Application of Isokinetic Dynamometry Data in Predicting Gait Deviation Index Using Machine Learning in Stroke Patients: A Cross-Sectional Study

Application of Isokinetic Dynamometry Data in Predicting Gait Deviation Index Using Machine Learning in Stroke Patients: A Cross-Sectional Study

Background: Three-dimensional gait analysis, supported by advanced sensor systems, is a crucial component in the rehabilitation assessment of post-stroke hemiplegic patients. However, the sensor data generated from such analyses are often complex and challenging to interpret in clinical practice, re...

Full description

Saved in:
Bibliographic Details
Main Authors: Xiaolei Lu, Chenye Qiao, Hujun Wang, Yingqi Li, Jingxuan Wang, Congxiao Wang, Yingpeng Wang, Shuyan Qie
Format: Article
Language:English
Published: MDPI AG 2024-11-01
Series:Sensors
Subjects:
sensors
isokinetic dynamometry
gait deviation index
machine learning
stroke
Online Access:https://www.mdpi.com/1424-8220/24/22/7258
Tags: Add Tag
No Tags, Be the first to tag this record!

Similar Items

Similar Items