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2017 | OriginalPaper | Buchkapitel

Tip-Toe Walking Detection Using CPG Parameters from Skeleton Data Gathered by Kinect

verfasst von : Rasool Taban, Atoosa Parsa, Hadi Moradi

Erschienen in: Ubiquitous Computing and Ambient Intelligence

Verlag: Springer International Publishing

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Abstract

Distinguishing tip-toe walking from normal walking, in human locomotion patterns, becomes important in applications such as Autism disorder identification. In this paper, we propose a novel approach for tip-toe walking detection based on the walk’s Central Pattern Generator (CPG) parameters. In the proposed approach, the tip-toe walking is modeled by a CPG. Then, the motions of subjects are recorded and skeleton data are extracted using the first-generation Microsoft Kinect sensor. The CPG parameters of these motions are determined and compared to the given patterns to distinguish between tip-toe walking and normal walking. The accuracy of classification is promising while further data will improve the accuracy rate.

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Metadaten
Titel
Tip-Toe Walking Detection Using CPG Parameters from Skeleton Data Gathered by Kinect
verfasst von
Rasool Taban
Atoosa Parsa
Hadi Moradi
Copyright-Jahr
2017
DOI
https://doi.org/10.1007/978-3-319-67585-5_30