Signal extraction of brain activity response by near infrared spectroscopy based on recursive least squares adaptive filtering

Y. Zhang, J. W. Sun, C. L. Yang, M. Zhu, B. Zhang, F. Scopesi, G. Serra, P. Rolfe

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Near infrared spectroscopy (NIRS) is a non-invasive technique having the potential to allow the study of brain functional activation through the monitoring of changes in haemodynamic variables. However, the NIRS data derived in this application are often contaminated by physiological interference arising, for example, from cardiac contraction, breathing, and spontaneous low frequency oscillations. There have therefore been efforts to develop signal processing schemes aimed at improving signal quality. In the present paper, the multidistance NIRS probe configuration has been adopted. The near-distance source-detector pair is used to derive the superficial haemodynamic changes and the fardistance source-detector pair is used to derive deep haemodynamic changes. The recursive least squares algorithm was used to process the NIRS data in order to suppress physiological interference. We also utilized Monte Carlo simulations, based on a five-layer model of the adult human head, to evaluate our methodology. The results suggest that the recursive least squares approach has the potential to reduce physiological interference in NIRS data. Important advantages of this method are that it is adaptive and it can be used for real-time signal extraction of brain activity.

Original languageEnglish
Title of host publicationIFMBE Proceedings
Pages371-374
Number of pages4
Volume39 IFMBE
DOIs
Publication statusPublished - 2013
EventWorld Congress on Medical Physics and Biomedical Engineering - Beijing, China
Duration: May 26 2012May 31 2012

Other

OtherWorld Congress on Medical Physics and Biomedical Engineering
CountryChina
CityBeijing
Period5/26/125/31/12

Fingerprint

Near infrared spectroscopy
Adaptive filtering
Brain
Hemodynamics
Detectors
Signal processing
Chemical activation
Monitoring

Keywords

  • Lambert-Beer law
  • Monte Carlo
  • Multidistance measurement
  • Near infrared spectroscopy
  • Recursive least squares

ASJC Scopus subject areas

  • Biomedical Engineering
  • Bioengineering

Cite this

Zhang, Y., Sun, J. W., Yang, C. L., Zhu, M., Zhang, B., Scopesi, F., ... Rolfe, P. (2013). Signal extraction of brain activity response by near infrared spectroscopy based on recursive least squares adaptive filtering. In IFMBE Proceedings (Vol. 39 IFMBE, pp. 371-374) https://doi.org/10.1007/978-3-642-29305-4_99

Signal extraction of brain activity response by near infrared spectroscopy based on recursive least squares adaptive filtering. / Zhang, Y.; Sun, J. W.; Yang, C. L.; Zhu, M.; Zhang, B.; Scopesi, F.; Serra, G.; Rolfe, P.

IFMBE Proceedings. Vol. 39 IFMBE 2013. p. 371-374.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Zhang, Y, Sun, JW, Yang, CL, Zhu, M, Zhang, B, Scopesi, F, Serra, G & Rolfe, P 2013, Signal extraction of brain activity response by near infrared spectroscopy based on recursive least squares adaptive filtering. in IFMBE Proceedings. vol. 39 IFMBE, pp. 371-374, World Congress on Medical Physics and Biomedical Engineering, Beijing, China, 5/26/12. https://doi.org/10.1007/978-3-642-29305-4_99
Zhang Y, Sun JW, Yang CL, Zhu M, Zhang B, Scopesi F et al. Signal extraction of brain activity response by near infrared spectroscopy based on recursive least squares adaptive filtering. In IFMBE Proceedings. Vol. 39 IFMBE. 2013. p. 371-374 https://doi.org/10.1007/978-3-642-29305-4_99
Zhang, Y. ; Sun, J. W. ; Yang, C. L. ; Zhu, M. ; Zhang, B. ; Scopesi, F. ; Serra, G. ; Rolfe, P. / Signal extraction of brain activity response by near infrared spectroscopy based on recursive least squares adaptive filtering. IFMBE Proceedings. Vol. 39 IFMBE 2013. pp. 371-374
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