Article

Man/machine interface based on the discharge timings of spinal motor neurons after targeted muscle reinnervation

  • Nature Biomedical Engineering 1, Article number: 0025 (2017)
  • doi:10.1038/s41551-016-0025
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Abstract

The intuitive control of upper-limb prostheses requires a man/machine interface that directly exploits biological signals. Here, we define and experimentally test an offline man/machine interface that takes advantage of the discharge timings of spinal motor neurons. The motor-neuron behaviour is identified by deconvolution of the electrical activity of muscles reinnervated by nerves of a missing limb in patients with amputation at the shoulder or humeral level. We mapped the series of motor-neuron discharges into control commands across multiple degrees of freedom via the offline application of direct proportional control, pattern recognition and musculoskeletal modelling. A series of experiments performed on six patients reveal that the man/machine interface has superior offline performance compared with conventional direct electromyographic control applied after targeted muscle innervation. The combination of surgical procedures, decoding and mapping into effective commands constitutes an interface with the output layers of the spinal cord circuitry that allows for the intuitive control of multiple degrees of freedom.

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Acknowledgements

This work was supported by the European Research Council Advanced Grant DEMOVE (contract #267888) (to D.F.), the Christian Doppler Research Foundation of the Austrian Federal Ministry of Science, Research and Economy (to O.C.A.), the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement number 702491 (NeuralCon) (to F.N.) and Defense Advanced Research Projects Agency (DARPA N66001-15-1-4054) (to J.P.). The authors are grateful to M. Schweisfurth and H. Rehbaum for support in the experimental measurements, M. Castronovo for support in the data analysis, and C. Hofer and S. Salminger for clinical support.

Author information

Author notes

    • Massimo Sartori
    •  & Tamás Kapelner

    These authors contributed equally to this work.

Affiliations

  1. Department of Bioengineering, Imperial College London, London SW7 2AZ, UK

    • Dario Farina
    •  & Ivan Vujaklija
  2. Clinic for Trauma Surgery, Orthopaedic Surgery and Plastic Surgery — Research Department of Neurorehabilitation Systems, University Medical Center Göttingen, Göttingen 37075, Germany

    • Dario Farina
    • , Ivan Vujaklija
    • , Massimo Sartori
    • , Tamás Kapelner
    •  & Francesco Negro
  3. Department of Clinical and Experimental Sciences, University of Brescia, 25123 Brescia, Italy

    • Francesco Negro
  4. Department of Systems Design Engineering, Faculty of Engineering, University of Waterloo, Waterloo, Ontario N2L 3G1, Canada

    • Ning Jiang
  5. Christian Doppler Laboratory for Restoration of Extremity Function, Medical University of Vienna, Vienna 1090, Austria

    • Konstantin Bergmeister
    •  & Oskar C. Aszmann
  6. Division of Plastic and Reconstructive Surgery, Department of Surgery, Medical University of Vienna, Vienna 1090, Austria

    • Konstantin Bergmeister
    •  & Oskar C. Aszmann
  7. Department of Electrical and Computer Engineering, University of Florida, Gainesville, Florida 32611, USA

    • Arash Andalib
    •  & Jose Principe

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Contributions

D.F. and O.C.A. conceived the study. I.V., T.K., M.S. and K.B. performed the acquisition. I.V., T.K., M.S., F.N., N.J., A.A. and J.P. conducted the analysis. D.F., I.V., T.K., M.S., F.N., N.J., K.B., J.P. and O.C.A. interpreted the data. D.F., I.V. and O.C.A. wrote and edited the manuscript.

Competing interests

The authors declare no competing financial interests.

Corresponding author

Correspondence to Dario Farina.