Gait event detection using a multilayer neural network

Gait & Posture
Adam Miller

Abstract

Manual detection of gait events via visual inspection of motion capture data is a laborious process. There are currently no robust techniques available to automate the process for pathologic gait. However, the detection of gait events is essentially a classification problem; an application for which artificial neural networks are well suited. In this paper, a multilayer artificial neural network is presented for the purpose of classifying foot-contact and foot-off events using the sagittal plane coordinates of heel and toe markers. The timing of events detected using this method was compared to the timing of events detected by measuring the ground reaction force using a force plate for a total of 40 pathologic subjects divided into two groups: barefoot and shod/braced. On average, the neural network detected foot-contact events 7.1 ms and 0.8 ms earlier than the force plate for the barefoot and shod/braced groups respectively. The average difference for foot-off events was 8.8 ms and 3.3 ms. Given that motion capture data were collected at 120 Hz, this implies that the force plate method and neural network method generally agreed within 1-2 frames of data. Consequently, the neural network was shown to be an accurate, autonomous...Continue Reading

References

Jul 1, 1990·Medical & Biological Engineering & Computing·S J StanhopeN L Roman
Dec 19, 2001·Journal of Biomechanics·Andrew H HansenMargrit R Meier
Aug 1, 2006·Gait & Posture·Ciara M O'ConnorChristopher L Vaughan

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Citations

Nov 3, 2010·Medical & Biological Engineering & Computing·Barry R GreeneBrian Caulfield
May 25, 2011·Computer Methods in Biomechanics and Biomedical Engineering·Sunwoo ParkYoungho Kim
Jun 12, 2014·Journal of Neuroengineering and Rehabilitation·Gabor J BartonMark A Robinson
Jan 12, 2016·Sensors·Juri TaborriPaolo Cappa
Jan 17, 2013·IEEE Transactions on Neural Systems and Rehabilitation Engineering : a Publication of the IEEE Engineering in Medicine and Biology Society·Min S H AungJohn Y Goulermas
Apr 8, 2010·IEEE Transactions on Information Technology in Biomedicine : a Publication of the IEEE Engineering in Medicine and Biology Society·Anita Sant'anna, Nicholas Wickström
Feb 1, 2019·PloS One·Łukasz KidzińskiMichael Schwartz
Oct 11, 2012·Microbial Drug Resistance : MDR : Mechanisms, Epidemiology, and Disease·Carlos F Amábile-Cuevas
Jul 30, 2020·Biomedical Engineering Online·Francesco Di NardoSandro Fioretti

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