Abstract

For hearing-impaired individuals with neurological motor deficits or finger/arm amputation due to accident or disease, hearing aid adjustment using a conventional finger manipulation-based remote controller is unavailable, and a more dedicated, hands-free alternative is required. In this study, we propose an eye-blinking-based beamforming control scheme for hearing aid users. Three electroencephalogram signals measured around the ears were utilized to detect eye-blinking patterns based on a three-layer artificial neural network. The performance of the proposed control scheme was evaluated by both subjective experiments and objective index comparison tests in simulated situations. Experimental results from the subjective test demonstrated that without the pretraining phase, the accuracy and latency time were 68.57 ± 18.50% and 10.06 ± 0.94 s, respectively; in contrast, after the pretraining phase, both the accuracy and latency time were improved to 91.00 ± 4.69% and 8.60 ± 1.05 s, respectively. In index comparison tests, the proposed control scheme exhibited improvements in the signal-to-noise ratio (SNR) as well as the segmental SNR in all tested situations, as compared to a conventional forward-focusing beamforming algorithm. We believe that the proposed control scheme provides a novel, hands-free way in which to control the operation of hearing aids for hearing-impaired patients with additional motor deficits or amputation.

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