Literature DB >> 15311830

Gait assessment in Parkinson's disease: toward an ambulatory system for long-term monitoring.

Arash Salarian1, Heike Russmann, François J G Vingerhoets, Catherine Dehollain, Yves Blanc, Pierre R Burkhard, Kamiar Aminian.   

Abstract

An ambulatory gait analysis method using body-attached gyroscopes to estimate spatio-temporal parameters of gait has been proposed and validated against a reference system for normal and pathologic gait. Later, ten Parkinson's disease (PD) patients with subthalamic nucleus deep brain stimulation (STN-DBS) implantation participated in gait measurements using our device. They walked one to three times on a 20-m walkway. Patients did the test twice: once STN-DBS was ON and once 180 min after turning it OFF. A group of ten age-matched normal subjects were also measured as controls. For each gait cycle, spatio-temporal parameters such as stride length (SL), stride velocity (SV), stance (ST), double support (DS), and gait cycle time (GC) were calculated. We found that PD patients had significantly different gait parameters comparing to controls. They had 52% less SV, 60% less SL, and 40% longer GC. Also they had significantly longer ST and DS (11% and 59% more, respectively) than controls. STN-DBS significantly improved gait parameters. During the stim ON period, PD patients had 31% faster SV, 26% longer SL, 6% shorter ST, and 26% shorter DS. GC, however, was not significantly different. Some of the gait parameters had high correlation with Unified Parkinson's Disease Rating Scale (UPDRS) subscores including SL with a significant correlation (r = -0.90) with UPDRS gait subscore. We concluded that our method provides a simple yet effective way of ambulatory gait analysis in PD patients with results confirming those obtained from much more complex and expensive methods used in gait labs.

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Year:  2004        PMID: 15311830     DOI: 10.1109/TBME.2004.827933

Source DB:  PubMed          Journal:  IEEE Trans Biomed Eng        ISSN: 0018-9294            Impact factor:   4.538


  130 in total

1.  An adaptive gyroscope-based algorithm for temporal gait analysis.

Authors:  Barry R Greene; Denise McGrath; Ross O'Neill; Karol J O'Donovan; Adrian Burns; Brian Caulfield
Journal:  Med Biol Eng Comput       Date:  2010-11-02       Impact factor: 2.602

2.  BioKin: an ambulatory platform for gait kinematic and feature assessment.

Authors:  Samitha W Ekanayake; Andrew J Morris; Mike Forrester; Pubudu N Pathirana
Journal:  Healthc Technol Lett       Date:  2015-02-25

3.  Characterizing knee loading asymmetry in individuals following anterior cruciate ligament reconstruction using inertial sensors.

Authors:  Susan M Sigward; Ming-Sheng M Chan; Paige E Lin
Journal:  Gait Posture       Date:  2016-06-18       Impact factor: 2.840

4.  Gait Cycle Validation and Segmentation Using Inertial Sensors.

Authors:  G V Prateek; Pietro Mazzoni; Gammon M Earhart; Arye Nehorai
Journal:  IEEE Trans Biomed Eng       Date:  2019-11-25       Impact factor: 4.538

5.  Capturing ambulatory activity decline in Parkinson's disease.

Authors:  James T Cavanaugh; Terry D Ellis; Gammon M Earhart; Matthew P Ford; K Bo Foreman; Leland E Dibble
Journal:  J Neurol Phys Ther       Date:  2012-06       Impact factor: 3.649

6.  Longitudinal Assessment of Balance and Gait After Concussion and Return to Play in Collegiate Athletes.

Authors:  Lucy Parrington; Peter C Fino; Clayton W Swanson; Charles F Murchison; James Chesnutt; Laurie A King
Journal:  J Athl Train       Date:  2019-04-01       Impact factor: 2.860

7.  Correlation among joint motions allows classification of Parkinsonian versus normal 3-D reaching.

Authors:  Jacky Chan; Howard Leung; Howard Poizner
Journal:  IEEE Trans Neural Syst Rehabil Eng       Date:  2009-06-02       Impact factor: 3.802

8.  Validity and repeatability of inertial measurement units for measuring gait parameters.

Authors:  Edward P Washabaugh; Tarun Kalyanaraman; Peter G Adamczyk; Edward S Claflin; Chandramouli Krishnan
Journal:  Gait Posture       Date:  2017-04-12       Impact factor: 2.840

9.  Analyzing 180 degrees turns using an inertial system reveals early signs of progression of Parkinson's disease.

Authors:  Arash Salarian; Cris Zampieri; Fay B Horak; Patricia Carlson-Kuhta; John G Nutt; Kamiar Aminian
Journal:  Conf Proc IEEE Eng Med Biol Soc       Date:  2009

10.  Validity of using tri-axial accelerometers to measure human movement - Part II: Step counts at a wide range of gait velocities.

Authors:  Emma Fortune; Vipul Lugade; Melissa Morrow; Kenton Kaufman
Journal:  Med Eng Phys       Date:  2014-03-20       Impact factor: 2.242

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