TY - GEN
T1 - Flexible force sensor based input device for gesture recognition applicable to augmented and virtual realities
AU - Kim, Jinyong
AU - Kwak, Yeon Hwa
AU - Kim, Wonhyo
AU - Park, Kwangbum
AU - Pak, James Jungho
AU - Kim, Kunnyun
N1 - Publisher Copyright:
© 2017 IEEE.
Copyright:
Copyright 2017 Elsevier B.V., All rights reserved.
PY - 2017/7/25
Y1 - 2017/7/25
N2 - With the development of smart devices supporting VR (Virtual Reality) and AR (Augmented Reality), users' input devices are changing to wearable devices. The existing input devices for gesture recognition were relatively rigid. In this research, we propose a gesture recognition device by using a flexible substrate to manufacture a device that can be used in close contact with a user's wrist. An array of flexible resistive strain gauge sensors was fabricated for sensing spatial muscle movements of the wrist. The fabricated strain sensors showed a linearly varying output characteristic, and a sensitivity of 0.05143 Ω/g was obtained for a load test from 0 to 500 g. A circuit board for processing sensor data was fabricated and a program was coded for collecting the sensor data from the circuit board. With this system, it was confirmed that the average recognition rate per gesture is 94.6% after applying these input devices directly to five basic wrists gestures on five test subjects.
AB - With the development of smart devices supporting VR (Virtual Reality) and AR (Augmented Reality), users' input devices are changing to wearable devices. The existing input devices for gesture recognition were relatively rigid. In this research, we propose a gesture recognition device by using a flexible substrate to manufacture a device that can be used in close contact with a user's wrist. An array of flexible resistive strain gauge sensors was fabricated for sensing spatial muscle movements of the wrist. The fabricated strain sensors showed a linearly varying output characteristic, and a sensitivity of 0.05143 Ω/g was obtained for a load test from 0 to 500 g. A circuit board for processing sensor data was fabricated and a program was coded for collecting the sensor data from the circuit board. With this system, it was confirmed that the average recognition rate per gesture is 94.6% after applying these input devices directly to five basic wrists gestures on five test subjects.
KW - AR (Augmented Reality)
KW - Flexible
KW - Gesture Recognition
KW - Input Device
KW - VR (Virtual Reality)
UR - http://www.scopus.com/inward/record.url?scp=85034242789&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85034242789&partnerID=8YFLogxK
U2 - 10.1109/URAI.2017.7992727
DO - 10.1109/URAI.2017.7992727
M3 - Conference contribution
AN - SCOPUS:85034242789
T3 - 2017 14th International Conference on Ubiquitous Robots and Ambient Intelligence, URAI 2017
SP - 271
EP - 273
BT - 2017 14th International Conference on Ubiquitous Robots and Ambient Intelligence, URAI 2017
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 14th International Conference on Ubiquitous Robots and Ambient Intelligence, URAI 2017
Y2 - 28 June 2017 through 1 July 2017
ER -