A Web-Based Platform for Hand Rehabilitation Assessment

Hand impairment affects millions of people. There are multiple factors that cause deficits, varying from physical injuries to neurological disorders. Upper-limb patients face significant difficulties in daily life. Rehabilitation aims at supporting them to regain functionality and increasing their independence and quality of life. Assessment is key to therapy, as it offers an evaluation of the condition of patients, leading to suitable treatments. Unfortunately, rehabilitation relies on clinical resources, making it expensive and time-consuming. Digital technology can provide solutions that make treatments more flexible and affordable. With the use of computer vision, we created an online platform that includes several exercises and serious games, based on movements and gestures performed in real-world treatments. Difficulty levels vary, and therapists can monitor these procedures remotely, while performance can be stored and tracked over time, identifying improvement. There is no need for any special equipment, as the platform can be accessed like a common website and all its applications require only a simple computer camera and stable Internet connection. In this article, we present our research approach, we analyze the development of the platform, and we provide a brief demonstration of its use in practice. Furthermore, we address some technical challenges and we share the results derived from preliminary test phases, concluding by outlining future plans.

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Publication Details

Journal
Big Data and Cognitive Computing
Published
2025-02-24
DOI
https://doi.org/10.3390/bdcc9030052
Citations
2
Primary Topic
Stroke Rehabilitation and Recovery
Type
article
Field-Weighted Citation Impact
2.05
Controls
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article

A Web-Based Platform for Hand Rehabilitation Assessment

Nikolaos D. Tselikas, Dimitrios N. Soumis
2 citations
Big Data and Cognitive Computing
Stroke Rehabilitation and Recovery
2.05
article

A Web-Based Platform for Hand Rehabilitation Assessment

Nikolaos D. Tselikas, Dimitrios N. Soumis
article en
2 citations

Abstract

Hand impairment affects millions of people. There are multiple factors that cause deficits, varying from physical injuries to neurological disorders. Upper-limb patients face significant difficulties in daily life. Rehabilitation aims at supporting them to regain functionality and increasing their independence and quality of life. Assessment is key to therapy, as it offers an evaluation of the condition of patients, leading to suitable treatments. Unfortunately, rehabilitation relies on clinical resources, making it expensive and time-consuming. Digital technology can provide solutions that make treatments more flexible and affordable. With the use of computer vision, we created an online platform that includes several exercises and serious games, based on movements and gestures performed in real-world treatments. Difficulty levels vary, and therapists can monitor these procedures remotely, while performance can be stored and tracked over time, identifying improvement. There is no need for any special equipment, as the platform can be accessed like a common website and all its applications require only a simple computer camera and stable Internet connection. In this article, we present our research approach, we analyze the development of the platform, and we provide a brief demonstration of its use in practice. Furthermore, we address some technical challenges and we share the results derived from preliminary test phases, concluding by outlining future plans.

Big Data and Cognitive ComputingVol. 9(3)
University of Peloponnese (GR)
Openalex Percentile: Top 15%
Stroke Rehabilitation and Recovery
2.05
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