Telemetry System for Multi-channel Neural Recording in 802.15.4 Wireless Sensor Network

• Main Authors: Liu, Cheng-Feng, 劉承峰
• Other Authors: Chen, You-Yin
• Format: Others
• Language: zh-TW
• Published: 2009
• Online Access: http://ndltd.ncl.edu.tw/handle/00904390158368213695

碩士 === 國立交通大學 === 電控工程系所 === 98 === With the utilization of neural recording system, recording from hundreds of neurons will allow neurophysiologists to better understand the complex circuits of the nerve system. Contemporary experimental neural recording systems aimed for a free-moving animal connect implanted microelectrodes to external processing equipment through a cable tether. On the wired paradigm, the animal must behaviorally contented with the sensation of being tethered. Besides, the long cables also limit the size of the recording environment. It is therefore clear that replacing the wired instruments with telemetry interface is better suited to record neural signals from the free-moving animal for chronic recording. In recent years, the relationship between the social behavior of animal and the neural activities has been attractive to many neurophysiologists in the world. In this study, neural recording system based on wireless sensor network where the star topology is adopted is designed for processing and recording the multi-channel neural signals of multi-subjects.The adaptive-threshold spike-detection method is included to produce the beter performance of spike-detection as the burst on the scale of noise exists. The waveform and timing of spikes resulted from hardware-implemented adaptive-threshold spike-detection using FPGA is collected and wirelessly transmitted to Client. Considering the packet collision in the start topology, the transmission time scheduling (TTS) protocol is served as scheduling the timing of transmitted packets of each node in the network. In result, this study utilizes simulations and experiments to analysis the effective bandwidth, spike latency with different number of channel, and comparing the performance of the proposed neural recording system with TTS scheme and without TTS scheme. In conclusion, the ratio of data reduction performed by spike-detection algorithm is about 15. The limitation of FPGA output data rate resulted from the multi-channl spike-detection method is been found out depending on the scale of star topology with TTS and without TTS. With the usage of TTS scheme, the packet loss rate is about zero whatever the number of data transmitter node in the star topology is.