Gait and balance analysis for patients with Alzheimer's disease using an inertial-sensor-based wearable instrument

Yu Liang Hsu, Pau Choo Chung, Wei Hsin Wang, Ming Chyi Pai, Chun Yao Wang, Chien Wen Lin, Hao Li Wu, Jeen Shing Wang

Research output: Contribution to journalArticle

48 Citations (Scopus)

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) andmedial-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.

Original languageEnglish
Article number6824156
Pages (from-to)1822-1830
Number of pages9
JournalIEEE Journal of Biomedical and Health Informatics
Volume18
Issue number6
DOIs
Publication statusPublished - 2014 Nov 1

Fingerprint

Gait
Alzheimer Disease
Sensors
Aptitude
Decomposition
Cognition
Walking
Early Diagnosis
Equipment and Supplies
Experiments
Control Groups

All Science Journal Classification (ASJC) codes

  • Biotechnology
  • Computer Science Applications
  • Electrical and Electronic Engineering
  • Health Information Management

Cite this

@article{ede90466e73a4a2d9f6ffd3105c9c430,
title = "Gait and balance analysis for patients with Alzheimer's disease using an inertial-sensor-based wearable instrument",
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) andmedial-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.",
author = "Hsu, {Yu Liang} and Chung, {Pau Choo} and Wang, {Wei Hsin} and Pai, {Ming Chyi} and Wang, {Chun Yao} and Lin, {Chien Wen} and Wu, {Hao Li} and Wang, {Jeen Shing}",
year = "2014",
month = "11",
day = "1",
doi = "10.1109/JBHI.2014.2325413",
language = "English",
volume = "18",
pages = "1822--1830",
journal = "IEEE Journal of Biomedical and Health Informatics",
issn = "2168-2194",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
number = "6",

}

Gait and balance analysis for patients with Alzheimer's disease using an inertial-sensor-based wearable instrument. / Hsu, Yu Liang; Chung, Pau Choo; Wang, Wei Hsin; Pai, Ming Chyi; Wang, Chun Yao; Lin, Chien Wen; Wu, Hao Li; Wang, Jeen Shing.

In: IEEE Journal of Biomedical and Health Informatics, Vol. 18, No. 6, 6824156, 01.11.2014, p. 1822-1830.

Research output: Contribution to journalArticle

TY - JOUR

T1 - Gait and balance analysis for patients with Alzheimer's disease using an inertial-sensor-based wearable instrument

AU - Hsu, Yu Liang

AU - Chung, Pau Choo

AU - Wang, Wei Hsin

AU - Pai, Ming Chyi

AU - Wang, Chun Yao

AU - Lin, Chien Wen

AU - Wu, Hao Li

AU - Wang, Jeen Shing

PY - 2014/11/1

Y1 - 2014/11/1

N2 - 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) andmedial-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.

AB - 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) andmedial-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.

UR - http://www.scopus.com/inward/record.url?scp=84909619354&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84909619354&partnerID=8YFLogxK

U2 - 10.1109/JBHI.2014.2325413

DO - 10.1109/JBHI.2014.2325413

M3 - Article

C2 - 25375679

AN - SCOPUS:84909619354

VL - 18

SP - 1822

EP - 1830

JO - IEEE Journal of Biomedical and Health Informatics

JF - IEEE Journal of Biomedical and Health Informatics

SN - 2168-2194

IS - 6

M1 - 6824156

ER -