{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,7,6]],"date-time":"2025-07-06T00:33:41Z","timestamp":1751762021749,"version":"3.37.3"},"reference-count":42,"publisher":"Wiley","license":[{"start":{"date-parts":[[2014,1,1]],"date-time":"2014-01-01T00:00:00Z","timestamp":1388534400000},"content-version":"unspecified","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/3.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Computational and Mathematical Methods in Medicine"],"published-print":{"date-parts":[[2014]]},"abstract":"<jats:p>In the last two decades, functional near-infrared spectroscopy (fNIRS) is getting more and more popular as a neuroimaging technique. The fNIRS instrument can be used to measure local hemodynamic response, which indirectly reflects the functional neural activities in human brain. In this study, an easily implemented way to establish DAQ-device-based fNIRS system was proposed. Basic instrumentation components (light sources driving, signal conditioning, sensors, and optical fiber) of the fNIRS system were described. The digital in-phase and quadrature demodulation method was applied in LabVIEW software to distinguish light sources from different emitters. The effectiveness of the custom-made system was verified by simultaneous measurement with a commercial instrument ETG-4000 during Valsalva maneuver experiment. The light intensity data acquired from two systems were highly correlated for lower wavelength (Pearson\u2019s correlation coefficient<mml:math xmlns:mml=\"http:\/\/www.w3.org\/1998\/Math\/MathML\" id=\"M1\"><mml:mrow><mml:mi>r<\/mml:mi><\/mml:mrow><\/mml:math>= 0.92,<mml:math xmlns:mml=\"http:\/\/www.w3.org\/1998\/Math\/MathML\" id=\"M2\"><mml:mrow><mml:mi>P<\/mml:mi><\/mml:mrow><\/mml:math>&lt; 0.01) and higher wavelength (<mml:math xmlns:mml=\"http:\/\/www.w3.org\/1998\/Math\/MathML\" id=\"M3\"><mml:mrow><mml:mi>r<\/mml:mi><\/mml:mrow><\/mml:math>= 0.84,<mml:math xmlns:mml=\"http:\/\/www.w3.org\/1998\/Math\/MathML\" id=\"M4\"><mml:mrow><mml:mi>P<\/mml:mi><\/mml:mrow><\/mml:math>&lt; 0.01). Further, another mental arithmetic experiment was implemented to detect neural activation in the prefrontal cortex. For 9 participants, significant cerebral activation was detected in 6 subjects (<mml:math xmlns:mml=\"http:\/\/www.w3.org\/1998\/Math\/MathML\" id=\"M5\"><mml:mrow><mml:mi>P<\/mml:mi><\/mml:mrow><\/mml:math>&lt; 0.05) for oxyhemoglobin and in 8 subjects (<mml:math xmlns:mml=\"http:\/\/www.w3.org\/1998\/Math\/MathML\" id=\"M6\"><mml:mrow><mml:mi>P<\/mml:mi><\/mml:mrow><\/mml:math>&lt; 0.01) for deoxyhemoglobin.<\/jats:p>","DOI":"10.1155\/2014\/107320","type":"journal-article","created":{"date-parts":[[2014,8,10]],"date-time":"2014-08-10T17:01:37Z","timestamp":1407690097000},"page":"1-9","source":"Crossref","is-referenced-by-count":8,"title":["A DAQ-Device-Based Continuous Wave Near-Infrared Spectroscopy System for Measuring Human Functional Brain Activity"],"prefix":"10.1155","volume":"2014","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-3408-0558","authenticated-orcid":true,"given":"Gang","family":"Xu","sequence":"first","affiliation":[{"name":"State Key Laboratory of Cognitive 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