Autonomous Gait Event Detection with Portable Single-Camera Gait Kinematics Analysis System

Yang, Cheng; Ugbolue, Ukadike C.; Kerr, Andrew; Stankovic, Vladimir; Stankovic, Lina; Carse, Bruce; Kaliarntas, Konstantinos T.; Rowe, Philip J.

Abstract

Laboratory-based nonwearable motion analysis systems have significantly advanced with robust objective measurement of the
limb motion, resulting in quantified, standardized, and reliable outcome measures compared with traditional, semisubjective,
observational gait analysis. However, the requirement for large laboratory space and operational expertise makes these systems
impractical for gait analysis at local clinics and homes. In this paper, we focus on autonomous gait event detection with our bespoke,
relatively inexpensive, and portable, single-camera gait kinematics analysis system. Our proposed systemincludes video acquisition
with camera calibration, Kalman filter + Structural-Similarity-based marker tracking, autonomous knee angle calculation, videoframe-
identification-based autonomous gait event detection, and result visualization. The only operational effort required is the
marker-template selection for tracking initialization, aided by an easy-to-use graphic user interface.The knee angle validation on
10 stroke patients and 5 healthy volunteers against a gold standard optical motion analysis system indicates very good agreement.
The autonomous gait event detection shows high detection rates for all gait events. Experimental results demonstrate that the
proposed system can automatically measure the knee angle and detect gait events with good accuracy and thus offer an alternative,
cost-effective, and convenient solution for clinical gait kinematics analysis.

Citation

Yang, C., Ugbolue, U. C., Kerr, A., Stankovic, V., Stankovic, L., Carse, B., Kaliarntas, K. T., & Rowe, P. J. (2016). Autonomous Gait Event Detection with Portable Single-Camera Gait Kinematics Analysis System. Journal of Sensors, 2016, 1-8. https://doi.org/10.1155/2016/5036857

• Journal Article Type: Article
• Acceptance Date: Dec 9, 2015
• Online Publication Date: Jan 18, 2016
• Publication Date: 2016
• Deposit Date: Dec 12, 2017
• Publicly Available Date: Dec 12, 2017
• Journal: Journal of Sensors
• Print ISSN: 1687-725X
• Electronic ISSN: 1687-7268
• Publisher: Hindawi
• Peer Reviewed: Peer Reviewed
• Volume: 2016
• Pages: 1-8
• DOI: https://doi.org/10.1155/2016/5036857
• Keywords: Control and Systems Engineering; Instrumentation; Electrical and Electronic Engineering
• Public URL: http://researchrepository.napier.ac.uk/Output/953127
• Contract Date: Dec 12, 2017