Literature DB >> 23000235

Estimation of spatio-temporal parameters for post-stroke hemiparetic gait using inertial sensors.

Shuozhi Yang1, Jun-Tian Zhang, Alison C Novak, Brenda Brouwer, Qingguo Li.   

Abstract

This paper represents the first step in developing an inertial sensor system that is capable of assessing post-stroke gait in terms of walking speed and temporal gait symmetry. Two inertial sensors were attached at the midpoint of each shank to measure the accelerations and angular velocity during walking. Despite the abnormalities in hemiparetic gait, the angular velocity of most of the testing subjects (12 out of 13) exhibited similar characteristics as those from a healthy population, enabling walking speed estimation and gait event detection based on the pendulum walking model. The results from a standardized 10-meter walk test demonstrated that the IMU-based method has an excellent agreement with the clinically used stopwatch method. The gait symmetry results were comparable with previous studies. The gait segmentation failed when the angular velocity deviates significantly from the healthy groups' profile. With further development and concurrent validations, the inertial sensor-based system may eventually become a useful tool for continually monitoring spatio-temporal gait parameters post stroke in a natural environment.
Copyright © 2012 Elsevier B.V. All rights reserved.

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Year:  2012        PMID: 23000235     DOI: 10.1016/j.gaitpost.2012.07.032

Source DB:  PubMed          Journal:  Gait Posture        ISSN: 0966-6362            Impact factor:   2.840


  23 in total

1.  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

2.  SIRRACT: An International Randomized Clinical Trial of Activity Feedback During Inpatient Stroke Rehabilitation Enabled by Wireless Sensing.

Authors:  Andrew K Dorsch; Seth Thomas; Xiaoyu Xu; William Kaiser; Bruce H Dobkin
Journal:  Neurorehabil Neural Repair       Date:  2014-09-26       Impact factor: 3.919

Review 3.  Next Steps in Wearable Technology and Community Ambulation in Multiple Sclerosis.

Authors:  Mikaela L Frechette; Brett M Meyer; Lindsey J Tulipani; Reed D Gurchiek; Ryan S McGinnis; Jacob J Sosnoff
Journal:  Curr Neurol Neurosci Rep       Date:  2019-09-04       Impact factor: 5.081

Review 4.  Wearable motion sensors to continuously measure real-world physical activities.

Authors:  Bruce H Dobkin
Journal:  Curr Opin Neurol       Date:  2013-12       Impact factor: 5.710

5.  Estimation of step-by-step spatio-temporal parameters of normal and impaired gait using shank-mounted magneto-inertial sensors: application to elderly, hemiparetic, parkinsonian and choreic gait.

Authors:  Diana Trojaniello; Andrea Cereatti; Elisa Pelosin; Laura Avanzino; Anat Mirelman; Jeffrey M Hausdorff; Ugo Della Croce
Journal:  J Neuroeng Rehabil       Date:  2014-11-11       Impact factor: 4.262

6.  Design and test of an automated version of the modified Jebsen test of hand function using Microsoft Kinect.

Authors:  Daniel Simonsen; Ida F Nielsen; Erika G Spaich; Ole K Andersen
Journal:  J Neuroeng Rehabil       Date:  2017-05-02       Impact factor: 4.262

7.  Observational Study of 180° Turning Strategies Using Inertial Measurement Units and Fall Risk in Poststroke Hemiparetic Patients.

Authors:  Rémi Pierre-Marie Barrois; Damien Ricard; Laurent Oudre; Leila Tlili; Clément Provost; Aliénor Vienne; Pierre-Paul Vidal; Stéphane Buffat; Alain P Yelnik
Journal:  Front Neurol       Date:  2017-05-15       Impact factor: 4.003

8.  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

9.  Drift removal for improving the accuracy of gait parameters using wearable sensor systems.

Authors:  Ryo Takeda; Giulia Lisco; Tadashi Fujisawa; Laura Gastaldi; Harukazu Tohyama; Shigeru Tadano
Journal:  Sensors (Basel)       Date:  2014-12-05       Impact factor: 3.576

10.  A Machine Learning Framework for Gait Classification Using Inertial Sensors: Application to Elderly, Post-Stroke and Huntington's Disease Patients.

Authors:  Andrea Mannini; Diana Trojaniello; Andrea Cereatti; Angelo M Sabatini
Journal:  Sensors (Basel)       Date:  2016-01-21       Impact factor: 3.576

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