title: A TinyOS-enabled MICA2-based wireless neural interface.
abstract: Existing approaches used to develop compact low-power multichannel wireless neural recording systems range from creating custom-integrated circuits to assembling commercial-off-the-shelf (COTS) PC-based components. Custom-integrated-circuit designs yield extremely compact and low-power devices at the expense of high development and upgrade costs and turn-around times, while assembling COTS-PC-technology yields high performance at the expense of large system size and increased power consumption. To achieve a balance between implementing an ultra-compact custom-fabricated neural transceiver and assembling COTS-PC-technology, an overlay of a neural interface upon the TinyOS-based MICA2 platform is described. The system amplifies, digitally encodes, and transmits neural signals real-time at a rate of 9.6 kbps, while consuming less than 66 mW of power. The neural signals are received and forwarded to a client PC over a serial connection. This data rate can be divided for recording on up to 6 channels, with a resolution of 8 bits/sample. This work demonstrates the strengths and limitations of the TinyOS-based sensor technology as a foundation for chronic remote biological monitoring applications and, thus, provides an opportunity to create a system that can leverage from the frequent networking and communications advancements being made by the global TinyOS-development community.
authors.affiliation: Electrical Engineering Department, University of California, Los Angeles, CA 90095, USA. shahin@ee.ucla.edu
authors.forename: Shahin
authors.initials: S
authors.lastname: Farshchi
authors.forename: Paul H
authors.initials: PH
authors.lastname: Nuyujukian
authors.forename: Aleksey
authors.initials: A
authors.lastname: Pesterev
authors.forename: Istvan
authors.initials: I
authors.lastname: Mody
authors.forename: Jack W
authors.initials: JW
authors.lastname: Judy
mesh_terms: D000669:Amplifiers, Electronic; D000703:Analog-Digital Conversion; D000818:Animals; D001921:Brain / Q000502:physiology*; D003936:Diagnosis, Computer-Assisted / Q000295:instrumentation* / Q000379:methods; D004569:Electroencephalography / Q000295:instrumentation* / Q000379:methods; D004867:Equipment Design; D019544:Equipment Failure Analysis; D051379:Mice; D008810:Mice, Inbred C57BL; D008839:Microelectrodes; D018670:Monitoring, Ambulatory / Q000295:instrumentation* / Q000379:methods; D051381:Rats; D012815:Signal Processing, Computer-Assisted / Q000295:instrumentation*; D013686:Telemetry / Q000295:instrumentation* / Q000379:methods; D014584:User-Computer Interface