Literature DB >> 23231985

Accessing the neural drive to muscle and translation to neurorehabilitation technologies.

Dario Farina1, Francesco Negro.   

Abstract

This review describes methods for interfacing motor neurons from muscle recordings and their applications in studies on the neural control of movement and in the design of technologies for neurorehabilitation. After describing methods for accessing the neural drive to muscles in vivo in humans, we discuss the mechanisms of transmission of synaptic input into motor neuron output and of force generation. The synaptic input received by a motor neuron population is largely common among motor neurons. This allows linear transmission of the input and a reduced dimensionality of control by the central nervous system. Force is generated by low-pass filtering the neural signal sent to the muscle. These concepts on neural control of movement are used for the development of neurorehabilitation technologies, which are discussed with representative examples on movement replacement, restoration, and neuromodulation. It is concluded that the analysis of the output of spinal motor neurons from muscle signals provides a unique means for understanding the neural coding of movement in vivo in humans and thus for reproducing this code artificially with the aim of restoring lost or impaired motor functions.

Entities:  

Mesh:

Year:  2012        PMID: 23231985     DOI: 10.1109/RBME.2012.2183586

Source DB:  PubMed          Journal:  IEEE Rev Biomed Eng        ISSN: 1937-3333


  21 in total

1.  Modeling and simulating the neuromuscular mechanisms regulating ankle and knee joint stiffness during human locomotion.

Authors:  Massimo Sartori; Marco Maculan; Claudio Pizzolato; Monica Reggiani; Dario Farina
Journal:  J Neurophysiol       Date:  2015-08-05       Impact factor: 2.714

2.  Accurate and representative decoding of the neural drive to muscles in humans with multi-channel intramuscular thin-film electrodes.

Authors:  Silvia Muceli; Wigand Poppendieck; Francesco Negro; Ken Yoshida; Klaus P Hoffmann; Jane E Butler; Simon C Gandevia; Dario Farina
Journal:  J Physiol       Date:  2015-09-01       Impact factor: 5.182

3.  Chronic electromyograms in treadmill running SOD1 mice reveal early changes in muscle activation.

Authors:  Katharina A Quinlan; Elma Kajtaz; Jody D Ciolino; Rebecca D Imhoff-Manuel; Matthew C Tresch; Charles J Heckman; Vicki M Tysseling
Journal:  J Physiol       Date:  2017-07-05       Impact factor: 5.182

4.  The effective neural drive to muscles is the common synaptic input to motor neurons.

Authors:  Dario Farina; Francesco Negro; Jakob Lund Dideriksen
Journal:  J Physiol       Date:  2014-05-23       Impact factor: 5.182

5.  A latent low-dimensional common input drives a pool of motor neurons: a probabilistic latent state-space model.

Authors:  Daniel F Feeney; François G Meyer; Nicholas Noone; Roger M Enoka
Journal:  J Neurophysiol       Date:  2017-08-02       Impact factor: 2.714

Review 6.  The future of upper extremity rehabilitation robotics: research and practice.

Authors:  Philip P Vu; Cynthia A Chestek; Samuel R Nason; Theodore A Kung; Stephen W P Kemp; Paul S Cederna
Journal:  Muscle Nerve       Date:  2020-06       Impact factor: 3.217

7.  A musculoskeletal model of human locomotion driven by a low dimensional set of impulsive excitation primitives.

Authors:  Massimo Sartori; Leonardo Gizzi; David G Lloyd; Dario Farina
Journal:  Front Comput Neurosci       Date:  2013-06-26       Impact factor: 2.380

8.  EMG-driven forward-dynamic estimation of muscle force and joint moment about multiple degrees of freedom in the human lower extremity.

Authors:  Massimo Sartori; Monica Reggiani; Dario Farina; David G Lloyd
Journal:  PLoS One       Date:  2012-12-26       Impact factor: 3.240

Review 9.  Surface electromyography signal processing and classification techniques.

Authors:  Rubana H Chowdhury; Mamun B I Reaz; Mohd Alauddin Bin Mohd Ali; Ashrif A A Bakar; K Chellappan; T G Chang
Journal:  Sensors (Basel)       Date:  2013-09-17       Impact factor: 3.576

10.  Design, development and testing of a low-cost sEMG system and its use in recording muscle activity in human gait.

Authors:  Tamara Grujic Supuk; Ana Kuzmanic Skelin; Maja Cic
Journal:  Sensors (Basel)       Date:  2014-05-07       Impact factor: 3.576

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