Title
Adaptive windowing for gait phase discrimination in Parkinsonian gait using 3-axis acceleration signals.
Abstract
In order to robustly analyze the gait of Parkinson's disease (PD) patients, a new gait phase discrimination method was developed for analyzing the three-axis accelerations of the ankle during walking. The magnitude of acceleration was compared with the lowpass-filtered signal of itself and pseudo foot-flat phases were determined. Four narrow windows were made sequentially and adaptively from the pseudo foot-flat phases. Each window contained a characteristic peak that discriminated the gait phases. From these windows, the initial contact (IC) point and end contact (EC) point were determined by finding the maximal point in the proximal-distal acceleration. Seven healthy individuals and 17 PD patients were subjected to a walking test on level ground for a distance of 6.5 m with the wearable activity monitoring system (W-AMS). Foot pressure and movement images were simultaneously recorded as references. The ICs and ECs detected by the proposed algorithm were compared with the manually marked events in the foot pressure signals. In healthy subjects, all the ICs and ECs were correctly detected. In the PD group, the detection accuracy was 97.6% for the ICs and 99.4% for the ECs. Based on these results, this novel method holds promise for use in monitoring temporal gait parameters continuously in PD patients, which will subsequently allow for the evaluation of motor fluctuations in PD patients.
Year
DOI
Venue
2009
10.1007/s11517-009-0521-5
Med. Biol. Engineering and Computing
Keywords
Field
DocType
gait phase discrimination � parkinson diseasewearable activity monitoring system
Computer vision,Monitoring system,Gait,Acceleration,Artificial intelligence,Parkinsonian gait,Ankle,Mathematics
Journal
Volume
Issue
ISSN
47
11
1741-0444
Citations 
PageRank 
References 
7
1.23
3
Authors
5
Name
Order
Citations
PageRank
Jonghee Han1166.23
Hyo Seon Jeon2172.42
Won Jin Yi371.23
Beom Seok Jeon491.59
Kwang Suk Park526646.43