A 36-Class Bimodal ERP Brain-Computer Interface Using Location-Congruent Auditory-Tactile Stimuli.

Boyang Zhang,Jing Jiang,Zongtan Zhou

doi:10.3390/brainsci10080524

Abstract

To date, traditional visual-based event-related potential brain-computer interface (ERP-BCI) systems continue to dominate the mainstream BCI research. However, these conventional BCIs are unsuitable for the individuals who have partly or completely lost their vision. Considering the poor performance of gaze independent ERP-BCIs, it is necessary to study techniques to improve the performance of these BCI systems. In this paper, we developed a novel 36-class bimodal ERP-BCI system based on tactile and auditory stimuli, in which six-virtual-direction audio files produced via head related transfer functions (HRTF) were delivered through headphones and location-congruent electro-tactile stimuli were simultaneously delivered to the corresponding position using electrodes placed on the abdomen and waist. We selected the eight best channels, trained a Bayesian linear discriminant analysis (BLDA) classifier and acquired the optimal trial number for target selection in online process. The average online information transfer rate (ITR) of the bimodal ERP-BCI reached 11.66 bit/min, improvements of 35.11% and 36.69% compared to the auditory (8.63 bit/min) and tactile approaches (8.53 bit/min), respectively. The results demonstrate the performance of the bimodal system is superior to each unimodal system. These facts indicate that the proposed bimodal system has potential utility as a gaze-independent BCI in future real-world applications.

Highlights

Brain-computer interface (BCI) systems are novel human-computer interaction technology, which bypasses peripheral nerves and muscles and instead uses human brain activity to directly communicate with a computer or external devices [1,2,3]
A novel 36-class auditory-tactile bimodal event-related potential brain-computer interface (ERP-BCI) system was proposed in this paper, in which six-virtual-direction audio files were delivered through the headphones and six-position electro-tactile stimuli were delivered from the corresponding directions simultaneously
The mean online information transfer rate (ITR) of the bimodal stimulus BCI reached 11.66 bit/min, increases of 35.11%

Summary

Introduction

Brain-computer interface (BCI) systems are novel human-computer interaction technology, which bypasses peripheral nerves and muscles and instead uses human brain activity to directly communicate with a computer or external devices [1,2,3]. In terms of signal acquisition methods, BCIs can be divided into two categories: invasive BCIs and non-invasive BCIs [7]. Non-invasive BCIs, most commonly using electroencephalography (EEG), have been widely applied in neural system and rehabilitation engineering [10,11]. In terms of EEG signal patterns, BCIs can be divided into spontaneous and evoked potential-based BCIs [12,13]. Event-related potential (ERP)-based BCIs are an important subset of evoked potential-based BCIs, in which, subjects are required to concentrate on infrequent target stimuli and ignore other non-target stimuli. Once the target event occurs, the EEG signals in the corresponding channels will change from a neutral ground state to an excited state [14].

Methods

Results

Conclusion