TY - GEN
T1 - Demo
T2 - 2019 ACM International Joint Conference on Pervasive and Ubiquitous Computing and 2019 ACM International Symposium on Wearable Computers, UbiComp/ISWC 2019
AU - Niu, Kai
AU - Zhang, Fusang
AU - Jiang, Yuhang
AU - Chang, Zhaoxin
AU - Wang, Leye
AU - Zhang, Daqing
N1 - Publisher Copyright:
© 2019 Copyright held by the owner/author(s).
PY - 2019/9/9
Y1 - 2019/9/9
N2 - For the patients with speech and motion impairments, there is an indispensable need to facilitate their communication with other people, using approaches such as eyeball tracking. However, these systems are usually complex and expensive. In this demo, we propose a WiFi-based contactless text input system, called WiMorse. The system allows these patients to communicate with other people by using WiFi signals to track single-finger movements and encoding them as Morse code to input text. However, we note that a small change in the target’s location would lead to a significant change in the received WiFi signal pattern, making it impossible to recognize the finger gestures. To tackle this problem, we propose a signal transformation mechanism to obtain a consistent and stable signal pattern at various locations. By deploying only a pair of COTS WiFi devices, WiMorse can achieve real time recognition of finger generated Morse code with high accuracy, and is robust against input position, environment change, and user diversity.
AB - For the patients with speech and motion impairments, there is an indispensable need to facilitate their communication with other people, using approaches such as eyeball tracking. However, these systems are usually complex and expensive. In this demo, we propose a WiFi-based contactless text input system, called WiMorse. The system allows these patients to communicate with other people by using WiFi signals to track single-finger movements and encoding them as Morse code to input text. However, we note that a small change in the target’s location would lead to a significant change in the received WiFi signal pattern, making it impossible to recognize the finger gestures. To tackle this problem, we propose a signal transformation mechanism to obtain a consistent and stable signal pattern at various locations. By deploying only a pair of COTS WiFi devices, WiMorse can achieve real time recognition of finger generated Morse code with high accuracy, and is robust against input position, environment change, and user diversity.
KW - Channel State Information (CSI)
KW - Contactless Sensing
KW - Gesture Recognition
KW - Text Input
U2 - 10.1145/3341162.3343850
DO - 10.1145/3341162.3343850
M3 - Conference contribution
AN - SCOPUS:85072884743
T3 - UbiComp/ISWC 2019- - Adjunct Proceedings of the 2019 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2019 ACM International Symposium on Wearable Computers
SP - 328
EP - 331
BT - UbiComp/ISWC 2019- - Adjunct Proceedings of the 2019 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2019 ACM International Symposium on Wearable Computers
PB - Association for Computing Machinery, Inc
Y2 - 9 September 2019 through 13 September 2019
ER -