Neural NoiseElectromyography (EMG) is the recording and analysis of electrical signals produced by skeletal muscles during contraction. Surface EMG uses electrodes placed on the skin to detect the aggregate activity of underlying motor units, while intramuscular EMG employs needle or fine-wire electrodes to record from individual motor units. Since its development in the mid-twentieth century, EMG has become a standard tool in clinical neurophysiology, rehabilitation, ergonomics, and human-machine interaction research.
In the context of neural-interfaces and bci-and-neural-decoding, EMG signals are widely used as control inputs for prosthetic limbs, exoskeletons, and assistive devices. Pattern recognition of multi-channel surface EMG allows decoding of hand gestures, grasp types, and limb movements, providing intuitive control of neuroprosthetics-and-rehabilitation systems. EMG-based interfaces bridge the gap between fully invasive neural recordings and non-invasive brain signals, offering a peripheral readout of motor intent with relatively high signal quality and ease of use.
Research frontiers include high-density EMG arrays that resolve individual motor unit activity non-invasively, decomposition algorithms for real-time motor unit tracking, and the integration of EMG with eeg and other modalities in hybrid control schemes. Clinical applications extend beyond prosthetics to neuromuscular disease diagnosis, intraoperative monitoring, and biofeedback-assisted neurorehabilitation of movement disorders and stroke recovery.