Abstract:
In order to explore the effect of low frequency stimulation on pupil size and electroencephalogram (EEG), we presented subjects with 1-6Hz black-and-white-alternating fli...Show MoreMetadata
Abstract:
In order to explore the effect of low frequency stimulation on pupil size and electroencephalogram (EEG), we presented subjects with 1-6Hz black-and-white-alternating flickering stimulus, and compared the differences of signal-to-noise ratio (SNR) and classification performance between pupil size and visual evoked potentials (VEPs). The results showed that the SNR of the pupillary response reached the highest at 1Hz (17.19±0.10dB) and 100% accuracy was obtained at 1s data length, while the performance was poor at the stimulation frequency above 3Hz. In contrast, the SNR of VEPs reached the highest at 6Hz (18.57±0.37dB), and the accuracy of all stimulus frequencies could reach 100%, with the minimum data length of 1.5s. This study lays a theoretical foundation for further implementation of a hybrid brain-computer interface (BCI) that integrates pupillometry and EEG.
Published in: 2020 42nd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC)
Date of Conference: 20-24 July 2020
Date Added to IEEE Xplore: 27 August 2020
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PubMed ID: 33018649