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Surface Myoelectric Control of Hand Prothetics

Award Information
Agency: Department of Health and Human Services
Branch: National Institutes of Health
Contract: 1R44NS065495-01
Agency Tracking Number: NS065495
Amount: $1,354,170.00
Phase: Phase I
Program: SBIR
Solicitation Topic Code: N/A
Solicitation Number: PHS2007-2
Timeline
Solicitation Year: 2008
Award Year: 2008
Award Start Date (Proposal Award Date): N/A
Award End Date (Contract End Date): N/A
Small Business Information
INFINITE BIOMEDICAL TECHNOLOGIES, LLC 3600 CLIPPER MILL ROAD #410
BALTIMORE, MD 21211
United States
DUNS: 037376022
HUBZone Owned: No
Woman Owned: No
Socially and Economically Disadvantaged: No
Principal Investigator
 () -
Business Contact
Phone: (410) 889-8011
Email: santosh@i-biomed.com
Research Institution
N/A
Abstract

DESCRIPTION (provided by applicant): There are approximately 500,000 upper extremity amputees currently living in the United States; with 18,000 new upper extremity amputees added each year. The loss of an upper limb causes a person's quality of life to pl
ummet and brings about massive physical and psychosocial challenges. The majority of amputees are hampered by restricted functionality and use a mechanical hook or a passive, cosmetic hand. Electric Grabber hands are available, but their use is limited due
to a cumbersome control mechanism. Therefore, we propose to develop a noninvasive Surface EMG Decoder And Controller (SEDAC) for use in currently available Electric Grabber hands. It employs a feature extractor and an artificial neural network classifier
to estimate intended hand movements. This will enable intuitive control of the prosthetic hand. Our Phase I effort is focused on the development and validation of SEDAC for real-time decoding and control of a two-function prosthesis. This offers three key
advantages over current technology: 1) intuitive activation of muscle groups for each kind of movement; 2) smooth transition from one movement to another; and 3) a learning capacity which transfers the burden of training from the patient to the prosthetic.
Our Phase II effort builds upon this to incorporate dimensionality reducing algorithms to improve accuracy, reduce latency, and enable intuitive control of 4 additional hand functions. This will allow for actuation of next- generation dexterous prosthetic
hands which are currently under development. Through these advances, we hope to bring about a much needed improvement in the quality of life for upper extremity amputees. PUBLIC HEALTH RELEVANCE: This project will provide trans-radial amputees with intuit
ive control of current generation prosthetics using surface electromyography (EMG). The technology will also provide a foundation for surface EMG control of fully dexterous prosthetics.

* Information listed above is at the time of submission. *

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