Ha, Jihyeon Park, Sangin Han, Yaeeun Kim, Lae hyun 2025-03-21T06:30:09Z 2025-03-21T06:30:09Z 2025-03-19 2025-02 https://pubs.kist.re.kr/handle/201004/151942 Brain-computer interface (BCI)-based assistive technologies enable intuitive and efficient user interaction, significantly enhancing the independence and quality of life of elderly and disabled individuals. Although existing wet EEG-based systems report high accuracy, they suffer from limited practicality. This study presents a hybrid BCI system combining dry-type EEG-based flash visual-evoked potentials (FVEP) and pupillary light reflex (PLR) designed to control an LED-based meal-assist robot. The hybrid system integrates dry-type EEG and eyewear-type infrared cameras, addressing the preparation challenges of wet electrodes, while maintaining practical usability and high classification performance. Offline experiments demonstrated an average accuracy of 88.59% and an information transfer rate (ITR) of 18.23 bit/min across the four target classifications. Real-time implementation uses PLR triggers to initiate the meal cycle and EMG triggers to detect chewing, indicating the completion of the cycle. These features allow intuitive and efficient operation of the meal-assist robot. This study advances the BCI-based assistive technologies by introducing a hybrid system optimized for real-world applications. The successful integration of the FVEP and PLR in a meal-assisted robot demonstrates the potential for robust and user-friendly solutions that empower the users with autonomy and dignity in their daily activities. English MDPI AG Hybrid BCI for Meal-Assist Robot Using Dry-Type EEG and Pupillary Light Reflex Article 10.3390/biomimetics10020118 1 Biomimetics, v.10, no.2 Biomimetics 10 2 Y scie scopus 001431656300001 2-s2.0-85218884413 Engineering, Multidisciplinary Materials Science, Biomaterials Engineering Materials Science Article flash visual evoked potential (FVEP) eyewear-type infrared cameras pupillary light reflex (PLR) electromyogram (EMG) electroencephalography (EEG) brain-computer interface (BCI) meal-assist robot dry-type EEG