Changes in sensorimotor function and increased trunk muscle fatigability have been identified in patients with chronic low back pain (cLBP). This study assessed the control of trunk force production ...in conditions with and without local erector spinae muscle vibration and evaluated the influence of muscle fatigue on trunk sensorimotor control.
Twenty non-specific cLBP patients and 20 healthy participants were asked to perform submaximal isometric trunk extension torque with and without local vibration stimulation, before and after a trunk extensor muscle fatigue protocol. Constant error (CE), variable error (VE) as well as absolute error (AE) in peak torque were computed and compared across conditions. Trunk extensor muscle activation during isometric contractions and during the fatigue protocol was measured using surface electromyography (sEMG).
Force reproduction accuracy of the trunk was significantly lower in the patient group (CE = 9.81 ± 2.23 Nm; AE = 18.16 ± 3.97 Nm) than in healthy participants (CE = 4.44 ± 1.68 Nm; AE = 12.23 ± 2.44 Nm). Local erector spinae vibration induced a significant reduction in CE (4.33 ± 2.14 Nm) and AE (13.71 ± 3.45 Nm) mean scores in the patient group. Healthy participants conversely showed a significant increase in CE (8.17 ± 2.10 Nm) and AE (16.29 ± 2.82 Nm) mean scores under vibration conditions. The fatigue protocol induced erector spinae muscle fatigue as illustrated by a significant decrease in sEMG median time-frequency slopes. Following the fatigue protocol, patients with cLBP showed significant decrease in sEMG root mean square activity at L4-5 level and responded in similar manner with and without vibration stimulation in regard to CE mean scores.
Patients with cLBP have a less accurate force reproduction sense than healthy participants. Local muscle vibration led to significant trunk neuromuscular control improvements in the cLBP patients before and after a muscle fatigue protocol. Muscle vibration stimulation during motor control exercises is likely to influence motor adaptation and could be considered in the treatment of cLBP. Further work is needed to clearly identify at what levels of the sensorimotor system these gains are achievable.
Previous studies observed that the intervertebral disc experiences the greatest forces during spinal manipulative therapy (SMT) and that the distribution of forces among spinal tissues changes as a ...function of the SMT parameters. However, contextualized SMT forces, relative to the ones applied to and experienced by the whole functional spinal unit, is needed to understand SMT's underlying mechanisms.
To describe the percentage force distribution between spinal tissues relative to the applied SMT forces and total force experienced by the functional unit.
This secondary analysis combined data from 35 fresh porcine cadavers exposed to a simulated 300N SMT to the skin overlying the L3/L4 facet joint via servo-controlled linear motor actuator. Vertebral kinematics were tracked optically using indwelling bone pins. The functional spinal unit was then removed and mounted on a parallel robotic platform equipped with a 6-axis load cell. The kinematics of the spine during SMT were replayed by the robotic platform. By using serial dissection, peak and mean forces induced by the simulated SMT experienced by spinal structures in all three axes of motion were recorded. Forces experienced by spinal structures were analyzed descriptively and the resultant force magnitude was calculated.
During SMT, the functional spinal unit experienced a median peak resultant force of 36.4N (IQR: 14.1N) and a mean resultant force of 25.4N (IQR: 11.9N). Peak resultant force experienced by the spinal segment corresponded to 12.1% of the total applied SMT force (300N). When the resultant force experienced by the functional spinal unit was considered to be 100%, the supra and interspinous ligaments experienced 0.3% of the peak forces and 0.5% of the mean forces. Facet joints and ligamentum flavum experienced 0.7% of the peak forces and 3% of the mean forces. Intervertebral disc and longitudinal ligaments experienced 99% of the peak and 96.5% of the mean forces.
In this animal model, a small percentage of the forces applied during a posterior-to-anterior SMT reached spinal structures in the lumbar spine. Most SMT forces (over 96%) are experienced by the intervertebral disc. This study provides a novel perspective on SMT force distribution within spinal tissues.
Abstract Objectives Previous studies have identified preload forces and an important feature of skillful execution of spinal manipulative therapy (SMT) as performed by manual therapists (eg, doctors ...of chiropractic and osteopathy). It has been suggested that applying a gradual force before the thrust increases the spinal unit stiffness, minimizing displacement during the thrust. Therefore, the main objective of this study was to assess the vertebral unit biomechanical and neuromuscular responses to a graded increase of preload forces. Methods Twenty-three participants underwent 4 different SMT force-time profiles delivered by a servo-controlled linear actuator motor and varying in their preload forces, respectively, set to 5, 50, 95, and 140 N in 1 experimental session. Kinematic markers were place on T6, T7, and T8 and electromyographic electrodes were applied over paraspinal muscles on both sides of the spine. Results Increasing preload forces led to an increase in neuromuscular responses of thoracic paraspinal muscles and vertebral segmental displacements during the preload phase of SMT. Increasing the preload force also yielded a significant decrease in sagittal vertebral displacement and paraspinal muscle activity during and immediately after the thrust phase of spinal manipulation. Changes observed during the SMT thrust phase could be explained by the proportional increase in preload force or the related changes in rate of force application. Although only healthy participants were tested in this study, preload forces may be an important parameter underlying SMT mechanism of action. Future studies should investigate the clinical implications of varying SMT dosages. Conclusion The present results suggest that neuromuscular and biomechanical responses to SMT may be modulated by preload through changes in the rate of force application. Overall, the present results suggest that preload and rate of force application may be important parameters underlying SMT mechanism of action.
Abstract Objective It is believed that systematic modulation of spinal manipulative therapy (SMT) parameters should yield varying levels of physiological responses and eventually a range of clinical ...responses. However, investigation of SMT dose–physiological response relationship is recent and has mostly been conducted using animal or cadaveric models. The main objective of the present study is to investigate SMT dose–physiological response relation in humans by determining how different levels of force can modify electromyographic (EMG) responses to spinal manipulation. Methods Twenty-six participants were subjected to 2 trials of 4 different SMT force-time profiles using a servo-controlled linear actuator motor. Normalized EMG activity of paraspinal muscles (left and right muscles at level T6 and T8) was recorded during and after SMT, and EMG values were compared across the varying levels of force. Results Increasing the level of force yielded an increase in paraspinal muscle EMG activity during the thrust phase of SMT but also in the two 250-millisecond time windows after the spinal manipulation impulse. These muscle activations quickly attenuated (500 milliseconds after spinal manipulation impulse). Conclusion The study confirmed the presence of a local paraspinal EMG response after SMT and highlighted the linear relationship between the SMT peak force and paraspinal muscle activation.
Recently, robotics has been seen as a key solution to improve the quality of life of amputees. In order to create smarter robotic prosthetic devices to be used in an everyday context, one must be ...able to interface them seamlessly with the end-user in an inexpensive, yet reliable way. In this paper, we are looking at guiding a robotic device by detecting gestures through measurement of the electrical activity of muscles captured by surface electromyography (sEMG). Reliable sEMG-based gesture classifiers for end-users are challenging to design, as they must be extremely robust to signal drift, muscle fatigue and small electrode displacement without the need for constant recalibration. In spite of extensive research, sophisticated sEMG classifiers for prostheses guidance are not yet widely used, as systems often fail to solve these issues simultaneously. We propose to address these problems by employing Convolutional Neural Networks. Specifically as a first step, we demonstrate their viability to the problem of gesture recognition for a low-cost, low-sampling rate (200Hz) consumer-grade, 8-channel, dry electrodes sEMG device called Myo armband (Thalmic Labs) on able-bodied subjects. To this effect, we assessed the robustness of this machine learning oriented approach by classifying a combination of 7 hand/wrist gestures with an accuracy of ~97.9% in real-time, over a period of 6 consecutive days with no recalibration. In addition, we used the classifier (in conjunction with orientation data) to guide a 6DoF robotic arm, using the armband with the same speed and precision as with a joystick. We also show that the classifier is able to generalize to different users by testing it on 18 participants.
Abstract Objective The objective of this study was to evaluate changes in neuromechanical responses and clinical outcomes in chronic low back pain participants after 4 sessions of biofeedback ...training. Methods Twenty-one participants took part in an electromyography biofeedback 4-session training program aimed at reducing lumbar paraspinal muscle activity during full trunk flexion. The sessions consisted of ~ 46 trunk flexion-extension divided into 5 blocks. The effects of training blocks and sessions on lumbar flexion-relaxation ratio and lumbopelvic ranges of motion were assessed. Changes in disability (Oswestry Disability Index), pain intensity (numerical rating scale), and fear of movement (Tampa Scale for Kinesiophobia) were also evaluated. Results Analyses of variance revealed a significant block effect for which an increase in the flexion-relaxation ratio and the lumbar range of motion between block 1 and the other blocks for sessions 1 and 2 ( P < .0001) was observed. However, no significant session or interaction effect was observed. Among clinical outcomes, only fear of movement significantly decreased between the baseline (mean SD, 33.05 7.18) and the fourth session (29.80 9.88) ( P = .02). There was no significant correlation between clinical outcomes and neuromechanical variables. Conclusion Biofeedback training led to decreases in lumbar paraspinal muscle activity in full trunk flexion and increases in lumbopelvic range of motion in participants with chronic nonspecific low back pain. Although the neuromechanical changes were mostly observed at the early stage of the program, the presence of a decrease in the fear of movement suggests that the participants' initially limited ROMs may have been modulated by fear avoidance behaviors.
The aim of this study was to identify adaptations in muscle activity distribution to spinal tissue creep in presence of muscle fatigue.
Twenty-three healthy participants performed a fatigue task ...before and after 30 minutes of passive spinal tissue deformation in flexion. Right and left erector spinae activity was recorded using large-arrays surface electromyography (EMG). To characterize muscle activity distribution, dispersion was used. During the fatigue task, EMG amplitude root mean square (RMS), median frequency and dispersion in x- and y-axis were compared before and after spinal creep.
Important fatigue-related changes in EMG median frequency were observed during muscle fatigue. Median frequency values showed a significant main creep effect, with lower median frequency values on the left side under the creep condition (p≤0.0001). A significant main creep effect on RMS values was also observed as RMS values were higher after creep deformation on the right side (p = 0.014); a similar tendency, although not significant, was observed on the left side (p = 0.06). A significant creep effects for x-axis dispersion values was observed, with higher dispersion values following the deformation protocol on the left side (p≤0.001). Regarding y-axis dispersion values, a significant creep x fatigue interaction effect was observed on the left side (p = 0.016); a similar tendency, although not significant, was observed on the right side (p = 0.08).
Combined muscle fatigue and creep deformation of spinal tissues led to changes in muscle activity amplitude, frequency domain and distribution.
This study aimed to predict the index of effectiveness (IE) and positive impulse proportion (PIP) to assess the cyclist's pedalling technique from lower limb kinematic variables. Several wrapped ...feature selection techniques were applied to select the best predictors. To predict IE and PIP two multiple linear regressions (MLR) composed of 11 predictors (R² = 0.81 ± 0.12, R² = 0.81 ± 0.05) and two artificial neural networks (ANN) composed of 21 and 28 predictors (R² = 0.95 ± 0.01, R² = 0.92 ± 0.02) were developed. The ANN predicts with accuracy, and the MLR shows the influence of each predictor.This study aimed to predict the index of effectiveness (IE) and positive impulse proportion (PIP) to assess the cyclist's pedalling technique from lower limb kinematic variables. Several wrapped feature selection techniques were applied to select the best predictors. To predict IE and PIP two multiple linear regressions (MLR) composed of 11 predictors (R² = 0.81 ± 0.12, R² = 0.81 ± 0.05) and two artificial neural networks (ANN) composed of 21 and 28 predictors (R² = 0.95 ± 0.01, R² = 0.92 ± 0.02) were developed. The ANN predicts with accuracy, and the MLR shows the influence of each predictor.
Purpose
To identify and characterize trunk neuromuscular adaptations during muscle fatigue in patients with chronic low back pain (LBP) and healthy participants.
Methods
Forty-six patients with ...non-specific chronic LBP and 23 healthy controls were asked to perform a trunk muscles fatigue protocol. Surface electromyography was recorded using two adhesive matrix of 64 electrodes applied bilaterally over the erector spinae. Pain score, kinesiophobia and physical disability were analyzed through different questionnaires. To characterize motor variability, dispersion of muscular activity center of gravity was computed. Motor variability between groups was compared using repeated-measures analyses of variance.
Results
Score of disability and kinesiophobia were significantly higher in patients with LBP. Results indicated a significant group effect characterized by an increased motor variability in the healthy group through the entire fatigue task on the left (
p
= 0.003) and right side (
p
= 0.048). Interestingly, increasing muscle fatigue led to increased motor variability in both groups (on both sides (
p
< 0.001) but with a greater increase in the healthy group.
Conclusion
Muscle recruitment is altered in patients with chronic LBP in the presence of muscle fatigue. Consequently, these patients exhibit changes in muscle recruitment pattern and intensity (lower levels of motor variability) during sustained isometric contraction that may be attributed to variation in the control of motor units within and between muscles. However, patients with LBP are able to increase their motor variability over time but with a lower increase compared to healthy participants.
The objective was to compare thoracic spinal stiffness between healthy participants and participants with chronic thoracic pain and to explore the associations between spinal stiffness, pain and ...muscle activity. The reliability of spinal stiffness was also evaluated.
Spinal stiffness was assessed from T5 to T8 using a mechanical device in 25 healthy participants and 50 participants with chronic thoracic pain (symptoms had to be reported within the evaluated region of the back). The spinal levels for which spinal stiffness was measured were standardized (i.e. T5 to T8 for all participants) to minimize between-individual variations due to the evaluation of different spinal levels. The device load and displacement data were used to calculate the global and terminal spinal stiffness coefficients at each spinal level. Immediately after each assessment, participants were asked to rate their pain intensity during the trial, while thoracic muscle activity was recorded during the load application using surface electromyography electrodes (sEMG). Within- and between-day reliability were evaluated using intraclass correlation coefficients (ICC), while the effects of chronic thoracic pain and spinal levels on spinal stiffness and sEMG activity were assessed using mixed model ANOVAs. Correlations between pain intensity, muscle activity and spinal stiffness were also computed.
ICC values for within- and between-day reliability of spinal stiffness ranged from 0.67 to 0.91 and from 0.60 to 0.94 (except at T5), respectively. A significant decrease in the global (F1,73 = 4.04, p = 0.048) and terminal (F1,73 = 4.93, p = 0.03) spinal stiffness was observed in participants with thoracic pain. sEMG activity was not significantly different between groups and between spinal levels. Pain intensity was only significantly and "moderately" correlated to spinal stiffness coefficients at one spinal level (-0.29≤r≤-0.51), while sEMG activity and spinal stiffness were not significantly correlated.
The results suggest that spinal stiffness can be reliably assessed using a mechanical device and that this parameter is decreased in participants with chronic thoracic pain. Studies are required to determine the value of instrumented spinal stiffness assessment in the evaluation and management of patients with chronic spine-related pain.
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