Year: 2025
Type: conference-paper
Abstract: For long-term bedridden patients with limb loss or severe motor function issues, they are often susceptible to pressure sores and require external assistance to adjust their body positions. We develop a wearable multimodal brain-computer interface (BCI) system for electric nursing bed control to assist these patients in independently operate an electric nursing bed. The system acquires users’ head posture, electrooculography (EOG), and electroencephalography (EEG) signals using a wireless headband, and transmits these signals to a tablet for multimodal signal decoding. Users perform head rotation to control cursor movement, and intentional blinking to perform click actions. Consequently, users can effortlessly control the electric bed through a specially designed graphical user interface (GUI) by head rotation and blinking, thereby achieving self-care. To assess the system's effectiveness, we recruited six participants to carry out simulating tasks for the control of an electric nursing bed. The results indicated that all participants successfully completed the tasks with an average accuracy rate of 98.2±2.2%. The average response time was 1.49±0.31 seconds, and the information transfer rate (ITR) was 133.5±36.1 bit/min. Furthermore, compared to most existing systems using discrete control, our system offers continuous control. These findings demonstrate the efficacy of our proposed system and its significant potential for practical application.
Authors: Junbiao Zhu, Kendi Li, Sicong Chen, Li Hu, Yuanqing Li
Language: English
Subfield: Cognitive Neuroscience
Field: Neuroscience
Domain: Life Sciences
Open Access status: gold
OpenAlex ID: W4413682802