There are well over 100,000 people living with upper limb loss in the United States today and 1 in 12 new amputations are of the upper limb. The loss of an upper limb is devastating to a person's quality of life, their work productivity and it bring about many psychosocial challenges. While there have been exciting technological advances which promise the availability of dexterous prosthetic hands, there is a wide gulf between what is technically possible and the reality faced by the overwhelming majority of amputees. In short, there is a need for an integrated cost-effective prosthetic system which can reliably control multiple degrees of freedom. In a direct response, and in accordance with the scope of PA-11-135 as related to the development and integration of complex instrumentation, we now propose an SBIR Phase IIB effort to develop such a system, based on the following innovative solutions: 1) the MyoLiner: a textile-electrode based system for comfortable all-day acquisition of multichannel "high- definition" electromyograms (HD-EMG);2) the PRO-Controller: a novel classifier algorithm and associated electronic hardware for decoding intentionality of coordinated hand movements;and 3) FlexCells: flexible high energy-density batteries that are conformal and adaptive to the limb. These technologies will be integrated for the first time with dexterous hand technology from our commercial partner to create an affordable, highly functional prosthesis, the Pattern-Recognition-Operated Arm (PRO- Arm). The system will be tested in a study designed to evaluate performance on an objective basis as well as from the standpoint of the patient. Of note, our goal is to have significant clinical impact, starting far before the end of the project. First, we have already launched FlexCells into the market and they have been well received. Second, we will prepare the MyoLiner system for clinical launch within the first year of the project. Third, we will build the system in a modular fashion, thereby allowing prosthetists to utilize the components with other companies'products. Fourth, the algorithm development and training is focused on real-world performance over the course of the day, not just idealized performance in the lab setting. And finally, fifth, the system will be sold to prosthetists well wihin the existing Medicare reimbursement codes - thus, there should be no financial impediments to clinical adoption of the technology. In short, we believe that this Phase IIB grant will enable us o bring this project, initiated through NIH support, to its logical conclusion. We will bring the PRO Arm into clinical use: an affordable but innovative solution, providing significant benefits to uppr extremity amputees.

National Institute of Health (NIH)
National Institute of Neurological Disorders and Stroke (NINDS)
Small Business Innovation Research Grants (SBIR) - Phase II (R44)
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Special Emphasis Panel (ZRG1-ETTN-K (10))
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Ludwig, Kip A
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Infinite Biomedical Technologies, LLC
United States
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Powell, Michael A; Kaliki, Rahul R; Thakor, Nitish V (2014) User training for pattern recognition-based myoelectric prostheses: improving phantom limb movement consistency and distinguishability. IEEE Trans Neural Syst Rehabil Eng 22:522-32