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SUMMARY:Wearable non-invasive human neural interface with action potential
  resolution - Dan Wetmore\, PhD\, Director of Clinical and Research partne
 rships\, CTRL-labs
DTSTART:20190910T090000Z
DTEND:20190910T100000Z
UID:TALK128779@talks.cam.ac.uk
CONTACT:Guillaume Hennequin
DESCRIPTION:As the nervous system's evolved output\, spinal motor neuron a
 ctivity is from an evolutionary perspective an appropriate source of signa
 ls for a neural interface\, and humans can learn to independently activate
  multiple individual motor neurons innervating the same muscle. Furthermor
 e\, the reliable amplification of motor neuron action potentials by muscle
  fibers allows them to be measured non-invasively with surface electromyog
 raphy (sEMG). We have developed a novel wearable wireless system for state
 -of-the-art dry electrode sEMG recording from the human wrist and forearm 
 without the need for any skin preparation. Using this system\, we demonstr
 ate real-time detection and identification of individual motor unit action
  potentials\, each of which corresponds to the firing of an individual spi
 nal motor neuron. This ability to monitor spiking activity of individual n
 eurons sets sEMG apart from other non-invasive measurements of neural acti
 vity. From the recorded sEMG signals\, we develop personalized discrete an
 d continuous control schemes\, and we also compute real-time predictions o
 f joint angles\, muscle tensions\, and forces of the wrist and hand. Relat
 ive to traditional human-computer interfaces\, neuromotor interfaces have 
 the potential to increase human-to-computer communication bandwidth\, and 
 substantial reductions in latency are also achievable because sEMG signals
  precede forces and movement by tens of milliseconds. Expanding the applic
 ability of neural interface technology beyond the clinical and research do
 mains\, this non-invasive spike-resolution neural interface provides the p
 otential to augment and ultimately test the limits of human output capacit
 y.
LOCATION:Cambridge University Engineering Department\, CBL\, BE4-38 (http:
 //learning.eng.cam.ac.uk/Public/Directions)
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