Characterizing Dynamic Walking Patterns and Detecting Falls with Wearable Sensors Using Gaussian Process Methods

Sensors
Taehwan KimJooyoung Park

Abstract

By incorporating a growing number of sensors and adopting machine learning technologies, wearable devices have recently become a prominent health care application domain. Among the related research topics in this field, one of the most important issues is detecting falls while walking. Since such falls may lead to serious injuries, automatically and promptly detecting them during daily use of smartphones and/or smart watches is a particular need. In this paper, we investigate the use of Gaussian process (GP) methods for characterizing dynamic walking patterns and detecting falls while walking with built-in wearable sensors in smartphones and/or smartwatches. For the task of characterizing dynamic walking patterns in a low-dimensional latent feature space, we propose a novel approach called auto-encoded Gaussian process dynamical model, in which we combine a GP-based state space modeling method with a nonlinear dimensionality reduction method in a unique manner. The Gaussian process methods are fit for this task because one of the most import strengths of the Gaussian process methods is its capability of handling uncertainty in the model parameters. Also for detecting falls while walking, we propose to recycle the latent samples...Continue Reading

References

Dec 23, 2000·Science·J B TenenbaumJ C Langford
Dec 23, 2000·Science·S T Roweis, L K Saul
Feb 1, 2006·IEEE Transactions on Information Technology in Biomedicine : a Publication of the IEEE Engineering in Medicine and Biology Society·Dean M KarantonisBranko G Celler
May 25, 2007·Neural Computation·Jooyoung ParkIvor W Tsang
Dec 18, 2007·IEEE Transactions on Pattern Analysis and Machine Intelligence·Jack M WangAaron Hertzmann
Jun 20, 2014·Sensors·Ahmet Turan Özdemir, Billur Barshan

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Citations

Nov 28, 2018·Sensors·Se-Min LimJooyoung Park
Sep 10, 2018·Aging Clinical and Experimental Research·Hoa NguyenMirza Mansoor Baig

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Methods Mentioned

BETA
feature extraction

Software Mentioned

Matlab
matplotlib
GPDM
pyplot

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