Radio frequency identification - An innovative solution to guide dexterous prosthetic hands

Matthew S. Trachtenberg, Girish Singhal, Rahul Kaliki, Ryan J. Smith, Nitish V. Thakor

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

14 Scopus citations

Abstract

Dexterous manipulation of a multi-fingered prosthetic hand requires far more cognitive effort compared to typical 1 degree of freedom hands, which hinders their acceptance clinically. This paper presents a Myoelectrically- Operated Radio Frequency Identification (RFID) Prosthetic Hand (MORPH); an implementation of RFID with a myoelectric prosthetic hand as a means to amplify the controllable degrees of freedom. Contextual information from an object equipped with an RFID tag allows automatic preshaping along with dexterous control in an attempt to reduce the cognitive effort required to operate the terminal device. The myoelectric-RFID hybrid has been demonstrated in a proof-of-concept case study where an amputee was fitted with the device and subjected to activities adapted from the Jebsen Hand Function Test and the Smith Hand Function Evaluation with RFID-tagged and untagged items. Evaluation tests revealed that the MORPH system performed significantly better in 4 of the 8 tasks, and comparable to the control in the remainder.

Original languageEnglish (US)
Title of host publication33rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS 2011
Pages3511-3514
Number of pages4
DOIs
StatePublished - 2011
Event33rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS 2011 - Boston, MA, United States
Duration: Aug 30 2011Sep 3 2011

Publication series

NameProceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS
ISSN (Print)1557-170X

Other

Other33rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS 2011
Country/TerritoryUnited States
CityBoston, MA
Period8/30/119/3/11

ASJC Scopus subject areas

  • Signal Processing
  • Biomedical Engineering
  • Computer Vision and Pattern Recognition
  • Health Informatics

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