A Single-Channel and Non-Invasive Wearable Brain-Computer Interface for Industry and Healthcare.

Journal of visualized experiments : JoVE(2023)

引用 0|浏览3
暂无评分
摘要
The present work focuses on how to build a wearable brain-computer interface (BCI). BCIs are a novel means of human-computer interaction that relies on direct measurements of brain signals to assist both people with disabilities and those who are able-bodied. Application examples include robotic control, industrial inspection, and neurorehabilitation. Notably, recent studies have shown that steady-state visually evoked potentials (SSVEPs) are particularly suited for communication and control applications, and efforts are currently being made to bring BCI technology into daily life. To achieve this aim, the final system must rely on wearable, portable, and low-cost instrumentation. In exploiting SSVEPs, a flickering visual stimulus with fixed frequencies is required. Thus, in considering daily-life constraints, the possibility to provide visual stimuli by means of smart glasses was explored in this study. Moreover, to detect the elicited potentials, a commercial device for electroencephalography (EEG) was considered. This consists of a single differential channel with dry electrodes (no conductive gel), thus achieving the utmost wearability and portability. In such a BCI, the user can interact with the smart glasses by merely staring at icons appearing on the display. Upon this simple principle, a user-friendly, low-cost BCI was built by integrating extended reality (XR) glasses with a commercially available EEG device. The functionality of this wearable XR-BCI was examined with an experimental campaign involving 20 subjects. The classification accuracy was between 80%-95% on average depending on the stimulation time. Given these results, the system can be used as a human-machine interface for industrial inspection but also for rehabilitation in ADHD and autism.
更多
查看译文
关键词
single-channel,non-invasive,brain-computer
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要