Development of a TV Human-machine-interface with Petri-net-based Wireless Sensor Network Architecture by Utilizing Biopotential Signals

• Main Authors: Yu-Cheng Kuo, 郭育丞
• Other Authors: Chung-Hsien Kuo
• Format: Others
• Language: zh-TW
• Published: 2012
• Online Access: http://ndltd.ncl.edu.tw/handle/22600043652542257640

碩士 === 國立臺灣科技大學 === 電機工程系 === 100 === This study presents a TV human-machine-interface (HMI) for high-level spinal cord patients. The TV HMI is developed with combining the electrooculography (EOG) and electroencephalography (EEG) biopotential signals. The above biopotential signals are responsible for detecting horizontal and vertical eye-gazing directions, as well as for recognizing opening and closing of eyes, so that the commands for TV on/off and changing channels and volumes can be desirable. In addition, a biopotential amplifier and processing device is futthetr developed to convert the two-channel EOG signals and a Pz EEG signal as five independent signal events, including the up-moving, down-moving, left-moving, right-moving of eye balls, and the closing of eyes. The five events are treated as the signal triggers for constructing a Petri net based wireless sensor node architecture (PN-WSNA) TV HMI model. Furthermore, the control scenario of generating the TV commands are implemented and evaluated by using the PN-WSNA approaches. A PN-WSNA-based autonomous sensor node is used to realize the TV HMI control system in terms of model-based implementation approach. Finally, several experiment results were discussed and evaluated to verify the feasibility of the proposed approaches.