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13 results on '"Chatzaki, Chariklia"'

1. Multi-task Neural Networks for Pain Intensity Estimation using Electrocardiogram and Demographic Factors

Author

Gkikas, Stefanos, Chatzaki, Chariklia, and Tsiknakis, Manolis

Subjects
Computer Science - Artificial Intelligence, Computer Science - Computer Vision and Pattern Recognition
Abstract

Pain is a complex phenomenon which is manifested and expressed by patients in various forms. The immediate and objective recognition of it is a great of importance in order to attain a reliable and unbiased healthcare system. In this work, we elaborate electrocardiography signals revealing the existence of variations in pain perception among different demographic groups. We exploit this insight by introducing a novel multi-task neural network for automatic pain estimation utilizing the age and the gender information of each individual, and show its advantages compared to other approaches.

Published
2024
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2. Smart Insole: A Gait Analysis Monitoring Platform Targeting Parkinson Disease Patients Based on Insoles

Author

Boucharas, Dimitrios, Androutsos, Christos, Gkois, George, Tsakanikas, Vassilis, Pezoulas, Vasileios, Manousos, Dimitrios, Skaramagkas, Vasileios, Chatzaki, Chariklia, Kontogiannis, Stathis, Spandonidis, Christos, Pantazis, Alexandros, Tachos, Nikolaos, Tsiknakis, Manolis, and Fotiadis, Dimitrios

Subjects
Computer Science - Human-Computer Interaction
Abstract

During the preceding decades, human gait analysis has been the center of attention for the scientific community, while the association between gait analysis and overall health monitoring has been extensively reported. Technological advances further assisted in this alignment, resulting in access to inexpensive and remote healthcare services. Various assessment tools, such as software platforms and mobile applications, have been proposed by the scientific community and the market that employ sensors to monitor human gait for various purposes ranging from biomechanics to the progression of functional recovery. The framework presented herein offers a valuable digital biomarker for diagnosing and monitoring Parkinson's disease that can help clinical experts in the decision-making process leading to corrective planning or patient-specific treatment. More accurate and reliable decisions can be provided through a wide variety of integrated Artificial Intelligence algorithms and straightforward visualization techniques, including, but not limited to, heatmaps and bar plots. The framework consists of three core components: the insole pair, the mobile application, and the cloud-based platform. The insole pair deploys 16 plantar pressure sensors, an accelerometer, and a gyroscope to acquire gait data. The mobile application formulates the data for the cloud platform, which orchestrates the component interaction through the web application. Utilizing open communication protocols enables the straightforward replacement of one of the core components with a relative one (e.g., a different model of insoles), transparently from the end user, without affecting the overall architecture, resulting in a framework with the flexibility to adjust its modularity., Comment: 8 pages, 9 figures

Published
2022

4. Evaluating Gait Impairment in Parkinson’s Disease from Instrumented Insole and IMU Sensor Data

Author

Tsakanikas, Vassilis, primary, Ntanis, Adamantios, additional, Rigas, George, additional, Androutsos, Christos, additional, Boucharas, Dimitrios, additional, Tachos, Nikolaos, additional, Skaramagkas, Vasileios, additional, Chatzaki, Chariklia, additional, Kefalopoulou, Zinovia, additional, Tsiknakis, Manolis, additional, and Fotiadis, Dimitrios, additional

Published
2023
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5. Can Gait Features Help in Differentiating Parkinson’s Disease Medication States and Severity Levels? A Machine Learning Approach

Author

Chatzaki, Chariklia, primary, Skaramagkas, Vasileios, additional, Kefalopoulou, Zinovia, additional, Tachos, Nikolaos, additional, Kostikis, Nicholas, additional, Kanellos, Foivos, additional, Triantafyllou, Eleftherios, additional, Chroni, Elisabeth, additional, Fotiadis, Dimitrios I., additional, and Tsiknakis, Manolis, additional

Published
2022
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8. A training tool to support the management and diagnosis of Sjögren's syndrome

Author

Chatzaki, Chariklia, Goules, Andreas, De Vita, Salvatore, Zabotti, Alen, Delporte, Christine, Soyfoo, Muhammad Shahnawaz, Barone, Francesca, Fisher, Benjamin B.A., Brito-Zerón, Pilar, Bartoloni, Elena, Mavragani, Clio C.P., Fotiadis, Dimitrios Ioannis, Tzioufas, Athanasios, Tsiknakis, Manolis, Chatzaki, Chariklia, Goules, Andreas, De Vita, Salvatore, Zabotti, Alen, Delporte, Christine, Soyfoo, Muhammad Shahnawaz, Barone, Francesca, Fisher, Benjamin B.A., Brito-Zerón, Pilar, Bartoloni, Elena, Mavragani, Clio C.P., Fotiadis, Dimitrios Ioannis, Tzioufas, Athanasios, and Tsiknakis, Manolis

Abstract

Objective. The objective of this work is to present a Training Tool designed to support healthcare professionals involved in the diagnosis and management of Sjögren's syndrome. Methods. The Training Tool aims to fulfil the gap of targeted education by providing a structured protocol of training including state of the art guidelines and practices. For the development of the Training Tool, latest relevant technologies have been used to assure efficiency and usability. Core functionalities include training by a series of multimedia courses, testing during the learning process, and profiling for monitoring the progress. An iterative requirement analysis process was established involving a large number of clinical experts, with the objective to identify user's training needs. Results. Comprehensive usability evaluation was performed by applying, an Unmoderated Remote Usability Test resulting to 97.2% Success Rate; and the well-established System Usability Scale, reaching a score of 90.4 which classifies the Training Tool as "A"gradedexcellent. Conclusion. The Training Tool offers open-online training of healthcare professionals involved in the diagnosis and management of Sjögren's syndrome, using a well-designed training protocol in highly usable manner. To our knowledge, this is the first such tool for Sjögren's syndrome., SCOPUS: ar.j, info:eu-repo/semantics/published

Published
2021

10. A training tool to support the management and diagnosis of Sjögren's syndrome

Author

Chatzaki, Chariklia, Goules, Andreas, De Vita, Salvatore, Zabotti, Alen, Delporte, Christine, Soyfoo, Muhammad S, Barone, Francesca, Fisher, Benjamin A, Brito-Zerón, Pilar, Bartoloni, Elena, Mavragani, Clio P, Fotiadis, Dimitrios I, Tzioufas, Athanasios G, and Tsiknakis, Manolis

Subjects
usability, stratification, Sjogren's Syndrome, diagnosis, Health Personnel, education, training tool, Humans, Sjögren's syndrome, signs, biopsy, ultrasonography
Abstract

Objectives:The objective of this work is to present a Training Tool designed to support healthcare professionals involved in the diagnosis and management of Sjögren's syndrome. Methods:The Training Tool aims to fulfil the gap of targeted education by providing a structured protocol of training including state of the art guidelines and practices. For the development of the Training Tool, latest relevant technologies have been used to assure efficiency and usability. Core functionalities include training by a series of multimedia courses, testing during the learning process, and profiling for monitoring the progress. An iterative requirement analysis process was established involving a large number of clinical experts, with the objective to identify user's training needs. Results:Comprehensive usability evaluation was performed by applying, an Unmoderated Remote Usability Test resulting to 97.2% Success Rate; and the well-established System Usability Scale, reaching a score of 90.4 which classifies the Training Tool as "A" graded-excellent. Conclusions:The Training Tool offers open-online training of healthcare professionals involved in the diagnosis and management of Sjögren's syndrome, using a well-designed training protocol in highly usable manner. To our knowledge, this is the first such tool for Sjögren's syndrome.

12. Gait and balance patterns related to Free-Walking and TUG tests in Parkinson's Disease based on plantar pressure data.

Author

Tsakanikas VD, Dimopoulos DG, Tachos NS, Chatzaki C, Skaramagkas V, Christodoulakis G, Tsiknakis M, and Fotiadis DI

Subjects
Exercise Therapy, Gait, Humans, Walking, Gait Disorders, Neurologic, Parkinson Disease
Abstract

Continuous monitoring of patients with Parkinson's Disease (PD) is critical for their effective management, as early detection of improvement or degradation signs play an important role on pharmaceutical and/or interventional plans. Within this work, a group of seven PD patients and a group of ten controls performed a set of exercises related to the evaluation of PD gait. Plantar pressure signals were collected and used to derive a set of analytics. Statistical tests and feature selection approaches revealed that the spatial distribution of the Center of Pressure during a static balance exercise is the most discriminative analytic and may be used for every-day monitoring of the patients. Results have revealed that out of the 28 features extracted from the collected signals, 10 were statistically significant (p < 0.05) and can be used to machine learning algorithms and/or similar approaches.

Published
2021
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13. A Training Tool to support the management and diagnosis of Sjögren's syndrome.

Author

Chatzaki C, Goules A, De Vita S, Zabotti A, Delporte C, Soyfoo MS, Barone F, Fisher BA, Brito-Zerón P, Bartoloni E, Mavragani CP, Fotiadis DI, Tzioufas AG, and Tsiknakis M

Subjects
Health Personnel, Humans, Sjogren's Syndrome diagnosis, Sjogren's Syndrome therapy
Abstract

Objectives: The objective of this work is to present a Training Tool designed to support healthcare professionals involved in the diagnosis and management of Sjögren's syndrome., Methods: The Training Tool aims to fulfil the gap of targeted education by providing a structured protocol of training including state of the art guidelines and practices. For the development of the Training Tool, latest relevant technologies have been used to assure efficiency and usability. Core functionalities include training by a series of multimedia courses, testing during the learning process, and profiling for monitoring the progress. An iterative requirement analysis process was established involving a large number of clinical experts, with the objective to identify user's training needs., Results: Comprehensive usability evaluation was performed by applying, an Unmoderated Remote Usability Test resulting to 97.2% Success Rate; and the well-established System Usability Scale, reaching a score of 90.4 which classifies the Training Tool as "A" graded-excellent., Conclusions: The Training Tool offers open-online training of healthcare professionals involved in the diagnosis and management of Sjögren's syndrome, using a well-designed training protocol in highly usable manner. To our knowledge, this is the first such tool for Sjögren's syndrome.

Published
2020

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