• 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