Automatic noise-level detection for extra-cellular micro-electrode recordings

Kevin Dolan; H. C. F. Martens; P. R. Schuurman; L. J. Bour

doi:https://doi.org/10.1007/s11517-009-0494-4

Automatic noise-level detection for extra-cellular micro-electrode recordings

Kevin Dolan, H. C. F. Martens, P. R. Schuurman, L. J. Bour

Research output: Contribution to journal › Article › Academic › peer-review

38 Citations (Scopus)

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

Original language	English
Pages (from-to)	791-800
Journal	Medical & Biological Engineering & Computing
Volume	47
Issue number	7
DOIs	https://doi.org/10.1007/s11517-009-0494-4
Publication status	Published - 2009

Access to Document

https://doi.org/10.1007/s11517-009-0494-4

Cite this

@article{f807856e05f448a8aef021341d440f31,

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",

author = "Kevin Dolan and Martens, {H. C. F.} and Schuurman, {P. R.} and Bour, {L. J.}",

year = "2009",

doi = "https://doi.org/10.1007/s11517-009-0494-4",

language = "English",

volume = "47",

pages = "791--800",

journal = "Medical & Biological Engineering & Computing",

issn = "0140-0118",

publisher = "Springer Verlag",

number = "7",

}

TY - JOUR

T1 - Automatic noise-level detection for extra-cellular micro-electrode recordings

AU - Dolan, Kevin

AU - Martens, H. C. F.

AU - Schuurman, P. R.

AU - Bour, L. J.

PY - 2009

Y1 - 2009

N2 - 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

AB - 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

U2 - https://doi.org/10.1007/s11517-009-0494-4

DO - https://doi.org/10.1007/s11517-009-0494-4

M3 - Article

C2 - 19468773

SN - 0140-0118

VL - 47

SP - 791

EP - 800

JO - Medical & Biological Engineering & Computing

JF - Medical & Biological Engineering & Computing

IS - 7

ER -