The use of surface EMG in neurorehabilitation following traumatic spinal cord injury: A scoping review

Balbinot, Gustavo; Wiest, Matheus Joner; Li, Guijin; Pakosh, Maureen; Furlan, Julio C.; Kalsi‐Ryan, Sukhvinder; Zariffa, José

doi:10.1016/j.clinph.2022.02.028

Cited by 9 publications

(6 citation statements)

References 123 publications

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“…Some research laboratories also use EMG to study biomechanics, motion control, gait analysis, neuromuscular physiology, dyskinesia, gesture control, and physical therapy. [31,32] ECG reflects the electrical activities of myocardial cells. The stimulation of myocardial cells induces ions to flow inside and outside the membranes and triggers depolarization and repolarization of myocardial cells.…”

Section: Common Bioelectrical Signals In Humanmentioning

confidence: 99%

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Recent Progress on Poly(3,4‐Ethylenedioxythiophene):Poly(Styrenesulfonate) Bioelectrodes

Yang

Liu

2023

Small Science

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Sensing bioelectrical signals paves a way for knowing the health and mental status, providing important clinical information about subjects' physiological and psychological activities. [1] Common bioelectrical signals include electromyogram (EMG), electrocardiogram (ECG), electrooculogram (EOG), and electroencephalogram (EEG). EMG is conducive to explore the activities of nerves and muscles. ECG signals, originating from heart, show the information related to cardiac function. EOG can help to recognize eye diseases. EEG is capable of showing complex neural activities in the brain. [2][3][4][5] Furthermore, bioelectrical signals could integrate with human-machine interfaces (HMI), such as prosthetic control, emotion recognition, eye movement tracking, virtual reality (VR), and augmented reality (AR). [6][7][8][9] So far, various bioelectrodes have been developed for recording bioelectrical signals, but it is still challenging to acquire high-quality, stable, and long-term signals. [10,11] Human skin/tissue will deform during body motion, which means that human skin/tissue has to withstand strain. Conventional bioelectrodes are mainly gel electrodes (Ag/AgCl electrodes) and dry electrodes made of metals (e.g., Au, Ag, Cu). Due to the mechanical mismatch with human skin/tissue, they are unable to continuously recording signals. In addition to, long-term use of such electrodes would cause skin irritation. Stretchability is a critical property to ensure bioelectrodes to work normally despite the deformation of human skin/tissue. Lots of interest is devoted to the fabrication of stretchable electrodes. [12][13][14][15][16] These electrodes need to possess matched modulus to adapt to the uneven surface of human skin/tissue. In addition to the mechanical properties, excellent conductivity, adhesion to skin, and biocompatibility are necessary. Furthermore, breathability and self-healing are also the properties people pursuing for. [17] Emerging materials used for bioelectrodes include conductive polymers, conductive hydrogels, carbon materials (e.g., graphene, carbon nanotubes), liquid metals, elastomer composites, etc. [18][19][20][21] Conductive polymers are kinds of organic conjugated polymers with heterocycle, whose conductivity stems from conjugated main chains of delocalized electron/hole. By combining the advantages of both metals and polymers, conductive polymers are easy for fabrication and structure modification. Among them, poly(3,4-ethylenedioxythiophene) (PEDOT) has attracted heightened interest due to its excellent conductivity, optical transmittance in the visible region, thermostability, relatively low redox potential, etc. Nevertheless, its insolubility in water hinders further development. It can be overcome by introducing polyelectrolyte like poly(styrenesulfonate) (PSS) into PEDOT matrix. PSS acts as both dopant and stabilizer by a charge balance mechanism. Since the problem of insolubility in water has been solved, PEDOT becomes the most successful commercial polyelectrolyte. [22] Figure 1 shows the s...

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Section: Common Bioelectrical Signals In Humanmentioning

confidence: 99%

“…Some research laboratories also use EMG to study biomechanics, motion control, gait analysis, neuromuscular physiology, dyskinesia, gesture control, and physical therapy. [ 31,32 ]…”

Section: Bioelectrical Signalmentioning

confidence: 99%

Recent Progress on Poly(3,4‐Ethylenedioxythiophene):Poly(Styrenesulfonate) Bioelectrodes

Yang

Liu

2023

Small Science

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“…[6] In recent years, Surface electromyography can detect the average electromyogram (AEMG) signals of the target muscle over a while, that is, the instantaneous EMG amplitude of all muscle fibers involved in the activity. [7] The flexion-relaxation phenomenon (FRP) is a term used to describe the sequence of events that occur during spinal flexion. FRP includes the initial movement towards a maximum flexion angle, followed by a return to a neutral position, during which the muscle contractions exhibit an up-down-up pattern.…”

Section: Introductionmentioning

confidence: 99%

Effects of Baduanjin exercise on patients with chronic nonspecific low back pain and surface electromyography signs of erector spinal muscle: A randomized controlled trial

Yang,

Huang,

et al. 2023

Medicine

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Background: Chronic nonspecific low back pain (CNLBP) is a common disease usually with lower back muscle fatigue and injuries that may contribute to lumbar muscle imbalance and pain recurrence. This study aimed to examine the effectiveness of Baduanjin exercise on patients of CNLBP and to assess its impact on the surface electromyographic signals of the lumbar erector spinae muscle. Methods: A total of 60 patients diagnosed with CNLBP were admitted from the Hubei Provincial Hospital of Traditional Chinese Medicine from March 2022 to December 2022. Those patients were randomly allocated into the Baduanjin group (n = 30) or the walking group (n = 30). Both groups received a 4-week intervention, with 5 training sessions per week. The numeric pain rating scale (the minimal clinically important difference = 2.4) and Oswestry Disability Index (the minimal clinically important difference = 13.4), electromyogram signals during lumbar flexion (FLEXAEMG), lumbar extension (EXTAEMG), and maximum lumbar flexion (MAEMG), the ratios of FLEXAEMG to MAEMG and EXTAEMG to MAEMG were collected at Baseline and posttreatment and compared using the Wilcoxon signed-rank test or Mann–Whitney U test. Results: After treatment, the numeric pain rating scale score in the Baduanjin group exhibited a significant decrease compared to baseline (P < .05) and was found to be lower than that of the Walking group (mean difference 2.36; CI 95% −2.323 to −1.742; P = .001). Similarly, the Oswestry disability index in the Baduanjin group demonstrated a reduction compared to baseline (P < .05) and was lower than that of the Walking group (the mean difference 7.59; CI 95% −8.861 to −6.312; P = .001). The FLEXAEMG and EXTAEMG of both groups had a significant increase (P < .05), with the Baduanjin group demonstrating higher levels compared to the Walking group (P < .05). Conversely, the MAEMG of both groups displayed a significant decrease (P < .05), with the Baduanjin group exhibiting lower levels than the Walking group (P < .05). The FLEXAEMG to MAEMG and EXTAEMG to MAEMG in the Baduanjin group increased (P < .05) and were significantly higher than the Walking group (P < .05). Conclusion: Baduanjin exercise has shown to be highly effective in reducing low back pain and in promoting lumber dysfunction, due to its ability to improve the strength and flexibility of the lumbar erector spinae muscle.

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“…In individuals with SCI, even without visible contractions of impaired muscles during voluntary movement attempts, sEMG signals can be detected [10][11][12][13][14][15]. Furthermore, sEMG has demonstrated great potential in capturing the impact from SCI, which has not been fully made use of in clinical assessments and neurorehabilitation [16][17][18][19][20]. Recent reviews by Balbinot et al demonstrated that sEMG features in time and frequency domains, other than traditional amplitude-based features, have not been fully leveraged [19,20].…”

Section: Introductionmentioning

confidence: 99%

“…Furthermore, sEMG has demonstrated great potential in capturing the impact from SCI, which has not been fully made use of in clinical assessments and neurorehabilitation [16][17][18][19][20]. Recent reviews by Balbinot et al demonstrated that sEMG features in time and frequency domains, other than traditional amplitude-based features, have not been fully leveraged [19,20]. Nonetheless, the use of sEMG in the clinical settings has been limited, with one of the key barriers being the specialized training and expertise required for signal interpretation [18,21].…”

Section: Introductionmentioning

confidence: 99%

A computational model of surface electromyography signal alterations after spinal cord injury

Li,

Balbinot,

Furlan

et al. 2023

J. Neural Eng.

Self Cite

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Spinal cord injury (SCI) can cause significant impairment and disability with an impact on the quality of life for individuals with SCI and their caregivers. Surface electromyography (sEMG) is a sensitive and non-invasive technique to measure muscle activity and has demonstrated great potential in capturing neuromuscular changes resulting from SCI. The mechanisms of the sEMG signal characteristic changes due to SCI are multi-faceted and difficult to study in vivo. In this study, we utilized well-established computational models to characterize changes in sEMG signal after SCI and identify sEMG features that are sensitive and specific to different aspects of the SCI. Starting from existing models for motor neuron pool organization and motor unit action potential generation for healthy neuromuscular systems, we implemented scenarios to model damages to upper motor neurons, lower motor neurons, and the number of muscle fibers within each motor unit. After simulating sEMG signals from each scenario, we extracted time and frequency domain features and investigated the impact of SCI disruptions on sEMG features using the Kendall Rank Correlation analysis. The results indicate that commonly used amplitude-based sEMG features (such as mean absolute values and root mean square) cannot differentiate between injury scenarios, but a broader set of features (including autoregression and cepstrum coefficients) provides greater specificity to the type of damage present. We introduce a novel approach to mechanistically relate sEMG features (often underused in SCI research) to different types of neuromuscular alterations that may occur after SCI. This work contributes to the further understanding and utilization of sEMG in clinical applications, which will ultimately improve patient outcomes after SCI.

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The use of surface EMG in neurorehabilitation following traumatic spinal cord injury: A scoping review

Cited by 9 publications

References 123 publications

Recent Progress on Poly(3,4‐Ethylenedioxythiophene):Poly(Styrenesulfonate) Bioelectrodes

Recent Progress on Poly(3,4‐Ethylenedioxythiophene):Poly(Styrenesulfonate) Bioelectrodes

Effects of Baduanjin exercise on patients with chronic nonspecific low back pain and surface electromyography signs of erector spinal muscle: A randomized controlled trial

A computational model of surface electromyography signal alterations after spinal cord injury

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