Literature DB >> 26292350

Contribution of a Trunk Accelerometer System to the Characterization of Gait in Patients With Mild-to-Moderate Parkinson's Disease.

Marie Demonceau, Anne-Françoise Donneau, Jean-Louis Croisier, Eva Skawiniak, Mohamed Boutaayamou, Didier Maquet, Gaëtan Garraux.   

Abstract

OBJECTIVE: Gait disturbances like shuffling and short steps are obvious at visual observation in patients with advanced Parkinson's disease (PD). However, quantitative methods are increasingly used to evaluate the wide range of gait abnormalities that may occur over the disease course. The goal of this study was to test the ability of a trunk accelerometer system to quantify the effects of PD on several gait features when walking at self-selected speed.
METHODS: We recruited 96 subjects split into three age-matched groups: 32 healthy controls (HC), 32 PD patients at Hoehn and Yahr stage < II (PD-1), and 32 patients at Hoehn and Yahr stage II-III (PD-2). The following outcomes were extracted from the signals of the triaxial accelerometer worn on the lower back: stride length, cadence, regularity index, symmetry index, and mechanical powers yielded in the cranial-caudal, anteroposterior, and medial-lateral directions. Walking speed was measured using a stopwatch.
RESULTS: Besides other gait features, the PD-1 and the PD-2 groups showed significantly reduced stride length normalized to height (p < 0.02) and symmetry index (p < 0.009) in comparison to the HC. Regularity index was the only feature significantly decreased in the PD-2 group as compared with the two other groups (p < 0.01). The clinical relevance of this finding was supported by significant correlations with mobility and gait scales (r is around -0.3; p < 0.05).
CONCLUSION: Gait quantified by a trunk accelerometer may provide clinically useful information for the screening and follow-up of PD patients.

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Year:  2015        PMID: 26292350     DOI: 10.1109/JBHI.2015.2469540

Source DB:  PubMed          Journal:  IEEE J Biomed Health Inform        ISSN: 2168-2194            Impact factor:   5.772


  9 in total

Review 1.  Gait metrics analysis utilizing single-point inertial measurement units: a systematic review.

Authors:  Ralph Jasper Mobbs; Jordan Perring; Suresh Mahendra Raj; Monish Maharaj; Nicole Kah Mun Yoong; Luke Wicent Sy; Rannulu Dineth Fonseka; Pragadesh Natarajan; Wen Jie Choy
Journal:  Mhealth       Date:  2022-01-20

Review 2.  How Wearable Sensors Can Support Parkinson's Disease Diagnosis and Treatment: A Systematic Review.

Authors:  Erika Rovini; Carlo Maremmani; Filippo Cavallo
Journal:  Front Neurosci       Date:  2017-10-06       Impact factor: 4.677

3.  Objective characterization of daily living transitions in patients with Parkinson's disease using a single body-fixed sensor.

Authors:  Hagar Bernad-Elazari; Talia Herman; Anat Mirelman; Eran Gazit; Nir Giladi; Jeffrey M Hausdorff
Journal:  J Neurol       Date:  2016-05-23       Impact factor: 4.849

4.  Inertial Sensor-Based Robust Gait Analysis in Non-Hospital Settings for Neurological Disorders.

Authors:  Can Tunca; Nezihe Pehlivan; Nağme Ak; Bert Arnrich; Gülüstü Salur; Cem Ersoy
Journal:  Sensors (Basel)       Date:  2017-04-11       Impact factor: 3.576

5.  Effects of Gait Strategy and Speed on Regularity of Locomotion Assessed in Healthy Subjects Using a Multi-Sensor Method.

Authors:  Marco Rabuffetti; Giovanni Marco Scalera; Maurizio Ferrarin
Journal:  Sensors (Basel)       Date:  2019-01-26       Impact factor: 3.576

6.  Gait parameters of Parkinson's disease compared with healthy controls: a systematic review and meta-analysis.

Authors:  Ana Paula Janner Zanardi; Edson Soares da Silva; Rochelle Rocha Costa; Elren Passos-Monteiro; Ivan Oliveira Dos Santos; Luiz Fernando Martins Kruel; Leonardo Alexandre Peyré-Tartaruga
Journal:  Sci Rep       Date:  2021-01-12       Impact factor: 4.379

7.  The Association of Fatigue With Decreasing Regularity of Locomotion During an Incremental Test in Trained and Untrained Healthy Adults.

Authors:  Marco Rabuffetti; Mathias Steinach; Julia Lichti; Hanns-Christian Gunga; Björn Balcerek; Philipp Nils Becker; Michael Fähling; Giampiero Merati; Martina Anna Maggioni
Journal:  Front Bioeng Biotechnol       Date:  2021-11-24

Review 8.  Detection and assessment of Parkinson's disease based on gait analysis: A survey.

Authors:  Yao Guo; Jianxin Yang; Yuxuan Liu; Xun Chen; Guang-Zhong Yang
Journal:  Front Aging Neurosci       Date:  2022-08-03       Impact factor: 5.702

9.  Test-Retest Reliability of an Automated Infrared-Assisted Trunk Accelerometer-Based Gait Analysis System.

Authors:  Chia-Yu Hsu; Yuh-Show Tsai; Cheng-Shiang Yau; Hung-Hai Shie; Chu-Ming Wu
Journal:  Sensors (Basel)       Date:  2016-07-23       Impact factor: 3.576

  9 in total

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