Abstract
A real-time algorithm for removing scalp-blood signals from functional near-infrared spectroscopy signals is proposed. Scalp and deep signals have different dependencies on the source-detector distance. These signals were separated using this characteristic. The algorithm was validated through an experiment using a dynamic phantom in which shallow and deep absorptions were independently changed. The algorithm for measurement of oxygenated and deoxygenated hemoglobins using two wavelengths was explicitly obtained. This algorithm is potentially useful for real-time systems, e.g., brain-computer interfaces and neuro-feedback systems.
Highlights
Functional near-infrared spectroscopy[1] has been used for observing brain activity in the fields that require everyday measurements because the equipment is smaller, more inexpensive, and requires less restriction of subjects than other neuro-imaging modalities such as functional MRI and PET
The multidistance independent analysis (MD-ICA) method using multidistance optodes[7] has an advantage in that scalp signals can be quantitatively separated from the obtained signals
The real-time process of MD-ICA has not been achieved due to ICA, which requires time series data, some other techniques are applicable for realtime processing
Summary
Functional near-infrared spectroscopy (fNIRS)[1] has been used for observing brain activity in the fields that require everyday measurements because the equipment is smaller, more inexpensive, and requires less restriction of subjects than other neuro-imaging modalities such as functional MRI and PET. Since the light is irradiated and detected from the brain through the scalp, the effects of hemodynamic changes in the scalp on the fNIRS signals have been reported.[2,3] an experimental design that compensates these effects using adequate control conditions is required. To lift or relax this limitation, several engineering techniques have been developed.[4,5,6] The multidistance independent analysis (MD-ICA) method using multidistance optodes[7] has an advantage in that scalp signals can be quantitatively separated from the obtained signals. The real-time process of MD-ICA has not been achieved due to ICA, which requires time series data, some other techniques are applicable for realtime processing. Because the scalp-signal effect potentially changes during experiments due to changes in emotion, the real-time separation is helpful to determine whether to stop or
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