Abstract
The human-computer interaction (HCI) is now playing a great role in computer technology. This study introduces an automatic document control technique which is based on the human hand waving movements. The recognition of hand movement is realized according to the surface electromyography (sEMG). A collector is set on the forearm. The sEMG signal is recorded and conveyed to a PC terminal by using wireless Zigbee. An automatic algorithm is developed in order to extract the characteristics of sEMG, recognize the waving movements, and transmit to document control command. The developed human-computer interaction technique can be used as a new gallery for teaching, as well as an assistant tool for disabled person.
Highlights
EMG recordings are often incorporated by the electrocardiogram (ECG), which can disturb the classifications of hand movement and result in misinterpretations [3]
The control command is produced through the analysis of surface electromyography (sEMG) signals
EOG signals are eliminated from sEMG with the independent component analysis method (ICA) algorithm which enhances the accuracy of control command
Summary
The normal HCI method is usually achieved with a keyboard along with a mouse or a touch screen. It is really inconvenient for disabled people to use these equipments by themselves. All the signals of muscle movement can be detected and recorded [1]. The normal sEMG collect method needs lots of complex electrodes linked with PC and experimenters which always make the users feel uncomfortable. This paper proposes a new method to convey the sEMG to PC wirelessly, so there are no miscellaneous link lines across researchers and users. Since EMG is often contaminated by the ECG, it usually hampers data analysis and potentially yields misinterpretations. The system comes true with stable, security and practical use
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