Bionic Hand 'Learns' from Muscle Movements to Gain Dexterity
From: Medical Design Technology - 05/04/2016

Simon Fraser University (SFU) researchers are working with paralympic skier
Danny Letain to design a new control system for one of the world's most
advanced bionic hands, promising a more intuitive experience for upper limb
amputees.

With the SFU team's new control system, Letain already has a variety of
different grip patterns that he says work "well beyond" what he could achieve
with prosthetic devices.

The new system consists of an armband of pressure sensors embedded in the
prosthetic socket. These track movements in Letain's remaining muscles as he
performs intuitive actions, such as grasping a bottle. Computer algorithms
then map the sensor data to decode his intentions and move the prosthesis.

The SFU team is pioneering the use of a band of pressure sensors that detect
intricate muscle movements across the surface of the remaining limb.

Besides being a more intuitive experience amputees do not require extensive
training to perform simple functions.

Read the entire article and view a video (2:33) at:
http://www.mdtmag.com/news/2016/05/bionic-hand-learns-muscle-movements-gain-dexterity
https://www.sfu.ca/sfunews/stories/2016/sfu-researchers-build-a-better-bionic-hand-danny-letain.html

Links:
Bionic Hand Developed for World's First Cyborg Olympics
http://www.pddnet.com/news/2016/05/photos-day-bionic-hand-developed-worlds-first-cyborg-olympics

Carlo Menon
http://www2.ensc.sfu.ca/~cmenon
http://www.sfu.ca/engineering/faculty-and-staff/faculty/carlo_menon.html

Muscle Activity Sensor Strip
https://sfu.useed.net/projects/500/home

MASS Impact
http://mass-impact.wix.com/home#!home/mainPage

MENRVA Research Group
http://menrva.ensc.sfu.ca