2017
DOI: 10.1117/1.jbo.22.6.066011
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Dynamic time warping-based averaging framework for functional near-infrared spectroscopy brain imaging studies

Abstract: We investigate the problem related to the averaging procedure in functional near-infrared spectroscopy (fNIRS) brain imaging studies. Typically, to reduce noise and to empower the signal strength associated with task-induced activities, recorded signals (e.g., in response to repeated stimuli or from a group of individuals) are averaged through a point-by-point conventional averaging technique. However, due to the existence of variable latencies in recorded activities, the use of the conventional averaging tech… Show more

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Cited by 8 publications
(1 citation statement)
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“…The similarity score computed using DTW might thus more accurately describe how well two time series match each other when compared to a more conventional Euclidean distance measurement, as similar features will still be detected even if they do not line up exactly. Zhu et al [37] successfully employed DTW to average fNIRS signals and localize cortical brain activity. Fig.…”
Section: Cnn Input Datamentioning
confidence: 99%
“…The similarity score computed using DTW might thus more accurately describe how well two time series match each other when compared to a more conventional Euclidean distance measurement, as similar features will still be detected even if they do not line up exactly. Zhu et al [37] successfully employed DTW to average fNIRS signals and localize cortical brain activity. Fig.…”
Section: Cnn Input Datamentioning
confidence: 99%