A TinyOS-Based Wireless Neural Sensing, Archiving, and Hosting System

We have designed and tested a comprehensive wireless neural recording system. The system amplifies, digitally encodes, transmits, archives, hosts, and displays multiple channels of neural recordings from any number of un-tethered test subjects. The neural transmitter and receiver are modified TinyOS-based MICAz wireless sensor nodes that can sample, transmit, and receive neural data real-time at a rate of 44.8 kbps while consuming less than 100 mW of power. This data rate can be divided for recording on up to eight channels, with a resolution of up to 10 bits per sample. An archive server records the neural signals received by the Ethernet-based gateway receivers, and hosts them to browser-based clients over the Internet. This work demonstrates the viability of the TinyOS-based sensor technology as a foundation for chronic remote biological monitoring applications, and demonstrated a system architecture that can actively leverage advancements in distributed sensing, networking, and communications technologies