Software Digital Lock-in Amplifier in the Application of fNIRS System

Xu Xian Yin; Bao Lei Xu; Zhi Dong Wang; Hong Yi Li; Shi Gang

doi:10.4028/www.scientific.net/AMM.333-335.535

Paper Titles

Study on Filtering Methods of Airborne Gravity
p.516

A Real-Time Processing Method of Underwater Ambient Noise Spectrum Based on One-Third Octave
p.522

The Method Based on Pattern Filter for Sonnd & Vibration Signal
p.526

The Algorithm of Digital Modulation Recognition Based on Stochastic
p.531

Software Digital Lock-in Amplifier in the Application of fNIRS System
p.535

A New Approach for Optimal Decomposition Level Selection in Wavelet De-Noising
p.540

Coal-Gangue Acoustic Signal Recognition Based on Sparse Representation
p.546

Rolling Bearing Fault Degree Recognition Based on Ensemble Empirical Mode Decomposition and Support Vector Regression
p.550

Duty Ratio Thresholds for Regular Transmission at Human Tissue of Near-Infrared Square-Wave Pulse
p.555

HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 333-335Software Digital Lock-in Amplifier in the...

Software Digital Lock-in Amplifier in the Application of fNIRS System

Abstract:

Lock-in amplifier is particularly important in the fNIRS-based system, because the lock-in amplifier can recover the low-level signals buried in significant amounts of noise. But the price of lock-in amplifier is very expensive. This paper presented a software method for designing digital lock-in amplifier. Compared with analogue lock-in amplifier, results show that software lock-in amplifier is feasible for experimental research and can replace the expensive analogue lock-in amplifier.

You might also be interested in these eBooks

Measurement Technology and Engineering Researches in Industry

View Preview

Info:

Periodical:

Applied Mechanics and Materials (Volumes 333-335)

Pages:

535-539

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.333-335.535

Citation:

Cite this paper

Online since:

July 2013

Authors:

Xu Xian Yin, Bao Lei Xu, Zhi Dong Wang, Hong Yi Li, Shi Gang

Keywords:

fNIRS, Software Digital Lock-in Amplifier

Export:

RIS, BibTeX

Price:

Permissions:

Request Permissions

References

[1] Boas D A, Gaudette T, Strangman G, et al. The accuracy of near infrared spectroscopy and imaging during focal changes in cerebral hemodynamics[J]. Neuroimage, 2001, 13(1): 76-90.

DOI: 10.1006/nimg.2000.0674

Google Scholar

[2] Jöbsis F F. Noninvasive, infrared monitoring of cerebral and myocardial oxygen sufficiency and circulatory parameters[J]. Science (New York, NY), 1977, 198(4323): 1264.

DOI: 10.1126/science.929199

Google Scholar

[3] Stepnoski R A, LaPorta A, Raccuia-Behling F, et al. Noninvasive detection of changes in membrane potential in cultured neurons by light scattering[J]. Proceedings of the National Academy of Sciences, 1991, 88(21): 9382-9386.

DOI: 10.1073/pnas.88.21.9382

Google Scholar

[4] Okada E, Firbank M, Schweiger M, et al. Theoretical and experimental investigation of near-infrared light propagation in a model of the adult head[J]. Applied optics, 1997, 36(1): 21-31.

DOI: 10.1364/ao.36.000021

Google Scholar

[5] Fuster J, Guiou M, Ardestani A, et al. Near-infrared spectroscopy (NIRS) in cognitive neuroscience of the primate brain[J]. Neuroimage, 2005, 26(1): 215-220.

DOI: 10.1016/j.neuroimage.2005.01.055

Google Scholar

[6] Suto T, Fukuda M, Ito M, et al. Multichannel near-infrared spectroscopy in depression and schizophrenia: cognitive brain activation study[J]. Biological Psychiatry, 2004, 55(5): 501-511.

DOI: 10.1016/j.biopsych.2003.09.008

Google Scholar

[7] Huang Z, McWilliams A, Lui H, et al. Near‐infrared Raman spectroscopy for optical diagnosis of lung cancer[J]. International journal of cancer, 2003, 107(6): 1047-1052.

DOI: 10.1002/ijc.11500

Google Scholar

[8] Boas D A, Gaudette T, Strangman G, et al. The accuracy of near infrared spectroscopy and imaging during focal changes in cerebral hemodynamics[J]. Neuroimage, 2001, 13(1): 76-90.

DOI: 10.1006/nimg.2000.0674

Google Scholar