Time Series Analysis of Muscle Deformation During Physiotherapy Using Optical Wearable Sensors

Wearable devices are used to acquire and analyze biometric information. However, the lack of consensus on standardized devices and analytical methods for representing the time series data of muscle force and coordination has hindered the interpretation and comparison of such data across studies. This study aimed to compare time series data between novices and experts during physiotherapy sessions to identify differences in the degree of force and coordination. Optical wearable muscle deformation sensor arrays were used to capture muscle bulging (muscle deformation) and visualize the force levels. Two types of physiotherapy sessions were conducted in the upper and lower limbs, and the time series data of muscle deformations collected during these sessions were analyzed using visualization, autocorrelation coefficients, and cross-correlation analysis. Although differences were observed visually and in effect sizes, no statistically significant group differences remained after covariate adjustment. The results revealed differences in the magnitude of force and muscle coordination. These findings highlight measurable distinctions in muscle activation patterns and coordination strategies between novices and experts, suggesting potential applications for training and skill evaluation in physiotherapy and related domains.

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Publication Details

Journal
Sensors
Published
2025-06-02
DOI
https://doi.org/10.3390/s25113507
Primary Topic
Muscle activation and electromyography studies
Type
article
Field-Weighted Citation Impact
0.00

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article

Time Series Analysis of Muscle Deformation During Physiotherapy Using Optical Wearable Sensors

Emi Tamaki, Satoshi Shimabukuro, Tamon Miyake
Sensors
Muscle activation and electromyography studies
article

Time Series Analysis of Muscle Deformation During Physiotherapy Using Optical Wearable Sensors

Emi Tamaki, Satoshi Shimabukuro, Tamon Miyake
article en

Abstract

Wearable devices are used to acquire and analyze biometric information. However, the lack of consensus on standardized devices and analytical methods for representing the time series data of muscle force and coordination has hindered the interpretation and comparison of such data across studies. This study aimed to compare time series data between novices and experts during physiotherapy sessions to identify differences in the degree of force and coordination. Optical wearable muscle deformation sensor arrays were used to capture muscle bulging (muscle deformation) and visualize the force levels. Two types of physiotherapy sessions were conducted in the upper and lower limbs, and the time series data of muscle deformations collected during these sessions were analyzed using visualization, autocorrelation coefficients, and cross-correlation analysis. Although differences were observed visually and in effect sizes, no statistically significant group differences remained after covariate adjustment. The results revealed differences in the magnitude of force and muscle coordination. These findings highlight measurable distinctions in muscle activation patterns and coordination strategies between novices and experts, suggesting potential applications for training and skill evaluation in physiotherapy and related domains.

SensorsVol. 25(11)
Waseda University (JP), University of the Ryukyus (JP), The University of Tokyo (JP)
New Energy and Industrial Technology Development Organization
Openalex Percentile: Top 89%
Muscle activation and electromyography studies
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