Literature DB >> 20153237

Inertial Gait Phase Detection for control of a drop foot stimulator Inertial sensing for gait phase detection.

D Kotiadis1, H J Hermens, P H Veltink.   

Abstract

An Inertial Gait Phase Detection system was developed to replace heel switches and footswitches currently being used for the triggering of drop foot stimulators. A series of four algorithms utilising accelerometers and gyroscopes individually and in combination were tested and initial results are shown. Sensors were positioned on the outside of the upper shank. Tests were performed on data gathered from a subject, sufferer of stroke, implanted with a drop foot stimulator and triggered with the current trigger, the heel switch. Data tested includes a variety of activities representing everyday life. Flat surface walking, rough terrain and carpet walking show 100% detection and the ability of the algorithms to ignore non-gait events such as weight shifts. Timing analysis is performed against the current triggering method, the heel switch. After evaluating the heel switch timing against a reference system, namely the Vicon 370 marker and force plates system. Initial results show a close correlation between the current trigger detection and the inertial sensor based triggering algorithms. Algorithms were tested for stairs up and stairs down. Best results are observed for algorithms using gyroscope data. Algorithms were designed using threshold techniques for lowest possible computational load and with least possible sensor components to minimize power requirements and to allow for potential future implantation of sensor system.

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Year:  2010        PMID: 20153237     DOI: 10.1016/j.medengphy.2009.10.014

Source DB:  PubMed          Journal:  Med Eng Phys        ISSN: 1350-4533            Impact factor:   2.242


  21 in total

1.  An adaptive gyroscope-based algorithm for temporal gait analysis.

Authors:  Barry R Greene; Denise McGrath; Ross O'Neill; Karol J O'Donovan; Adrian Burns; Brian Caulfield
Journal:  Med Biol Eng Comput       Date:  2010-11-02       Impact factor: 2.602

2.  Gait Cycle Validation and Segmentation Using Inertial Sensors.

Authors:  G V Prateek; Pietro Mazzoni; Gammon M Earhart; Arye Nehorai
Journal:  IEEE Trans Biomed Eng       Date:  2019-11-25       Impact factor: 4.538

3.  Bipedal gait model for precise gait recognition and optimal triggering in foot drop stimulator: a proof of concept.

Authors:  Muhammad Faraz Shaikh; Zoran Salcic; Kevin I-Kai Wang; Aiguo Patrick Hu
Journal:  Med Biol Eng Comput       Date:  2018-03-10       Impact factor: 2.602

4.  Assessing Neurokinematic and Neuromuscular Connectivity During Walking Using Mobile Brain-Body Imaging.

Authors:  Mingqi Zhao; Gaia Bonassi; Jessica Samogin; Gaia Amaranta Taberna; Camillo Porcaro; Elisa Pelosin; Laura Avanzino; Dante Mantini
Journal:  Front Neurosci       Date:  2022-06-03       Impact factor: 5.152

5.  A Nonlinear Dynamics-Based Estimator for Functional Electrical Stimulation: Preliminary Results From Lower-Leg Extension Experiments.

Authors:  Marcus Allen; Qiang Zhong; Nicholas Kirsch; Ashwin Dani; William W Clark; Nitin Sharma
Journal:  IEEE Trans Neural Syst Rehabil Eng       Date:  2017-09-07       Impact factor: 3.802

6.  Gait event detection during stair walking using a rate gyroscope.

Authors:  Paola Catalfamo Formento; Ruben Acevedo; Salim Ghoussayni; David Ewins
Journal:  Sensors (Basel)       Date:  2014-03-19       Impact factor: 3.576

7.  Towards Real-Time Detection of Gait Events on Different Terrains Using Time-Frequency Analysis and Peak Heuristics Algorithm.

Authors:  Hui Zhou; Ning Ji; Oluwarotimi Williams Samuel; Yafei Cao; Zheyi Zhao; Shixiong Chen; Guanglin Li
Journal:  Sensors (Basel)       Date:  2016-10-01       Impact factor: 3.576

Review 8.  Gait Partitioning Methods: A Systematic Review.

Authors:  Juri Taborri; Eduardo Palermo; Stefano Rossi; Paolo Cappa
Journal:  Sensors (Basel)       Date:  2016-01-06       Impact factor: 3.576

9.  Continuous gait cycle index estimation for electrical stimulation assisted foot drop correction.

Authors:  Christine Azevedo Coste; Jovana Jovic; Roger Pissard-Gibollet; Jérôme Froger
Journal:  J Neuroeng Rehabil       Date:  2014-08-09       Impact factor: 4.262

10.  A locomotion intent prediction system based on multi-sensor fusion.

Authors:  Baojun Chen; Enhao Zheng; Qining Wang
Journal:  Sensors (Basel)       Date:  2014-07-10       Impact factor: 3.576

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