research-article

A Home Rehabilitation System Motivating Stroke Patients with Upper and/or Lower Limb Disability

Authors:

Michael Opoku Agyeman,

Ali Al-Mahmood,

Igla HoxhaAuthors Info & Claims

ISCSIC 2019: Proceedings of the 2019 3rd International Symposium on Computer Science and Intelligent Control

Article No.: 64, Pages 1 - 6

https://doi.org/10.1145/3386164.3386168

Published: 06 June 2020 Publication History

Abstract

Stroke survivors often suffer from a permanent or partial disability that restricts the movement of the hands, arms and/or legs. To help patients recover, rehabilitation should be at an earlier stage of the injury. Without motivation, it would be challenging for patients to successfully engage in the recovery process which can sometimes be painful of inconvenient. The application of wearable devices, games and Internet-of-Things (IoT) can create a motivating atmosphere to facilitate the rehabilitation process of patients while enabling remote monitoring of their health and progress. This paper presents the design and implementation of a rehabilitation system for aimed at helping stroke patients suffering from upper limb disability that exploits IoT by integrating gaming and wearable technology.

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Michael Opoku Agyeman, Ali Al-Mahmood: Design and Implementation of a Wearable Device for Motivating Patients With Upper and/or Lower Limb Disability Via Gaming and Home Rehabilitation. FMEC 2019: 247--252

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Cited By

Loewen GCochrane KGirouard A(2024)From Imagination to Innovation: Using Participatory Design Fiction to Envision the Future of Accessible Gaming Wearables for Players with Upper Limb Motor DisabilitiesProceedings of the ACM on Human-Computer Interaction10.1145/36770738:CHI PLAY(1-30)Online publication date: 15-Oct-2024
https://dl.acm.org/doi/10.1145/3677073
Opoku Agyeman MGuerrero AVien Q(2022)Classification Techniques for Arrhythmia Patterns Using Convolutional Neural Networks and Internet of Things (IoT) DevicesIEEE Access10.1109/ACCESS.2022.319239010(87387-87403)Online publication date: 2022
https://doi.org/10.1109/ACCESS.2022.3192390
Edughele HZhang YMuhammad-Sukki FVien QMorris-Cafiero HOpoku Agyeman M(2022)Eye-Tracking Assistive Technologies for Individuals With Amyotrophic Lateral SclerosisIEEE Access10.1109/ACCESS.2022.316407510(41952-41972)Online publication date: 2022
https://doi.org/10.1109/ACCESS.2022.3164075
Show More Cited By

Index Terms

A Home Rehabilitation System Motivating Stroke Patients with Upper and/or Lower Limb Disability
1. Hardware
  1. Communication hardware, interfaces and storage
    1. Printers

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cover image ACM Other conferences

ISCSIC 2019: Proceedings of the 2019 3rd International Symposium on Computer Science and Intelligent Control

September 2019

397 pages

ISBN:9781450376617

DOI:10.1145/3386164

Copyright © 2019 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Publication History

Published: 06 June 2020

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ISCSIC 2019

ISCSIC 2019: 2019 3rd International Symposium on Computer Science and Intelligent Control

September 25 - 27, 2019

Amsterdam, Netherlands

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ISCSIC 2019 Paper Acceptance Rate 77 of 152 submissions, 51%;

Overall Acceptance Rate 192 of 401 submissions, 48%

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Cited By

Loewen GCochrane KGirouard A(2024)From Imagination to Innovation: Using Participatory Design Fiction to Envision the Future of Accessible Gaming Wearables for Players with Upper Limb Motor DisabilitiesProceedings of the ACM on Human-Computer Interaction10.1145/36770738:CHI PLAY(1-30)Online publication date: 15-Oct-2024
https://dl.acm.org/doi/10.1145/3677073
Opoku Agyeman MGuerrero AVien Q(2022)Classification Techniques for Arrhythmia Patterns Using Convolutional Neural Networks and Internet of Things (IoT) DevicesIEEE Access10.1109/ACCESS.2022.319239010(87387-87403)Online publication date: 2022
https://doi.org/10.1109/ACCESS.2022.3192390
Edughele HZhang YMuhammad-Sukki FVien QMorris-Cafiero HOpoku Agyeman M(2022)Eye-Tracking Assistive Technologies for Individuals With Amyotrophic Lateral SclerosisIEEE Access10.1109/ACCESS.2022.316407510(41952-41972)Online publication date: 2022
https://doi.org/10.1109/ACCESS.2022.3164075
Halisyah AHumaidi RRafly MSilvia CAdiputra D(2022)A Review for Designing a Low-Cost Online Lower Limb Monitoring System of a Post-stroke RehabilitationProceedings of the 2nd International Conference on Electronics, Biomedical Engineering, and Health Informatics10.1007/978-981-19-1804-9_36(479-490)Online publication date: 25-Jun-2022
https://doi.org/10.1007/978-981-19-1804-9_36
Ferre MBatista ESolanas AMartínez-Ballesté A(2021)Smart Health-Enhanced Early Mobilisation in Intensive Care UnitsSensors10.3390/s2116540821:16(5408)Online publication date: 10-Aug-2021
https://doi.org/10.3390/s21165408
Akbari AHaghverd FBehbahani S(2021)Robotic Home-Based Rehabilitation Systems Design: From a Literature Review to a Conceptual Framework for Community-Based Remote Therapy During COVID-19 PandemicFrontiers in Robotics and AI10.3389/frobt.2021.6123318Online publication date: 22-Jun-2021
https://doi.org/10.3389/frobt.2021.612331
Alarcón-Aldana ACallejas-Cuervo MBo A(2020)Upper Limb Physical Rehabilitation Using Serious Videogames and Motion Capture Systems: A Systematic ReviewSensors10.3390/s2021598920:21(5989)Online publication date: 22-Oct-2020
https://doi.org/10.3390/s20215989

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