Template-Based Step Detection with Inertial Measurement Units
This article presents a method for step detection from accelerometer and gyrometer signals recorded with Inertial Measurement Units (IMUs). The principle of our step detection algorithm is to recognize the start and end times of the steps in the signal thanks to a predefined library of templates. Th...
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doaj-f4cb7550df4e4298bf1550df9c0a21a52020-11-24T23:22:34ZengMDPI AGSensors1424-82202018-11-011811403310.3390/s18114033s18114033Template-Based Step Detection with Inertial Measurement UnitsLaurent Oudre0Rémi Barrois-Müller1Thomas Moreau2Charles Truong3Aliénor Vienne-Jumeau4Damien Ricard5Nicolas Vayatis6Pierre-Paul Vidal7L2TI, University Paris 13, 93430 Villetaneuse, FranceCOGNAC-G (UMR 8257), CNRS Service de Santé des Armées University Paris Descartes, 75006 Paris, FranceCMLA (UMR 8536), CNRS ENS Paris-Saclay, 94235 Cachan, FranceCMLA (UMR 8536), CNRS ENS Paris-Saclay, 94235 Cachan, FranceCOGNAC-G (UMR 8257), CNRS Service de Santé des Armées University Paris Descartes, 75006 Paris, FranceService de neurologie, Hôpital d’Instruction des Armées Percy, Service de Santé des Armées, 92190 Clamart, FranceCMLA (UMR 8536), CNRS ENS Paris-Saclay, 94235 Cachan, FranceHangzhou Dianzi University, Hangzhou 310005, Zhejiang, ChinaThis article presents a method for step detection from accelerometer and gyrometer signals recorded with Inertial Measurement Units (IMUs). The principle of our step detection algorithm is to recognize the start and end times of the steps in the signal thanks to a predefined library of templates. The algorithm is tested on a database of 1020 recordings, composed of healthy subjects and patients with various neurological or orthopedic troubles. Simulations on more than 40,000 steps show that the template-based method achieves remarkable results with a 98% recall and a 98% precision. The method adapts well to pathological subjects and can be used in a medical context for robust step estimation and gait characterization.https://www.mdpi.com/1424-8220/18/11/4033inertial measurement unitsgait analysisbiomedical signal processingpattern recognitionstep detectionphysiological signals |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Laurent Oudre Rémi Barrois-Müller Thomas Moreau Charles Truong Aliénor Vienne-Jumeau Damien Ricard Nicolas Vayatis Pierre-Paul Vidal |
spellingShingle |
Laurent Oudre Rémi Barrois-Müller Thomas Moreau Charles Truong Aliénor Vienne-Jumeau Damien Ricard Nicolas Vayatis Pierre-Paul Vidal Template-Based Step Detection with Inertial Measurement Units Sensors inertial measurement units gait analysis biomedical signal processing pattern recognition step detection physiological signals |
author_facet |
Laurent Oudre Rémi Barrois-Müller Thomas Moreau Charles Truong Aliénor Vienne-Jumeau Damien Ricard Nicolas Vayatis Pierre-Paul Vidal |
author_sort |
Laurent Oudre |
title |
Template-Based Step Detection with Inertial Measurement Units |
title_short |
Template-Based Step Detection with Inertial Measurement Units |
title_full |
Template-Based Step Detection with Inertial Measurement Units |
title_fullStr |
Template-Based Step Detection with Inertial Measurement Units |
title_full_unstemmed |
Template-Based Step Detection with Inertial Measurement Units |
title_sort |
template-based step detection with inertial measurement units |
publisher |
MDPI AG |
series |
Sensors |
issn |
1424-8220 |
publishDate |
2018-11-01 |
description |
This article presents a method for step detection from accelerometer and gyrometer signals recorded with Inertial Measurement Units (IMUs). The principle of our step detection algorithm is to recognize the start and end times of the steps in the signal thanks to a predefined library of templates. The algorithm is tested on a database of 1020 recordings, composed of healthy subjects and patients with various neurological or orthopedic troubles. Simulations on more than 40,000 steps show that the template-based method achieves remarkable results with a 98% recall and a 98% precision. The method adapts well to pathological subjects and can be used in a medical context for robust step estimation and gait characterization. |
topic |
inertial measurement units gait analysis biomedical signal processing pattern recognition step detection physiological signals |
url |
https://www.mdpi.com/1424-8220/18/11/4033 |
work_keys_str_mv |
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