Research on hybrid brain-computer interface based on imperceptible visual and auditory stimulation responses.
10.7507/1001-5515.202504033
- Author:
Zexin PANG
1
;
Yijun WANG
2
;
Qingpeng DONG
3
;
Zijian CHENG
3
;
Zhaohui LI
1
;
Ruoqing ZHANG
1
;
Hongyan CUI
1
;
Xiaogang CHEN
1
Author Information
1. Institute of Biomedical Engineering, Chinese Academy of Medical Sciences and Peking Union Medical College, Tianjin 300192, P. R. China.
2. Institute of Semiconductors, Chinese Academy of Sciences, Beijing 100083, P. R. China.
3. School of Life Sciences, Tiangong University, Tianjin 300387, P. R. China.
- Publication Type:Journal Article
- Keywords:
Auditory steady-state response;
Electroencephalogram;
Hybrid brain-computer interface;
Imperceptible stimulation;
Steady-state visual evoked potential
- MeSH:
Brain-Computer Interfaces;
Humans;
Evoked Potentials, Visual/physiology*;
Acoustic Stimulation;
Photic Stimulation;
Electroencephalography;
Evoked Potentials, Auditory/physiology*;
Adult
- From:
Journal of Biomedical Engineering
2025;42(4):660-667
- CountryChina
- Language:Chinese
-
Abstract:
In recent years, hybrid brain-computer interfaces (BCIs) have gained significant attention due to their demonstrated advantages in increasing the number of targets and enhancing robustness of the systems. However, Existing studies usually construct BCI systems using intense auditory stimulation and strong central visual stimulation, which lead to poor user experience and indicate a need for improving system comfort. Studies have proved that the use of peripheral visual stimulation and lower intensity of auditory stimulation can effectively boost the user's comfort. Therefore, this study used high-frequency peripheral visual stimulation and 40-dB weak auditory stimulation to elicit steady-state visual evoked potential (SSVEP) and auditory steady-state response (ASSR) signals, building a high-comfort hybrid BCI based on weak audio-visual evoked responses. This system coded 40 targets via 20 high-frequency visual stimulation frequencies and two auditory stimulation frequencies, improving the coding efficiency of BCI systems. Results showed that the hybrid system's averaged classification accuracy was (78.00 ± 12.18) %, and the information transfer rate (ITR) could reached 27.47 bits/min. This study offers new ideas for the design of hybrid BCI paradigm based on imperceptible stimulation.
