title: Power feasibility of implantable digital spike sorting circuits for neural prosthetic systems.
abstract: A new class of neural prosthetic systems aims to assist disabled patients by translating cortical neural activity into control signals for prosthetic devices. Based on the success of proof-of-concept systems in the laboratory, there is now considerable interest in increasing system performance and creating implantable electronics for use in clinical systems. A critical question that impacts system performance and the overall architecture of these systems is whether it is possible to identify the neural source of each action potential (spike sorting) in real-time and with low power. Low power is essential both for power supply considerations and heat dissipation in the brain. In this paper we report that state-of-the-art spike sorting algorithms are not only feasible using modern complementary metal oxide semiconductor very large scale integration processes, but may represent the best option for extracting large amounts of data in implantable neural prosthetic interfaces.
authors.affiliation: Department of Electrical Engineering, Stanford University, Stanford, CA 94305, USA. zzumsteg@stanford.edu
authors.forename: Zachary S
authors.initials: ZS
authors.lastname: Zumsteg
authors.forename: Caleb
authors.initials: C
authors.lastname: Kemere
authors.forename: Stephen
authors.initials: S
authors.lastname: O'Driscoll
authors.forename: Gopal
authors.initials: G
authors.lastname: Santhanam
authors.forename: Rizwan E
authors.initials: RE
authors.lastname: Ahmed
authors.forename: Krishna V
authors.initials: KV
authors.lastname: Shenoy
authors.forename: Teresa H
authors.initials: TH
authors.lastname: Meng
mesh_terms: D000200:Action Potentials / Q000502:physiology*; D000465:Algorithms; D000703:Analog-Digital Conversion; D001921:Brain / Q000502:physiology*; D011211:Electric Power Supplies; D004569:Electroencephalography / Q000295:instrumentation* / Q000379:methods; D004735:Energy Transfer; D019544:Equipment Failure Analysis / Q000379:methods; D005240:Feasibility Studies; D006801:Humans; D009422:Nervous System Diseases / Q000534:rehabilitation; D019736:Prostheses and Implants; D012815:Signal Processing, Computer-Assisted / Q000295:instrumentation*; D013813:Therapy, Computer-Assisted / Q000295:instrumentation* / Q000379:methods; D014584:User-Computer Interface