Functional Movement Screen (FMS) Computerized Automated Scoring Technology Research

Functional Movement Screen (FMS) is an evaluation system widely utilized in various fields such as physical therapy, rehabilitation, physical fitness training, and sports education. Its objective is to assess the performance of individuals in areas such as movement control, balance, and agility. FMS has been extensively employed, requiring substantial manpower. This study is grounded in the FMS scoring criteria and employs the Azure Kinect depth camera to capture three-dimensional skeletal sequence data of the test subject's movements. Through a fully automated process, FMS scoring is initially conducted. Within this automated process, manifold learning algorithms and the dynamic time warping (DTW) algorithm are applied to recognize key frames. The implementation of this approach establishes an automated scoring system for FMS, offering insights for the advancement of human posture assessment systems rooted in functional movements. This contributes to the widespread application of FMS systems.

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Publication Details

Published
2024-08-15
DOI
https://doi.org/10.1109/prai62207.2024.10826745
Primary Topic
Ergonomics and Musculoskeletal Disorders
Type
article
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article

Functional Movement Screen (FMS) Computerized Automated Scoring Technology Research

Yiteng Jin, Lin‐Tao Fu, Xia Zheng, HE Yu-hua
Ergonomics and Musculoskeletal Disorders
article

Functional Movement Screen (FMS) Computerized Automated Scoring Technology Research

Yiteng Jin, Lin‐Tao Fu, Xia Zheng, HE Yu-hua
article en

Abstract

Functional Movement Screen (FMS) is an evaluation system widely utilized in various fields such as physical therapy, rehabilitation, physical fitness training, and sports education. Its objective is to assess the performance of individuals in areas such as movement control, balance, and agility. FMS has been extensively employed, requiring substantial manpower. This study is grounded in the FMS scoring criteria and employs the Azure Kinect depth camera to capture three-dimensional skeletal sequence data of the test subject's movements. Through a fully automated process, FMS scoring is initially conducted. Within this automated process, manifold learning algorithms and the dynamic time warping (DTW) algorithm are applied to recognize key frames. The implementation of this approach establishes an automated scoring system for FMS, offering insights for the advancement of human posture assessment systems rooted in functional movements. This contributes to the widespread application of FMS systems.

Wenzhou University (CN)
Openalex Percentile: Top 66%
Ergonomics and Musculoskeletal Disorders
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