Kai Tang

Dr. Kai Tang


Research Focus & Metrics

Academic Career Length

9Years (2018-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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28 May 2018 in Sensors
Verified
Journal Article
Open access
PDF file
MLMengxuan Li
Mengxuan Li
LPLi Pengfei
Li Pengfei
STShanshan Tian
Shanshan Tian
KTKai Tang
Kai Tang
XCXi Chen
Xi Chen
Accurate estimation of gait parameters is essential for obtaining quantitative information on motor deficits in Parkinson’s disease and other neurodegenerative diseases, which helps determine disease progression and therapeutic interventions. Due to the demand for high accuracy, unobtrusive measurement methods such as optical motion capture systems, foot pressure plates, and other systems have been commonly used in clinical environments. However, the high cost of existing lab-based methods greatly hinders their wider usage, especially in developing countries. In this study, we present a low-cost, noncontact, and an accurate temporal gait parameters estimation method by sensing and analyzing the electrostatic field generated from human foot stepping. The proposed method achieved an average 97% accuracy on gait phase detection and was further validated by comparison to the foot pressure system in 10 healthy subjects. Two results were compared using the Pearson coefficient r and obtained an excellent consistency (r = 0.99, p < 0.05). The repeatability of the purposed method was calculated between days by intraclass correlation coefficients (ICC), and showed good test-retest reliability (ICC = 0.87, p < 0.01). The proposed method could be an affordable and accurate tool to measure temporal gait parameters in hospital laboratories and in patients’ home environments.