Brain-Machine Interface: Human-Computer Interaction

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Author(s): Manoj Kumar Mukul (BIT Mesra, India)and Sumanta Bhattaharyya (BIT Mesra, India)
Copyright: 2017
Pages: 27
Source title: Handbook of Research on Data Science for Effective Healthcare Practice and Administration
Source Author(s)/Editor(s): Elham Akhond Zadeh Noughabi (University of Calgary, Canada), Bijan Raahemi (University of Ottawa, Canada), Amir Albadvi (Tarbiat Modares University, Iran)and Behrouz H. Far (University of Calgary, Canada)
DOI: 10.4018/978-1-5225-2515-8.ch018

Keywords: Business & Management / Business Science Reference / Decision Support Systems / Healthcare Administration

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Abstract

The brain-machine interface (BMI) is a very recent development in the area of the human machine interaction (HCI) and emerged as the sister technology of BCI. A physiological signal related to these electrical potentials in response of the mental thoughts is known as Electroencephalogram (EEG) signals. The BMI is most commonly known as the BCI because there is a direct communication between the brain and the external machine via a computer, which analyses and interprets the incoming physiological signals, which contain the shadow of the mental activity and the different types of artefacts. A multi-channel recording of the electromagnetic waves emerging from the neural currents in the brain generate a large amounts of the EEG data. The neural activity of the human brain recorded non-invasively is sufficient to control the external machine, if advanced methods of signal analysis and feature extraction are used in combination with the machine learning techniques either supervised or unsupervised.

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