sBCI-Headset—Wearable and Modular Device for Hybrid Brain-Computer Interface

Abstract

Severely disabled people, like completely paralyzed persons either with tetraplegia or similar disabilities who cannot use their arms and hands, are often considered as a user group of Brain Computer Interfaces (BCI). In order to achieve high acceptance of the BCI by this user group and their supporters, the BCI system has to be integrated into their support infrastructure. Critical disadvantages of a BCI are the time consuming preparation of the user for the electroencephalography (EEG) measurements and the low information transfer rate of EEG based BCI. These disadvantages become apparent if a BCI is used to control complex devices. In this paper, a hybrid BCI is described that enables research for a Human Machine Interface (HMI) that is optimally adapted to requirements of the user and the tasks to be carried out. The solution is based on the integration of a Steady-state visual evoked potential (SSVEP)-BCI, an Event-related (de)-synchronization (ERD/ERS)-BCI, an eye tracker, an environmental observation camera, and a new EEG head cap for wearing comfort and easy preparation. The design of the new fast multimodal BCI (called sBCI) system is described and first test results, obtained in experiments with six healthy subjects, are presented. The sBCI concept may also become useful for healthy people in cases where a "hands-free" handling of devices is necessary. OPEN ACCESSMicromachines 2015, 6 292

A systematic review of hybrid brain-computer interfaces: Taxonomy and usability perspectives

“…On the other hand, Park & colleagues [ 92 ] distinguished between navigational intentions (searching images to obtain the information) and informational intentions (finding a predefined target from images) by analyzing eye tracking data and EEG signal, and the authors reported that the classification accuracy of combining eye movement and EEG features showed higher accuracy than that of the eye movement feature and EEG features alone (90.9%, 85.8%, and 83.9%, respectively). From the literature review, we found that the role of each signal varies in experimental conditions, and the physiological signals were usually utilized as a selector or switch to support the neurological signal [ 76 , 93 , 94 ] while external inputs utilized direct control [ 83 , 84 ].…”

“…Simultaneous BCI can be utilized for 2-demensional space control, and Allison et al [ 111 ] showed promising results by apply MI for vertical movement and SSVEP for horizontal movement at the same time. Malechka et al [ 94 ] proposed a BCI system with graphical User Interface (UI) to control activities of daily living applications by analyzing eye-tracker, SSVEP, and MI signals. In this system, participants select a device via eye tracker, select submenus such as volume and channel of radio by either SSVEP or MI.…”

Discussion on the Rehabilitation of Stroke Hemiplegia Based on Interdisciplinary Combination of Medicine and Engineering

“…BCI via wearable and wireless EEG headsets can record EEG signals in different environments, making EEG-BCI more flexible, yet the recording quality of current headset technology usually declines after about an hour [ 50 , 51 ]. Dry EEG sensors have also been developed to replace traditional wet sensors and do not require humidifying electrodes or applying gel on the skin.…”

Soft Material-Enabled, Flexible Hybrid Electronics for Medicine, Healthcare, and Human-Machine Interfaces

“…The electronic skin on the prosthetic hand with the soft sensor package demonstrated capabilities of hand shaking, keyboard typing, ball grasping, and feeling surface temperature in daily lives. Another wearable set of FHE embedded in a headset [ 180 ] with EEG electrodes demonstrated the feasibility of hybrid brain-controlled computer ( Figure 6 d). In this study, the wearable head set recorded steady-state visually evoked potentials to control a computer interface, which can be directly usable for severely disabled people who cannot use their arms and hands.…”

“…Reprinted with permission from Macmillan Publishers Ltd.: Nature Communications [ 179 ]; ( d ) Wearable headset and EEG (electroencephalogram) recording for a brain-interfaced system. Reprinted with permission from Reference [ 180 ]. Copyright 2015, MDPI; ( e ) Recording of EOG via a wearable forehead system for a wheelchair control.…”