Auditory Based Brain-computer Interfaces Research Articles

Event-Related Potential-Based Brain-Computer Interface Using the Thai Vowels' and Numerals' Auditory Stimulus Pattern.

Herein, we developed an auditory stimulus pattern for an event-related potential (ERP)-based brain–computer interface (BCI) system to improve control and communication in quadriplegia with visual impairment. Auditory stimulus paradigms for multicommand electroencephalogram (EEG)-based BCIs and audio stimulus patterns were examined. With the proposed auditory stimulation, using the selected Thai vowel, similar to the English vowel, and Thai numeral sounds, as simple target recognition, we explored the ERPs’ response and classification efficiency from the suggested EEG channels. We also investigated the use of single and multi-loudspeakers for auditory stimuli. Four commands were created using the proposed paradigm. The experimental paradigm was designed to observe ERP responses and verify the proposed auditory stimulus pattern. The conventional classification method produced four commands using the proposed auditory stimulus pattern. The results established that the proposed auditory stimulation with 20 to 30 trials of stream stimuli could produce a prominent ERP response from Pz channels. The vowel stimuli could achieve higher accuracy than the proposed numeral stimuli for two auditory stimuli intervals (100 and 250 ms). Additionally, multi-loudspeaker patterns through vowel and numeral sound stimulation provided an accuracy greater than 85% of the average accuracy. Thus, the proposed auditory stimulation patterns can be implemented as a real-time BCI system to aid in the daily activities of quadratic patients with visual and tactile impairments. In future, practical use of the auditory ERP-based BCI system will be demonstrated and verified in an actual scenario.

Analysis of Prefrontal Single-Channel EEG Data for Portable Auditory ERP-Based Brain-Computer Interfaces.

An electroencephalogram (EEG)-based brain-computer interface (BCI) is a tool to non-invasively control computers by translating the electrical activity of the brain. This technology has the potential to provide patients who have severe generalized myopathy, such as those suffering from amyotrophic lateral sclerosis (ALS), with the ability to communicate. Recently, auditory oddball paradigms have been developed to implement more practical event-related potential (ERP)-based BCIs because they can operate without ocular activities. These paradigms generally make use of clinical (over 16-channel) EEG devices and natural sound stimuli to maintain the user's motivation during the BCI operation; however, most ALS patients who have taken part in auditory ERP-based BCIs tend to complain about the following factors: (i) total device cost and (ii) setup time. The development of a portable auditory ERP-based BCI could overcome considerable obstacles that prevent the use of this technology in communication in everyday life. To address this issue, we analyzed prefrontal single-channel EEG data acquired from a consumer-grade single-channel EEG device using a natural sound-based auditory oddball paradigm. In our experiments, EEG data was gathered from nine healthy subjects and one ALS patient. The performance of auditory ERP-based BCI was quantified under an offline condition and two online conditions. The offline analysis indicated that our paradigm maintained a high level of detection accuracy (%) and ITR (bits/min) across all subjects through a cross-validation procedure (for five commands: 70.0 ± 16.1 and 1.29 ± 0.93, for four commands: 73.8 ± 14.2 and 1.16 ± 0.78, for three commands: 78.7 ± 11.8 and 0.95 ± 0.61, and for two commands: 85.7 ± 8.6 and 0.63 ± 0.38). Furthermore, the first online analysis demonstrated that our paradigm also achieved high performance for new data in an online data acquisition stream (for three commands: 80.0 ± 19.4 and 1.16 ± 0.83). The second online analysis measured online performances on the different day of offline and first online analyses on a different day (for three commands: 62.5 ± 14.3 and 0.43 ± 0.36). These results indicate that prefrontal single-channel EEGs have the potential to contribute to the development of a user-friendly portable auditory ERP-based BCI.

Influence of attention on speech-rhythm evoked potentials: first steps towards an auditory brain-computer interface driven by speech

A brain-computer interface (BCI) uses neuronal responses to control external systems. The majority of BCI systems are based on visual stimuli, only few apply auditory input. Because auditory-based BCI do not rely on visual skills or mobility of the body, they could be an alternative for visually or physically disabled people. This study investigates the performance of an auditory paradigm using two competing streams of repeatedly presented speech syllables. The streams had different repetition rates of 2.3 and 3.1 Hz. Our auditory BCI approach uses the auditory steady-state response (ASSR) to automatically detect which stream a listener selectively attends to. In a single trial classification ten healthy volunteers achieved an accuracy significantly above chance of 61% and an information transfer-rate (ITR) of 0.2 bit min−1. The use of the average over six random trials improved the average classification accuracy to 79% while keeping the ITR comparable. In conclusion it is possible to classify ASSR evoked from streams of spoken syllables. For a real life application it is necessary to improve the performance of this auditory BCI, but it is a step towards the long term goal of using BCI on natural speech features and eventually controlling the processing of hearing devices.

Visual and auditory brain-computer interfaces.

Over the past several decades, electroencephalogram (EEG)-based brain-computer interfaces (BCIs) have attracted attention from researchers in the field of neuroscience, neural engineering, and clinical rehabilitation. While the performance of BCI systems has improved, they do not yet support widespread usage. Recently, visual and auditory BCI systems have become popular because of their high communication speeds, little user training, and low user variation. However, building robust and practical BCI systems from physiological and technical knowledge of neural modulation of visual and auditory brain responses remains a challenging problem. In this paper, we review the current state and future challenges of visual and auditory BCI systems. First, we describe a new taxonomy based on the multiple access methods used in telecommunication systems. Then, we discuss the challenges of translating current technology into real-life practices and outline potential avenues to address them. Specifically, this review aims to provide useful guidelines for exploring new paradigms and methodologies to improve the current visual and auditory BCI technology.

A portable auditory P300 brain–computer interface with directional cues

ObjectivesThe main objective of the current study was to implement and evaluate a P300 based brain–computer interface (BCI) speller that uses directional cues of auditory stimuli, which are presented over headphones. The interstimulus interval (ISI) was successively reduced to determine the optimal combination of speed and accuracy. The study further aimed at quantifying the differences in subjective workload between the auditory and the visual P300 spelling application. The influence of workload, mood and motivation on BCI performance and P300 amplitude was investigated. MethodsTwenty healthy participants performed auditory and visual spelling tasks in an EEG experiment with online feedback. ResultsSixteen of twenty participants performed at or above a level necessary for satisfactory communication (⩾70% spelling accuracy) with the auditory BCI. Average bit rates of up to 2.76bits/min (best subject 7.43bits/min) were achieved. A significantly higher workload was reported for the auditory speller compared to the visual paradigm. Motivation significantly influenced P300 amplitude at Pz in the auditory condition. ConclusionsThe results of the online study suggest that the proposed paradigm offers a means of communication for most healthy users. SignificanceThe described auditory BCI can serve as a communication channel for completely paralyzed patients.

Auditory brain-computer interfaces (BCIs) and their practical applications

Brain-computer interfaces (BCIs) can provide a communication pathway for patients with severe neuromuscular diseases such as amyotrophic lateral sclerosis. Most current BCI systems rely upon the remaining visual function of individuals; however, patients with severe neuromuscular diseases may lose the ability to gaze at visual targets or to maintain gaze. Therefore, auditory-based BCI paradigms have been recently investigated as one of the alternative BCI modalities. This paper briefly reviews several studies focused on auditory BCI paradigms and discusses their prospects in terms of practical applications.