DocumentCode :
2490847
Title :
A methodology for validating artifact removal techniques for fNIRS
Author :
Sweeney, Kevin T. ; Ayaz, Hasan ; Ward, Tomás E. ; Izzetoglu, Meltem ; McLoone, Seán F. ; Onaral, Banu
Author_Institution :
Dept. of Electron. Eng., Nat. Univ. of Ireland Maynooth, Maynooth, Ireland
fYear :
2011
fDate :
Aug. 30 2011-Sept. 3 2011
Firstpage :
4943
Lastpage :
4946
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.
Keywords :
accelerometers; brain; cognition; haemodynamics; infrared spectra; medical signal processing; noise; patient monitoring; patient rehabilitation; patient treatment; accelerometer based reference; artifact removal technique; brain activity; cerebral hemodynamics; clinical interpretation; clinical setting; cognitive performance; connected health setting; dementia; fNIRS channel; fNIRS data collection; motion artifact epoch; motor performance; movement rehabilitation therapy; noise; optical recordings; patient monitoring; signal processing strategy; uncontaminated signal; Accelerometers; Biomedical measurements; Detectors; Noise measurement; Pollution measurement; Signal to noise ratio; Algorithms; Artifacts; Brain; Diagnosis, Computer-Assisted; Functional Neuroimaging; Humans; Movement; Reproducibility of Results; Sensitivity and Specificity; Spectroscopy, Near-Infrared;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Engineering in Medicine and Biology Society, EMBC, 2011 Annual International Conference of the IEEE
Conference_Location :
Boston, MA
ISSN :
1557-170X
Print_ISBN :
978-1-4244-4121-1
Electronic_ISBN :
1557-170X
Type :
conf
DOI :
10.1109/IEMBS.2011.6091225
Filename :
6091225
Link To Document :
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