An Embedded System Architecture for Wireless Neural Recording

Abstract

We have designed and tested a complete end-to-end neural-signal communications system. To achieve a compromise between programmability and size/power consumption, we have used the TelosB mote as a platform for our wireless signal acquisition, processing, and communications device. The system operates in two modes of operation: (1) real-time, in which the raw signal is acquired via a custom neural-signal amplifier circuit, ADPCM compressed, and transmitted in real time at a rate of 4000 12-bit samples per second; (2) and spike-detection, where data is sampled at a rate of 16670 12-bit samples per second, and spike waveforms are detected via an adaptive absolute threshold algorithm. Data is transmitted wirelessly to a gateway mote, which forwards the signals to an archive server. The archive server makes the neural signals available to a client application, which retrieves waveforms and detected spike parameters. The client application also enables the user to set amplifier gain and high-pass corner frequency remotely. The system consumes approximately 50 mW of power in the real-time mode of operation, and approximately 1 to 5 mW of power in the spike-acquisition mode of operation. The animal-mounted sensor is approximately the size of a matchbox, and weighs 66 g.