Validity of the Microsoft Kinect for providing lateral trunk lean feedback during gait retraining
Ross A. Clark · Yong‐Hao Pua · Adam L. Bryant · Michael A. Hunt
Gait and Posture
Abstract
Gait retraining programs are prescribed to assist in the rehabilitation process of many clinical conditions. Using lateral trunk lean modification as the model, the aim of this study was to assess the concurrent validity of kinematic data recorded using a marker-based 3D motion analysis (3DMA) system and a low-cost alternative, the Microsoft Kinect™ (Kinect), during a gait retraining session. Twenty healthy adults were trained to modify their gait to obtain a lateral trunk lean angle of 10°. Real-time biofeedback of the lateral trunk lean angle was provided on a computer screen in front of the subject using data extracted from the Kinect skeletal tracking algorithm. Marker coordinate data were concurrently recorded using the 3DMA system, and the similarity and equivalency of the trunk lean angle data from each system were compared. The lateral trunk lean angle data obtained from the Kinect system without any form of calibration resulted in errors of a high (>2°) magnitude (mean error=3.2±2.2°). Performing global and individualized calibration significantly (P<0.001) improved this error to 1.7±1.5° and 0.8±0.8° respectively. With the addition of a simple calibration the anatomical position coordinates of the Kinect can be used to create a real-time biofeedback system for gait retraining. Given that this system is low-cost, portable and does not require any sensors to be attached to the body, it could provide numerous advantages when compared to laboratory-based gait retraining systems.
Abstract source ↗Cite this publication
Download Plain textCitation fields reflect the indexed metadata. Check author formatting and publication details against the source before submission.
Explore related topics
Suggested by subject matter. These links do not imply that a tool was used or validated in this study.
Record provenance
Indexed record: W1971691194. Matched to Scopus author 55279534900.
Scopus record ↗Metadata retrieved 2026-09-20. Topic labels are navigation aids derived from title and abstract text.