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

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 demonstrat

SUBMITTER: Wang XM 

PROVIDER: S-EPMC10593217 | biostudies-literature | 2023

REPOSITORIES: biostudies-literature