Adapting proportional myoelectric-controlled interfaces for prosthetic hands

Tobias Pistohl, Christian Cipriani, Andrew Jackson, Kianoush Nazarpour

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Powered hand prostheses with many degrees of freedom are moving from research into the market for prosthetics. In order to make use of the prostheses' full functionality, it is essential to find efficient ways to control their multiple actuators. Human subjects can rapidly learn to employ electromyographic (EMG) activity of several hand and arm muscles to control the position of a cursor on a computer screen, even if the muscle-cursor map contradicts directions in which the muscles would act naturally. We investigated whether a similar control scheme, using signals from four hand muscles, could be adopted for real-time operation of a dexterous robotic hand. Despite different mapping strategies, learning to control the robotic hand over time was surprisingly similar to the learning of two-dimensional cursor control.
Original languageEnglish
Title of host publication2013 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)
PublisherInstitute of Electrical and Electronics Engineers
Pages6195-6198
Number of pages4
ISBN (Electronic)978-1-4577-0216-7
DOIs
Publication statusPublished - 26 Sept 2013
Event35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society - Osaka, Japan
Duration: 3 Jul 20137 Jul 2013

Publication series

Name
PublisherIEEE
ISSN (Print)1094-687X
ISSN (Electronic)1558-4615

Conference

Conference35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society
Country/TerritoryJapan
CityOsaka
Period3/07/137/07/13

Fingerprint

Dive into the research topics of 'Adapting proportional myoelectric-controlled interfaces for prosthetic hands'. Together they form a unique fingerprint.

Cite this