DocumentCode
30409
Title
Gait and Balance Analysis for Patients With Alzheimer's Disease Using an Inertial-Sensor-Based Wearable Instrument
Author
Yu-Liang Hsu ; Pau-Choo Chung ; Wei-Hsin Wang ; Ming-Chyi Pai ; Chun-Yao Wang ; Chien-Wen Lin ; Hao-Li Wu ; Jeen-Shing Wang
Author_Institution
Dept. of Electr. Eng., Nat. Cheng Kung Univ. (NCKU), Tainan, Taiwan
Volume
18
Issue
6
fYear
2014
fDate
Nov. 2014
Firstpage
1822
Lastpage
1830
Abstract
Despite patients with Alzheimer´s disease (AD) were reported of revealing gait disorders and balance problems, there is still lack of objective quantitative measurement of gait patterns and balance capability of AD patients. Based on an inertial-sensor-based wearable device, this paper develops gait and balance analyzing algorithms to obtain quantitative measurements and explores the essential indicators from the measurements for AD diagnosis. The gait analyzing algorithm is composed of stride detection followed by gait cycle decomposition so that gait parameters are developed from the decomposed gait details. On the other hand, the balance is measured by the sway speed in anterior-posterior (AP) and medial-lateral (ML) directions of the projection path of body´s center of mass (COM). These devised gait and balance parameters were explored on twenty-one AD patients and fifty healthy controls (HCs). Special evaluation procedure including single-task and dual-task walking experiments for observing the cognitive function and attention is also devised for the comparison of AD and HC groups. Experimental results show that the wearable instrument with the designed gait and balance analyzing system is a promising tool for automatically analyzing gait information and balance ability, serving as assistant indicators for early diagnosis of AD.
Keywords
biomedical measurement; diseases; gait analysis; mechanoception; patient diagnosis; AD diagnosis; Alzheimers disease; anterior-posterior directions; balance analyzing algorithms; body center of mass; cognitive function; dual-task walking experiments; gait analyzing algorithms; gait cycle decomposition; gait parameters; healthy controls; inertial-sensor-based wearable instrument; medial-lateral directions; quantitative measurements; single-task walking experiments; stride detection; Acceleration; Accelerometers; Algorithm design and analysis; Alzheimer´s disease; Angular velocity; Legged locomotion; Alzheimer???s disease (AD); balance; balance analyzing algorithm; gait; gait analyzing algorithm; inertial sensor;
fLanguage
English
Journal_Title
Biomedical and Health Informatics, IEEE Journal of
Publisher
ieee
ISSN
2168-2194
Type
jour
DOI
10.1109/JBHI.2014.2325413
Filename
6824156
Link To Document