A webcam-based machine learning approach for three-dimensional range of motion evaluation

TL;DR

This study introduces a webcam-based machine learning method for remote three-dimensional joint range of motion evaluation, offering a reliable alternative to traditional goniometry and marker-based systems for physical therapy assessments.

Contribution

The paper presents a novel, accessible, and reliable webcam-based system for 3D ROM measurement, validated against optical motion capture, suitable for tele-rehabilitation.

Findings

High test-retest reliability across joints

Substantial to almost perfect inter-rater reliability for some joints

Lower inter-rater reliability for shoulder and elbow flexion

Abstract

Background. Joint range of motion (ROM) is an important quantitative measure for physical therapy. Commonly relying on a goniometer, accurate and reliable ROM measurement requires extensive training and practice. This, in turn, imposes a significant barrier for those who have limited in-person access to healthcare. Objective. The current study presents and evaluates an alternative machine learning-based ROM evaluation method that could be remotely accessed via a webcam. Methods. To evaluate its reliability, the ROM measurements for a diverse set of joints (neck, spine, and upper and lower extremities) derived using this method were compared to those obtained from a marker-based optical motion capture system. Results. Data collected from 25 healthy adults demonstrated that the webcam solution exhibited high test-retest reliability, with substantial to almost perfect intraclass correlation coefficients for most joints. Compared with the marker-based system, the webcam-based system demonstrated substantial to almost perfect inter-rater reliability for some joints, and lower inter-rater reliability for other joints (e.g., shoulder flexion and elbow flexion), which could be attributed to the reduced sensitivity to joint locations at the apex of the movement. Conclusions. The proposed webcam-based method exhibited high test-retest and inter-rater reliability, making it a versatile alternative for existing ROM evaluation methods in clinical practice and the tele-implementation of physical therapy and rehabilitation.