DocumentCode
77826
Title
Human?Machine Interfacing by Decoding the Surface Electromyogram [Life Sciences]
Author
Farina, D. ; Holobar, A.
Volume
32
Issue
1
fYear
2015
fDate
Jan. 2015
Firstpage
115
Lastpage
120
Abstract
Human-machine interfacing (HMI) uses biological signals, such as brain signals,and translates them into control commands for external devices. An exciting application of HMI is the active control of robotic limbs that substitute lost body parts (bionic reconstruction).Despite recent progresses in brain-computer interfacing [1], muscle electrical potentials are still the most important input for clinical HMI. The ensemble electrical activity of a muscle, the electromyogram (EMG), is generated by the neural activation of the motor neurons innervating the muscle and thus contains information on the neural control of movement. Muscle recordings can be performed noninvasively (surface EMG) by electrodes located on the skin to record the electrical activity of the underlying muscle fibers. This recording modality has advantages compared to other HMI modalities, such as those based on implanted electrodes, in terms of long-term stability, biocompatibility, reduced risks of infections, and ethical constraints.
Keywords
biomedical electrodes; brain-computer interfaces; decoding; electromyography; human-robot interaction; medical robotics; medical signal processing; muscle; skin; HMI; biocompatibility; biological signals; bionic reconstruction; brain signals; brain translates; brain-computer interface; clinical HMI; electrical activity; electrodes; ethical constraints; human-machine interface; implanted electrodes; motor neurons; muscle electrical potentials; muscle fibers; muscle recordings; neural activation; neural movement control; robotic limbs; skin; surface EMG; surface electromyogram; Decoding; Discharges (electric); Electric potential; Electromyography; Human computer interaction; Neurons; Surface treatment; Surface waves; User interfaces;
fLanguage
English
Journal_Title
Signal Processing Magazine, IEEE
Publisher
ieee
ISSN
1053-5888
Type
jour
DOI
10.1109/MSP.2014.2359242
Filename
6975278
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