Literature DB >> 22955865

Heel and toe clearance estimation for gait analysis using wireless inertial sensors.

Benoit Mariani1, Stephane Rochat, Christophe J Büla, Kamiar Aminian.   

Abstract

Tripping is considered a major cause of fall in older people. Therefore, foot clearance (i.e., height of the foot above ground during swing phase) could be a key factor to better understand the complex relationship between gait and falls. This paper presents a new method to estimate clearance using a foot-worn and wireless inertial sensor system. The method relies on the computation of foot orientation and trajectory from sensors signal data fusion, combined with the temporal detection of toe-off and heel-strike events. Based on a kinematic model that automatically estimates sensor position relative to the foot, heel and toe trajectories are estimated. 2-D and 3-D models are presented with different solving approaches, and validated against an optical motion capture system on 12 healthy adults performing short walking trials at self-selected, slow, and fast speed. Parameters corresponding to local minimum and maximum of heel and toe clearance were extracted and showed accuracy ± precision of 4.1 ± 2.3 cm for maximal heel clearance and 1.3 ± 0.9 cm for minimal toe clearance compared to the reference. The system is lightweight, wireless, easy to wear and to use, and provide a new and useful tool for routine clinical assessment of gait outside a dedicated laboratory.

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Year:  2012        PMID: 22955865     DOI: 10.1109/TBME.2012.2216263

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


  36 in total

1.  Sensor-based gait analysis of individualized improvement during apomorphine titration in Parkinson's disease.

Authors:  Franz Marxreiter; Heiko Gaßner; Olga Borozdina; Jens Barth; Zacharias Kohl; Johannes C M Schlachetzki; Caroline Thun-Hohenstein; Dieter Volc; Bjoern M Eskofier; Jürgen Winkler; Jochen Klucken
Journal:  J Neurol       Date:  2018-09-08       Impact factor: 4.849

2.  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

3.  Gait apraxia evaluation in normal pressure hydrocephalus using inertial sensors. Clinical correlates, ventriculoperitoneal shunt outcomes, and tap-test predictive capacity.

Authors:  Alberto Ferrari; David Milletti; Pierpaolo Palumbo; Giulia Giannini; Sabina Cevoli; Elena Magelli; Luca Albini-Riccioli; Paolo Mantovani; Pietro Cortelli; Lorenzo Chiari; Giorgio Palandri
Journal:  Fluids Barriers CNS       Date:  2022-06-23

4.  Blood Pressure Drop Prediction by using HRV Measurements in Orthostatic Hypotension.

Authors:  Giovanna Sannino; Paolo Melillo; Saverio Stranges; Giuseppe De Pietro; Leandro Pecchia
Journal:  J Med Syst       Date:  2015-09-07       Impact factor: 4.460

5.  Spatio-temporal gait parameters obtained from foot-worn inertial sensors are reliable in healthy adults in single- and dual-task conditions.

Authors:  J Soulard; J Vaillant; R Balaguier; N Vuillerme
Journal:  Sci Rep       Date:  2021-05-13       Impact factor: 4.379

6.  Reliability in the parameterization of the functional reach test in elderly stroke patients: a pilot study.

Authors:  Jose Antonio Merchán-Baeza; Manuel González-Sánchez; Antonio Ignacio Cuesta-Vargas
Journal:  Biomed Res Int       Date:  2014-04-29       Impact factor: 3.411

7.  Estimation of spatial-temporal gait parameters using a low-cost ultrasonic motion analysis system.

Authors:  Yongbin Qi; Cheong Boon Soh; Erry Gunawan; Kay-Soon Low; Rijil Thomas
Journal:  Sensors (Basel)       Date:  2014-08-20       Impact factor: 3.576

8.  Gait and foot clearance parameters obtained using shoe-worn inertial sensors in a large-population sample of older adults.

Authors:  Farzin Dadashi; Benoit Mariani; Stephane Rochat; Christophe J Büla; Brigitte Santos-Eggimann; Kamiar Aminian
Journal:  Sensors (Basel)       Date:  2013-12-27       Impact factor: 3.576

9.  Detecting falls with wearable sensors using machine learning techniques.

Authors:  Ahmet Turan Özdemir; Billur Barshan
Journal:  Sensors (Basel)       Date:  2014-06-18       Impact factor: 3.576

10.  Physical Behavior in Older Persons during Daily Life: Insights from Instrumented Shoes.

Authors:  Christopher Moufawad El Achkar; Constanze Lenoble-Hoskovec; Anisoara Paraschiv-Ionescu; Kristof Major; Christophe Büla; Kamiar Aminian
Journal:  Sensors (Basel)       Date:  2016-08-03       Impact factor: 3.576

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