Literature DB >> 25085660

Accuracy, sensitivity and robustness of five different methods for the estimation of gait temporal parameters using a single inertial sensor mounted on the lower trunk.

Diana Trojaniello1, Andrea Cereatti2, Ugo Della Croce2.   

Abstract

In the last decade, various methods for the estimation of gait events and temporal parameters from the acceleration signals of a single inertial measurement unit (IMU) mounted at waist level have been proposed. Despite the growing interest for such methodologies, a thorough comparative analysis of methods with regards to number of extra and missed events, accuracy and robustness to IMU location is still missing in the literature. The aim of this work was to fill this gap. Five methods have been tested on single IMU data acquired from fourteen healthy subjects walking while being recorded by a stereo-photogrammetric system and two force platforms. The sensitivity in detecting initial and final contacts varied between 81% and 100% across methods, whereas the positive predictive values ranged between 94% and 100%. For all tested methods, stride and step time estimates were obtained; three of the selected methods also allowed estimation of stance, swing and double support time. Results showed that the accuracy in estimating step and stride durations was acceptable for all methods. Conversely, a statistical difference was found in the error in estimating stance, swing and double support time, due to the larger errors in the final contact determination. Except for one method, the IMU positioning on the lower trunk did not represent a critical factor for the estimation of gait temporal parameters. Results obtained in this study may not be applicable to pathologic gait.
Copyright © 2014 Elsevier B.V. All rights reserved.

Keywords:  Accelerometry; Gait analysis; Gait events; Inertial sensor; Temporal parameters

Mesh:

Year:  2014        PMID: 25085660     DOI: 10.1016/j.gaitpost.2014.07.007

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


  27 in total

1.  Extraction of stride events from gait accelerometry during treadmill walking.

Authors:  Ervin Sejdić; Kristin A Lowry; Jennica Bellanca; Subashan Perera; Mark S Redfern; Jennifer S Brach
Journal:  IEEE J Transl Eng Health Med       Date:  2015-12-18       Impact factor: 3.316

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

Authors:  Emeline Simonetti; Coralie Villa; Joseph Bascou; Giuseppe Vannozzi; Elena Bergamini; Hélène Pillet
Journal:  Med Biol Eng Comput       Date:  2019-12-23       Impact factor: 2.602

3.  Stride variability measures derived from wrist- and hip-worn accelerometers.

Authors:  Jacek K Urbanek; Jaroslaw Harezlak; Nancy W Glynn; Tamara Harris; Ciprian Crainiceanu; Vadim Zipunnikov
Journal:  Gait Posture       Date:  2016-11-30       Impact factor: 2.840

Review 4.  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

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.  Fourier-based integration of quasi-periodic gait accelerations for drift-free displacement estimation using inertial sensors.

Authors:  Angelo Maria Sabatini; Gabriele Ligorio; Andrea Mannini
Journal:  Biomed Eng Online       Date:  2015-11-23       Impact factor: 2.819

7.  A novel accelerometry-based algorithm for the detection of step durations over short episodes of gait in healthy elderly.

Authors:  M Encarna Micó-Amigo; Idsart Kingma; Erik Ainsworth; Stefan Walgaard; Martijn Niessen; Rob C van Lummel; Jaap H van Dieën
Journal:  J Neuroeng Rehabil       Date:  2016-04-19       Impact factor: 4.262

8.  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

9.  Free-living and laboratory gait characteristics in patients with multiple sclerosis.

Authors:  Fabio A Storm; K P S Nair; Alison J Clarke; Jill M Van der Meulen; Claudia Mazzà
Journal:  PLoS One       Date:  2018-05-01       Impact factor: 3.240

10.  Robust Stride Segmentation of Inertial Signals Based on Local Cyclicity Estimation.

Authors:  Sebastijan Šprager; Matjaž B Jurič
Journal:  Sensors (Basel)       Date:  2018-04-04       Impact factor: 3.576

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