Literature DB >> 23070290

A novel approach to reducing number of sensing units for wearable gait analysis systems.

Arash Salarian1, Pierre R Burkhard, François J G Vingerhoets, Brigitte M Jolles, Kamiar Aminian.   

Abstract

Gait analysis methods to estimate spatiotemporal measures, based on two, three or four gyroscopes attached on lower limbs have been discussed in the literature. The most common approach to reduce the number of sensing units is to simplify the underlying biomechanical gait model. In this study, we propose a novel method based on prediction of movements of thighs from movements of shanks. Datasets from three previous studies were used. Data from the first study (ten healthy subjects and ten with Parkinson's disease) were used to develop and calibrate a system with only two gyroscopes attached on shanks. Data from two other studies (36 subjects with hip replacement, seven subjects with coxarthrosis, and eight control subjects) were used for comparison with the other methods and for assessment of error compared to a motion capture system. Results show that the error of estimation of stride length compared to motion capture with the system with four gyroscopes and our new method based on two gyroscopes was close ( -0.8 ±6.6 versus 3.8 ±6.6 cm). An alternative with three sensing units did not show better results (error: -0.2 ±8.4 cm). Finally, a fourth that also used two units but with a simpler gait model had the highest bias compared to the reference (error: -25.6 ±7.6 cm). We concluded that it is feasible to estimate movements of thighs from movements of shanks to reduce number of needed sensing units from 4 to 2 in context of ambulatory gait analysis.

Entities:  

Mesh:

Year:  2012        PMID: 23070290     DOI: 10.1109/TBME.2012.2223465

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


  18 in total

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Journal:  Front Neurosci       Date:  2017-10-06       Impact factor: 4.677

2.  A wearable system for gait training in subjects with Parkinson's disease.

Authors:  Filippo Casamassima; Alberto Ferrari; Bojan Milosevic; Pieter Ginis; Elisabetta Farella; Laura Rocchi
Journal:  Sensors (Basel)       Date:  2014-03-28       Impact factor: 3.576

Review 3.  Technologies for Advanced Gait and Balance Assessments in People with Multiple Sclerosis.

Authors:  Camille J Shanahan; Frederique M C Boonstra; L Eduardo Cofré Lizama; Myrte Strik; Bradford A Moffat; Fary Khan; Trevor J Kilpatrick; Anneke van der Walt; Mary P Galea; Scott C Kolbe
Journal:  Front Neurol       Date:  2018-02-02       Impact factor: 4.003

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

Review 5.  Quantitative Analysis of Motor Status in Parkinson's Disease Using Wearable Devices: From Methodological Considerations to Problems in Clinical Applications.

Authors:  Masahiko Suzuki; Hiroshi Mitoma; Mitsuru Yoneyama
Journal:  Parkinsons Dis       Date:  2017-05-18

6.  Fusion of Inertial/Magnetic Sensor Measurements and Map Information for Pedestrian Tracking.

Authors:  Shu-Di Bao; Xiao-Li Meng; Wendong Xiao; Zhi-Qiang Zhang
Journal:  Sensors (Basel)       Date:  2017-02-10       Impact factor: 3.576

7.  Multiple-Wearable-Sensor-Based Gait Classification and Analysis in Patients with Neurological Disorders.

Authors:  Wei-Chun Hsu; Tommy Sugiarto; Yi-Jia Lin; Fu-Chi Yang; Zheng-Yi Lin; Chi-Tien Sun; Chun-Lung Hsu; Kuan-Nien Chou
Journal:  Sensors (Basel)       Date:  2018-10-11       Impact factor: 3.576

8.  Gait analysis methods: an overview of wearable and non-wearable systems, highlighting clinical applications.

Authors:  Alvaro Muro-de-la-Herran; Begonya Garcia-Zapirain; Amaia Mendez-Zorrilla
Journal:  Sensors (Basel)       Date:  2014-02-19       Impact factor: 3.576

Review 9.  Sensor Fusion and Smart Sensor in Sports and Biomedical Applications.

Authors:  José Jair Alves Mendes; Mário Elias Marinho Vieira; Marcelo Bissi Pires; Sergio Luiz Stevan
Journal:  Sensors (Basel)       Date:  2016-09-23       Impact factor: 3.576

10.  What is the Best Configuration of Wearable Sensors to Measure Spatiotemporal Gait Parameters in Children with Cerebral Palsy?

Authors:  Lena Carcreff; Corinna N Gerber; Anisoara Paraschiv-Ionescu; Geraldo De Coulon; Christopher J Newman; Stéphane Armand; Kamiar Aminian
Journal:  Sensors (Basel)       Date:  2018-01-30       Impact factor: 3.576

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