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Measurement of Step Angle for Quantifying the Gait Impairment of Parkinson’s Disease by Wearable Sensors: Controlled Study

Authors :
Wang, Jingying
Gong, Dawei
Luo, Huichun
Zhang, Wenbin
Zhang, Lei
Zhang, Han
Zhou, Junhong
Wang, Shouyan
Source :
JMIR mHealth and uHealth, Vol 8, Iss 3, p e16650 (2020)
Publication Year :
2020
Publisher :
JMIR Publications, 2020.

Abstract

BackgroundGait impairments including shuffling gait and hesitation are common in people with Parkinson’s disease (PD), and have been linked to increased fall risk and freezing of gait. Nowadays the gait metrics mostly focus on the spatiotemporal characteristics of gait, but less is known of the angular characteristics of the gait, which may provide helpful information pertaining to the functional status and effects of the treatment in PD. ObjectiveThis study aimed to quantify the angles of steps during walking, and explore if this novel step angle metric is associated with the severity of PD and the effects of the treatment including the acute levodopa challenge test (ALCT) and deep brain stimulation (DBS). MethodsA total of 18 participants with PD completed the walking test before and after the ALCT, and 25 participants with PD completed the test with the DBS on and off. The walking test was implemented under two conditions: walking normally at a preferred speed (single task) and walking while performing a cognitive serial subtraction task (dual task). A total of 17 age-matched participants without PD also completed this walking test. The angular velocity was measured using wearable sensors on each ankle, and three gait angular metrics were obtained, that is mean step angle, initial step angle, and last step angle. The conventional gait metrics (ie, step time and step number) were also calculated. ResultsThe results showed that compared to the control, the following three step angle metrics were significantly smaller in those with PD: mean step angle (F1,48=69.75, P

Details

Language :
English
ISSN :
22915222
Volume :
8
Issue :
3
Database :
Directory of Open Access Journals
Journal :
JMIR mHealth and uHealth
Publication Type :
Academic Journal
Accession number :
edsdoj.9d985117d5cd49bc99ea61a63b680573
Document Type :
article
Full Text :
https://doi.org/10.2196/16650