A low-cost wearable system to support upper limb rehabilitation in resource-constrained settings

Ahmed, Md. Sabbir, Amir, Shajnush, Atiba, Samuelson ORCID: https://orcid.org/0000-0001-5913-4503, Rony, Rahat Jahangir, Verdezoto Dias, Nervo ORCID: https://orcid.org/0000-0001-5006-4262, Sparkes, Valerie ORCID: https://orcid.org/0000-0003-4500-9327, Stawarz, Katarzyna ORCID: https://orcid.org/0000-0001-9021-0615 and Ahmed, Nova 2022. A low-cost wearable system to support upper limb rehabilitation in resource-constrained settings. Presented at: EAI PervasiveHealth 2022 - 16th EAI International Conference on Pervasive Computing Technologies for Healthcare, Thessaloniki, Greece, 12-14 December 2022.

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Abstract

There is a lack of professional rehabilitation therapists and facilities in low-resource settings such as Bangladesh. In particular, the restrictively high costs of rehabilitative therapy have prompted a search for alternatives to tradi- tional in-patient/out-patient hospital rehabilitation moving therapy outside healthcare settings. Considering the potential for home-based rehabilitation, we implemented a low-cost wearable system for 5 basic exercises namely, hand raised, wrist flexion, wrist extension, wrist pronation, and wrist supination, of upper limb (UL) rehabilitation through the incorporation of physiotherapists’ per- spectives. As a proof of concept, we collected data through our system from 10 Bangladeshi participants: 9 researchers and 1 undergoing physical therapy. Lev- eraging the system’s sensed data, we developed a diverse set of machine learning models. and selected important features through three feature selection ap- proaches: filter, wrapper, and embedded. We find that the Multilayer Perceptron classification model, which was developed by the embedded method Random Forest selected features, can identify the five exercises with a ROC-AUC score of 98.2% and sensitivity of 98%. Our system has the potential for providing real- time insights regarding the precision of the exercises which can facilitate home- based UL rehabilitation in resource-constrained settings.

Item Type:	Conference or Workshop Item (Paper)
Date Type:	Submission
Status:	Unpublished
Schools:	Healthcare Sciences Computer Science & Informatics
Subjects:	T Technology > T Technology (General)
Date of First Compliant Deposit:	15 November 2022
Last Modified:	10 Jun 2023 01:34
URI:	https://orca.cardiff.ac.uk/id/eprint/154233

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