Synchronizing Motor Imagery Cue in fNIRS Brain-Computer Interface to reduce confounding effects of respiration.

Abstract

Functional near-infrared spectroscopy (fNIRS) is a neuroimaging method that measures oxygenated hemoglobin (HbO) levels in the brain to infer neural activity using near-infrared light. Measured HbO levels are directly affected by a person's respiration. Hence, respiration cycles tend to confound fNIRS readings in motor imagery-based fNIRS Brain-Computer Interfaces (BCI). To reduce this confounding effect, we propose a method of synchronizing the motor imagery cue timing with the subject's respiration cycle using a breathing sensor. We conducted an experiment to collect 160 single trials from 10 subjects performing motor imagery using an fNIRS-based BCI and the breathing sensor. We then compared the HbO levels in trials with and without respiration synchronization. The results showed that respiration synchronization yielded HbO levels that were less dispersed across trials, and a negative correlation between the dispersion index of HbO levels with MI decoding accuracies was found across the 10 subjects. This showed that synchronizing motor imagery cues to respiration can yield increased HbO level consistency leading to better MI performance. Hence, the proposed method holds promise to improve the decoding performance of fNIRS-BCI by reducing the confounding effects of respiration.