A Review on Recent Applications of EEG-based BCI in Wheelchairs and other Assistive Devices

Electroencephalography (EEG) is a powerful method in determining brain activity. It is conventionally used in the clinical setting, mainly as a diagnostic tool. Nonetheless, EEG integration into brain computer interfaces (BCIs) has become a prominent field of study ushered by the rapid growth of signal acquisition and artificial intelligence. Such advancement is particularly significant in assistive devices designed for persons with severe motor impairments. These devices include, but are not limited to, wheelchairs, exoskeletons, prosthesis, and smart home technologies. Given the non-clinical nature of these devices, dry electrodes are the preferred and default EEG type. However, signal inputs and BCI paradigms may vary depending on the intended system design. EEG-based BCI wheelchairs mostly make use of commercially available wireless EEG devices coupled with at least one BCI type to process the acquired signal and send instructions to the wheelchair’s motors. Also. signals collected and processed differ according to the input mechanism. Similar processes occur in other assistive devices with the significant difference in target output. While most, if not all, studies reviewed are still in their initial stages of development, all have an optimistic outlook for the future of EEG-based BCI. In addition, studies highly recommend hybrid BCI for a multimodal approach to ensure greater system accuracy and safety.