Acquiring high-rate neural spike data with hardware-constrained embedded sensors.
In an effort to enable embedded sensors that are hardware and bandwidth constrained to acquire high- frequency neural signals, signal-filtering and signal- compression algorithms have been implemented and tested on a commercial-off-the-shelf embedded-system platform. The sensor modules have been programmed to acquire, filter, and transmit raw biological signals at a rate of 32 kbps. Furthermore, on-board signal processing enables one channel sampled at a rate of 4 kS/s at 12-bit resolution to be compressed via ADPCM and transmitted in real time. In addition, the sensors can be configured to only transmit individual time-referenced "spike" waveforms, or only the spike parameters for alleviating network traffic and increasing battery life.
Farshchi
Shahin
S
Department of Electrical Engineering, University of California-Los Angeles, CA 90095, USA. shahin@ee.ucla.edu
Pesterev
Aleksey
A
Ho
Wan-Lun
WL
Judy
Jack W
JW
D000200:Action Potentials / Q000502:physiology*; D000465:Algorithms; D000669:Amplifiers, Electronic; D000703:Analog-Digital Conversion; D044962:Data Compression / Q000379:methods*; D004867:Equipment Design; D019544:Equipment Failure Analysis; D006801:Humans; D009474:Neurons / Q000502:physiology*; D012815:Signal Processing, Computer-Assisted / Q000295:instrumentation*; D014159:Transducers