Evaluating the Performance of Balance Physiotherapy Exercises Using a Sensory Platform: The Basis for a Persuasive Balance Rehabilitation Virtual Coaching System

Rehabilitation programs play an important role in improving the quality of life of patients with balance disorders. Such programs are usually executed in a home environment, due to lack of resources. This procedure usually results in poorly performed exercises or even complete drop outs from the pro...

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Main Authors: Vassilios D. Tsakanikas, Dimitrios Gatsios, Dimitrios Dimopoulos, Athanasios Pardalis, Marousa Pavlou, Matthew B. Liston, Dimitrios I. Fotiadis
Format: Article
Language:English
Published: Frontiers Media S.A. 2020-11-01
Series:Frontiers in Digital Health
Subjects:
Online Access:https://www.frontiersin.org/articles/10.3389/fdgth.2020.545885/full
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language English
format Article
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author Vassilios D. Tsakanikas
Dimitrios Gatsios
Dimitrios Dimopoulos
Athanasios Pardalis
Marousa Pavlou
Matthew B. Liston
Dimitrios I. Fotiadis
spellingShingle Vassilios D. Tsakanikas
Dimitrios Gatsios
Dimitrios Dimopoulos
Athanasios Pardalis
Marousa Pavlou
Matthew B. Liston
Dimitrios I. Fotiadis
Evaluating the Performance of Balance Physiotherapy Exercises Using a Sensory Platform: The Basis for a Persuasive Balance Rehabilitation Virtual Coaching System
Frontiers in Digital Health
virtual coach
persuasive technology
motion capture
motor score
balance disorders
physiotherapy exercises
author_facet Vassilios D. Tsakanikas
Dimitrios Gatsios
Dimitrios Dimopoulos
Athanasios Pardalis
Marousa Pavlou
Matthew B. Liston
Dimitrios I. Fotiadis
author_sort Vassilios D. Tsakanikas
title Evaluating the Performance of Balance Physiotherapy Exercises Using a Sensory Platform: The Basis for a Persuasive Balance Rehabilitation Virtual Coaching System
title_short Evaluating the Performance of Balance Physiotherapy Exercises Using a Sensory Platform: The Basis for a Persuasive Balance Rehabilitation Virtual Coaching System
title_full Evaluating the Performance of Balance Physiotherapy Exercises Using a Sensory Platform: The Basis for a Persuasive Balance Rehabilitation Virtual Coaching System
title_fullStr Evaluating the Performance of Balance Physiotherapy Exercises Using a Sensory Platform: The Basis for a Persuasive Balance Rehabilitation Virtual Coaching System
title_full_unstemmed Evaluating the Performance of Balance Physiotherapy Exercises Using a Sensory Platform: The Basis for a Persuasive Balance Rehabilitation Virtual Coaching System
title_sort evaluating the performance of balance physiotherapy exercises using a sensory platform: the basis for a persuasive balance rehabilitation virtual coaching system
publisher Frontiers Media S.A.
series Frontiers in Digital Health
issn 2673-253X
publishDate 2020-11-01
description Rehabilitation programs play an important role in improving the quality of life of patients with balance disorders. Such programs are usually executed in a home environment, due to lack of resources. This procedure usually results in poorly performed exercises or even complete drop outs from the programs, as the patients lack guidance and motivation. This paper introduces a novel system for managing balance disorders in a home environment using a virtual coach for guidance, instruction, and inducement. The proposed system comprises sensing devices, augmented reality technology, and intelligent inference agents, which capture, recognize, and evaluate a patient's performance during the execution of exercises. More specifically, this work presents a home-based motion capture and assessment module, which utilizes a sensory platform to recognize an exercise performed by a patient and assess it. The sensory platform comprises IMU sensors (Mbientlab MMR© 9axis), pressure insoles (Moticon©), and a depth RGB camera (Intel D415©). This module is designed to deliver messages both during the performance of the exercise, delivering personalized notifications and alerts to the patient, and after the end of the exercise, scoring the overall performance of the patient. A set of proof of concept validation studies has been deployed, aiming to assess the accuracy of the different components for the sub-modules of the motion capture and assessment module. More specifically, Euler angle calculation algorithm in 2D (R2 = 0.99) and in 3D (R2 = 0.82 in yaw plane and R2 = 0.91 for the pitch plane), as well as head turns speed (R2 = 0.96), showed good correlation between the calculated and ground truth values provided by experts' annotations. The posture assessment algorithm resulted to accuracy = 0.83, while the gait metrics were validated against two well-established gait analysis systems (R2 = 0.78 for double support, R2 = 0.71 for single support, R2 = 0.80 for step time, R2 = 0.75 for stride time (WinTrack©), R2 = 0.82 for cadence, and R2 = 0.79 for stride time (RehaGait©). Validation results provided evidence that the proposed system can accurately capture and assess a physiotherapy exercise within the balance disorders context, thus providing a robust basis for the virtual coaching ecosystem and thereby improve a patient's commitment to rehabilitation programs while enhancing the quality of the performed exercises. In summary, virtual coaching can improve the quality of the home-based rehabilitation programs as long as it is combined with accurate motion capture and assessment modules, which provides to the virtual coach the capacity to tailor the interaction with the patient and deliver personalized experience.
topic virtual coach
persuasive technology
motion capture
motor score
balance disorders
physiotherapy exercises
url https://www.frontiersin.org/articles/10.3389/fdgth.2020.545885/full
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spelling doaj-e5b5621c75ce40c9ac73a22717450f452020-12-08T08:41:02ZengFrontiers Media S.A.Frontiers in Digital Health2673-253X2020-11-01210.3389/fdgth.2020.545885545885Evaluating the Performance of Balance Physiotherapy Exercises Using a Sensory Platform: The Basis for a Persuasive Balance Rehabilitation Virtual Coaching SystemVassilios D. Tsakanikas0Dimitrios Gatsios1Dimitrios Dimopoulos2Athanasios Pardalis3Marousa Pavlou4Matthew B. Liston5Dimitrios I. Fotiadis6Unit of Medical Technology and Intelligent Information Systems, Department of Materials Science and Engineering, University of Ioannina, Ioannina, GreeceUnit of Medical Technology and Intelligent Information Systems, Department of Materials Science and Engineering, University of Ioannina, Ioannina, GreeceUnit of Medical Technology and Intelligent Information Systems, Department of Materials Science and Engineering, University of Ioannina, Ioannina, GreeceUnit of Medical Technology and Intelligent Information Systems, Department of Materials Science and Engineering, University of Ioannina, Ioannina, GreeceCentre for Human and Applied Physiological Sciences, King's College London, London, United KingdomCentre for Human and Applied Physiological Sciences, King's College London, London, United KingdomUnit of Medical Technology and Intelligent Information Systems, Department of Materials Science and Engineering, University of Ioannina, Ioannina, GreeceRehabilitation programs play an important role in improving the quality of life of patients with balance disorders. Such programs are usually executed in a home environment, due to lack of resources. This procedure usually results in poorly performed exercises or even complete drop outs from the programs, as the patients lack guidance and motivation. This paper introduces a novel system for managing balance disorders in a home environment using a virtual coach for guidance, instruction, and inducement. The proposed system comprises sensing devices, augmented reality technology, and intelligent inference agents, which capture, recognize, and evaluate a patient's performance during the execution of exercises. More specifically, this work presents a home-based motion capture and assessment module, which utilizes a sensory platform to recognize an exercise performed by a patient and assess it. The sensory platform comprises IMU sensors (Mbientlab MMR© 9axis), pressure insoles (Moticon©), and a depth RGB camera (Intel D415©). This module is designed to deliver messages both during the performance of the exercise, delivering personalized notifications and alerts to the patient, and after the end of the exercise, scoring the overall performance of the patient. A set of proof of concept validation studies has been deployed, aiming to assess the accuracy of the different components for the sub-modules of the motion capture and assessment module. More specifically, Euler angle calculation algorithm in 2D (R2 = 0.99) and in 3D (R2 = 0.82 in yaw plane and R2 = 0.91 for the pitch plane), as well as head turns speed (R2 = 0.96), showed good correlation between the calculated and ground truth values provided by experts' annotations. The posture assessment algorithm resulted to accuracy = 0.83, while the gait metrics were validated against two well-established gait analysis systems (R2 = 0.78 for double support, R2 = 0.71 for single support, R2 = 0.80 for step time, R2 = 0.75 for stride time (WinTrack©), R2 = 0.82 for cadence, and R2 = 0.79 for stride time (RehaGait©). Validation results provided evidence that the proposed system can accurately capture and assess a physiotherapy exercise within the balance disorders context, thus providing a robust basis for the virtual coaching ecosystem and thereby improve a patient's commitment to rehabilitation programs while enhancing the quality of the performed exercises. In summary, virtual coaching can improve the quality of the home-based rehabilitation programs as long as it is combined with accurate motion capture and assessment modules, which provides to the virtual coach the capacity to tailor the interaction with the patient and deliver personalized experience.https://www.frontiersin.org/articles/10.3389/fdgth.2020.545885/fullvirtual coachpersuasive technologymotion capturemotor scorebalance disordersphysiotherapy exercises