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Published in:
Estimation of Arbitrary Human Models from Anthropometric Dimensions Read chapter Read first chapter

2015 | OriginalPaper | Chapter

Real-Time Static Gesture Recognition for Upper Extremity Rehabilitation Using the Leap Motion

Authors : Shawn N. Gieser, Angie Boisselle, Fillia Makedon

Published in: Digital Human Modeling. Applications in Health, Safety, Ergonomics and Risk Management: Ergonomics and Health

Publisher: Springer International Publishing

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Abstract

Cerebral Palsy is a motor disability that occurs in early childhood. Conventional therapy methods have proven useful for upper extremity rehabilitation, but can lead to non-compliance due to children getting bored with the repetition of exercises. Virtual reality and game-like simulations of conventional methods have proven to lead to higher rates of compliance, the patient being more engaged during exercising, and yield better performance during exercises. Most games are good at keeping players engaged, but does not focus on exercising fine motor control functions. In this paper, we present an analysis of classification techniques for static hand gestures. We also present a prototype of a game-like simulation of matching static hand gestures in order to increase motor control of the hand.

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previous chapter Modeling and Simulating Lifting Task of Below-Knee Amputees
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Metadata
Title
Real-Time Static Gesture Recognition for Upper Extremity Rehabilitation Using the Leap Motion
Authors
Shawn N. Gieser
Angie Boisselle
Fillia Makedon
Copyright Year
2015
Book
Digital Human Modeling. Applications in Health, Safety, Ergonomics and Risk Management: Ergonomics and Health

Print ISBN: 978-3-319-21069-8

Electronic ISBN: 978-3-319-21070-4

Copyright Year: 2015

DOI
https://doi.org/10.1007/978-3-319-21070-4_15