NDLI: Regenerative peripheral nerve interfaces for real-time, proportional control of a Neuroprosthetic hand

Content Provider	Springer Nature : BioMed Central
Author	Frost, Christopher M. Ursu, Daniel C. Flattery, Shane M. Nedic, Andrej Hassett, Cheryl A. Moon, Jana D. Buchanan, Patrick J. Brent Gillespie, R. Kung, Theodore A. Kemp, Stephen W. P. Cederna, Paul S. Urbanchek, Melanie G.
Abstract	Introduction Regenerative peripheral nerve interfaces (RPNIs) are biological constructs which amplify neural signals and have shown long-term stability in rat models. Real-time control of a neuroprosthesis in rat models has not yet been demonstrated. The purpose of this study was to: a) design and validate a system for translating electromyography (EMG) signals from an RPNI in a rat model into real-time control of a neuroprosthetic hand, and; b) use the system to demonstrate RPNI proportional neuroprosthesis control. Methods Animals were randomly assigned to three experimental groups: (1) Control; (2) Denervated, and; (3) RPNI. In the RPNI group, the extensor digitorum longus (EDL) muscle was dissected free, denervated, transferred to the lateral thigh and neurotized with the residual end of the transected common peroneal nerve. Rats received tactile stimuli to the hind-limb via monofilaments, and electrodes were used to record EMG. Signals were filtered, rectified and integrated using a moving sample window. Processed EMG signals (iEMG) from RPNIs were validated against Control and Denervated group outputs. Results Voluntary reflexive rat movements produced signaling that activated the prosthesis in both the Control and RPNI groups, but produced no activation in the Denervated group. Signal-to-Noise ratio between hind-limb movement and resting iEMG was 3.55 for Controls and 3.81 for RPNIs. Both Control and RPNI groups exhibited a logarithmic iEMG increase with increased monofilament pressure, allowing graded prosthetic hand speed control (R2 = 0.758 and R2 = 0.802, respectively). Conclusion EMG signals were successfully acquired from RPNIs and translated into real-time neuroprosthetic control. Signal contamination from muscles adjacent to the RPNI was minimal. RPNI constructs provided reliable proportional prosthetic hand control.
Related Links	https://jneuroengrehab.biomedcentral.com/counter/pdf/10.1186/s12984-018-0452-1.pdf
Ending Page	9
Page Count	9
Starting Page	1
File Format	HTM / HTML
ISSN	17430003
DOI	10.1186/s12984-018-0452-1
Journal	Journal of NeuroEngineering and Rehabilitation
Issue Number	1
Volume Number	15
Language	English
Publisher	BioMed Central
Publisher Date	2018-11-20
Access Restriction	Open
Subject Keyword	Neurosciences Neurology Rehabilitation Medicine Biomedical Engineering and Bioengineering Peripheral nerve Interface Prosthetics Regenerative medicine Amputees
Content Type	Text
Resource Type	Article
Subject	Health Informatics Rehabilitation
Journal Impact Factor	5.2/2023
5-Year Journal Impact Factor	5.6/2023

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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