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Your search keyword '"Département Electronique et Physique (TSP - EPH)"' showing total 3 results
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3 results on '"Département Electronique et Physique (TSP - EPH)"'

1. Voice characteristics from isolated rapid eye movement sleep behavior disorder to early Parkinson's disease

Author

Laetitia Jeancolas, Graziella Mangone, Dijana Petrovska-Delacrétaz, Habib Benali, Badr-Eddine Benkelfat, Isabelle Arnulf, Jean-Christophe Corvol, Marie Vidailhet, Stéphane Lehéricy, Center for NeuroImaging Research-Human MRI Neuroimaging core facility for clinical research [ICM Paris] (CENIR), Institut du Cerveau = Paris Brain Institute (ICM), Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Institut National de la Santé et de la Recherche Médicale (INSERM)-CHU Pitié-Salpêtrière [AP-HP], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Sorbonne Université (SU)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Institut National de la Santé et de la Recherche Médicale (INSERM)-CHU Pitié-Salpêtrière [AP-HP], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Sorbonne Université (SU)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), Institut Polytechnique de Paris (IP Paris), Département Electronique et Physique (TSP - EPH), Institut Mines-Télécom [Paris] (IMT)-Télécom SudParis (TSP), ARMEDIA (ARMEDIA-SAMOVAR), Services répartis, Architectures, MOdélisation, Validation, Administration des Réseaux (SAMOVAR), Institut Mines-Télécom [Paris] (IMT)-Télécom SudParis (TSP)-Institut Mines-Télécom [Paris] (IMT)-Télécom SudParis (TSP), Centre d'investigation clinique Neurosciences [CHU Pitié Salpêtrière] (CIC Neurosciences), Centre d'investigation clinique pluridisciplinaire [CHU Pitié Salpêtrière] (CIC-P 1421), Institut National de la Santé et de la Recherche Médicale (INSERM)-CHU Pitié-Salpêtrière [AP-HP], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Institut National de la Santé et de la Recherche Médicale (INSERM)-CHU Pitié-Salpêtrière [AP-HP], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU), PERFORM Centre, Electrical and Computer Engineering Department [Concordia] (ECE), Concordia University [Montreal], Traitement de l'Information Pour Images et Communications (TIPIC-SAMOVAR), Service de Pathologies du sommeil [CHU Pitié-Salpêtrière], CHU Pitié-Salpêtrière [AP-HP], Service de Neuroradiologie [CHU Pitié-Salpêtrière], and BENKELFAT, Badr-Eddine

Subjects
Male, [SCCO.NEUR]Cognitive science/Neuroscience, [SCCO.NEUR] Cognitive science/Neuroscience, [INFO.INFO-NE] Computer Science [cs]/Neural and Evolutionary Computing [cs.NE], Prodromal Symptoms, Parkinson Disease, [INFO.INFO-LG] Computer Science [cs]/Machine Learning [cs.LG], REM Sleep Behavior Disorder, [INFO.INFO-NE]Computer Science [cs]/Neural and Evolutionary Computing [cs.NE], Speech Disorders, [INFO.INFO-LG]Computer Science [cs]/Machine Learning [cs.LG], Neurology, Acoustic analysis, Parkinson’s disease, Supervised classification, Voice, Humans, Female, Neurology (clinical), Geriatrics and Gerontology, [SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing, [SPI.SIGNAL] Engineering Sciences [physics]/Signal and Image processing
Abstract

International audience; Background: Speech disorders are amongst the first symptoms to appear in Parkinson's disease (PD). Objectives: We aimed to characterize PD voice signature from the prodromal stage (isolated rapid eye movement sleep behavior disorder, iRBD) to early PD using an automated acoustic analysis and compare male and female patients. We carried out supervised learning classifications to automatically detect patients using voice only. Methods: Speech samples were acquired in 256 French speakers (117 participants with early PD, 41 with iRBD, and 98 healthy controls), with a professional quality microphone, a computer microphone and their own telephone. High-level features related to prosody, phonation, speech fluency and rhythm abilities were extracted. Group analyses were performed to determine the most discriminant features, as well as the impact of sex, vocal tasks, and microphone type. These speech features were used as inputs of a support vector machine and were combined with classifiers using low-level features. Results: PD related impairments were found in prosody, pause durations and rhythmic abilities, from the prodromal stage. These alterations were more pronounced in men than in women. Early PD detection was achieved with a balanced accuracy of 89% in males and 70% in females. Participants with iRBD were detected with a balanced accuracy of 63% (reaching 70% in the subgroup with mild motor symptoms). Conclusion: This study provides new insight in the characterization of sex-dependent early PD speech impairments, and demonstrates the valuable benefit of including automated voice analysis in future diagnostic procedures of prodromal PD.

Published
2022
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2. Integrated lasers on silicon for optical communications

Author

Manel Ramirez, Joan, Souleiman, Amin, Fanneau, Pierre, Besancon, Claire, Vaissiere, Nicolas, Neel, Delphine, Ramez, Valentin, Malhouitre, Stéphane, Hassan, Karim, Merghem, Kamel, Decobert, Jean, Bitauld, David, Nokia Bell Labs [Paris-Saclay], Institut Polytechnique de Paris (IP Paris), Département Electronique et Physique (TSP - EPH), Institut Mines-Télécom [Paris] (IMT)-Télécom SudParis (TSP), Traitement de l'Information Pour Images et Communications (TIPIC-SAMOVAR), Services répartis, Architectures, MOdélisation, Validation, Administration des Réseaux (SAMOVAR), Institut Mines-Télécom [Paris] (IMT)-Télécom SudParis (TSP)-Institut Mines-Télécom [Paris] (IMT)-Télécom SudParis (TSP), Alcatel-Thalès III-V lab (III-V Lab), THALES [France]-ALCATEL, Commissariat à l'énergie atomique et aux énergies alternatives - Laboratoire d'Electronique et de Technologie de l'Information (CEA-LETI), Direction de Recherche Technologique (CEA) (DRT (CEA)), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA), Alcatel-Thales III-V Lab (III-V Lab ), and THALES [France]

Subjects
[PHYS]Physics [physics], Silicon, Optical communications, Lasers
Abstract

We review our work on integrated lasers for optical communications. An InP-based multilayer stack containing Al-based quantum wells with optical gain in the telecom window is bonded onto a silicon-on-insulator wafer with patterned photonic circuits and cavities. Ring-based widely tunable lasers and narrow linewidth DFB lasers are demonstrated.

Published
2023
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3. Treatment outcome prediction using multi-task learning: application to botulinum toxin in gait rehabilitation

Author

Adil Khan, Antoine Hazart, Omar Galarraga, Sonia Garcia-Salicetti, Vincent Vigneron, Informatique, BioInformatique, Systèmes Complexes (IBISC), Université d'Évry-Val-d'Essonne (UEVE)-Université Paris-Saclay, Institut Polytechnique de Paris (IP Paris), Département Electronique et Physique (TSP - EPH), Institut Mines-Télécom [Paris] (IMT)-Télécom SudParis (TSP), ARMEDIA (ARMEDIA-SAMOVAR), Services répartis, Architectures, MOdélisation, Validation, Administration des Réseaux (SAMOVAR), and Institut Mines-Télécom [Paris] (IMT)-Télécom SudParis (TSP)-Institut Mines-Télécom [Paris] (IMT)-Télécom SudParis (TSP)

Subjects
Cerebral Palsy, Deep learning, Biochemistry, Atomic and Molecular Physics, and Optics, Analytical Chemistry, Clinical gait analysis, Treatment Outcome, multi-task learning, clinical gait analysis, gait rehabilitation, deep learning, long short-term memory, botulinum toxin, Neuromuscular Agents, Muscle Spasticity, Botulinum toxin, Multi-task learning, Long short-term memory, Humans, Electrical and Electronic Engineering, Botulinum Toxins, Type A, Instrumentation, Gait, [SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing, Gait rehabilitation
Abstract

We propose a framework for optimizing personalized treatment outcomes for patients with neurological diseases. A typical consequence of such diseases is gait disorders, partially explained by command and muscle tone problems associated with spasticity. Intramuscular injection of botulinum toxin type A is a common treatment for spasticity. According to the patient’s profile, offering the optimal treatment combined with the highest possible benefit-risk ratio is important. For the prediction of knee and ankle kinematics after botulinum toxin type A (BTX-A) treatment, we propose: (1) a regression strategy based on a multi-task architecture composed of LSTM models; (2) to introduce medical treatment data (MTD) for context modeling; and (3) a gating mechanism to model treatment interaction more efficiently. The proposed models were compared with and without metadata describing treatments and with serial models. Multi-task learning (MTL) achieved the lowest root-mean-squared error (RMSE) (5.60°) for traumatic brain injury (TBI) patients on knee trajectories and the lowest RMSE (3.77°) for cerebral palsy (CP) patients on ankle trajectories, with only a difference of 5.60° between actual and predicted. Overall, the best RMSE ranged from 5.24° to 6.24° for the MTL models. To the best of our knowledge, this is the first time that MTL has been used for post-treatment gait trajectory prediction. The MTL models outperformed the serial models, particularly when introducing treatment metadata. The gating mechanism is efficient in modeling treatment interaction and improving trajectory prediction.

Published
2022
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