Evoked Hemodynamic Response Estimation to Auditory Stimulus Using Recursive Least Squares Adaptive Filtering with Multidistance Measurement of Near-Infrared Spectroscopy

Author:

Zhang Yan12ORCID,Liu Xin3ORCID,Liu Dan1ORCID,Yang Chunling1,Wang Qisong1,Sun Jinwei1,Wang Kuanquan2ORCID

Affiliation:

1. School of Electrical Engineering and Automaton, Harbin Institute of Technology, Harbin 150001, China

2. School of Computer Science and Technology, Harbin Institute of Technology, Harbin 150001, China

3. School of Transportation Science and Engineering, Harbin Institute of Technology, Harbin 150090, China

Abstract

The performance of functional near-infrared spectroscopy (fNIRS) is sometimes degraded by the interference caused by the physical or the systemic physiological activities. Several interferences presented during fNIRS recordings are mainly induced by cardiac pulse, breathing, and spontaneous physiological low-frequency oscillations. In previous work, we introduced a multidistance measurement to reduce physiological interference based on recursive least squares (RLS) adaptive filtering. Monte Carlo simulations have been implemented to evaluate the performance of RLS adaptive filtering. However, its suitability and performance on human data still remain to be evaluated. Here, we address the issue of how to detect evoked hemodynamic response to auditory stimulus using RLS adaptive filtering method. A multidistance probe based on continuous wave fNIRS is devised to achieve the fNIRS measurement and further study the brain functional activation. This study verifies our previous findings that RLS adaptive filtering is an effective method to suppress global interference and also provides a practical way for real-time detecting brain activity based on multidistance measurement.

Funder

Fundamental Research Funds for the Central Universities

Publisher

Hindawi Limited

Subject

Health Informatics,Biomedical Engineering,Surgery,Biotechnology

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