two Convolutional Recurrent Neural Networks (CRNNs) to perform sound event detection (SED) and time difference of arrival (TDOA) estimation on each pair of microphones in a microphone array. In this paper, the system is evaluated with a four-microphone array, and thus combines the results from six pairs of microphones to provide a final classification and a 3-D direction of arrival (DOA) estimate. Results demonstrate that the proposed approach outperforms the DCASE 2019 baseline system.

Published
2019
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17. Contact-Free Respiration Rate Monitoring Using a Pan–Tilt Thermal Camera for Stationary Bike Telerehabilitation Sessions

Author

Simon Brière, François Ferland, Ronan Chauvin, François Michaud, Mathieu Hamel, Dominic Létourneau, Francois Grondin, and Michel Tousignant

Subjects
Engineering, Computer Networks and Communications, ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION, 02 engineering and technology, 01 natural sciences, Expired air, Stationary bike, Telerehabilitation, 0202 electrical engineering, electronic engineering, information engineering, book.short_story, Electrical and Electronic Engineering, book, Simulation, Contact free, Remote Consultation, business.industry, Track (disk drive), 010401 analytical chemistry, 0104 chemical sciences, Computer Science Applications, Control and Systems Engineering, Breathing, 020201 artificial intelligence & image processing, business, Tilt (camera), Information Systems
Abstract

One typical remote consultation envisioned for in-home telerehabilitation involves having the patient exercise on a stationary bike. Making sure that the patient is breathing well while pedaling is of primary concern for the remote clinician. One key requirement for in-home telerehabilitation is to make the system as simple as possible for the patients, avoiding, for instance, to have them wear sensors and devices. This paper presents a contact-free respiration rate monitoring system measuring temperature variations between inspired and expired air in the mouth–nose region using thermal imaging. The thermal camera is installed on a pan–tilt unit and coupled to a tracking algorithm, allowing the system to keep track of the mouth–nose region as the patient exercises. Results demonstrate that the system works in real time even when the patient moves or rotates its head while exercising. Recommendations are also made to minimize limitations of the system, such as the presence of people in the background or when the patient is talking, for its eventual use in in-home telerehabilitation sessions.

Published
2016
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18. SVD-PHAT: A Fast Sound Source Localization Method

Author

Francois Grondin and James Glass

Subjects
Signal Processing (eess.SP), FOS: Computer and information sciences, Sound (cs.SD), geography, geography.geographical_feature_category, Speedup, Computer science, Direction of arrival, 020206 networking & telecommunications, 02 engineering and technology, Acoustic source localization, 01 natural sciences, Computer Science - Sound, Singular value, Tree (data structure), Audio and Speech Processing (eess.AS), 0103 physical sciences, Singular value decomposition, FOS: Electrical engineering, electronic engineering, information engineering, 0202 electrical engineering, electronic engineering, information engineering, Electrical Engineering and Systems Science - Signal Processing, 010301 acoustics, Algorithm, Sound (geography), Electrical Engineering and Systems Science - Audio and Speech Processing
Abstract

This paper introduces a new localization method called SVD-PHAT. The SVD-PHAT method relies on Singular Value De-composition of the SRP-PHAT projection matrix. A k-d tree is also proposed to speed up the search for the most likely direction of arrival of sound. We show that this method per-forms as accurately as SRP-PHAT, while reducing significantly the amount of computation required.

Published
2018

19. Albiglutide and cardiovascular outcomes in patients with type 2 diabetes and cardiovascular disease (Harmony Outcomes): a double-blind, randomised placebo-controlled trial

Author

Adrian F Hernandez, Jennifer B Green, Salim Janmohamed, Ralph B D'Agostino, Christopher B Granger, Nigel P Jones, Lawrence A Leiter, Anne E Rosenberg, Kristina N Sigmon, Matthew C Somerville, Karl M Thorpe, John J V McMurray, Stefano Del Prato, John J.V. McMurray, Ralph B. D'Agostino, Christopher B. Granger, Adrian F. Hernandez, Lawrence A. Leiter, Robert M Califf, Rury Holman, David DeMets, Matthew Riddle, Shaun Goodman, Darren McGuire, Karen Alexander, Adam Devore, Chiara Melloni, Chetan Patel, David Kong, Gerald Bloomfield, Matthew Roe, Pierluigi Tricoci, Rob Harrison, Renato Lopes, Robin Mathews, Rajendra Mehta, William Schuyler Jones, Sreekanth Vemulapalli, Thomas Povsic, Zubin Eapen, Keith Dombrowski, Brad Kolls, Dedrick Jordan, Andrew Ambrosy, Stephen Greene, Aditya Mandawat, Jay Shavadia, Lauren Cooper, Abhinav Sharma, Patricia Guimaraes, Daniel Friedman, Matt Wilson, Patricia Endsley, Tracy Gentry, Jeannie Collier, Kathleen Perez, Kourtnei James, Jennifer Roush, Connie Pope, Christina Howell, Megan Johnson, Matt Bailey, Joanna Cole, Teresa Akers, Beth Vandyne, Betsy Thomas, Jenny Rich, Susan Bartone, Gail Beaulieu, Kim Brown, Tuan Chau, Tamra Christian, Rebecca Coker, Deb Greene, Trevorlyn Haddock, Wendy Jenkins, Ghazala Haque, Marsha Marquess, Jean Pesarchick, Renee Rethaford, Allegra Stone, Firas Al Kawas, Michelle Anderson, Robert Enns, Isaac Sinay, Chantal Mathieu, Victor Yordanov, Irene Hramiak, Martin Haluzik, Søren Galatius, Bruno Guerci, Michael Nauck, Ilias Migdalis, Choon Beng Kathryn Tan, Gyozo Kocsis, Andrea Giaccari, Moon Kyu Lee, Ernesto German Cardona Muñoz, Jan Cornel, Kare Birkeland, Miguel Pinto, Louie Tirador, Martyna Olesinska-Mader, Marina Shestakova, Larry Distiller, Jose Lopez-Sendon, Bjorn Eliasson, Chern-En Chiang, Suphot Srimahachota, Boris Mankovsky, M Angelyn Bethel, Kathleen Dungan, Mikhail Kosiborod, Andres Alvarisqueta, Jorge Baldovino, Diego Besada, Pedro Calella, Maria Cecilia Cantero, Patricia Castaño, Alejandro Chertkoff, Jesus Cuadrado, Luis De Loredo, Andrea Dominguez, Maria Vanesa Español, Hernan Finkelstein, Gustavo Frechtel, Jose Fretes, Natalia Garrido Santos, Joaquin Gonzalez, Marcos Litvak, Juan Loureyro, Laura Maffei, Natacha Maldonado, Diego Mohr Gasparini, Silvia Orio, Federico Perez Manghi, Nelson Rodriguez Papini, Jorgelina Sala, Pablo Schygiel, Georgina Sposetti, Maria Ulla, Fernando Verra, Silvina Zabalua, Cesar Zaidman, Laurent Crenier, Corinne Debroye, Francis Duyck, André Scheen, Luc Van Gaal, Chris Vercammen, Velichka Damyanova, Stefan Dimitrov, Snezhina Kovacheva, Lachezar Lozanov, Viktor Margaritov, Rositsa Mihaylova-Shumkova, Antoaneta Nikolaeva, Zhasmina Stoyanova, Ronald Akhras, Yves Beaudry, Jacques Bedard, Joseph Berlingieri, Raja Chehayeb, Stephen Cheung, James Conway, Jean Cusson, Anthony Della Siega, Richard Dumas, Peter Dzongowski, Murdo Ferguson, Daniel Gaudet, Francois Grondin, Anil Gupta, Milan Gupta, Frank Halperin, Pierre-Alain Houle, Michael Jones, Simon Kouz, Christopher Kovacs, Daniel Landry, Eva Lonn, William O'Mahony, Sean Peterson, Dennis Reich, Alan Rosenbloom, Francois St-Maurice, Barna Tugwell, Saul Vizel, Vincent Woo, Tomas Brychta, Vladimir Cech, Eva Dvorakova, Tomas Edelsberger, Katarina Halciakova, Jarmila Krizova, Jiri Lastuvka, Martin Piperek, Vera Prymkova, Lea Raclavska, Elena Silhova, Robin Urbanek, Jan Vrkoc, Ulla Andersen, Jens Brønnum-Schou, Jens Hove, Jan Skov Jensen, Lars Kober, Ole Peter Kristiansen, Per Lund, Thomas Melchior, Ole Nyvad, Morten Schou, Alain Boye, Didier Cadinot, Didier Gouet, Patrick Henry, Laurence Kessler, Jean-Daniel Lalau, Catherine Petit, Jean-Francois Thuan, Christel Voinot, Julien Vouillarmet, Christoph Axthelm, Dirk Berger, Tasso Bieler, Andreas Birkenfeld, Jochen Bott, Klaus Busch, Karel Caca, Julia Chevts, Torsten Donaubauer, Rudolf Erlinger, Klaus Funke, Josef Grosskopf, Andreas Hagenow, Monika Hamann, Manfred Hartard, Peter Heymer, Wolfgang Huppertz, Gabriele Illies, Stephan Jacob, Thomas Jung, Gerd Kahrmann, Petra Kast, Monika Kellerer, Hans-Peter Kempe, Andrei Khariouzov, Gerhard Klausmann, Christiane Klein, Uwe Kleinecke-Pohl, Klaus Kleinertz, Thorsten Koch, Christine Kosch, Babette Lorra, Joerg Luedemann, Matthias Luttermann, Stephan Maxeiner, Karsten Milek, Andrea Moelle, Gerhard Neumann, Ruth Nischik, Edith Oehrig-Pohl, Georg Plassmann, Lars Pohlmeier, Felix Proepper, Stefan Regner, Werner Rieker, Ludger Rose, Holger Samer, Joachim Sauter, Frank Schaper, Clemens Schiffer, Juergen Schmidt, Bernd-M. Scholz, Joerg Schulze, Alexander Segner, Jochen Seufert, Helena Sigal, Joerg Steindorf, Juergen Stockhausen, Petra Stuebler, Heidrun Taeschner, Dietrich Tews, Diethelm Tschoepe, Karl Wilhelm, Helga Zeller-Stefan, Iakovos Avramidis, Stavros Bousboulas, Magdalini Bristianou, Georgios Dimitriadis, Moses Elisaf, Kalliopi Kotsa, Andreas Melidonis, Asimina Mitrakou, Emmanouil Pagkalos, Nikolaos Papanas, Angelos Pappas, Christos Sampanis, Nikolaos Tentolouris, Apostolos Tsapas, Glykeria Tzatzagou, Risa Ozaki, Csaba Hajdú, Eleonóra Harcsa, Laszlo Konyves, János Mucsi, Zsolt Pauker, Gizella Petró, Zsolt Plés, Katalin Revesz, Vangel Sándor, Viktor Vass, Angelo Avogaro, Massimo Boemi, Riccardo Bonadonna, Agostino Consoli, Salvatore De Cosmo, Paolo Di Bartolo, Francesco Dotta, Simona Frontoni, Marianna Galetta, Alessandra Gambineri, Carmine Gazzaruso, Francesco Giorgino, Davide Lauro, Emanuela Orsi, Giuseppe Paolisso, Gabriele Perriello, Piermarco Piatti, Antonio Pontiroli, Paola Ponzani, Angela Albarosa Rivellese, Giorgio Sesti, Giancarlo Tonolo, Roberto Trevisan, Chul Woo Ahn, Sei-Hyun Baik, Bong-Soo Cha, Choon-Hee Chung, Hak Chul Jang, Chong-Jin Kim, Hye Soon Kim, In Joo Kim, Eun Young Lee, Hyoung Woo Lee, Kwan-Woo Lee, Keon-Woong Moon, June Namgung, Kyong Soo Park, Soon Jib Yoo, Jaemyung Yu, Edmundo-Alfredo Bayram Llamas, Jose-Luis Cervantes-Escárcega, Luis Fernando Flota-Cervera, José Gerardo González-González, Sara Pascoe-Gonzalez, Emilia Susana Pelayo-Orozco, Santiago-Paulino Ramirez-Diaz, Arturo Saldana-Mendoza, Carlos Sánchez Jerjes-Díaz, Jose Juan Torres-Colores, Maricela Vidrio-Velázquez, Juan Villagordoa-Mesa, Hugo Peter Beijerbacht, Reginald G.E.J. Groutars, Boudewijn A Hoek, Pieter A.M. Hoogslag, Adriaan Kooy, Johannes A. Kragten, Aloysius G. Lieverse, Hendrik P. Swart, Eric P. Viergever, Jørn Ahlqvist, John Cooper, Hanne Gulseth, Gaute Guttormsen, Cecilie Wium, Hugo Arbañil, Jorge Calderon, Luis Camacho, Augusto Dextre Espinoza, Elizabeth Garrido, Alejandro Luna, Helard Manrique, Frederick Massucco Revoredo, Rolando Vargas Gonzales, Luis Zapata Rincon, Carlos Zubiate, Geraldine Ebo, Ellen Morales-Palomares, Malgorzata Arciszewska, Marek Banach, Renata Bijata-Bronisz, Tadeusz Derezinski, Waldemar Gadzinski, Jacek Gajek, Katarzyna Klodawska, Ewa Krzyzagorska, Andrzej Madej, Pawel Miekus, Jaroslaw Opiela, Piotr Romanczuk, Anna Siegel, Ewa Skokowska, Andrzej Stankiewicz, Teresa Stasinska, Iwona Trznadel-Morawska, Robert Witek, Sergey Aksentyev, Irina Bondar, Irina Demidova, Alexander Dreval, Olga Ershova, Gagik Galstyan, Alla Garganeeva, Nadezhda Izmozherova, Victoria Karetnikova, Marina Kharakhulakh, Aleksandr Khokhlov, Zhanna Kobalava, Olga Koshelskaya, Elena Kosmacheva, Vladimir Kostin, Natalia Koziolova, Anatoly Kuzin, Victor Lesnov, Tatyana Lysenko, Valentin Markov, Alexander Mayorov, Sergey Moiseev, Svetlana Myasoedova, Nina Petunina, Andrey Rebrov, Ludmila Ruyatkina, Julia Samoylova, Olga Sazonova, Natalia Shilkina, Nadezhda Sokolova, Olga Vasilevskaya, Nelli Verbovaya, Elena Vishneva, Sergey Vorobyev, Natalya Vorokhobina, Olga Zanozina, Elena Zhdanova, Tatyana Zykova, Lesley Burgess, Kathleen Coetzee, Saleem Dawood, Landman Lombard, Ellen Makotoko, Rajendran Moodley, Wessels Oosthuysen, Mohamed Sarvan, Carlos Calvo Gómez, Isidoro Cano Rodríguez, Almudena Castro Conde, Angel Cequier Fillat, Guillem Cuatrecasas Cambra, Fernando de Álvaro Moreno, Luis De Teresa Parreño, Javier Delgado Lista, José Ramón Domínguez Escribano, Santiago Durán García, Javier Elvira González, José María Fernández Rodríguez, Alberto Goday Arno, Ricardo Gomez Huelgas, José Ramón González Juanatey, Antonio Hernandez Mijares, Víctor Alfonso Jiménez Díaz, Esteban Jodar Gimeno, Tomás Lucas Morante, Monica Marazuela, Nieves Martell Claros, Didac Mauricio Puente, Elena Mena Ribas, Juan Francisco Merino Torres, Pedro Mezquita Raya, Andreu Nubiola Calonge, Xavier Ordoñez Sánchez, Jose Maria Pascual Izuel, Verónica Perea Castilla, Antonio Pérez Pérez, Isabel Perez Soto, Miguel Quesada Charneco, Angustias Quesada Simón, Josep Redón Mas, Antonia Rego Iraeta, Maria Rodriguez Alvarez, Irene Rodríguez Rodríguez, José Sabán Ruiz, Alfonso Soto González, Francisco Tinahones Madueno, Carlos Trescoli Serrano, Angels Ulied Armiñana, Erasmus Bachus, Katarina Berndtsson Blom, Ken Eliasson, Pekka Koskinen, Hans Larnefeldt, Cornelia Lif-Tiberg, Carina Linderfalk, Gustav Lund, Pia Lundman, Linda Moris, Åke Olsson, Staffan Salmonsson, Johan Sanmartin Berglund, Folke Sjöberg, Stefan Söderberg, Ingemar Torstensson, Jung-Fu Chen, Kai Jen Tien, Shih-Ting Tseng, Shih-Te Tu, Chih-Yuan Wang, Ji-Hung Wang, Arintaya Phrommintikul, Sukit Yamwong, Woravut Jintapakorn, Pisit Hutayanon, Nakarin Sansanayudh, Larysa Bazhan, Ivan Fushtey, Mariya Grachova, Vitaliy Katerenchuk, Vadym Korpachev, Nonna Kravchun, Oleksandr Larin, Galyna Mykhalchyshyn, Halyna Myshanych, Olga Oleksyk, Valeriia Orlenko, Nataliia Pashkovska, Nataliia Pertseva, Olena Petrosyan, Ivan Smirnov, Maryna Vlasenko, Tetiana Zlova, Myint Aye, Arun Baksi, Mathangi Balasubramani, Ronnie Beboso, Mark Blagden, Charles Bundy, Tobias Cookson, Allan Copland, Alistair Emslie-Smith, Fiona Green, Anthony Gunstone, Basil Issa, Ewart Jackson-Voyzey, Andrew Johnson, Malcolm Maclean, John McKnight, Solomon Muzulu, Ian O'Connell, Babatunde Oyesile, Catherine Patterson, Ewan Pearson, Sam Philip, Paul Smith, Usha Sukumaran, Jalal Abbas, Gaurav Aggarwala, Faiq Akhter, James Andersen, Moise Anglade, Georges Argoud, Mehrdad Ariani, Reswan Ashdji, Ladan Bakhtari, Subhash Banerjee, Andrew Bartlett, Howard Baum, Harold Bays, Richard Beasley, Renata Belfort de Aguiar, Sabrina Benjamin, Ravi Bhagwat, Anuj Bhargava, Bruce Bode, Christina Bratcher, Toby Briskin, Andrew Brockmyre, Raymond Broughton, Judith Brown, Madhusudan Budhraja, Kevin Cannon, Jewell Carr, Harold Cathcart, Arvind Cavale, Louis Chaykin, Deanna Cheung, Richard Childress, Allan Cohen, Jonathan Condit, Erin Cooksey, George Mitchell Cornett, Ira Dauber, William Davila, Luis De Armas, Julius Dean, Robert Detweiler, Ernesto Diaz, Michael Di Giovanna, Isaac Dor, Waymon Drummond, Donald Eagerton, John Earl, Charles Eaton, Howard Ellison, Neil Farris, Thomas Fiel, Anthony Firek, Brian First, Les Forgosh, William French, Winston Gandy, Ronald Garcia, Santosh Gill, Murray Gordon, Michael Guice, Siva Gummadi, Jonathan Hackenyos, Kristen Hairston, Lenita Hanson, Lindsay Harrison, Israel Hartman, John Heitner, Srini Hejeebu, Paul Hermany, Carlos Hernandez-Cassis, Horacio Hidalgo, Alexander Higgins, Hassan Ibrahim, Shahram Jacobs, David Johnson, Parag Joshi, Steven Kaster, Daniel Kellum, Christopher Kim, Ellen Kim, William Kirby, Albert Knouse, Steven Kulback, Mariananda Kumar, Tulsidas Kuruvanka, Ajay Labroo, William Lasswell, John Lentz, Thomas Lenzmeier, David Lewis, Zhaoping Li, Michael Lillestol, Raymond Little, Richard Lorraine, Cecilia McKeown-Biagas, Robert McNeill, Anand Mehta, Alan Miller, Joseph Moran, Emily Morawski, Venkatesh Nadar, Thomas O'Connor, Alberto Odio, Reginald Parker, Rajesh Patel, Lawrence Phillips, George Raad, Aref Rahman, Marina Raikhel, Ajit Raisinghani, Raj Rajan, Neda Rasouli, Frank Rauzi, Kathryn Rohr, Hal Roseman, Sergio Rovner, Fadi Saba, Richard Sachson, Alex Schabauer, Ricky Schneider, Timothy Schuchard, John Sensenbrenner, Yshay Shlesinger, Narendra Singh, Kanagaratnam Sivalingam, Larry Stonesifer, Daniel Storey, David Suh, Mohammed Tahir, Anjanette Tan, Marilyn Tan, Alain Taylon, Maitreya Thakkar, Devjit Tripathy, Gabriel Uwaifo, Amarnath Vedere, Chandra Venugopal, Anthony Vo, Michelle Welch, James Welker, Alexander White, John Willis, Alan Wynne, Shahram Yazdani, Anne Rosenberg, Lauren Price, Kristina Sigmon, Yuliya Lokhngina, Weibing Xing, Robert Overton, Murray Stewart, Janet Stead, Alistair Lindsay, Vickas Patel, Jorge Ross, Joseph Soffer, Shruti Daga, Margaret Sowell, Prashant Patel, Louisa Garvey, Jessica Ackert, Sybil Abraham, Mary Beth Sabol, Desma Altobelli, JuYoung Ha, Mangesh Kulkarni, Matthew Somerville, Drusilla Noronha, Ed Casson, Eddie Zang, Chamandeep Sandhu, Rakesh Kumar, David Chen, Lin Taft, Rajivkumar Patel, June Ye, Jennifer Shannon, Tim Wilson, Charleen Babi, Diane Miller, Karl Thorpe, Rachael Russell, Georgina Bull, Belinda Hereghty, Eva Fernandez-Salazar, Troy Longley, Jill Donaldson, Marie Jarosz, Karen Murphy, Patricia Adams, Peter Smith, Rachel James, Jackie Richards, Sangeeta Sedani, Denise Althouse, David Watson, Jamie Lorimer, Steven Lauder, Ron Schultheis, Terese Womer, Ella Wraight, Wenyan Li, Emma Price-Olsen, Anthony Watson, Aoife Kelly, Patricia McLaughlin, John Fleming, Jessica Schubert, Debra Schleiden, Tara Harris, Rahul Prakash, Jody Breneman, Sameer Deshpande, Aarti Saswadkar, Aditi Kumari, Aditi Shitut, Amruta Raorane, Anisha Karmalkar, Ankita Mhambrey, Archana Bhosale, Ashok Vaphare, Ashwini P Patil, Chaitali Khandelwal, Fayaz Shaik, Madhumitha Nadar, Mounika Karka, Neha Kadgaonkar, Nikita Gupta, Nutan Aher, Omkar Potnis, Pallavi Naicker, Rakesh Shinde, Richa Sharma, Rupali Godse, Sheetal Solanki, Shruti Sahu, Snehal Dumbre, Somesh Kumar, Suradnya Patil, Trisha Mandal, Hernandez, Adrian F, Green, Jennifer B, Janmohamed, Salim, D'Agostino, Ralph B, Granger, Christopher B, Jones, Nigel P, Leiter, Lawrence A, Rosenberg, Anne E, Sigmon, Kristina N, Somerville, Matthew C, Thorpe, Karl M, Mcmurray, John J V, Del Prato, Stefano, Mcmurray, John J. V., D'Agostino, Ralph B., Granger, Christopher B., Hernandez, Adrian F., Leiter, Lawrence A., Califf, Robert M, Holman, Rury, Demets, David, Riddle, Matthew, Goodman, Shaun, Mcguire, Darren, Alexander, Karen, Devore, Adam, Melloni, Chiara, Patel, Chetan, Kong, David, Bloomfield, Gerald, Roe, Matthew, Tricoci, Pierluigi, Harrison, Rob, Lopes, Renato, Mathews, Robin, Mehta, Rajendra, Schuyler Jones, William, Vemulapalli, Sreekanth, Povsic, Thoma, Eapen, Zubin, Dombrowski, Keith, Kolls, Brad, Jordan, Dedrick, Ambrosy, Andrew, Greene, Stephen, Mandawat, Aditya, Shavadia, Jay, Cooper, Lauren, Sharma, Abhinav, Guimaraes, Patricia, Friedman, Daniel, Wilson, Matt, Endsley, Patricia, Gentry, Tracy, Collier, Jeannie, Perez, Kathleen, James, Kourtnei, Roush, Jennifer, Pope, Connie, Howell, Christina, Johnson, Megan, Bailey, Matt, Cole, Joanna, Akers, Teresa, Vandyne, Beth, Thomas, Betsy, Rich, Jenny, Bartone, Susan, Beaulieu, Gail, Brown, Kim, Chau, Tuan, Christian, Tamra, Coker, Rebecca, Greene, Deb, Haddock, Trevorlyn, Jenkins, Wendy, Haque, Ghazala, Marquess, Marsha, Pesarchick, Jean, Rethaford, Renee, Stone, Allegra, Al Kawas, Fira, Anderson, Michelle, Enns, Robert, Sinay, Isaac, Mathieu, Chantal, Yordanov, Victor, Hramiak, Irene, Haluzik, Martin, Galatius, Søren, Guerci, Bruno, Nauck, Michael, Migdalis, Ilia, Tan, Choon Beng Kathryn, Kocsis, Gyozo, Giaccari, Andrea, Lee, Moon Kyu, Muñoz, Ernesto German Cardona, Cornel, Jan, Birkeland, Kare, Pinto, Miguel, Tirador, Louie, Olesinska-Mader, Martyna, Shestakova, Marina, Distiller, Larry, Lopez-Sendon, Jose, Eliasson, Bjorn, Chiang, Chern-En, Srimahachota, Suphot, Mankovsky, Bori, Bethel, M Angelyn, Dungan, Kathleen, Kosiborod, Mikhail, Alvarisqueta, Andre, Baldovino, Jorge, Besada, Diego, Calella, Pedro, Cantero, Maria Cecilia, Castaño, Patricia, Chertkoff, Alejandro, Cuadrado, Jesu, De Loredo, Lui, Dominguez, Andrea, Español, Maria Vanesa, Finkelstein, Hernan, Frechtel, Gustavo, Fretes, Jose, Garrido Santos, Natalia, Gonzalez, Joaquin, Litvak, Marco, Loureyro, Juan, Maffei, Laura, Maldonado, Natacha, Mohr Gasparini, Diego, Orio, Silvia, Perez Manghi, Federico, Rodriguez Papini, Nelson, Sala, Jorgelina, Schygiel, Pablo, Sposetti, Georgina, Ulla, Maria, Verra, Fernando, Zabalua, Silvina, Zaidman, Cesar, Crenier, Laurent, Debroye, Corinne, Duyck, Franci, Scheen, André, Van Gaal, Luc, Vercammen, Chri, Damyanova, Velichka, Dimitrov, Stefan, Kovacheva, Snezhina, Lozanov, Lachezar, Margaritov, Viktor, Mihaylova-Shumkova, Rositsa, Nikolaeva, Antoaneta, Stoyanova, Zhasmina, Akhras, Ronald, Beaudry, Yve, Bedard, Jacque, Berlingieri, Joseph, Chehayeb, Raja, Cheung, Stephen, Conway, Jame, Cusson, Jean, Della Siega, Anthony, Dumas, Richard, Dzongowski, Peter, Ferguson, Murdo, Gaudet, Daniel, Grondin, Francoi, Gupta, Anil, Gupta, Milan, Halperin, Frank, Houle, Pierre-Alain, Jones, Michael, Kouz, Simon, Kovacs, Christopher, Landry, Daniel, Lonn, Eva, O'Mahony, William, Peterson, Sean, Reich, Denni, Rosenbloom, Alan, St-Maurice, Francoi, Tugwell, Barna, Vizel, Saul, Woo, Vincent, Brychta, Toma, Cech, Vladimir, Dvorakova, Eva, Edelsberger, Toma, Halciakova, Katarina, Krizova, Jarmila, Lastuvka, Jiri, Piperek, Martin, Prymkova, Vera, Raclavska, Lea, Silhova, Elena, Urbanek, Robin, Vrkoc, Jan, Andersen, Ulla, Brønnum-Schou, Jen, Hove, Jen, Jensen, Jan Skov, Kober, Lar, Kristiansen, Ole Peter, Lund, Per, Melchior, Thoma, Nyvad, Ole, Schou, Morten, Boye, Alain, Cadinot, Didier, Gouet, Didier, Henry, Patrick, Kessler, Laurence, Lalau, Jean-Daniel, Petit, Catherine, Thuan, Jean-Francoi, Voinot, Christel, Vouillarmet, Julien, Axthelm, Christoph, Berger, Dirk, Bieler, Tasso, Birkenfeld, Andrea, Bott, Jochen, Busch, Klau, Caca, Karel, Chevts, Julia, Donaubauer, Torsten, Erlinger, Rudolf, Funke, Klau, Grosskopf, Josef, Hagenow, Andrea, Hamann, Monika, Hartard, Manfred, Heymer, Peter, Huppertz, Wolfgang, Illies, Gabriele, Jacob, Stephan, Jung, Thoma, Kahrmann, Gerd, Kast, Petra, Kellerer, Monika, Kempe, Hans-Peter, Khariouzov, Andrei, Klausmann, Gerhard, Klein, Christiane, Kleinecke-Pohl, Uwe, Kleinertz, Klau, Koch, Thorsten, Kosch, Christine, Lorra, Babette, Luedemann, Joerg, Luttermann, Matthia, Maxeiner, Stephan, Milek, Karsten, Moelle, Andrea, Neumann, Gerhard, Nischik, Ruth, Oehrig-Pohl, Edith, Plassmann, Georg, Pohlmeier, Lar, Proepper, Felix, Regner, Stefan, Rieker, Werner, Rose, Ludger, Samer, Holger, Sauter, Joachim, Schaper, Frank, Schiffer, Clemen, Schmidt, Juergen, Scholz, Bernd-M., Schulze, Joerg, Segner, Alexander, Seufert, Jochen, Sigal, Helena, Steindorf, Joerg, Stockhausen, Juergen, Stuebler, Petra, Taeschner, Heidrun, Tews, Dietrich, Tschoepe, Diethelm, Wilhelm, Karl, Zeller-Stefan, Helga, Avramidis, Iakovo, Bousboulas, Stavro, Bristianou, Magdalini, Dimitriadis, Georgio, Elisaf, Mose, Kotsa, Kalliopi, Melidonis, Andrea, Mitrakou, Asimina, Pagkalos, Emmanouil, Papanas, Nikolao, Pappas, Angelo, Sampanis, Christo, Tentolouris, Nikolao, Tsapas, Apostolo, Tzatzagou, Glykeria, Ozaki, Risa, Hajdú, Csaba, Harcsa, Eleonóra, Konyves, Laszlo, Mucsi, Jáno, Pauker, Zsolt, Petró, Gizella, Plés, Zsolt, Revesz, Katalin, Sándor, Vangel, Vass, Viktor, Avogaro, Angelo, Boemi, Massimo, Bonadonna, Riccardo, Consoli, Agostino, De Cosmo, Salvatore, Di Bartolo, Paolo, Dotta, Francesco, Frontoni, Simona, Galetta, Marianna, Gambineri, Alessandra, Gazzaruso, Carmine, Giorgino, Francesco, Lauro, Davide, Orsi, Emanuela, Paolisso, Giuseppe, Perriello, Gabriele, Piatti, Piermarco, Pontiroli, Antonio, Ponzani, Paola, Rivellese, Angela Albarosa, Sesti, Giorgio, Tonolo, Giancarlo, Trevisan, Roberto, Ahn, Chul Woo, Baik, Sei-Hyun, Cha, Bong-Soo, Chung, Choon-Hee, Jang, Hak Chul, Kim, Chong-Jin, Kim, Hye Soon, Kim, In Joo, Lee, Eun Young, Lee, Hyoung Woo, Lee, Kwan-Woo, Moon, Keon-Woong, Namgung, June, Park, Kyong Soo, Yoo, Soon Jib, Yu, Jaemyung, Llamas, Edmundo-Alfredo Bayram, Cervantes-Escárcega, Jose-Lui, Flota-Cervera, Luis Fernando, González-González, José Gerardo, Pascoe-Gonzalez, Sara, Pelayo-Orozco, Emilia Susana, Ramirez-Diaz, Santiago-Paulino, Saldana-Mendoza, Arturo, Jerjes-Díaz, Carlos Sánchez, Torres-Colores, Jose Juan, Vidrio-Velázquez, Maricela, Villagordoa-Mesa, Juan, Beijerbacht, Hugo Peter, Groutars, Reginald G. E. J., Hoek, Boudewijn A, Hoogslag, Pieter A. M., Kooy, Adriaan, Kragten, Johannes A., Lieverse, Aloysius G., Swart, Hendrik P., Viergever, Eric P., Ahlqvist, Jørn, Cooper, John, Gulseth, Hanne, Guttormsen, Gaute, Wium, Cecilie, Arbañil, Hugo, Calderon, Jorge, Camacho, Lui, Espinoza, Augusto Dextre, Garrido, Elizabeth, Luna, Alejandro, Manrique, Helard, Revoredo, Frederick Massucco, Gonzales, Rolando Varga, Rincon, Luis Zapata, Zubiate, Carlo, Ebo, Geraldine, Morales-Palomares, Ellen, Arciszewska, Malgorzata, Banach, Marek, Bijata-Bronisz, Renata, Derezinski, Tadeusz, Gadzinski, Waldemar, Gajek, Jacek, Klodawska, Katarzyna, Krzyzagorska, Ewa, Madej, Andrzej, Miekus, Pawel, Opiela, Jaroslaw, Romanczuk, Piotr, Siegel, Anna, Skokowska, Ewa, Stankiewicz, Andrzej, Stasinska, Teresa, Trznadel-Morawska, Iwona, Witek, Robert, Aksentyev, Sergey, Bondar, Irina, Demidova, Irina, Dreval, Alexander, Ershova, Olga, Galstyan, Gagik, Garganeeva, Alla, Izmozherova, Nadezhda, Karetnikova, Victoria, Kharakhulakh, Marina, Khokhlov, Aleksandr, Kobalava, Zhanna, Koshelskaya, Olga, Kosmacheva, Elena, Kostin, Vladimir, Koziolova, Natalia, Kuzin, Anatoly, Lesnov, Victor, Lysenko, Tatyana, Markov, Valentin, Mayorov, Alexander, Moiseev, Sergey, Myasoedova, Svetlana, Petunina, Nina, Rebrov, Andrey, Ruyatkina, Ludmila, Samoylova, Julia, Sazonova, Olga, Shilkina, Natalia, Sokolova, Nadezhda, Vasilevskaya, Olga, Verbovaya, Nelli, Vishneva, Elena, Vorobyev, Sergey, Vorokhobina, Natalya, Zanozina, Olga, Zhdanova, Elena, Zykova, Tatyana, Burgess, Lesley, Coetzee, Kathleen, Dawood, Saleem, Lombard, Landman, Makotoko, Ellen, Moodley, Rajendran, Oosthuysen, Wessel, Sarvan, Mohamed, Calvo Gómez, Carlo, Cano Rodríguez, Isidoro, Castro Conde, Almudena, Cequier Fillat, Angel, Cuatrecasas Cambra, Guillem, de Álvaro Moreno, Fernando, De Teresa Parreño, Lui, Delgado Lista, Javier, Domínguez Escribano, José Ramón, Durán García, Santiago, Elvira González, Javier, Fernández Rodríguez, José María, Goday Arno, Alberto, Gomez Huelgas, Ricardo, González Juanatey, José Ramón, Hernandez Mijares, Antonio, Jiménez Díaz, Víctor Alfonso, Jodar Gimeno, Esteban, Lucas Morante, Tomá, Marazuela, Monica, Martell Claros, Nieve, Mauricio Puente, Didac, Mena Ribas, Elena, Merino Torres, Juan Francisco, Mezquita Raya, Pedro, Nubiola Calonge, Andreu, Ordoñez Sánchez, Xavier, Pascual Izuel, Jose Maria, Perea Castilla, Verónica, Pérez Pérez, Antonio, Perez Soto, Isabel, Quesada Charneco, Miguel, Quesada Simón, Angustia, Redón Mas, Josep, Rego Iraeta, Antonia, Rodriguez Alvarez, Maria, Rodríguez Rodríguez, Irene, Sabán Ruiz, José, Soto González, Alfonso, Tinahones Madueno, Francisco, Trescoli Serrano, Carlo, Ulied Armiñana, Angel, Bachus, Erasmu, Berndtsson Blom, Katarina, Eliasson, Ken, Koskinen, Pekka, Larnefeldt, Han, Lif-Tiberg, Cornelia, Linderfalk, Carina, Lund, Gustav, Lundman, Pia, Moris, Linda, Olsson, Åke, Salmonsson, Staffan, Sanmartin Berglund, Johan, Sjöberg, Folke, Söderberg, Stefan, Torstensson, Ingemar, Chen, Jung-Fu, Tien, Kai Jen, Tseng, Shih-Ting, Tu, Shih-Te, Wang, Chih-Yuan, Wang, Ji-Hung, Phrommintikul, Arintaya, Yamwong, Sukit, Jintapakorn, Woravut, Hutayanon, Pisit, Sansanayudh, Nakarin, Bazhan, Larysa, Fushtey, Ivan, Grachova, Mariya, Katerenchuk, Vitaliy, Korpachev, Vadym, Kravchun, Nonna, Larin, Oleksandr, Mykhalchyshyn, Galyna, Myshanych, Halyna, Oleksyk, Olga, Orlenko, Valeriia, Pashkovska, Nataliia, Pertseva, Nataliia, Petrosyan, Olena, Smirnov, Ivan, Vlasenko, Maryna, Zlova, Tetiana, Aye, Myint, Baksi, Arun, Balasubramani, Mathangi, Beboso, Ronnie, Blagden, Mark, Bundy, Charle, Cookson, Tobia, Copland, Allan, Emslie-Smith, Alistair, Green, Fiona, Gunstone, Anthony, Issa, Basil, Jackson-Voyzey, Ewart, Johnson, Andrew, Maclean, Malcolm, Mcknight, John, Muzulu, Solomon, O'Connell, Ian, Oyesile, Babatunde, Patterson, Catherine, Pearson, Ewan, Philip, Sam, Smith, Paul, Sukumaran, Usha, Abbas, Jalal, Aggarwala, Gaurav, Akhter, Faiq, Andersen, Jame, Anglade, Moise, Argoud, George, Ariani, Mehrdad, Ashdji, Reswan, Bakhtari, Ladan, Banerjee, Subhash, Bartlett, Andrew, Baum, Howard, Bays, Harold, Beasley, Richard, Belfort de Aguiar, Renata, Benjamin, Sabrina, Bhagwat, Ravi, Bhargava, Anuj, Bode, Bruce, Bratcher, Christina, Briskin, Toby, Brockmyre, Andrew, Broughton, Raymond, Brown, Judith, Budhraja, Madhusudan, Cannon, Kevin, Carr, Jewell, Cathcart, Harold, Cavale, Arvind, Chaykin, Loui, Cheung, Deanna, Childress, Richard, Cohen, Allan, Condit, Jonathan, Cooksey, Erin, Cornett, George Mitchell, Dauber, Ira, Davila, William, De Armas, Lui, Dean, Juliu, Detweiler, Robert, Diaz, Ernesto, Di Giovanna, Michael, Dor, Isaac, Drummond, Waymon, Eagerton, Donald, Earl, John, Eaton, Charle, Ellison, Howard, Farris, Neil, Fiel, Thoma, Firek, Anthony, First, Brian, Forgosh, Le, French, William, Gandy, Winston, Garcia, Ronald, Gill, Santosh, Gordon, Murray, Guice, Michael, Gummadi, Siva, Hackenyos, Jonathan, Hairston, Kristen, Hanson, Lenita, Harrison, Lindsay, Hartman, Israel, Heitner, John, Hejeebu, Srini, Hermany, Paul, Hernandez-Cassis, Carlo, Hidalgo, Horacio, Higgins, Alexander, Ibrahim, Hassan, Jacobs, Shahram, Johnson, David, Joshi, Parag, Kaster, Steven, Kellum, Daniel, Kim, Christopher, Kim, Ellen, Kirby, William, Knouse, Albert, Kulback, Steven, Kumar, Mariananda, Kuruvanka, Tulsida, Labroo, Ajay, Lasswell, William, Lentz, John, Lenzmeier, Thoma, Lewis, David, Li, Zhaoping, Lillestol, Michael, Little, Raymond, Lorraine, Richard, McKeown-Biagas, Cecilia, Mcneill, Robert, Mehta, Anand, Miller, Alan, Moran, Joseph, Morawski, Emily, Nadar, Venkatesh, O'Connor, Thoma, Odio, Alberto, Parker, Reginald, Patel, Rajesh, Phillips, Lawrence, Raad, George, Rahman, Aref, Raikhel, Marina, Raisinghani, Ajit, Rajan, Raj, Rasouli, Neda, Rauzi, Frank, Rohr, Kathryn, Roseman, Hal, Rovner, Sergio, Saba, Fadi, Sachson, Richard, Schabauer, Alex, Schneider, Ricky, Schuchard, Timothy, Sensenbrenner, John, Shlesinger, Yshay, Singh, Narendra, Sivalingam, Kanagaratnam, Stonesifer, Larry, Storey, Daniel, Suh, David, Tahir, Mohammed, Tan, Anjanette, Tan, Marilyn, Taylon, Alain, Thakkar, Maitreya, Tripathy, Devjit, Uwaifo, Gabriel, Vedere, Amarnath, Venugopal, Chandra, Vo, Anthony, Welch, Michelle, Welker, Jame, White, Alexander, Willis, John, Wynne, Alan, Yazdani, Shahram, Rosenberg, Anne, Price, Lauren, Sigmon, Kristina, Lokhngina, Yuliya, Xing, Weibing, Overton, Robert, Stewart, Murray, Stead, Janet, Lindsay, Alistair, Patel, Vicka, Ross, Jorge, Soffer, Joseph, Daga, Shruti, Sowell, Margaret, Patel, Prashant, Garvey, Louisa, Ackert, Jessica, Abraham, Sybil, Sabol, Mary Beth, Altobelli, Desma, Ha, Juyoung, Kulkarni, Mangesh, Somerville, Matthew, Noronha, Drusilla, Casson, Ed, Zang, Eddie, Sandhu, Chamandeep, Kumar, Rakesh, Chen, David, Taft, Lin, Patel, Rajivkumar, Ye, June, Shannon, Jennifer, Wilson, Tim, Babi, Charleen, Miller, Diane, Thorpe, Karl, Russell, Rachael, Bull, Georgina, Hereghty, Belinda, Fernandez-Salazar, Eva, Longley, Troy, Donaldson, Jill, Jarosz, Marie, Murphy, Karen, Adams, Patricia, Smith, Peter, James, Rachel, Richards, Jackie, Sedani, Sangeeta, Althouse, Denise, Watson, David, Lorimer, Jamie, Lauder, Steven, Schultheis, Ron, Womer, Terese, Wraight, Ella, Li, Wenyan, Price-Olsen, Emma, Watson, Anthony, Kelly, Aoife, Mclaughlin, Patricia, Fleming, John, Schubert, Jessica, Schleiden, Debra, Harris, Tara, Prakash, Rahul, Breneman, Jody, Deshpande, Sameer, Saswadkar, Aarti, Kumari, Aditi, Shitut, Aditi, Raorane, Amruta, Karmalkar, Anisha, Mhambrey, Ankita, Bhosale, Archana, Vaphare, Ashok, Patil, Ashwini P, Khandelwal, Chaitali, Shaik, Fayaz, Nadar, Madhumitha, Karka, Mounika, Kadgaonkar, Neha, Gupta, Nikita, Aher, Nutan, Potnis, Omkar, Naicker, Pallavi, Shinde, Rakesh, Sharma, Richa, Godse, Rupali, Solanki, Sheetal, Sahu, Shruti, Dumbre, Snehal, Kumar, Somesh, Patil, Suradnya, Mandal, Trisha, McMurray, John J V, McMurray, John J.V., DeMets, David, McGuire, Darren, Groutars, Reginald G.E.J., Hoogslag, Pieter A.M., McKnight, John, McNeill, Robert, Ha, JuYoung, McLaughlin, Patricia, Hernandez, A. F., Green, J. B., Janmohamed, S., D'Agostino, R. B., Granger, C. B., Jones, N. P., Leiter, L. A., Rosenberg, A. E., Sigmon, K. N., Somerville, M. C., Thorpe, K. M., Mcmurray, J. J. V., Del Prato, S., Califf, R. M., Holman, R., Demets, D., Riddle, M., Goodman, S., Mcguire, D., Alexander, K., Devore, A., Melloni, C., Patel, C., Kong, D., Bloomfield, G., Roe, M., Tricoci, P., Harrison, R., Lopes, R., Mathews, R., Mehta, R., Schuyler Jones, W., Vemulapalli, S., Povsic, T., Eapen, Z., Dombrowski, K., Kolls, B., Jordan, D., Ambrosy, A., Greene, S., Mandawat, A., Shavadia, J., Cooper, L., Sharma, A., Guimaraes, P., Friedman, D., Wilson, M., Endsley, P., Gentry, T., Collier, J., Perez, K., James, K., Roush, J., Pope, C., Howell, C., Johnson, M., Bailey, M., Cole, J., Akers, T., Vandyne, B., Thomas, B., Rich, J., Bartone, S., Beaulieu, G., Brown, K., Chau, T., Christian, T., Coker, R., Greene, D., Haddock, T., Jenkins, W., Haque, G., Marquess, M., Pesarchick, J., Rethaford, R., Stone, A., Al Kawas, F., Anderson, M., Enns, R., Sinay, I., Mathieu, C., Yordanov, V., Hramiak, I., Haluzik, M., Galatius, S., Guerci, B., Nauck, M., Migdalis, I., Tan, C. B. K., Kocsis, G., Giaccari, A., Lee, M. K., Munoz, E. G. C., Cornel, J., Birkeland, K., Pinto, M., Tirador, L., Olesinska-Mader, M., Shestakova, M., Distiller, L., Lopez-Sendon, J., Eliasson, B., Chiang, C. -E., Srimahachota, S., Mankovsky, B., Bethel, M. A., Dungan, K., Kosiborod, M., Alvarisqueta, A., Baldovino, J., Besada, D., Calella, P., Cantero, M. C., Castano, P., Chertkoff, A., Cuadrado, J., De Loredo, L., Dominguez, A., Espanol, M. V., Finkelstein, H., Frechtel, G., Fretes, J., Garrido Santos, N., Gonzalez, J., Litvak, M., Loureyro, J., Maffei, L., Maldonado, N., Mohr Gasparini, D., Orio, S., Perez Manghi, F., Rodriguez Papini, N., Sala, J., Schygiel, P., Sposetti, G., Ulla, M., Verra, F., Zabalua, S., Zaidman, C., Crenier, L., Debroye, C., Duyck, F., Scheen, A., Van Gaal, L., Vercammen, C., Damyanova, V., Dimitrov, S., Kovacheva, S., Lozanov, L., Margaritov, V., Mihaylova-Shumkova, R., Nikolaeva, A., Stoyanova, Z., Akhras, R., Beaudry, Y., Bedard, J., Berlingieri, J., Chehayeb, R., Cheung, S., Conway, J., Cusson, J., Della Siega, A., Dumas, R., Dzongowski, P., Ferguson, M., Gaudet, D., Grondin, F., Gupta, A., Gupta, M., Halperin, F., Houle, P. -A., Jones, M., Kouz, S., Kovacs, C., Landry, D., Lonn, E., O'Mahony, W., Peterson, S., Reich, D., Rosenbloom, A., St-Maurice, F., Tugwell, B., Vizel, S., Woo, V., Brychta, T., Cech, V., Dvorakova, E., Edelsberger, T., Halciakova, K., Krizova, J., Lastuvka, J., Piperek, M., Prymkova, V., Raclavska, L., Silhova, E., Urbanek, R., Vrkoc, J., Andersen, U., Bronnum-Schou, J., Hove, J., Jensen, J. S., Kober, L., Kristiansen, O. P., Lund, P., Melchior, T., Nyvad, O., Schou, M., Boye, A., Cadinot, D., Gouet, D., Henry, P., Kessler, L., Lalau, J. -D., Petit, C., Thuan, J. -F., Voinot, C., Vouillarmet, J., Axthelm, C., Berger, D., Bieler, T., Birkenfeld, A., Bott, J., Busch, K., Caca, K., Chevts, J., Donaubauer, T., Erlinger, R., Funke, K., Grosskopf, J., Hagenow, A., Hamann, M., Hartard, M., Heymer, P., Huppertz, W., Illies, G., Jacob, S., Jung, T., Kahrmann, G., Kast, P., Kellerer, M., Kempe, H. -P., Khariouzov, A., Klausmann, G., Klein, C., Kleinecke-Pohl, U., Kleinertz, K., Koch, T., Kosch, C., Lorra, B., Luedemann, J., Luttermann, M., Maxeiner, S., Milek, K., Moelle, A., Neumann, G., Nischik, R., Oehrig-Pohl, E., Plassmann, G., Pohlmeier, L., Proepper, F., Regner, S., Rieker, W., Rose, L., Samer, H., Sauter, J., Schaper, F., Schiffer, C., Schmidt, J., Scholz, B. -M., Schulze, J., Segner, A., Seufert, J., Sigal, H., Steindorf, J., Stockhausen, J., Stuebler, P., Taeschner, H., Tews, D., Tschoepe, D., Wilhelm, K., Zeller-Stefan, H., Avramidis, I., Bousboulas, S., Bristianou, M., Dimitriadis, G., Elisaf, M., Kotsa, K., Melidonis, A., Mitrakou, A., Pagkalos, E., Papanas, N., Pappas, A., Sampanis, C., Tentolouris, N., Tsapas, A., Tzatzagou, G., Ozaki, R., Hajdu, C., Harcsa, E., Konyves, L., Mucsi, J., Pauker, Z., Petro, G., Ples, Z., Revesz, K., Sandor, V., Vass, V., Avogaro, A., Boemi, M., Bonadonna, R., Consoli, A., De Cosmo, S., Di Bartolo, P., Dotta, F., Frontoni, S., Galetta, M., Gambineri, A., Gazzaruso, C., Giorgino, F., Lauro, D., Orsi, E., Paolisso, G., Perriello, G., Piatti, P., Pontiroli, A., Ponzani, P., Rivellese, A. A., Sesti, G., Tonolo, G., Trevisan, R., Ahn, C. W., Baik, S. -H., Cha, B. -S., Chung, C. -H., Jang, H. C., Kim, C. -J., Kim, H. S., Kim, I. J., Lee, E. Y., Lee, H. W., Lee, K. -W., Moon, K. -W., Namgung, J., Park, K. S., Yoo, S. J., Yu, J., Llamas, E. -A. B., Cervantes-Escarcega, J. -L., Flota-Cervera, L. F., Gonzalez-Gonzalez, J. G., Pascoe-Gonzalez, S., Pelayo-Orozco, E. S., Ramirez-Diaz, S. -P., Saldana-Mendoza, A., Jerjes-Diaz, C. S., Torres-Colores, J. J., Vidrio-Velazquez, M., Villagordoa-Mesa, J., Beijerbacht, H. P., Groutars, R. G. E. J., Hoek, B. A., Hoogslag, P. A. M., Kooy, A., Kragten, J. A., Lieverse, A. G., Swart, H. P., Viergever, E. P., Ahlqvist, J., Cooper, J., Gulseth, H., Guttormsen, G., Wium, C., Arbanil, H., Calderon, J., Camacho, L., Espinoza, A. D., Garrido, E., Luna, A., Manrique, H., Revoredo, F. M., Gonzales, R. V., Rincon, L. Z., Zubiate, C., Ebo, G., Morales-Palomares, E., Arciszewska, M., Banach, M., Bijata-Bronisz, R., Derezinski, T., Gadzinski, W., Gajek, J., Klodawska, K., Krzyzagorska, E., Madej, A., Miekus, P., Opiela, J., Romanczuk, P., Siegel, A., Skokowska, E., Stankiewicz, A., Stasinska, T., Trznadel-Morawska, I., Witek, R., Aksentyev, S., Bondar, I., Demidova, I., Dreval, A., Ershova, O., Galstyan, G., Garganeeva, A., Izmozherova, N., Karetnikova, V., Kharakhulakh, M., Khokhlov, A., Kobalava, Z., Koshelskaya, O., Kosmacheva, E., Kostin, V., Koziolova, N., Kuzin, A., Lesnov, V., Lysenko, T., Markov, V., Mayorov, A., Moiseev, S., Myasoedova, S., Petunina, N., Rebrov, A., Ruyatkina, L., Samoylova, J., Sazonova, O., Shilkina, N., Sokolova, N., Vasilevskaya, O., Verbovaya, N., Vishneva, E., Vorobyev, S., Vorokhobina, N., Zanozina, O., Zhdanova, E., Zykova, T., Burgess, L., Coetzee, K., Dawood, S., Lombard, L., Makotoko, E., Moodley, R., Oosthuysen, W., Sarvan, M., Calvo Gomez, C., Cano Rodriguez, I., Castro Conde, A., Cequier Fillat, A., Cuatrecasas Cambra, G., de Alvaro Moreno, F., De Teresa Parreno, L., Delgado Lista, J., Dominguez Escribano, J. R., Duran Garcia, S., Elvira Gonzalez, J., Fernandez Rodriguez, J. M., Goday Arno, A., Gomez Huelgas, R., Gonzalez Juanatey, J. R., Hernandez Mijares, A., Jimenez Diaz, V. A., Jodar Gimeno, E., Lucas Morante, T., Marazuela, M., Martell Claros, N., Mauricio Puente, D., Mena Ribas, E., Merino Torres, J. F., Mezquita Raya, P., Nubiola Calonge, A., Ordonez Sanchez, X., Pascual Izuel, J. M., Perea Castilla, V., Perez Perez, A., Perez Soto, I., Quesada Charneco, M., Quesada Simon, A., Redon Mas, J., Rego Iraeta, A., Rodriguez Alvarez, M., Rodriguez Rodriguez, I., Saban Ruiz, J., Soto Gonzalez, A., Tinahones Madueno, F., Trescoli Serrano, C., Ulied Arminana, A., Bachus, E., Berndtsson Blom, K., Eliasson, K., Koskinen, P., Larnefeldt, H., Lif-Tiberg, C., Linderfalk, C., Lund, G., Lundman, P., Moris, L., Olsson, A., Salmonsson, S., Sanmartin Berglund, J., Sjoberg, F., Soderberg, S., Torstensson, I., Chen, J. -F., Tien, K. J., Tseng, S. -T., Tu, S. -T., Wang, C. -Y., Wang, J. -H., Phrommintikul, A., Yamwong, S., Jintapakorn, W., Hutayanon, P., Sansanayudh, N., Bazhan, L., Fushtey, I., Grachova, M., Katerenchuk, V., Korpachev, V., Kravchun, N., Larin, O., Mykhalchyshyn, G., Myshanych, H., Oleksyk, O., Orlenko, V., Pashkovska, N., Pertseva, N., Petrosyan, O., Smirnov, I., Vlasenko, M., Zlova, T., Aye, M., Baksi, A., Balasubramani, M., Beboso, R., Blagden, M., Bundy, C., Cookson, T., Copland, A., Emslie-Smith, A., Green, F., Gunstone, A., Issa, B., Jackson-Voyzey, E., Johnson, A., Maclean, M., Mcknight, J., Muzulu, S., O'Connell, I., Oyesile, B., Patterson, C., Pearson, E., Philip, S., Smith, P., Sukumaran, U., Abbas, J., Aggarwala, G., Akhter, F., Andersen, J., Anglade, M., Argoud, G., Ariani, M., Ashdji, R., Bakhtari, L., Banerjee, S., Bartlett, A., Baum, H., Bays, H., Beasley, R., Belfort de Aguiar, R., Benjamin, S., Bhagwat, R., Bhargava, A., Bode, B., Bratcher, C., Briskin, T., Brockmyre, A., Broughton, R., Brown, J., Budhraja, M., Cannon, K., Carr, J., Cathcart, H., Cavale, A., Chaykin, L., Cheung, D., Childress, R., Cohen, A., Condit, J., Cooksey, E., Cornett, G. M., Dauber, I., Davila, W., De Armas, L., Dean, J., Detweiler, R., Diaz, E., Di Giovanna, M., Dor, I., Drummond, W., Eagerton, D., Earl, J., Eaton, C., Ellison, H., Farris, N., Fiel, T., Firek, A., First, B., Forgosh, L., French, W., Gandy, W., Garcia, R., Gill, S., Gordon, M., Guice, M., Gummadi, S., Hackenyos, J., Hairston, K., Hanson, L., Harrison, L., Hartman, I., Heitner, J., Hejeebu, S., Hermany, P., Hernandez-Cassis, C., Hidalgo, H., Higgins, A., Ibrahim, H., Jacobs, S., Johnson, D., Joshi, P., Kaster, S., Kellum, D., Kim, C., Kim, E., Kirby, W., Knouse, A., Kulback, S., Kumar, M., Kuruvanka, T., Labroo, A., Lasswell, W., Lentz, J., Lenzmeier, T., Lewis, D., Li, Z., Lillestol, M., Little, R., Lorraine, R., McKeown-Biagas, C., Mcneill, R., Mehta, A., Miller, A., Moran, J., Morawski, E., Nadar, V., O'Connor, T., Odio, A., Parker, R., Patel, R., Phillips, L., Raad, G., Rahman, A., Raikhel, M., Raisinghani, A., Rajan, R., Rasouli, N., Rauzi, F., Rohr, K., Roseman, H., Rovner, S., Saba, F., Sachson, R., Schabauer, A., Schneider, R., Schuchard, T., Sensenbrenner, J., Shlesinger, Y., Singh, N., Sivalingam, K., Stonesifer, L., Storey, D., Suh, D., Tahir, M., Tan, A., Tan, M., Taylon, A., Thakkar, M., Tripathy, D., Uwaifo, G., Vedere, A., Venugopal, C., Vo, A., Welch, M., Welker, J., White, A., Willis, J., Wynne, A., Yazdani, S., Price, L., Lokhngina, Y., Xing, W., Overton, R., Stewart, M., Stead, J., Lindsay, A., Patel, V., Ross, J., Soffer, J., Daga, S., Sowell, M., Patel, P., Garvey, L., Ackert, J., Abraham, S., Sabol, M. B., Altobelli, D., Ha, J., Kulkarni, M., Noronha, D., Casson, E., Zang, E., Sandhu, C., Kumar, R., Chen, D., Taft, L., Ye, J., Shannon, J., Wilson, T., Babi, C., Miller, D., Russell, R., Bull, G., Hereghty, B., Fernandez-Salazar, E., Longley, T., Donaldson, J., Jarosz, M., Murphy, K., Adams, P., James, R., Richards, J., Sedani, S., Althouse, D., Watson, D., Lorimer, J., Lauder, S., Schultheis, R., Womer, T., Wraight, E., Li, W., Price-Olsen, E., Watson, A., Kelly, A., Mclaughlin, P., Fleming, J., Schubert, J., Schleiden, D., Harris, T., Prakash, R., Breneman, J., Deshpande, S., Saswadkar, A., Kumari, A., Shitut, A., Raorane, A., Karmalkar, A., Mhambrey, A., Bhosale, A., Vaphare, A., Patil, A. P., Khandelwal, C., Shaik, F., Nadar, M., Karka, M., Kadgaonkar, N., Gupta, N., Aher, N., Potnis, O., Naicker, P., Shinde, R., Sharma, R., Godse, R., Solanki, S., Sahu, S., Dumbre, S., Kumar, S., Patil, S., Mandal, T., Skin function and permeability, Dermatology, Hernandez, A, Green, J, Janmohamed, S, D'Agostino, R, Granger, C, Jones, N, Leiter, L, Rosenberg, A, Sigmon, K, Somerville, M, Thorpe, K, Mcmurray, J, Del Prato, S, Califf, R, Holman, R, Demets, D, Riddle, M, Goodman, S, Mcguire, D, Alexander, K, Devore, A, Melloni, C, Patel, C, Kong, D, Bloomfield, G, Roe, M, Tricoci, P, Harrison, R, Lopes, R, Mathews, R, Mehta, R, Schuyler Jones, W, Vemulapalli, S, Povsic, T, Eapen, Z, Dombrowski, K, Kolls, B, Jordan, D, Ambrosy, A, Greene, S, Mandawat, A, Shavadia, J, Cooper, L, Sharma, A, Guimaraes, P, Friedman, D, Wilson, M, Endsley, P, Gentry, T, Collier, J, Perez, K, James, K, Roush, J, Pope, C, Howell, C, Johnson, M, Bailey, M, Cole, J, Akers, T, Vandyne, B, Thomas, B, Rich, J, Bartone, S, Beaulieu, G, Brown, K, Chau, T, Christian, T, Coker, R, Greene, D, Haddock, T, Jenkins, W, Haque, G, Marquess, M, Pesarchick, J, Rethaford, R, Stone, A, Al Kawas, F, Anderson, M, Enns, R, Sinay, I, Mathieu, C, Yordanov, V, Hramiak, I, Haluzik, M, Galatius, S, Guerci, B, Nauck, M, Migdalis, I, Tan, C, Kocsis, G, Giaccari, A, Lee, M, Munoz, E, Cornel, J, Birkeland, K, Pinto, M, Tirador, L, Olesinska-Mader, M, Shestakova, M, Distiller, L, Lopez-Sendon, J, Eliasson, B, Chiang, C, Srimahachota, S, Mankovsky, B, Bethel, M, Dungan, K, Kosiborod, M, Alvarisqueta, A, Baldovino, J, Besada, D, Calella, P, Cantero, M, Castano, P, Chertkoff, A, Cuadrado, J, De Loredo, L, Dominguez, A, Espanol, M, Finkelstein, H, Frechtel, G, Fretes, J, Garrido Santos, N, Gonzalez, J, Litvak, M, Loureyro, J, Maffei, L, Maldonado, N, Mohr Gasparini, D, Orio, S, Perez Manghi, F, Rodriguez Papini, N, Sala, J, Schygiel, P, Sposetti, G, Ulla, M, Verra, F, Zabalua, S, Zaidman, C, Crenier, L, Debroye, C, Duyck, F, Scheen, A, Van Gaal, L, Vercammen, C, Damyanova, V, Dimitrov, S, Kovacheva, S, Lozanov, L, Margaritov, V, Mihaylova-Shumkova, R, Nikolaeva, A, Stoyanova, Z, Akhras, R, Beaudry, Y, Bedard, J, Berlingieri, J, Chehayeb, R, Cheung, S, Conway, J, Cusson, J, Della Siega, A, Dumas, R, Dzongowski, P, Ferguson, M, Gaudet, D, Grondin, F, Gupta, A, Gupta, M, Halperin, F, Houle, P, Jones, M, Kouz, S, Kovacs, C, Landry, D, Lonn, E, O'Mahony, W, Peterson, S, Reich, D, Rosenbloom, A, St-Maurice, F, Tugwell, B, Vizel, S, Woo, V, Brychta, T, Cech, V, Dvorakova, E, Edelsberger, T, Halciakova, K, Krizova, J, Lastuvka, J, Piperek, M, Prymkova, V, Raclavska, L, Silhova, E, Urbanek, R, Vrkoc, J, Andersen, U, Bronnum-Schou, J, Hove, J, Jensen, J, Kober, L, Kristiansen, O, Lund, P, Melchior, T, Nyvad, O, Schou, M, Boye, A, Cadinot, D, Gouet, D, Henry, P, Kessler, L, Lalau, J, Petit, C, Thuan, J, Voinot, C, Vouillarmet, J, Axthelm, C, Berger, D, Bieler, T, Birkenfeld, A, Bott, J, Busch, K, Caca, K, Chevts, J, Donaubauer, T, Erlinger, R, Funke, K, Grosskopf, J, Hagenow, A, Hamann, M, Hartard, M, Heymer, P, Huppertz, W, Illies, G, Jacob, S, Jung, T, Kahrmann, G, Kast, P, Kellerer, M, Kempe, H, Khariouzov, A, Klausmann, G, Klein, C, Kleinecke-Pohl, U, Kleinertz, K, Koch, T, Kosch, C, Lorra, B, Luedemann, J, Luttermann, M, Maxeiner, S, Milek, K, Moelle, A, Neumann, G, Nischik, R, Oehrig-Pohl, E, Plassmann, G, Pohlmeier, L, Proepper, F, Regner, S, Rieker, W, Rose, L, Samer, H, Sauter, J, Schaper, F, Schiffer, C, Schmidt, J, Scholz, B, Schulze, J, Segner, A, Seufert, J, Sigal, H, Steindorf, J, Stockhausen, J, Stuebler, P, Taeschner, H, Tews, D, Tschoepe, D, Wilhelm, K, Zeller-Stefan, H, Avramidis, I, Bousboulas, S, Bristianou, M, Dimitriadis, G, Elisaf, M, Kotsa, K, Melidonis, A, Mitrakou, A, Pagkalos, E, Papanas, N, Pappas, A, Sampanis, C, Tentolouris, N, Tsapas, A, Tzatzagou, G, Ozaki, R, Hajdu, C, Harcsa, E, Konyves, L, Mucsi, J, Pauker, Z, Petro, G, Ples, Z, Revesz, K, Sandor, V, Vass, V, Avogaro, A, Boemi, M, Bonadonna, R, Consoli, A, De Cosmo, S, Di Bartolo, P, Dotta, F, Frontoni, S, Galetta, M, Gambineri, A, Gazzaruso, C, Giorgino, F, Lauro, D, Orsi, E, Paolisso, G, Perriello, G, Piatti, P, Pontiroli, A, Ponzani, P, Rivellese, A, Sesti, G, Tonolo, G, Trevisan, R, Ahn, C, Baik, S, Cha, B, Chung, C, Jang, H, Kim, C, Kim, H, Kim, I, Lee, E, Lee, H, Lee, K, Moon, K, Namgung, J, Park, K, Yoo, S, Yu, J, Llamas, E, Cervantes-Escarcega, J, Flota-Cervera, L, Gonzalez-Gonzalez, J, Pascoe-Gonzalez, S, Pelayo-Orozco, E, Ramirez-Diaz, S, Saldana-Mendoza, A, Jerjes-Diaz, C, Torres-Colores, J, Vidrio-Velazquez, M, Villagordoa-Mesa, J, Beijerbacht, H, Groutars, R, Hoek, B, Hoogslag, P, Kooy, A, Kragten, J, Lieverse, A, Swart, H, Viergever, E, Ahlqvist, J, Cooper, J, Gulseth, H, Guttormsen, G, Wium, C, Arbanil, H, Calderon, J, Camacho, L, Espinoza, A, Garrido, E, Luna, A, Manrique, H, Revoredo, F, Gonzales, R, Rincon, L, Zubiate, C, Ebo, G, Morales-Palomares, E, Arciszewska, M, Banach, M, Bijata-Bronisz, R, Derezinski, T, Gadzinski, W, Gajek, J, Klodawska, K, Krzyzagorska, E, Madej, A, Miekus, P, Opiela, J, Romanczuk, P, Siegel, A, Skokowska, E, Stankiewicz, A, Stasinska, T, Trznadel-Morawska, I, Witek, R, Aksentyev, S, Bondar, I, Demidova, I, Dreval, A, Ershova, O, Galstyan, G, Garganeeva, A, Izmozherova, N, Karetnikova, V, Kharakhulakh, M, Khokhlov, A, Kobalava, Z, Koshelskaya, O, Kosmacheva, E, Kostin, V, Koziolova, N, Kuzin, A, Lesnov, V, Lysenko, T, Markov, V, Mayorov, A, Moiseev, S, Myasoedova, S, Petunina, N, Rebrov, A, Ruyatkina, L, Samoylova, J, Sazonova, O, Shilkina, N, Sokolova, N, Vasilevskaya, O, Verbovaya, N, Vishneva, E, Vorobyev, S, Vorokhobina, N, Zanozina, O, Zhdanova, E, Zykova, T, Burgess, L, Coetzee, K, Dawood, S, Lombard, L, Makotoko, E, Moodley, R, Oosthuysen, W, Sarvan, M, Calvo Gomez, C, Cano Rodriguez, I, Castro Conde, A, Cequier Fillat, A, Cuatrecasas Cambra, G, de Alvaro Moreno, F, De Teresa Parreno, L, Delgado Lista, J, Dominguez Escribano, J, Duran Garcia, S, Elvira Gonzalez, J, Fernandez Rodriguez, J, Goday Arno, A, Gomez Huelgas, R, Gonzalez Juanatey, J, Hernandez Mijares, A, Jimenez Diaz, V, Jodar Gimeno, E, Lucas Morante, T, Marazuela, M, Martell Claros, N, Mauricio Puente, D, Mena Ribas, E, Merino Torres, J, Mezquita Raya, P, Nubiola Calonge, A, Ordonez Sanchez, X, Pascual Izuel, J, Perea Castilla, V, Perez Perez, A, Perez Soto, I, Quesada Charneco, M, Quesada Simon, A, Redon Mas, J, Rego Iraeta, A, Rodriguez Alvarez, M, Rodriguez Rodriguez, I, Saban Ruiz, J, Soto Gonzalez, A, Tinahones Madueno, F, Trescoli Serrano, C, Ulied Arminana, A, Bachus, E, Berndtsson Blom, K, Eliasson, K, Koskinen, P, Larnefeldt, H, Lif-Tiberg, C, Linderfalk, C, Lund, G, Lundman, P, Moris, L, Olsson, A, Salmonsson, S, Sanmartin Berglund, J, Sjoberg, F, Soderberg, S, Torstensson, I, Chen, J, Tien, K, Tseng, S, Tu, S, Wang, C, Wang, J, Phrommintikul, A, Yamwong, S, Jintapakorn, W, Hutayanon, P, Sansanayudh, N, Bazhan, L, Fushtey, I, Grachova, M, Katerenchuk, V, Korpachev, V, Kravchun, N, Larin, O, Mykhalchyshyn, G, Myshanych, H, Oleksyk, O, Orlenko, V, Pashkovska, N, Pertseva, N, Petrosyan, O, Smirnov, I, Vlasenko, M, Zlova, T, Aye, M, Baksi, A, Balasubramani, M, Beboso, R, Blagden, M, Bundy, C, Cookson, T, Copland, A, Emslie-Smith, A, Green, F, Gunstone, A, Issa, B, Jackson-Voyzey, E, Johnson, A, Maclean, M, Mcknight, J, Muzulu, S, O'Connell, I, Oyesile, B, Patterson, C, Pearson, E, Philip, S, Smith, P, Sukumaran, U, Abbas, J, Aggarwala, G, Akhter, F, Andersen, J, Anglade, M, Argoud, G, Ariani, M, Ashdji, R, Bakhtari, L, Banerjee, S, Bartlett, A, Baum, H, Bays, H, Beasley, R, Belfort de Aguiar, R, Benjamin, S, Bhagwat, R, Bhargava, A, Bode, B, Bratcher, C, Briskin, T, Brockmyre, A, Broughton, R, Brown, J, Budhraja, M, Cannon, K, Carr, J, Cathcart, H, Cavale, A, Chaykin, L, Cheung, D, Childress, R, Cohen, A, Condit, J, Cooksey, E, Cornett, G, Dauber, I, Davila, W, De Armas, L, Dean, J, Detweiler, R, Diaz, E, Di Giovanna, M, Dor, I, Drummond, W, Eagerton, D, Earl, J, Eaton, C, Ellison, H, Farris, N, Fiel, T, Firek, A, First, B, Forgosh, L, French, W, Gandy, W, Garcia, R, Gill, S, Gordon, M, Guice, M, Gummadi, S, Hackenyos, J, Hairston, K, Hanson, L, Harrison, L, Hartman, I, Heitner, J, Hejeebu, S, Hermany, P, Hernandez-Cassis, C, Hidalgo, H, Higgins, A, Ibrahim, H, Jacobs, S, Johnson, D, Joshi, P, Kaster, S, Kellum, D, Kim, E, Kirby, W, Knouse, A, Kulback, S, Kumar, M, Kuruvanka, T, Labroo, A, Lasswell, W, Lentz, J, Lenzmeier, T, Lewis, D, Li, Z, Lillestol, M, Little, R, Lorraine, R, McKeown-Biagas, C, Mcneill, R, Mehta, A, Miller, A, Moran, J, Morawski, E, Nadar, V, O'Connor, T, Odio, A, Parker, R, Patel, R, Phillips, L, Raad, G, Rahman, A, Raikhel, M, Raisinghani, A, Rajan, R, Rasouli, N, Rauzi, F, Rohr, K, Roseman, H, Rovner, S, Saba, F, Sachson, R, Schabauer, A, Schneider, R, Schuchard, T, Sensenbrenner, J, Shlesinger, Y, Singh, N, Sivalingam, K, Stonesifer, L, Storey, D, Suh, D, Tahir, M, Tan, A, Tan, M, Taylon, A, Thakkar, M, Tripathy, D, Uwaifo, G, Vedere, A, Venugopal, C, Vo, A, Welch, M, Welker, J, White, A, Willis, J, Wynne, A, Yazdani, S, Price, L, Lokhngina, Y, Xing, W, Overton, R, Stewart, M, Stead, J, Lindsay, A, Patel, V, Ross, J, Soffer, J, Daga, S, Sowell, M, Patel, P, Garvey, L, Ackert, J, Abraham, S, Sabol, M, Altobelli, D, Ha, J, Kulkarni, M, Noronha, D, Casson, E, Zang, E, Sandhu, C, Kumar, R, Chen, D, Taft, L, Ye, J, Shannon, J, Wilson, T, Babi, C, Miller, D, Russell, R, Bull, G, Hereghty, B, Fernandez-Salazar, E, Longley, T, Donaldson, J, Jarosz, M, Murphy, K, Adams, P, James, R, Richards, J, Sedani, S, Althouse, D, Watson, D, Lorimer, J, Lauder, S, Schultheis, R, Womer, T, Wraight, E, Li, W, Price-Olsen, E, Watson, A, Kelly, A, Mclaughlin, P, Fleming, J, Schubert, J, Schleiden, D, Harris, T, Prakash, R, Breneman, J, Deshpande, S, Saswadkar, A, Kumari, A, Shitut, A, Raorane, A, Karmalkar, A, Mhambrey, A, Bhosale, A, Vaphare, A, Patil, A, Khandelwal, C, Shaik, F, Nadar, M, Karka, M, Kadgaonkar, N, Gupta, N, Aher, N, Potnis, O, Naicker, P, Shinde, R, Sharma, R, Godse, R, Solanki, S, Sahu, S, Dumbre, S, Kumar, S, Patil, S, and Mandal, T

Subjects
Male, Placebo-controlled study, Myocardial Infarction, alanine aminotransferase, albiglutide, bilirubin, placebo, antidiabetic agent, glucagon like peptide 1, rGLP-1 protein, Kaplan-Meier Estimate, 030204 cardiovascular system & hematology, law.invention, 0302 clinical medicine, Randomized controlled trial, law, Glucagon-Like Peptide 1, Cardiovascular Disease, Medicine(all), education.field_of_study, Subcutaneous, Medicine (all), albigutide, Hazard ratio, General Medicine, Middle Aged, Albiglutide, Stroke, Treatment Outcome, Tolerability, Cardiovascular Diseases, Female, type 2 diabetes, Type 2, Human, Adult, medicine.medical_specialty, Injections, Subcutaneous, Population, 030209 endocrinology & metabolism, Placebo, Injections, Subcutaneou, Drug Administration Schedule, Injections, 03 medical and health sciences, Double-Blind Method, Internal medicine, Diabetes Mellitus, medicine, Humans, Hypoglycemic Agents, education, Aged, Diabetes Mellitus, Type 2, Hypoglycemic Agent, business.industry, Semaglutide, Settore MED/13 - ENDOCRINOLOGIA, Harmony, business
Abstract

Background: \ud Glucagon-like peptide 1 receptor agonists differ in chemical structure, duration of action, and in their effects on clinical outcomes. The cardiovascular effects of once-weekly albiglutide in type 2 diabetes are unknown. We aimed to determine the safety and efficacy of albiglutide in preventing cardiovascular death, myocardial infarction, or stroke.\ud \ud Methods: \ud We did a double-blind, randomised, placebo-controlled trial in 610 sites across 28 countries. We randomly assigned patients aged 40 years and older with type 2 diabetes and cardiovascular disease (at a 1:1 ratio) to groups that either received a subcutaneous injection of albiglutide (30–50 mg, based on glycaemic response and tolerability) or of a matched volume of placebo once a week, in addition to their standard care. Investigators used an interactive voice or web response system to obtain treatment assignment, and patients and all study investigators were masked to their treatment allocation. We hypothesised that albiglutide would be non-inferior to placebo for the primary outcome of the first occurrence of cardiovascular death, myocardial infarction, or stroke, which was assessed in the intention-to-treat population. If non-inferiority was confirmed by an upper limit of the 95% CI for a hazard ratio of less than 1·30, closed testing for superiority was prespecified. This study is registered with ClinicalTrials.gov, number NCT02465515.\ud \ud Findings: \ud Patients were screened between July 1, 2015, and Nov 24, 2016. 10 793 patients were screened and 9463 participants were enrolled and randomly assigned to groups: 4731 patients were assigned to receive albiglutide and 4732 patients to receive placebo. On Nov 8, 2017, it was determined that 611 primary endpoints and a median follow-up of at least 1·5 years had accrued, and participants returned for a final visit and discontinuation from study treatment; the last patient visit was on March 12, 2018. These 9463 patients, the intention-to-treat population, were evaluated for a median duration of 1·6 years and were assessed for the primary outcome. The primary composite outcome occurred in 338 (7%) of 4731 patients at an incidence rate of 4·6 events per 100 person-years in the albiglutide group and in 428 (9%) of 4732 patients at an incidence rate of 5·9 events per 100 person-years in the placebo group (hazard ratio 0·78, 95% CI 0·68–0·90), which indicated that albiglutide was superior to placebo (p

Published
2018

20. A Study of Enhancement, Augmentation, and Autoencoder Methods for Domain Adaptation in Distant Speech Recognition

Author

Wei-Ning Hsu, Francois Grondin, James Glass, and Hao Tang

Subjects
FOS: Computer and information sciences, Sound (cs.SD), Computer Science - Computation and Language, Computer science, Speech recognition, Perspective (graphical), Word error rate, Autoencoder, Computer Science - Sound, Machine Learning (cs.LG), Speech enhancement, Data set, Computer Science - Learning, Transformation (function), Audio and Speech Processing (eess.AS), FOS: Electrical engineering, electronic engineering, information engineering, Adaptation (computer science), Focus (optics), Computation and Language (cs.CL), Electrical Engineering and Systems Science - Audio and Speech Processing
Abstract

Speech recognizers trained on close-talking speech do not generalize to distant speech and the word error rate degradation can be as large as 40% absolute. Most studies focus on tackling distant speech recognition as a separate problem, leaving little effort to adapting close-talking speech recognizers to distant speech. In this work, we review several approaches from a domain adaptation perspective. These approaches, including speech enhancement, multi-condition training, data augmentation, and autoencoders, all involve a transformation of the data between domains. We conduct experiments on the AMI data set, where these approaches can be realized under the same controlled setting. These approaches lead to different amounts of improvement under their respective assumptions. The purpose of this paper is to quantify and characterize the performance gap between the two domains, setting up the basis for studying adaptation of speech recognizers from close-talking speech to distant speech. Our results also have implications for improving distant speech recognition., Comment: Interspeech, 2018

Published
2018
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21. Localization of RW-UAVs using particle filtering over distributed microphone arrays

Author

Jean-Samuel Lauzon, François Michaud, Dominic Létourneau, Francois Grondin, and Alexis Lussier Desbiens

Subjects
0209 industrial biotechnology, Observer (quantum physics), Computer science, business.industry, Microphone, 02 engineering and technology, Acoustic source localization, Drone, Background noise, Noise, 020901 industrial engineering & automation, Position (vector), 0202 electrical engineering, electronic engineering, information engineering, 020201 artificial intelligence & image processing, Computer vision, Artificial intelligence, business, Particle filter
Abstract

Rotary-Wing Air Vehicles (RW-UAVs), also referred to as drones, have gained in popularity over the last few years. Intrusions over secured areas have become common and authorities are actively looking for solutions to detect and localize undesired drones. The sound generated by the propellers of the RW-UAVs is powerful enough to be perceived by a human observer nearby. In this paper, we examine the use of particle filtering to detect and localize in 3D the position of a RW-UAV based on sound source localization (SSL) over distributed microphone arrays (MAs). Results show that the proposed method is able to detect and track a drone with precision, as long as the noise emitted by the RW-UAVs dominates the background noise.

Published
2017
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22. Adding navigation, artificial audition and vital sign monitoring capabilities to a telepresence mobile robot for remote home care applications

Author

Janice M. Polgar, François Michaud, Sebastien Laniel, Francois Grondin, Dominic Létourneau, and Mathieu Labbé

Subjects
0209 industrial biotechnology, Engineering, 020205 medical informatics, 02 engineering and technology, 020901 industrial engineering & automation, Human–computer interaction, 0202 electrical engineering, electronic engineering, information engineering, Humans, Monitoring, Physiologic, Telerobotics, Robot kinematics, Social robot, Vital Signs, business.industry, Mobile robot, Equipment Design, Robotics, Self-Help Devices, Home Care Services, Telemedicine, Mobile robot navigation, Robot control, Embedded system, Teleoperation, Robot, business
Abstract

A telepresence mobile robot is a remote-controlled, wheeled device with wireless internet connectivity for bidirectional audio, video and data transmission. In health care, a telepresence robot could be used to have a clinician or a caregiver assist seniors in their homes without having to travel to these locations. Many mobile telepresence robotic platforms have recently been introduced on the market, bringing mobility to telecommunication and vital sign monitoring at reasonable costs. What is missing for making them effective remote telepresence systems for home care assistance are capabilities specifically needed to assist the remote operator in controlling the robot and perceiving the environment through the robot's sensors or, in other words, minimizing cognitive load and maximizing situation awareness. This paper describes our approach adding navigation, artificial audition and vital sign monitoring capabilities to a commercially available telepresence mobile robot. This requires the use of a robot control architecture to integrate the autonomous and teleoperation capabilities of the platform.

Published
2017
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23. Enhancing a beam+ telepresence robot for remote home care applications

Author

Francois Grondin, Sebastien Laniel, François Michaud, Dominic Létourneau, and Mathieu Labbé

Subjects
0209 industrial biotechnology, Telerobotics, SIMPLE (military communications protocol), business.industry, Computer science, 05 social sciences, Mobile robot, 02 engineering and technology, Robot control, 020901 industrial engineering & automation, Human–computer interaction, Embedded system, Health care, Robot control architecture, Robot, 0501 psychology and cognitive sciences, business, 050107 human factors, Vital sign monitoring
Abstract

The aging population is putting increasing pressure on health care systems in many developed countries, and maintaining quality of care while controlling costs becomes a major issue that needs to be addressed. With platforms now available at 2,000 $US, telepresence robots are one potential solution to provide remote care services to elders living in their homes. However, they need improved capabilities to make them more than simple “Skype on wheels” devices. To make telepresence robots suitable for remote home care applications, they must offer enhanced and robust functionalities such as autonomous navigation, artificial audition and vital sign monitoring. Therefore, we integrated such capabilities on a beam+ platform using a robot control architecture, demonstrating the feasibility of adding these capabilities on a commercial robot.

Published
2017
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24. A quadtree replication method to optimize web and mobile applications dealing with large sets of objects on a map

Author

Eric Beaudry, Francois Grondin, Patrick Munroe, Naouel Moha, and Jonathan Milot

Subjects
Computer science, Quality of service, Distributed computing, Real-time computing, CPU time, Response time, 02 engineering and technology, Client-side, Replication (computing), 020204 information systems, 0202 electrical engineering, electronic engineering, information engineering, Bandwidth (computing), Quadtree, 020201 artificial intelligence & image processing, Server-side
Abstract

This paper presents an original caching method called Minimal Quadtree Replication (MQTR) for Web and Mobile Applications (WMA) to query and display large sets of objects on a map. This method pre-builds a quadtree at the server side that is incrementally replicated at the client side. Our method tends to avoid useless queries and to minimize the overlaps of content when similar queries to remote services are done. This caching method offers benefits that increase the quality of service (QoS) provided by the WMA using it, when measured in terms of CPU time, bandwidth, and response time. We compared our MQTR approach with common approaches that are currently used by some popular web sites. Results show that MQTR significantly outperforms the other approaches. The best variant of our method reduces in average the number of requests by a factor of 5.5, transfers 3.9 times less data and requires 2.4 times less CPU time at the server side.

Published
2017
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25. The ManyEars open framework

Author

Vincent Rousseau, François Ferland, François Michaud, Francois Grondin, and Dominic Létourneau

Subjects
Microphone array, Microphone, Computer science, business.industry, Acoustic source localization, Modular design, computer.software_genre, Sound card, Software framework, Artificial Intelligence, Audio signal processing, business, computer, Computer hardware, Graphical user interface
Abstract

ManyEars is an open framework for microphone array-based audio processing. It consists of a sound source localization, tracking and separation system that can provide an enhanced speaker signal for improved speech and sound recognition in real-world settings. ManyEars software framework is composed of a portable and modular C library, along with a graphical user interface for tuning the parameters and for real-time monitoring. This paper presents the integration of the ManyEars Library with Willow Garage's Robot Operating System. To facilitate the use of ManyEars on various robotic platforms, the paper also introduces the customized microphone board and sound card distributed as an open hardware solution for implementation of robotic audition systems.

Published
2013
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26. Integration framework for speech processing with live visualization interfaces

Author

Yazid Attabi, Francois Grondin, François Michaud, David Brodeur, and Pierre Dumouchel

Subjects
0209 industrial biotechnology, Voice activity detection, Computer science, Speech recognition, Speech corpus, Speech synthesis, 02 engineering and technology, Acoustic source localization, Speech processing, computer.software_genre, Visualization, 030507 speech-language pathology & audiology, 03 medical and health sciences, 020901 industrial engineering & automation, Speech analytics, 0305 other medical science, computer
Abstract

Audition is a rich source of spatial, identity, linguistic and paralinguistic information. Processing all this information requires acquisition, processing and interpretation of sound sources, which are instantaneous, invisible and noisy signals. This can lead to different responses by the system in relation to the information perceived. This paper presents our first implementation of an integration framework for speech processing. Acquisition includes sound capture, sound source localization, tracking, separation and enhancement, and voice activity detection. Processing involves speech and emotion recognition. Interpretation consists of translating speech utterances into commands that can influence interaction through dialogue management and speech synthesis. The paper also describes two visualization interfaces, inspired by comic strips, to represent live vocal interactions in real life environments. These interfaces are used to demonstrate how the framework performs in live interactions and its use in a usability study.

Published
2016
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27. Noise mask for TDOA sound source localization of speech on mobile robots in noisy environments

Author

François Michaud and Francois Grondin

Subjects
0209 industrial biotechnology, Engineering, geography, geography.geographical_feature_category, business.industry, Speech recognition, Mobile robot, 02 engineering and technology, Acoustic source localization, Multilateration, Background noise, Noise, 020901 industrial engineering & automation, Computer Science::Sound, Colors of noise, Broadband, 0202 electrical engineering, electronic engineering, information engineering, 020201 artificial intelligence & image processing, business, Sound (geography)
Abstract

Sound source localization is an important challenge for mobile robots operating in real life settings. Sound sources of interest, such as speech, are often corrupted by broadband coherent noise sound source(s) that are non-stationary during transitions between steady-state segments. The interfering noise introduces localization ambiguities leading to the localization of invalid sound sources. Masks to reduce such interferences perform well under stationary noise, but the performance degrades as localization of invalid sound sources generated by noise appear and disappear suddenly during transitions between steady-state. This paper presents a new mask based on speech non-stationarity to discriminate between the time difference of arrival (TDOA) of speech source and noise transition. Simulations and experiments on a mobile robot suggest that the proposed technique improve TDOA discrimination and reduces significantly localization of invalid sound sources caused by noise.

Published
2016
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28. Robust speech/non-speech discrimination based on pitch estimation for mobile robots

Author

François Michaud and Francois Grondin

Subjects
0209 industrial biotechnology, Reverberation, Engineering, business.industry, Speech recognition, Latency (audio), Mobile robot, 02 engineering and technology, Mixture model, 030507 speech-language pathology & audiology, 03 medical and health sciences, Noise, ComputingMethodologies_PATTERNRECOGNITION, 020901 industrial engineering & automation, Speech discrimination, Position (vector), 0305 other medical science, Environmental noise, business
Abstract

To be used on a mobile robot, speech/non-speech discrimination must be robust to environmental noise and to the position of the interlocutor, without necessarily having to satisfy low-latency requirements. To address these conditions, this paper presents a speech/non-speech discrimination approach based on pitch estimation. Pitch features are robust to noise and reverberation, and can be estimated over a few seconds. Results suggest that our approach is more robust compared to the use of Mel-Frequency Cepstrum Coefficients with Gaussian Mixture Models (MFCC-GMM) under high reverberation levels and additive noise (with an accuracy above 98% with a latency of 2.21 sec), which makes it ideal for mobile robot applications. The approach is also validated on a mobile robot equipped with a 8-microphone array, using speech/non-speech discrimination based on pitch estimation as a post-processing module of a localization, tracking and separation system.

Published
2016
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29. Lookupia

Author

Jonathan Milot, Eric Beaudry, Guillaume Bourdeau, Patrick Munroe, and Francois Grondin

Subjects
020203 distributed computing, Point of interest, business.industry, Computer science, 0211 other engineering and technologies, Real estate, 02 engineering and technology, General Transit Feed Specification, Transport engineering, Search engine, Public transport, 0202 electrical engineering, electronic engineering, information engineering, Web application, business, Transit (satellite), Simulation, 021101 geological & geomatics engineering
Abstract

Lookupia is an intelligent real estate search engine for finding houses optimally geolocated to reach points of interest. It uses data from OpenStreetMap and most of public transit corporations that publish transit schedules in the General Transit Feed Specification (GTFS) format.

Published
2016
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30. Time difference of arrival estimation based on binary frequency mask for sound source localization on mobile robots

Author

Francois Grondin and François Michaud

Subjects
Sound localization, Engineering, business.industry, Speech recognition, Binary number, Mobile robot, Acoustic source localization, Multilateration, Noise, Signal-to-noise ratio, Robustness (computer science), Computer vision, Artificial intelligence, business
Abstract

Localization of sound sources in adverse environments is an important challenge in robot audition. The target sound source is often corrupted by coherent broadband noise, which introduces localization ambiguities as noise is often mistaken as the target source. To discriminate the time difference of arrival (TDOA) parameters of the target source and noise, this paper presents a binary mask for weighted generalized cross-correlation with phase transform (GCC-PHAT). Simulation and experiments on a mobile robot suggest that the proposed technique improves TDOA discrimination. It also brings the additional benefit of modulating the computing load requirement according to voice activity.

Published
2015
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31. Multimodal biometric identification system for mobile robots combining human metrology to face recognition and speaker identification

Author

Francis Leconte, Francois Grondin, François Michaud, and Simon Ouellet

Subjects
Background subtraction, Modality (human–computer interaction), Biometrics, business.industry, Computer science, Speech recognition, Feature extraction, Mobile robot, Speaker recognition, Facial recognition system, Identification (information), Multimodal biometrics, Three-dimensional face recognition, Computer vision, Artificial intelligence, business
Abstract

Recognizing a person from a distance is important to establish meaningful social interaction and to provide additional cues regarding the situations experienced by a robot. To do so, face recognition and speaker identification are biometrics commonly used, with identification performance that are influenced by the distance between the person and the robot. This paper presents a system that combines these biometrics with human metrology (HM) to increase identification performance and range. HM measures are derived from 2D silhouettes extracted online using a dynamic background subtraction approach, processing in parallel 45 front features and 24 side features in 400 ms compared to 38 front and 22 side features extracted in sequence in 30 sec by using the approach presented by Lin and Wang [1]. By having each modality identify a set of up to five possible candidates, results suggest that combining modalities provide better performance compared to what each individual modality provides, from a wider range of distances.

Published
2014
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32. WISS, a speaker identification system for mobile robots

Author

Francois Grondin and François Michaud

Subjects
Noise, Engineering, Signal-to-noise ratio, Noise measurement, business.industry, Speech recognition, Speaker identification, Mobile robot, Acoustic source localization, business, Speaker recognition, Hidden Markov model
Abstract

This paper presents WISS, a speaker identification system for mobile robots integrated to ManyEars, a sound source localization, tracking and separation system. Speaker identification consists in recognizing an individual among a group of known speakers. For mobile robots, performing speaker identification in presence of noise that changes over time is one important challenge. To deal with this issue, WISS uses Parallel Model Combination (PMC) and masks to update in real-time the speaker models (obtained in clean conditions) to both additive and convolutive noises. The results show that the weighted rate of good speaker identifications is 96% on average for a Signal-to-Noise Ratio (SNR) of 16 dB, whereas it only decreases to 84% when the SNR drops to 2 dB.

Published
2012
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33. ODAS: Open embeddeD Audition System

Author

François Grondin, Dominic Létourneau, Cédric Godin, Jean-Samuel Lauzon, Jonathan Vincent, Simon Michaud, Samuel Faucher, and François Michaud

Subjects
robot audition, sound source localization, microphone array, embedded computing, open source framework, Mechanical engineering and machinery, TJ1-1570, Electronic computers. Computer science, QA75.5-76.95
Abstract

Artificial audition aims at providing hearing capabilities to machines, computers and robots. Existing frameworks in robot audition offer interesting sound source localization, tracking and separation performance, although involve a significant amount of computations that limit their use on robots with embedded computing capabilities. This paper presents ODAS, the Open embeddeD Audition System framework, which includes strategies to reduce the computational load and perform robot audition tasks on low-cost embedded computing systems. It presents key features of ODAS, along with cases illustrating its uses in different robots and artificial audition applications.

Published
2022
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34. Evaluation of Various State of the Art Head Pose Estimation Algorithms for Clinical Scenarios

Author

Yassine Hammadi, François Grondin, François Ferland, and Karina Lebel

Subjects
movement analysis, face recognition, neural networks, OpenFace 2.0, 3DDFA_V2, realsense, Chemical technology, TP1-1185
Abstract

Head pose assessment can reveal important clinical information on human motor control. Quantitative assessment have the potential to objectively evaluate head pose and movements’ specifics, in order to monitor the progression of a disease or the effectiveness of a treatment. Optoelectronic camera-based motion-capture systems, recognized as a gold standard in clinical biomechanics, have been proposed for head pose estimation. However, these systems require markers to be positioned on the person’s face which is impractical for everyday clinical practice. Furthermore, the limited access to this type of equipment and the emerging trend to assess mobility in natural environments support the development of algorithms capable of estimating head orientation using off-the-shelf sensors, such as RGB cameras. Although artificial vision is a popular field of research, limited validation of human pose estimation based on image recognition suitable for clinical applications has been performed. This paper first provides a brief review of available head pose estimation algorithms in the literature. Current state-of-the-art head pose algorithms designed to capture the facial geometry from videos, OpenFace 2.0, MediaPipe and 3DDFA_V2, are then further evaluated and compared. Accuracy is assessed by comparing both approaches to a baseline, measured with an optoelectronic camera-based motion-capture system. Results reveal a mean error lower or equal to 5.6∘ for 3DDFA_V2 depending on the plane of movement, while the mean error reaches 14.1∘ and 11.0∘ for OpenFace 2.0 and MediaPipe, respectively. This demonstrates the superiority of the 3DDFA_V2 algorithm in estimating head pose, in different directions of motion, and suggests that this algorithm can be used in clinical scenarios.

Published
2022
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35. Machine Learning for Touch Localization on an Ultrasonic Lamb Wave Touchscreen

Author

Sahar Bahrami, Jérémy Moriot, Patrice Masson, and François Grondin

Subjects
signal processing, machine earning, ultrasonic wave, touch technology, human–machine interface, Chemical technology, TP1-1185
Abstract

Classification and regression employing a simple Deep Neural Network (DNN) are investigated to perform touch localization on a tactile surface using ultrasonic guided waves. A robotic finger first simulates the touch action and captures the data to train a model. The model is then validated with data from experiments conducted with human fingers. The localization root mean square errors (RMSE) in time and frequency domains are presented. The proposed method provides satisfactory localization results for most human–machine interactions, with a mean error of 0.47 cm and standard deviation of 0.18 cm and a computing time of 0.44 ms. The classification approach is also adapted to identify touches on an access control keypad layout, which leads to an accuracy of 97% with a computing time of 0.28 ms. These results demonstrate that DNN-based methods are a viable alternative to signal processing-based approaches for accurate and robust touch localization using ultrasonic guided waves.

Published
2022
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