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      Unique case study: Impact of single‐session neuromuscular biofeedback on motor unit properties following 12 days of Achilles tendon surgical repair

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          Abstract

          We explored the first evidence of a single‐session neuromuscular biofeedback effect on motor unit properties, neuromuscular activation, and the Achilles tendon (AT) length 12 days after undergoing AT surgical repair. We hypothesized that immediate neuromuscular biofeedback enhances motor unit properties and activation without causing AT lengthening. After 12 days AT surgical repair, Medial Gastrocnemius (MG) motor unit decomposition was performed on a 58‐year‐old male before and after a neuromuscular biofeedback intervention (surface electromyography (sEMG) and ultrasonography), involving unressited plantar flexion. The analysis included motor unit population properties, sEMG amplitude, force paradigm, and AT length. There were increased MG motor unit recruitment, peak and average firing rate, coefficient of variation, and sEMG amplitude, and decreased recruitment and derecruitment threshold in the repaired AT limb. The non‐injured limb increased the motor unit recruitment, and decreased the coefficient of variation, peak and average firing rate, inter‐pulse interval, derecruitment threshold and sEMG amplitude. The AT length experienced −0.4 and 0.3 cm changes in the repaired AT and non‐injured limb, respectively. This single‐session neuromuscular biofeedback 12 days after AT surgery shows evidence of enhanced motor unit properties and activation without signs of AT lengthening when unresisted plantar flexion is performed in the repaired AT limb.

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          Most cited references25

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          Development of recommendations for SEMG sensors and sensor placement procedures

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            The proprioceptive senses: their roles in signaling body shape, body position and movement, and muscle force.

            This is a review of the proprioceptive senses generated as a result of our own actions. They include the senses of position and movement of our limbs and trunk, the sense of effort, the sense of force, and the sense of heaviness. Receptors involved in proprioception are located in skin, muscles, and joints. Information about limb position and movement is not generated by individual receptors, but by populations of afferents. Afferent signals generated during a movement are processed to code for endpoint position of a limb. The afferent input is referred to a central body map to determine the location of the limbs in space. Experimental phantom limbs, produced by blocking peripheral nerves, have shown that motor areas in the brain are able to generate conscious sensations of limb displacement and movement in the absence of any sensory input. In the normal limb tendon organs and possibly also muscle spindles contribute to the senses of force and heaviness. Exercise can disturb proprioception, and this has implications for musculoskeletal injuries. Proprioceptive senses, particularly of limb position and movement, deteriorate with age and are associated with an increased risk of falls in the elderly. The more recent information available on proprioception has given a better understanding of the mechanisms underlying these senses as well as providing new insight into a range of clinical conditions.
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              Decomposition of surface EMG signals.

              This report describes an early version of a technique for decomposing surface electromyographic (sEMG) signals into the constituent motor unit (MU) action potential trains. A surface sensor array is used to collect four channels of differentially amplified EMG signals. The decomposition is achieved by a set of algorithms that uses a specially developed knowledge-based Artificial Intelligence framework. In the automatic mode the accuracy ranges from 75 to 91%. An Interactive Editor is used to increase the accuracy to > 97% in signal epochs of about 30-s duration. The accuracy was verified by comparing the firings of action potentials from the EMG signals detected simultaneously by the surface sensor array and by a needle sensor. We have decomposed up to six MU action potential trains from the sEMG signal detected from the orbicularis oculi, platysma, and tibialis anterior muscles. However, the yield is generally low, with typically < or = 5 MUs per contraction. Both the accuracy and the yield should increase as the algorithms are developed further. With this technique it is possible to investigate the behavior of MUs in muscles that are not easily studied by needle sensors. We found that the inverse relationship between the recruitment threshold and the firing rate previously reported for muscles innervated by spinal nerves is also present in the orbicularis oculi and the platysma, which are innervated by cranial nerves. However, these two muscles were found to have greater and more widespread values of firing rates than those of large limb muscles.
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                Author and article information

                Contributors
                carpes@unipampa.edu.br
                Journal
                Physiol Rep
                Physiol Rep
                10.1002/(ISSN)2051-817X
                PHY2
                physreports
                Physiological Reports
                John Wiley and Sons Inc. (Hoboken )
                2051-817X
                09 January 2024
                January 2024
                : 12
                : 1 ( doiID: 10.1002/phy2.v12.1 )
                : e15868
                Affiliations
                [ 1 ] Exercise and Rehabilitation Sciences Institute, Postgraduate, Faculty of Rehabilitation Sciences, Universidad Andres Bello Universidad Andres Bello Santiago de Chile Chile
                [ 2 ] Unidad de Biomecánica, Centro de Innovación, Clínica MEDS Santiago Chile
                [ 3 ] Foot and Ankle Surgery Department Clinica MEDS Santiago Chile
                [ 4 ] Carrera de Kinesiología, Departamento de Ciencias de la Salud, Facultad de Medicina Pontificia Universidad Catolica de Chile Santiago Chile
                [ 5 ] Escuela de Kinesiología, Facultad de Medicina y Ciencias de la Salud Universidad Mayor Santiago Chile
                [ 6 ] Escuela de Kinesiologia Universidad de los Andes Santiago Chile
                [ 7 ] Laboratory of Neuromechanics Federal University of Pampa Uruguaiana RS Brazil
                Author notes
                [*] [* ] Correspondence

                Felipe P. Carpes, Applied Neuromechanics Research Group, Universidade Federal do Pampa, Uruguaiana, RS, Brazil.

                Email: carpes@ 123456unipampa.edu.br

                Author information
                https://orcid.org/0000-0002-2429-837X
                https://orcid.org/0000-0001-8923-4855
                Article
                PHY215868 PHYSREP-2023-08-316
                10.14814/phy2.15868
                10776338
                38195250
                3b009a5f-c849-4adc-abb8-ba8622c1cd72
                © 2024 The Authors. Physiological Reports published by Wiley Periodicals LLC on behalf of The Physiological Society and the American Physiological Society.

                This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

                History
                : 30 October 2023
                : 04 September 2023
                : 04 November 2023
                Page count
                Figures: 2, Tables: 2, Pages: 7, Words: 3893
                Funding
                Funded by: Universidad Mayor (Santiago, Chile)
                Categories
                Case Report
                Case Report
                Custom metadata
                2.0
                January 2024
                Converter:WILEY_ML3GV2_TO_JATSPMC version:6.3.6 mode:remove_FC converted:09.01.2024

                case‐report,decomposition,neuromechanical adaptation,surface electromyography,rehabilitation

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