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

Shancang Li*, Jue Wang, Xinheng Wang

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

8 Citations (Scopus)


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.

Original languageEnglish
Pages (from-to)262-274
Number of pages13
JournalInternational Journal of Communication Networks and Distributed Systems
Issue number3-4
Publication statusPublished - Sept 2011
Externally publishedYes


  • BSN
  • Body sensor network
  • Gait recognition
  • PD
  • Parkinson's disease

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