A Comprehensive Review on Brain-Computer Interface Controlled Movements
DOI:
https://doi.org/10.24113/ijoscience.v5i6.243Keywords:
electroencephalogram (EEG), Brain-Computer Interface (BCI), Arm Movements, Machine LearningAbstract
A brain-computer interface (BCI), also referred to as a mind-machine interface (MMI) or a brain-machine interface (BMI), provides a non-muscular channel of communication between the human brain and a computer system. With the advancements in low-cost electronics and computer interface equipment, as well as the need to serve people suffering from disabilities of neuromuscular disorders, a new field of research has emerged by understanding different functions of the brain. The electroencephalogram (EEG) is an electrical activity generated by brain structures and recorded from the scalp surface through electrodes. Researchers primarily rely on EEG to characterize the brain activity, because it can be recorded noninvasively by using portable equipment. The EEG or the brain activity can be used in real time to control external devices via a complete BCI system. For these applications there is need of such machine learning application which can be efficiently applied on these EEG signals. The aim of this research is review different research work in the field of brain computer interface related to body parts movements.
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Copyright (c) 2019 Kulsheet Kaur Virdi, Satish Pawar
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