Literature DB >> 31873834

Gait event detection using inertial measurement units in people with transfemoral amputation: a comparative study.

Emeline Simonetti1,2,3, Coralie Villa4,5, Joseph Bascou4,5, Giuseppe Vannozzi6, Elena Bergamini6, Hélène Pillet5.   

Abstract

In recent years, inertial measurement units (IMUs) have been proposed as an alternative to force platforms and pressure sensors for gait events (i.e., initial and final contacts) detection. While multiple algorithms have been developed, the impact of gait event timing errors on temporal parameters and asymmetry has never been investigated in people with transfemoral amputation walking freely on level ground. In this study, five algorithms were comparatively assessed on gait data of seven people with transfemoral amputation, equipped with three IMUs mounted at the pelvis and both shanks, using pressure insoles for reference. Algorithms' performance was first quantified in terms of gait event detection rate (sensitivity, positive predictive value). Only two algorithms, based on shank mounted IMUs, achieved an acceptable detection rate (positive predictive value > 99%). For these two, accuracy of gait events timings, temporal parameters, and absolute symmetry index of stance-phase duration (SPD-ASI) were assessed. Whereas both algorithms achieved high accuracy for stride duration estimates (median errors: 0%, interquartile ranges < 1.75%), lower accuracy was found for other temporal parameters due to relatively high errors in the detection of final contact events. Furthermore, SPD-ASI derived from IMU-based algorithms proved to be significantly different to that obtained from insoles data. Graphical abstract Gait event detection with IMU in people with transfemoral amputation: initial contact (IC) and final contact (FC) events at the sound (s) and prosthetic (p) side are identified. Five algorithms were implemented using either shank-mounted or pelvis-mounted IMUs. Gait events were used to estimate temporal parameters (stride duration, stance phase duration [SPD], and double support time) and SPD asymmetry.

Entities:  

Keywords:  Asymmetry; Gait events; Gait temporal parameters; Inertial measurement units; Transfemoral amputee

Year:  2019        PMID: 31873834     DOI: 10.1007/s11517-019-02098-4

Source DB:  PubMed          Journal:  Med Biol Eng Comput        ISSN: 0140-0118            Impact factor:   2.602


  29 in total

1.  An enhanced estimate of initial contact and final contact instants of time using lower trunk inertial sensor data.

Authors:  John McCamley; Marco Donati; Eleni Grimpampi; Claudia Mazzà
Journal:  Gait Posture       Date:  2012-03-31       Impact factor: 2.840

2.  Assessment of walking features from foot inertial sensing.

Authors:  Angelo M Sabatini; Chiara Martelloni; Sergio Scapellato; Filippo Cavallo
Journal:  IEEE Trans Biomed Eng       Date:  2005-03       Impact factor: 4.538

3.  Gait event detection using linear accelerometers or angular velocity transducers in able-bodied and spinal-cord injured individuals.

Authors:  Jan M Jasiewicz; John H J Allum; James W Middleton; Andrew Barriskill; Peter Condie; Brendan Purcell; Raymond Che Tin Li
Journal:  Gait Posture       Date:  2006-02-23       Impact factor: 2.840

4.  Inertial Sensing for Gait Event Detection and Transfemoral Prosthesis Control Strategy.

Authors:  Elissa D Ledoux
Journal:  IEEE Trans Biomed Eng       Date:  2018-03-09       Impact factor: 4.538

5.  Quantitative estimation of foot-flat and stance phase of gait using foot-worn inertial sensors.

Authors:  Benoit Mariani; Hossein Rouhani; Xavier Crevoisier; Kamiar Aminian
Journal:  Gait Posture       Date:  2012-08-09       Impact factor: 2.840

6.  A comparison of variability in spatiotemporal gait parameters between treadmill and overground walking conditions.

Authors:  John H Hollman; Molly K Watkins; Angela C Imhoff; Carly E Braun; Kristen A Akervik; Debra K Ness
Journal:  Gait Posture       Date:  2015-10-23       Impact factor: 2.840

7.  IMU-based gait analysis in lower limb prosthesis users: Comparison of step demarcation algorithms.

Authors:  Gerasimos Bastas; Joshua J Fleck; Richard A Peters; Karl E Zelik
Journal:  Gait Posture       Date:  2018-05-22       Impact factor: 2.840

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

Authors:  Arash Salarian; Heike Russmann; François J G Vingerhoets; Catherine Dehollain; Yves Blanc; Pierre R Burkhard; Kamiar Aminian
Journal:  IEEE Trans Biomed Eng       Date:  2004-08       Impact factor: 4.538

9.  Gait event detection on level ground and incline walking using a rate gyroscope.

Authors:  Paola Catalfamo; Salim Ghoussayni; David Ewins
Journal:  Sensors (Basel)       Date:  2010-06-04       Impact factor: 3.576

10.  Estimation of spatio-temporal parameters of gait from magneto-inertial measurement units: multicenter validation among Parkinson, mildly cognitively impaired and healthy older adults.

Authors:  Matilde Bertoli; Andrea Cereatti; Diana Trojaniello; Laura Avanzino; Elisa Pelosin; Silvia Del Din; Lynn Rochester; Pieter Ginis; Esther M J Bekkers; Anat Mirelman; Jeffrey M Hausdorff; Ugo Della Croce
Journal:  Biomed Eng Online       Date:  2018-05-09       Impact factor: 2.819

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  2 in total

1.  Estimation of 3D Body Center of Mass Acceleration and Instantaneous Velocity from a Wearable Inertial Sensor Network in Transfemoral Amputee Gait: A Case Study.

Authors:  Emeline Simonetti; Elena Bergamini; Giuseppe Vannozzi; Joseph Bascou; Hélène Pillet
Journal:  Sensors (Basel)       Date:  2021-04-30       Impact factor: 3.576

2.  Detection of Movement Events of Long-Track Speed Skating Using Wearable Inertial Sensors.

Authors:  Yosuke Tomita; Tomoki Iizuka; Koichi Irisawa; Shigeyuki Imura
Journal:  Sensors (Basel)       Date:  2021-05-24       Impact factor: 3.576

  2 in total

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