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Cited 4 time in webofscience Cited 8 time in scopus
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Gyroscope-Based Continuous Human Hand Gesture Recognition for Multi-Modal Wearable Input Device for Human Machine Interactionopen access

Authors
Han, HobeomYoon, Sang Won
Issue Date
Jun-2019
Publisher
MDPI
Keywords
hand gesture; continuous gesture recognition; gyroscope; multi-modal input devices; unified wearable input devices
Citation
SENSORS, v.19, no.11, pp.1 - 18
Indexed
SCIE
SCOPUS
Journal Title
SENSORS
Volume
19
Number
11
Start Page
1
End Page
18
URI
https://scholarworks.bwise.kr/hanyang/handle/2021.sw.hanyang/3819
DOI
10.3390/s19112562
ISSN
1424-8220
Abstract
Human hand gestures are a widely accepted form of real-time input for devices providing a human-machine interface. However, hand gestures have limitations in terms of effectively conveying the complexity and diversity of human intentions. This study attempted to address these limitations by proposing a multi-modal input device, based on the observation that each application program requires different user intentions (and demanding functions) and the machine already acknowledges the running application. When the running application changes, the same gesture now offers a new function required in the new application, and thus, we can greatly reduce the number and complexity of required hand gestures. As a simple wearable sensor, we employ one miniature wireless three-axis gyroscope, the data of which are processed by correlation analysis with normalized covariance for continuous gesture recognition. Recognition accuracy is improved by considering both gesture patterns and signal strength and by incorporating a learning mode. In our system, six unit hand gestures successfully provide most functions offered by multiple input devices. The characteristics of our approach are automatically adjusted by acknowledging the application programs or learning user preferences. In three application programs, the approach shows good accuracy (90-96%), which is very promising in terms of designing a unified solution. Furthermore, the accuracy reaches 100% as the users become more familiar with the system.
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서울 공과대학 > 서울 미래자동차공학과 > 1. Journal Articles

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