Paper Info
Title
Towards Finger Gestures and Force Recognition Based on Wrist Electromyography and Accelerometers.
Abstract
Surface electromyography (EMG) is widely used in hand gesture recognition for human-computer interface (HCI). This paper presents a finger gesture recognition scheme at two level of plane pressing force through the fusion of wrist EMG and accelerometers (ACC). The classification algorithm is evaluated on eight healthy subjects for identifying five finger gestures at two plane pressing force level. Experimental results show that frequency domain (improved discrete Fourier, iDFT) feature is better than time domain (TD) feature for wrist EMG classification. Moreover, it indicates that the fusion of EMG and ACC achieved improved recognition performance (85.77%) for finger gestures at two level of plane pressing force when compared to that obtained using EMG (80.65%) or ACC (56.86%) solely.
Year
Venue
Field
2017
ICIRA
Frequency domain,Time domain,Computer vision,Wrist,Accelerometer,Gesture,Control theory,Gesture recognition,Electromyography,Artificial intelligence,Engineering,Discrete Fourier transform
DocType
Citations 
PageRank 
Conference
0
0.34
References 
Authors
11
5
Name
Order
Citations
PageRank
Bo Lv1139.79
Xinjun Sheng217047.79
Weichao Guo3184.59
Xiangyang Zhu445376.24
Han Ding549978.16