Sweeney, Kevin and Ayaz, Hasan and Ward, Tomas E. and Izzetoglu, Meltem and McLoone, Sean F. and Onaral, Banu (2011) A methodology for validating artifact removal techniques for fNIRS. In: 33rd Annual International Conference of the IEEE EMBS, August 30 - September 3, 2011, Boston, Massachusetts USA.

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Abstract

fNIRS recordings are increasingly utilized to monitor brain activity in both clinical and connected health settings. These optical recordings provide a convenient measurement of cerebral hemodynamic changes which can be linked to motor and cognitive performance. Such measurements are of clinical utility in a broad range of conditions ranging from dementia to movement rehabilitation therapy. For such applications fNIRS is increasingly deployed outside the clinic for patient monitoring in the home. However, such a measurement environment is poorly controlled and motion, in particular, is a major source of artifacts in the signal, leading to poor signal quality for subsequent clinical interpretation. Artifact removal techniques are increasingly being employed with an aim of reducing the effect of the noise in the desired signal. Currently no methodology is available to accurately determine the efficacy of a given artifact removal technique due to the lack of a true reference for the uncontaminated signal. In this paper we propose a novel methodology for fNIRS data collection allowing for effective validation of artifact removal techniques. This methodology describes the use of two fNIRS channels in close proximity allowing them to sample the same measurement location; allowing for the introducing of motion artifact to only one channel while having the other free of contamination. Through use of this methodology, for each motion artifact epoch, a true reference for the uncontaminated signal becomes available for use in the development and performance evaluation of signal processing strategies. The advantage of the described methodology is demonstrated using a simple artifact removal technique with an accelerometer based reference.

Item Type:	Conference or Workshop Item (Paper)
Keywords:	Accelerometers; Biomedical measurements; Detectors; Noise measurement; Pollution measurement; Signal to noise ratio;
Academic Unit:	Faculty of Science and Engineering > Electronic Engineering
Item ID:	3644
Depositing User:	Sean McLoone
Date Deposited:	08 May 2012 13:44
Refereed:	Yes
URI:
Use Licence:	This item is available under a Creative Commons Attribution Non Commercial Share Alike Licence (CC BY-NC-SA). Details of this licence are available here

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