EMGRIE : Ergonomic Microgesture Recognition and Interaction Evaluation, a case study
Name
895676074-MIT.pdf
Description
Full printable version
Size
11.67 MB
Format
Adobe PDF
Checksum (MD5)
9d93a7e575fe397d0a6813ce9a548bdc
Author(s)
Way, David (David H.)
Advisor(s)
Joseph Paradiso.
Date Issued
2014
Publisher
Massachusetts Institute of Technology
Abstract
Given the recent success of hand pose gesture recognition via wrist-worn camera based sensors, specific hand pose interaction evaluation is needed. In order to evaluate such interactions, we built EMGRIE: a quick-prototype wrist-worn vision-based gesture recognition system that applies necessary feature extraction and training data collection techniques to facilitate user customization of specific hand pose gestures. We use EMGRIE to extract differences in microgesture task times, perceived effort, and perceived command associations across users, gestures, gesture performance iterations, and various applications. This thesis gives a summary of past wrist-worn gesture recognition systems and past gestural application design research, EMGRIE system implementation details and differences, free-hand microgesture choice rational, and sample case studies concerning Google Glass application design and associated usability experimentation. Given the results of our system and application experimentation, we find that specific hand pose gesture preferences may change drastically between users and propose hypotheses concerning hand pose usability.
Description
Thesis: M. Eng., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2014.
Cataloged from PDF version of thesis.
Includes bibliographical references (pages 103-105).
Subjects
Electrical Engineering and Computer Science.
MIT Department
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
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