A novel online BCI system using speech imagery and ear-EEG for home appliances control

计算机科学 会话(web分析) 脑-机接口 任务(项目管理) 接口(物质) 脑电图 语音识别 运动表象 人机交互 可穿戴计算机 可用性 嵌入式系统 最大气泡压力法 万维网 气泡 经济 精神科 并行计算 管理 心理学
作者
Netiwit Kaongoen,Jae-Hoon Choi,Sungho Jo
出处
期刊:Computer Methods and Programs in Biomedicine [Elsevier BV]
卷期号:224: 107022-107022 被引量:16
标识
DOI:10.1016/j.cmpb.2022.107022
摘要

This paper investigates a novel way to interact with home appliances via a brain-computer interface (BCI), using electroencephalograph (EEG) signals acquired from around the user's ears with a custom-made wearable BCI headphone.The users engage in speech imagery (SI), a type of mental task where they imagine speaking out a specific word without producing any sound, to control an interactive simulated home appliance. In this work, multiple models are employed to improve the performance of the system. Temporally-stacked multi-band covariance matrix (TSMBC) method is used to represent the neural activities during SI tasks with spatial, temporal, and spectral information included. To further increase the usability of our proposed system in daily life, a calibration session, where the pre-trained models are fine-tuned, is added to maintain performance over time with minimal training. Eleven participants were recruited to evaluate our method over three different sessions: a training session, a calibration session, and an online session where users were given the freedom to achieve a given goal on their own.In the offline experiment, all participants were able to achieve a classification accuracy significantly higher than the chance level. In the online experiments, a few participants were able to use the proposed system to freely control the home appliance with high accuracy and relatively fast command delivery speed. The best participant achieved an average true positive rate and command delivery time of 0.85 and 3.79 s/command, respectively.Based on the positive experimental results and user surveys, the novel ear-EEG-SI-based BCI paradigm is a promising approach for the wearable BCI system for daily life.
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