arrow
Return

iGAIT: An interactive accelerometer based gait analysis system

delete2012-11-01
delete60
PRE
AI
M
Mingjing Yang
H
Huiru Zheng *
王海鹰 cover
王海鹰 (Haiying Wang)
S
Sally McClean
D
David Newell
DOI:10.1016/j.cmpb.2012.04.004delete
deleteOriginal
deleteOriginal request for help
deleteShare
deleteSave
Abstract

Abstract

En 中文
This paper presents a software program (iGAIT) developed in MATLAB, for the analysis of gait patterns extracted from accelerometer recordings. iGAIT provides a user-friendly graphical interface to display and analyse gait acceleration data recorded by an accelerometer attached to the lower back of subjects. The core function of iGAIT is gait feature extraction, which can be used to derive 31 features from acceleration data, including 6 spatio-temporal features, 7 regularity and symmetry features, and 18 spectral features. Features extracted are summarised and displayed on screen, as well as an option to be stored in text files for further review or analysis if required. Another unique feature of iGAIT is that it provides interactive functionality allowing users to manually adjust the analysis process according to their requirements. The system has been tested under Window XP, Vista and Window 7 using three different types of accelerometer data. It is designed for analysis of accelerometer data recorded with sample frequencies ranging from 5 Hz to 200 Hz. (C) 2012 Elsevier Ireland Ltd. All rights reserved.
Keywords:
Gait analysis
Accelerometer
MATLAB
Feature extraction
AI Summary

AI Summary

Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.

Journal

Computer Methods and Programs in Biomedicine cover
Computer Methods and Programs in Biomedicine
IF:
4.8
Papers:
7.0K
Citations:
2.1W

Organization

U
Ulster University
Scholars:
5.7K
Papers: 5.9K
Citations: 25
Cited Papers

Cited Papers

err
IF0
err
err0
PREAI
err
errShare
errSave
Gait dynamics in Parkinson's disease: relationship to Parkinsonian features, falls and response to levodopa
err2003-08-01
err380
PREAI
errSchaafsma, JD; Giladi, N; Balash, Y; Bartels, AL; Gurevich, T; Hausdorff, JM
errShare
errSave
errShare
errSave
Fractal dynamics in physiology: Alterations with disease and aging
err2002-02-19
err1.7K
errOAAI
errGoldberger, AL; Amaral, LAN; Hausdorff, JM; Ivanov, PC; Peng, CK; Stanley, HE
errShare
errSave
Effects of attention on the control of locomotion in individuals with chronic low back pain
err2008-04-25
err94
errOAAI
errLamoth, Claudine J. C.; Stins, John F.; Pont, Menno; Kerckhoff, Frederick; Beek, Peter J.
errShare
errSave
A Fully Autonomous Integrated Interface Circuit for Piezoelectric Harvesters
err2012-09-01
err0
PREAI
errThorsten Hehn; Friedrich Hagedorn; Dominic Maurath; Djordje Marinkovic; Ingo Kuehne; Alexander Frey; Yiannos Manoli
errShare
errSave
Tuning the curing behavior of fluoroelastomer (FKM) by incorporation of nitrogen doped graphene nanoribbons (CNx-GNRs)
err2014-11-01
err0
PREAI
errMaryam Khajehpour; Soheil Sadeghi; Alireza Zehtab Yazdi; Uttandaraman Sundararaj
errShare
errSave
Reliability and validity of bilateral thigh and foot accelerometry measures of walking in healthy and hemiparetic subjects
err2006-06-01
err100
PREAI
errSaremi, Kaveh; Marehbian, Jon; Yan, Xiaohong; Regnaux, Jean-Philippe; Elashoff, Robert; Bussel, Bernard; Dobkin, Bruce H.
errShare
errSave
researcher View more