title: Automatic noise-level detection for extra-cellular micro-electrode recordings.
abstract: Extra-cellular neuro-recording signals used for functional mapping in deep brain stimulation (DBS) surgery and invasive brain computer interfaces, may suffer from poor signal to noise ratio. Therefore, a reliable automatic noise estimate is essential to extract spikes from recordings. We show that current methods are biased toward overestimation of noise-levels with increasing neuronal activity or artifacts. An improved and novel method is proposed that is based on an estimate of the mode of the distribution of the signal envelope. Our method makes use of the inherent characteristics of the noise distribution. For band-limited Gaussian noise the envelope of the signal is known to follow the Rayleigh distribution. The location of the peak of this distribution provides a reliable noise-level estimate. It is demonstrated that this new 'envelope' method gives superior performance both on simulated data, and on actual micro-electrode recordings made during the implantation surgery of DBS electrodes for the treatment of Parkinson's disease.
authors.affiliation: Philips Research, High Tech Campus 34, 5656 AE, Eindhoven, The Netherlands. kevin.dolan@philips.com
authors.forename: Kevin
authors.initials: K
authors.lastname: Dolan
authors.forename: H C F
authors.initials: HC
authors.lastname: Martens
authors.forename: P R
authors.initials: PR
authors.lastname: Schuurman
authors.forename: L J
authors.initials: LJ
authors.lastname: Bour
mesh_terms: D016477:Artifacts; D001931:Brain Mapping / Q000379:methods*; D046690:Deep Brain Stimulation / Q000379:methods*; D006801:Humans; D007430:Intraoperative Care / Q000379:methods; D008839:Microelectrodes; D010300:Parkinson Disease / Q000503:physiopathology / Q000601:surgery; D012815:Signal Processing, Computer-Assisted