Computational Intelligence Based-Brain-Body Machine Interface

Dear Colleagues,

The research focused on brain–body–machine interfaces and their computational intelligence. Brain–body–machine interfacing is a rapidly expanding field of research, and it provides the link between a human and an external machine by using different types of modalities such as electroencephalogram/EEG (brain signal), magnetoencephalogram/MEG (brain data/image), functional magnetic resonance imaging/fMRI (brain image), functional near-infrared spectroscopy/fNIRS (brain image/data), electrocorticogram/ECoG (brain signal), local field potential/LFP (brain signal), electromyogram/EMG (muscle signal), electrocardiogram/ECG, electrooculogram/EOG, inertia measurement unit/IMU (body movement) and camera (body movement).

The components for the computational intelligence of the brain–body–machine interface consist of several elements, including signal acquisition, signal pre-processing, features extraction and classification or translation modules, which will give the output of commands or logical control signals to operate application devices that replace, restore, enhance and supplement the natural way that the central nervous system functions.

This Special Issue will explore original research on recent advances, technologies, solutions, computational intelligence, applications and new challenges in brain–body–machine–computer interfaces.

Possible topics include, but are not limited to:

• Brain–computer interface (BCI)/brain–machine interface (BMI) and applications with different modalities, EEG, MEG, fMRI, fNIRS, ECoG, Spikes, LFP and microelectrodes.
• Body–machine interfaces using EMG, ECG, EOG, IMU and camera.
• Hybrid/multimodal human–machine interface.
• Multimodal feature extraction and classification for brain–body–machine interfaces.
• Computational intelligence for brain–body–machine interface pattern recognition.
• Brain and body signal processing.
• Machine learning and deep learning used in brain–body–machine interfaces.
• Online and offline brain–body–machine interfaces.
• Novel sensor technologies for brain and body machine interfaces.

Dr. Rifai Chai
Guest Editor

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