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Cabral HV, Inglis JG, Cudicio A, Cogliati M, Orizio C, Yavuz US, Negro F. Muscle contractile properties directly influence shared synaptic inputs to spinal motor neurons. J Physiol 2024. [PMID: 38709959 DOI: 10.1113/jp286078] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/01/2023] [Accepted: 04/18/2024] [Indexed: 05/08/2024] Open
Abstract
Alpha band oscillations in shared synaptic inputs to the alpha motor neuron pool can be considered an involuntary source of noise that hinders precise voluntary force production. This study investigated the impact of changing muscle length on the shared synaptic oscillations to spinal motor neurons, particularly in the physiological tremor band. Fourteen healthy individuals performed low-level dorsiflexion contractions at ankle joint angles of 90° and 130°, while high-density surface electromyography (HDsEMG) was recorded from the tibialis anterior (TA). We decomposed the HDsEMG into motor units spike trains and calculated the motor units' coherence within the delta (1-5 Hz), alpha (5-15 Hz), and beta (15-35 Hz) bands. Additionally, force steadiness and force spectral power within the tremor band were quantified. Results showed no significant differences in force steadiness between 90° and 130°. In contrast, alpha band oscillations in both synaptic inputs and force output decreased as the length of the TA was moved from shorter (90°) to longer (130°), with no changes in delta and beta bands. In a second set of experiments (10 participants), evoked twitches were recorded with the ankle joint at 90° and 130°, revealing longer twitch durations in the longer TA muscle length condition compared to the shorter. These experimental results, supported by a simple computational simulation, suggest that increasing muscle length enhances the muscle's low-pass filtering properties, influencing the oscillations generated by the Ia afferent feedback loop. Therefore, this study provides valuable insights into the interplay between muscle biomechanics and neural oscillations. KEY POINTS: We investigated whether changes in muscle length, achieved by changing joint position, could influence common synaptic oscillations to spinal motor neurons, particularly in the tremor band (5-15 Hz). Our results demonstrate that changing muscle length from shorter to longer induces reductions in the magnitude of alpha band oscillations in common synaptic inputs. Importantly, these reductions were reflected in the oscillations of muscle force output within the alpha band. Longer twitch durations were observed in the longer muscle length condition compared to the shorter, suggesting that increasing muscle length enhances the muscle's low-pass filtering properties. Changes in the peripheral contractile properties of motor units due to changes in muscle length significantly influence the transmission of shared synaptic inputs into muscle force output. These findings prove the interplay between muscle mechanics and neural adaptations.
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Affiliation(s)
- Hélio V Cabral
- Department of Clinical and Experimental Sciences, Università degli Studi di Brescia, Brescia, Italy
| | - J Greig Inglis
- Department of Clinical and Experimental Sciences, Università degli Studi di Brescia, Brescia, Italy
| | - Alessandro Cudicio
- Department of Clinical and Experimental Sciences, Università degli Studi di Brescia, Brescia, Italy
| | - Marta Cogliati
- Department of Clinical and Experimental Sciences, Università degli Studi di Brescia, Brescia, Italy
| | - Claudio Orizio
- Department of Clinical and Experimental Sciences, Università degli Studi di Brescia, Brescia, Italy
| | - Utku S Yavuz
- Biomedical Signals and Systems, University of Twente, Enschede, Netherlands
| | - Francesco Negro
- Department of Clinical and Experimental Sciences, Università degli Studi di Brescia, Brescia, Italy
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Braem CIR, Yavuz US, Hermens HJ, Veltink PH. Missing Data Statistics Provide Causal Insights into Data Loss in Diabetes Health Monitoring by Wearable Sensors. Sensors (Basel) 2024; 24:1526. [PMID: 38475061 DOI: 10.3390/s24051526] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/22/2023] [Revised: 02/14/2024] [Accepted: 02/25/2024] [Indexed: 03/14/2024]
Abstract
BACKGROUND Data loss in wearable sensors is an inevitable problem that leads to misrepresentation during diabetes health monitoring. We systematically investigated missing wearable sensors data to get causal insight into the mechanisms leading to missing data. METHODS Two-week-long data from a continuous glucose monitor and a Fitbit activity tracker recording heart rate (HR) and step count in free-living patients with type 2 diabetes mellitus were used. The gap size distribution was fitted with a Planck distribution to test for missing not at random (MNAR) and a difference between distributions was tested with a Chi-squared test. Significant missing data dispersion over time was tested with the Kruskal-Wallis test and Dunn post hoc analysis. RESULTS Data from 77 subjects resulted in 73 cleaned glucose, 70 HR and 68 step count recordings. The glucose gap sizes followed a Planck distribution. HR and step count gap frequency differed significantly (p < 0.001), and the missing data were therefore MNAR. In glucose, more missing data were found in the night (23:00-01:00), and in step count, more at measurement days 6 and 7 (p < 0.001). In both cases, missing data were caused by insufficient frequency of data synchronization. CONCLUSIONS Our novel approach of investigating missing data statistics revealed the mechanisms for missing data in Fitbit and CGM data.
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Affiliation(s)
- Carlijn I R Braem
- Department of Biomedical Signals and Systems, University of Twente, 7522 NB Enschede, The Netherlands
| | - Utku S Yavuz
- Department of Biomedical Signals and Systems, University of Twente, 7522 NB Enschede, The Netherlands
| | - Hermie J Hermens
- Department of Biomedical Signals and Systems, University of Twente, 7522 NB Enschede, The Netherlands
| | - Peter H Veltink
- Department of Biomedical Signals and Systems, University of Twente, 7522 NB Enschede, The Netherlands
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Gogeascoechea A, Ornelas-Kobayashi R, Yavuz US, Sartori M. Characterization of Motor Unit Firing and Twitch Properties for Decoding Musculoskeletal Force in the Human Ankle Joint In Vivo. IEEE Trans Neural Syst Rehabil Eng 2023; 31:4040-4050. [PMID: 37756177 DOI: 10.1109/tnsre.2023.3319959] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 09/29/2023]
Abstract
Understanding how motor units (MUs) contribute to skeletal mechanical force is crucial for unraveling the underlying mechanism of human movement. Alterations in MU firing, contractile and force-generating properties emerge in response to physical training, aging or injury. However, how changes in MU firing and twitch properties dictate skeletal muscle force generation in healthy and impaired individuals remains an open question. In this work, we present a MU-specific approach to identify firing and twitch properties of MU samples and employ them to decode musculoskeletal function in vivo. First, MU firing events were decomposed offline from high-density electromyography (HD-EMG) of six lower leg muscles involved in ankle plantar-dorsi flexion. We characterized their twitch responses based on the statistical distributions of their firing properties and employed them to compute MU-specific activation dynamics. Subsequently, we decoded ankle joint moments by linking our framework to a subject-specific musculoskeletal model. We validated our approach at different ankle positions and levels of activation and compared it with traditional EMG-driven models. Our proposed MU-specific formulation achieves higher generalization across conditions than the EMG-driven models, with significantly lower coefficients of variation in torque predictions. Furthermore, our approach shows distinct neural strategies across a large repertoire of contractile conditions in different muscles. Our proposed approach may open new avenues for characterizing the relationship between MU firing and twitch properties and their influence on force capacity. This can facilitate the development of targeted rehabilitation strategies tailored to individuals with specific neuromuscular conditions.
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Koelewijn AD, Audu M, del-Ama AJ, Colucci A, Font-Llagunes JM, Gogeascoechea A, Hnat SK, Makowski N, Moreno JC, Nandor M, Quinn R, Reichenbach M, Reyes RD, Sartori M, Soekadar S, Triolo RJ, Vermehren M, Wenger C, Yavuz US, Fey D, Beckerle P. Adaptation Strategies for Personalized Gait Neuroprosthetics. Front Neurorobot 2021; 15:750519. [PMID: 34975445 PMCID: PMC8716811 DOI: 10.3389/fnbot.2021.750519] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/30/2021] [Accepted: 11/18/2021] [Indexed: 11/13/2022] Open
Abstract
Personalization of gait neuroprosthetics is paramount to ensure their efficacy for users, who experience severe limitations in mobility without an assistive device. Our goal is to develop assistive devices that collaborate with and are tailored to their users, while allowing them to use as much of their existing capabilities as possible. Currently, personalization of devices is challenging, and technological advances are required to achieve this goal. Therefore, this paper presents an overview of challenges and research directions regarding an interface with the peripheral nervous system, an interface with the central nervous system, and the requirements of interface computing architectures. The interface should be modular and adaptable, such that it can provide assistance where it is needed. Novel data processing technology should be developed to allow for real-time processing while accounting for signal variations in the human. Personalized biomechanical models and simulation techniques should be developed to predict assisted walking motions and interactions between the user and the device. Furthermore, the advantages of interfacing with both the brain and the spinal cord or the periphery should be further explored. Technological advances of interface computing architecture should focus on learning on the chip to achieve further personalization. Furthermore, energy consumption should be low to allow for longer use of the neuroprosthesis. In-memory processing combined with resistive random access memory is a promising technology for both. This paper discusses the aforementioned aspects to highlight new directions for future research in gait neuroprosthetics.
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Affiliation(s)
- Anne D. Koelewijn
- Biomechanical Data Analysis and Creation (BIOMAC) Group, Machine Learning and Data Analytics Lab, Faculty of Engineering, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany
| | - Musa Audu
- Department of Veterans Affairs, Louis Stokes Clevel and Veterans Affairs Medical Center, Advanced Platform Technology Center, Cleveland, OH, United States
- Department of Biomedical Engineering, Case Western Reserve University, Cleveland, OH, United States
| | - Antonio J. del-Ama
- Applied Mathematics, Materials Science and Technology and Electronic Technology Department, Rey Juan Carlos University, Mostoles, Spain
| | - Annalisa Colucci
- Clinical Neurotechnology Lab, Neuroscience Research Center (NWFZ), Department of Psychiatry and Neurosciences, Charité - Universita¨tsmedizin Berlin, Berlin, Germany
| | - Josep M. Font-Llagunes
- Biomechanical Engineering Lab, Department of Mechanical Engineering and Research Centre for Biomedical Engineering, Universitat Politècnica de Catalunya, Barcelona, Spain
- Institut de Recerca Sant Joan de Déu, Esplugues de Llobregat, Spain
| | - Antonio Gogeascoechea
- Department of Biomechanical Engineering, Faculty of Engineering Technology, University of Twente, Enschede, Netherlands
| | - Sandra K. Hnat
- Department of Veterans Affairs, Louis Stokes Clevel and Veterans Affairs Medical Center, Advanced Platform Technology Center, Cleveland, OH, United States
- Department of Biomedical Engineering, Case Western Reserve University, Cleveland, OH, United States
| | - Nathan Makowski
- Department of Veterans Affairs, Louis Stokes Clevel and Veterans Affairs Medical Center, Advanced Platform Technology Center, Cleveland, OH, United States
- Department of Physical Medicine and Rehabilitation, MetroHealth Medical Center, Cleveland, OH, United States
| | - Juan C. Moreno
- Neural Rehabilitation Group, Department of Translational Neuroscience, Cajal Institute, CSIC, Madrid, Spain
| | - Mark Nandor
- Department of Veterans Affairs, Louis Stokes Clevel and Veterans Affairs Medical Center, Advanced Platform Technology Center, Cleveland, OH, United States
- Department of Mechanical Engineering, Case Western Reserve University, Cleveland, OH, United States
| | - Roger Quinn
- Department of Veterans Affairs, Louis Stokes Clevel and Veterans Affairs Medical Center, Advanced Platform Technology Center, Cleveland, OH, United States
- Department of Mechanical Engineering, Case Western Reserve University, Cleveland, OH, United States
| | - Marc Reichenbach
- Chair of Computer Engineering, Brandenburg University of Technology Cottbus-Senftenberg, Cottbus, Germany
- Chair for Computer Architecture, Department of Computer Science, Faculty of Engineering, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany
| | - Ryan-David Reyes
- Department of Veterans Affairs, Louis Stokes Clevel and Veterans Affairs Medical Center, Advanced Platform Technology Center, Cleveland, OH, United States
- Department of Biomedical Engineering, Case Western Reserve University, Cleveland, OH, United States
| | - Massimo Sartori
- Department of Biomechanical Engineering, Faculty of Engineering Technology, University of Twente, Enschede, Netherlands
| | - Surjo Soekadar
- Clinical Neurotechnology Lab, Neuroscience Research Center (NWFZ), Department of Psychiatry and Neurosciences, Charité - Universita¨tsmedizin Berlin, Berlin, Germany
| | - Ronald J. Triolo
- Department of Veterans Affairs, Louis Stokes Clevel and Veterans Affairs Medical Center, Advanced Platform Technology Center, Cleveland, OH, United States
- Department of Biomedical Engineering, Case Western Reserve University, Cleveland, OH, United States
| | - Mareike Vermehren
- Clinical Neurotechnology Lab, Neuroscience Research Center (NWFZ), Department of Psychiatry and Neurosciences, Charité - Universita¨tsmedizin Berlin, Berlin, Germany
| | - Christian Wenger
- IHP-Leibniz Institut Fuer Innovative Mikroelektronik, Frankfurt (Oder), Germany
| | - Utku S. Yavuz
- Biomedical Signals and Systems Group, University of Twente, Enschede, Netherlands
| | - Dietmar Fey
- Chair for Computer Architecture, Department of Computer Science, Faculty of Engineering, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany
| | - Philipp Beckerle
- Chair of Autonomous Systems and Mechatronics, Department of Electrical Engineering, Artificial Intelligence in Biomedical Engineering, Faculty of Engineering, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany
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Hernandez AG, Kobayashi RO, Yavuz US, Sartori M. Identification of Motor Unit Twitch Properties in the Intact Human In Vivo. Annu Int Conf IEEE Eng Med Biol Soc 2021; 2021:6310-6313. [PMID: 34892556 DOI: 10.1109/embc46164.2021.9630328] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/14/2023]
Abstract
Restoring natural motor function in neurologically injured individuals is challenging, largely due to the lack of personalization in current neurorehabilitation technologies. Signal-driven neuro-musculoskeletal models may offer a novel paradigm for devising novel closed-loop rehabilitation strategies according to an individual's physiology. However, current modelling techniques are constrained to bipolar electromyography (EMG), thereby lacking the resolution necessary to extract the activity of individual motor units (MUs) in vivo. In this work, we decoded MU spike trains from high-density (HD)-EMG to obtain relevant neural properties across multiple isometric plantar-dorsiflexion tasks. Then, we sampled MU statistical distributions and used them to reproduce MU specific activation profiles. Results showed bimodal distributions which may correspond to slow and fast MU populations. The estimated activation profiles showed a high degree of similarity to the reference torque (R2>0.8) across the recorded muscles. This suggests that the estimation of MU twitch properties is a crucial step for the translation of neural information into muscle force.Clinical Relevance- This work has multiple implications for understanding the underlying mechanism of motor impairment and for developing closed-loop strategies for modulating alpha motor circuitries in neurologically injured individuals.
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Gogeascoechea A, Kuck A, van Asseldonk E, Negro F, Buitenweg JR, Yavuz US, Sartori M. Interfacing With Alpha Motor Neurons in Spinal Cord Injury Patients Receiving Trans-spinal Electrical Stimulation. Front Neurol 2020; 11:493. [PMID: 32582012 PMCID: PMC7296155 DOI: 10.3389/fneur.2020.00493] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/20/2020] [Accepted: 05/05/2020] [Indexed: 12/22/2022] Open
Abstract
Trans-spinal direct current stimulation (tsDCS) provides a non-invasive, clinically viable approach to potentially restore physiological neuromuscular function after neurological impairment, e.g., spinal cord injury (SCI). Use of tsDCS has been hampered by the inability of delivering stimulation patterns based on the activity of neural targets responsible to motor function, i.e., α-motor neurons (α-MNs). State of the art modeling and experimental techniques do not provide information about how individual α-MNs respond to electrical fields. This is a major element hindering the development of neuro-modulative technologies highly tailored to an individual patient. For the first time, we propose the use of a signal-based approach to infer tsDCS effects on large α-MNs pools in four incomplete SCI individuals. We employ leg muscles spatial sampling and deconvolution of high-density fiber electrical activity to decode accurate α-MNs discharges across multiple lumbosacral segments during isometric plantar flexion sub-maximal contractions. This is done before, immediately after and 30 min after sub-threshold cathodal stimulation. We deliver sham tsDCS as a control measure. First, we propose a new algorithm for removing compromised information from decomposed α-MNs spike trains, thereby enabling robust decomposition and frequency-domain analysis. Second, we propose the analysis of α-MNs spike trains coherence (i.e., frequency-domain) as an indicator of spinal response to tsDCS. Results showed that α-MNs spike trains coherence analysis sensibly varied across stimulation phases. Coherence analyses results suggested that the common synaptic input to α-MNs pools decreased immediately after cathodal tsDCS with a persistent effect after 30 min. Our proposed non-invasive decoding of individual α-MNs behavior may open up new avenues for the design of real-time closed-loop control applications including both transcutaneous and epidural spinal electrical stimulation where stimulation parameters are adjusted on-the-fly.
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Affiliation(s)
- Antonio Gogeascoechea
- Department of Biomechanical Engineering, University of Twente, Enschede, Netherlands
| | - Alexander Kuck
- Department of Biomechanical Engineering, University of Twente, Enschede, Netherlands
| | - Edwin van Asseldonk
- Department of Biomechanical Engineering, University of Twente, Enschede, Netherlands
| | - Francesco Negro
- Department of Clinical and Experimental Sciences, Università degli Studi di Brescia, Brescia, Italy
| | - Jan R Buitenweg
- Biomedical Signals and Systems Group, University of Twente, Enschede, Netherlands
| | - Utku S Yavuz
- Biomedical Signals and Systems Group, University of Twente, Enschede, Netherlands
| | - Massimo Sartori
- Department of Biomechanical Engineering, University of Twente, Enschede, Netherlands
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Prasartwuth O, Suteebut R, Chawawisuttikool J, Yavuz US, Turker KS. Using first bout effect to study the mechanisms underlying eccentric exercise induced force loss. J Bodyw Mov Ther 2019; 23:48-53. [PMID: 30691760 DOI: 10.1016/j.jbmt.2017.11.008] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/16/2017] [Revised: 09/05/2017] [Accepted: 11/21/2017] [Indexed: 10/18/2022]
Abstract
INTRODUCTION The first bout of eccentric exercise is known to have a protective effect on the consequent bouts. This effect is still disputable as it is not known whether it protects muscle damage by reducing force production or by improving force recovery in the healing process. The underlying mechanisms of this protective effect have not been fully understood. OBJECTIVES To determine the mechanisms of this protective effect, three different loads were used for the first eccentric bout. This was done to investigate whether the protective effect is related to the size of the load in the first bout. To determine the neural adaptations, voluntary activation was assessed and to determine the muscular adaptations, the resting twitch was measured. METHOD Thirty healthy participants were selectively allocated into three groups (low-, moderate- and high-load group) to match for maximal voluntary contraction (MVC) (n = 10 per group). Participants in each group performed only one of the three sets of ten eccentric (ECC) exercises of the elbow flexors (10%, 20% and 40% of MVC) as their first eccentric bout. The second bout of eccentric exercise was performed two weeks later and was identical for all the three groups, i.e., 40% ECC. RESULTS The results showed that for the first bout, MVC, voluntary activation and the resting twitch displayed significant (p < 0.0001) interaction (group x time). This was not the case however for the second bout as there was no significant (group x time) interaction in all outcome variables immediately after exercise. When the first and second bouts were compared, it was found that the high-load group had faster recovery in MVC at day 1 and 4 corresponding to voluntary activation and only at day 4 corresponding to the resting twitch. CONCLUSIONS In this study, it was found that high-load exercise aids fast recovery either via neural or muscular adaptations.
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Affiliation(s)
- Orawan Prasartwuth
- Department of Physical Therapy, Faculty of Associated Medical Sciences, Chiang Mai University, Thailand.
| | - Roongtip Suteebut
- Department of Physical Therapy, Faculty of Associated Medical Sciences, Chiang Mai University, Thailand
| | - Jitapa Chawawisuttikool
- Department of Physical Therapy, Faculty of Associated Medical Sciences, Chiang Mai University, Thailand
| | - Utku S Yavuz
- Department of Neurorehabilitation Engineering, Bernstein Focus Neurotechnology Gottingen, Bernstein Centre for Computational Neuroscience, Germany
| | - Kemal S Turker
- Koc University School of Medicine, Sariyer, Istanbul, Turkey
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De Nunzio AM, Yavuz US, Martinez-Valdes E, Farina D, Falla D. Electro-tactile stimulation of the posterior neck induces body anteropulsion during upright stance. Exp Brain Res 2018; 236:1471-1478. [PMID: 29549403 PMCID: PMC5937870 DOI: 10.1007/s00221-018-5229-z] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/19/2017] [Accepted: 03/06/2018] [Indexed: 12/19/2022]
Abstract
Sensory information conveyed along afferent fibers from muscle and joint proprioceptors play an important role in the control of posture and gait in humans. In particular, proprioceptive information from the neck is fundamental in supplying the central nervous system with information about the orientation and movement of the head relative to the rest of the body. The previous studies have confirmed that proprioceptive afferences originating from the neck region, evoked via muscle vibration, lead to strong body-orienting effects during static conditions (e.g., leaning of the body forwards or backwards, depending on location of vibration). However, it is not yet certain in humans, whether the somatosensory receptors located in the deep skin (cutaneous mechanoreceptors) have a substantive contribution to postural control, as vibratory stimulation encompasses the receptive field of all the somatosensory receptors from the skin to the muscles. The aim of this study was to investigate the postural effect of cutaneous mechanoreceptor afferences using electro-tactile stimulation applied to the neck. Ten healthy volunteers (8M, 2F) were evaluated. The average position of their centre of foot pressure (CoP) was acquired before, during, and after a subtle electro-tactile stimulation over their posterior neck (mean ± SD = 5.1 ± 2.3 mA at 100 Hz—140% of the perception threshold) during upright stance with their eyes closed. The electro-tactile stimulation led to a body-orienting effect with the subjects consistently leaning forward. An average shift of the CoP of 12.1 ± 11.9 mm (mean ± SD) was reported, which significantly (p < 0.05) differed from its average position under a control condition (no stimulation). These results indicate that cutaneous mechanoreceptive inflow from the neck is integrated to control stance. The findings are relevant for the exploitation of electro-tactile stimulation for rehabilitation interventions where induced anteropulsion of the body is desired.
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Affiliation(s)
- A M De Nunzio
- Centre of Precision Rehabilitation for Spinal Pain (CPR Spine), School of Sport, Exercise and Rehabilitation Sciences, College of Life and Environmental Sciences, University of Birmingham, Birmingham, UK.
| | - U S Yavuz
- Institute of Applied Mechanics, University of Stuttgart, Stuttgart, Germany
| | - E Martinez-Valdes
- Centre of Precision Rehabilitation for Spinal Pain (CPR Spine), School of Sport, Exercise and Rehabilitation Sciences, College of Life and Environmental Sciences, University of Birmingham, Birmingham, UK
| | - D Farina
- Department of Bioengineering, Imperial College London, Royal School of Mines, London, UK
| | - D Falla
- Centre of Precision Rehabilitation for Spinal Pain (CPR Spine), School of Sport, Exercise and Rehabilitation Sciences, College of Life and Environmental Sciences, University of Birmingham, Birmingham, UK
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