Skeletons distance evaluation for automated control of exercises in physical therapy

Abstract. The paper focuses on developing a method for evaluating the similarity between skeletal models of an instructor and a patient during physical therapy exercises. Unlike general-purpose measures, our approach considers the specific characteristics of therapeutic exercises, including initial positioning, predominant movements, and exercise pace. By incorporating the concept of informativeness for skeletal points and refining normalization techniques, we improve the accuracy of pairwise dissimilarity measures. Experimental results demonstrate improved separability of records based on the accuracy of exercise repetition, highlighting the potential of this approach for enhancing automated physical rehabilitation systems.

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Publication Details

Journal
˜The œinternational archives of the photogrammetry, remote sensing and spatial information sciences/International archives of the photogrammetry, remote sensing and spatial information sciences
Published
2025-09-04
DOI
https://doi.org/10.5194/isprs-archives-xlviii-2-w9-2025-33-2025
Primary Topic
Stroke Rehabilitation and Recovery
Type
article
Field-Weighted Citation Impact
0.00

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article

Skeletons distance evaluation for automated control of exercises in physical therapy

Parama Bagchi, A.R. Tokarev, Oleg Seredin, Egor Surkov et al.
˜The œinternational archives of the photogrammetry, remote sensing and spatial information sciences/International archives of the photogrammetry, remote sensing and spatial information sciences
Stroke Rehabilitation and Recovery
article

Skeletons distance evaluation for automated control of exercises in physical therapy

Parama Bagchi, A.R. Tokarev, Oleg Seredin, Egor Surkov, Nikita Mityugov, Andrey Kopylov, Debotosh Bhattacharjee
article en

Abstract

Abstract. The paper focuses on developing a method for evaluating the similarity between skeletal models of an instructor and a patient during physical therapy exercises. Unlike general-purpose measures, our approach considers the specific characteristics of therapeutic exercises, including initial positioning, predominant movements, and exercise pace. By incorporating the concept of informativeness for skeletal points and refining normalization techniques, we improve the accuracy of pairwise dissimilarity measures. Experimental results demonstrate improved separability of records based on the accuracy of exercise repetition, highlighting the potential of this approach for enhancing automated physical rehabilitation systems.

˜The œinternational archives of the photogrammetry, remote sensing and spatial information sciences/International archives of the photogrammetry, remote sensing and spatial information sciencesVol. XLVIII-2/W9-2025
Tula State University (RU), Jadavpur University (IN)
Ministry of Science and Higher Education of the Russian Federation
Openalex Percentile: Top 71%
Stroke Rehabilitation and Recovery
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