Title: A novel gait recognition analysis system based on body sensor networks for patients with Parkinson's disease

Authors: Shancang Li, Jue Wang, Xinheng Wang

Addresses: Key Laboratory of Biomedical Information Engineering of Education Ministry, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an 710049, China. ' Key Laboratory of Biomedical Information Engineering of Education Ministry, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an 710049, China. ' School of Engineering, Swansea University, Swansea SA2 8PP, UK

Abstract: Gait analysis of human plays a significant role in maintaining the well-being of our mobility and healthcare, and it can be used for various e-healthcare systems for fast medical prognosis and diagnosis. In this paper, we have developed a novel body sensor network-based recognition system to identify the specific gait pattern of Parkinson|s disease (PD). Firstly, a BSN with 16-nodes is used to acquire the gait information from the PD patients. Then, an algorithm is developed based on local linear embedding (LLE) to extract and recognise the gait features. Experiments demonstrate the effectiveness of proposed scheme. The results show that the proposed scheme has a recognition rate of about 95.57% for gait patterns of PD, which is higher than the conventional PCA feature extraction method. The proposed system can identify PD patients from normal people and by their gait map with high reliability and appears a promising aid in the diagnosis of the Parkinson|s disease.

Keywords: body sensor networks; BSNs; gait recognition; Parkinson|s disease; gait patterns; gait analysis; medical diagnosis.

DOI: 10.1504/IJCNDS.2011.042379

International Journal of Communication Networks and Distributed Systems, 2011 Vol.7 No.3/4, pp.262 - 274

Published online: 26 Feb 2015 *

Full-text access for editors Full-text access for subscribers Purchase this article Comment on this article