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

Nature Biomedical Engineering volume 1, Article number: 0025 (2017) Cite this article

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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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Figure 1: Interfacing spinal motor neurons in humans.
Figure 2: Confusion matrices for the classification of motions of patients T1, T2 and T3 when using features extracted from global EMG analysis (r.m.s. and r.m.s. with time domain) and when using the neural information as motor-neuron discharge timings.
Figure 3: Single-channel electromyographic (EMG) recordings obtained from subject T1 during hand close and wrist supination of the phantom limb.
Figure 4: Motor-neuron behaviour during linearly increasing and decreasing intensity of activation in patient T4.
Figure 5: Estimates of muscle activation from EMG amplitude and motor neuron discharges.
Figure 6: Signal-based estimates of limb kinematics for three concurrently active degrees of freedom.
Figure 7: Subject-specific musculoskeletal geometry model built for patient T6.

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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.

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Author notes

  1. Massimo Sartori and Tamás Kapelner: These authors contributed equally to this work.

Authors and Affiliations

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

    Dario Farina & Ivan Vujaklija

  2. Orthopaedic Surgery and Plastic Surgery — Research Department of Neurorehabilitation Systems, Clinic for Trauma Surgery, 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, Brescia, 25123, Italy

    Francesco Negro

  4. Department of Systems Design Engineering, Faculty of Engineering, University of Waterloo, Ontario N2L 3G1, Waterloo, 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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  1. Dario Farina
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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.

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Correspondence to Dario Farina.

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Farina, D., Vujaklija, I., Sartori, M. et al. Man/machine interface based on the discharge timings of spinal motor neurons after targeted muscle reinnervation. Nat Biomed Eng 1, 0025 (2017). https://doi.org/10.1038/s41551-016-0025

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