Multivariate disturbance filtering in auditory fNIRS signals using maximum likelihood gradient estimation method: Feasibility study using sound quality indices

Functional near-infrared spectroscopy (fNIRS) technology has been widely used to analyze biomechanics and diagnose brain activity. Despite being a promising tool for assessing the brain cortex status, this system is susceptible to disturbances and noise from electrical instrumentation and basal meta...

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Vydané v:	Computers in biology and medicine Ročník 179; s. 108840
Hlavní autori:	Yoo, So-Hyeon, Hong, Jiyoung, Hong, Keum-Shik, Lee, Yonghee
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	United States Elsevier Ltd 01.09.2024 Elsevier Limited
Predmet:	Acoustic Stimulation - methods Acoustics Adult Algorithms Auditory stimuli Auditory stimulus Biomechanics Brain Brain research Comparative analysis Disturbances Ergonomics Feasibility Studies Female Functional near-infrared spectroscopy General linear model Hearing Hemodynamic responses Hemodynamics Hemoglobin Humans Infrared analysis Infrared filters Infrared spectra Infrared spectroscopy Internal Medicine Investigations Likelihood Functions Loudness Male Maximum likelihood estimation Maximum likelihood generalized extended stochastic gradient Medical imaging Metabolism Methods Multivariate analysis Multivariate disturbance parameter Near infrared radiation Other Oxygen saturation Parameter estimation Parameter identification Physiological effects Physiological responses Physiology Psycho-acoustic factor Respiration Shivering Signal processing Signal Processing, Computer-Assisted Signal quality Sound Sound quality index Spectroscopy, Near-Infrared - methods Technology assessment Wavelet transforms fNIRS Multivariate disturbance parameter Auditory stimulus mBLL Sound quality index GLM SQI General linear model ML-GESG Psycho-acoustic factor Functional near-infrared spectroscopy Maximum likelihood generalized extended stochastic gradient HbO HbR ARMA modified Beer–Lambert law autoregressive moving average oxygenated hemoglobin deoxygenated hemoglobin
ISSN:	0010-4825, 1879-0534, 1879-0534
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Shrnutí:	Functional near-infrared spectroscopy (fNIRS) technology has been widely used to analyze biomechanics and diagnose brain activity. Despite being a promising tool for assessing the brain cortex status, this system is susceptible to disturbances and noise from electrical instrumentation and basal metabolism. In this study, an alternative filtering method, maximum likelihood generalized extended stochastic gradient (ML-GESG) estimation, is proposed to overcome the limitations of these disturbance factors. The proposed algorithm was designed to reduce multiple disturbances originating from heartbeats, breathing, shivering, and instrumental noises as multivariate parameters. To evaluate the effectiveness of the algorithm in filtering involuntary signals, a comparative analysis was conducted with a conventional filtering method, using hemodynamic responses to auditory stimuli and psycho-acoustic factors as quality indices. Using auditory sound stimuli consisting of 12 voice sources (six males and six females), the fNIRS test was configured with 18 channels and conducted on 10 volunteers. The psycho-acoustic factors of loudness and sharpness were used to evaluate physiological responses to the stimuli. Applying the proposed filtering method, the oxygenated hemoglobin concentration correlated better with the psychoacoustic analysis of each auditory stimulus than that of the conventional filtering method. •Method to process fNIRS signals via maximum likelihood gradient estimation proposed.•Designed to reduce multiple disturbances originating from various noise signals.•Comparative analysis was conducted with conventional filtering systems.•In Psycho-acoustic factors, loudness and sharpness, used to evaluate response to stimuli.•fNIRS–SQI analysis can be used to assess psychological effects of human responses.
Bibliografia:	ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14 content type line 23
ISSN:	0010-4825 1879-0534 1879-0534
DOI:	10.1016/j.compbiomed.2024.108840