Hypogravity reduces trunk admittance and lumbar muscle activation in response to external perturbations

Reduced paraspinal muscle size and flattening of spinal curvatures have been documented after spaceflight. Assessment of trunk adaptations to hypogravity can contribute to develop specific countermeasures. In this study, parabolic flights were used to investigate spinal curvature and muscle responses to hypogravity. Data from five trials at 0.25g, 0.50g and 0.75g were recorded from six participants, positioned in a kneeling-seated position. During the first two trials, participants maintained a normal, upright posture. In the last three trials, small-amplitude perturbations were delivered in the anterior direction at the T10 level. Spinal curvature was estimated using motion capture cameras. Trunk displacement and contact force between the actuator and participant were recorded. Muscle activity responses were collected using intramuscular electromyography (iEMG) of the deep and superficial lumbar multifidus, iliocostalis lumborum, longissimus thoracis, quadratus lumborum, transversus abdominis, obliquus internus and obliquus externus muscles. The root mean square iEMG and the average spinal angles were calculated. Trunk admittance and muscle responses to perturbations were calculated as closed-loop frequency response functions. Compared with 0.75g, 0.25g resulted in: lower activation of the longissimus thoracis (P=0.002); lower responses of the superficial multifidus at low frequencies (P=0.043); lower responses of the superficial multifidus (P=0.029) and iliocostalis lumborum (P=0.043); lower trunk admittance (P=0.037) at intermediate frequencies; and stronger responses of the transversus abdominis at higher frequencies (p=0.032). These findings indicate that exposure to hypogravity reduces trunk admittance, partially compensated by weaker stabilizing contributions of the paraspinal muscles and coinciding with an apparent increase of the deep abdominal muscle activity

A Multiday Evaluation of Real-Time Intramuscular EMG Usability with ANN

Recent developments in implantable technology, such as high-density recordings, wireless transmission of signals to a prosthetic hand, may pave the way for intramuscular electromyography (iEMG)-based myoelectric control in the future. This study aimed to investigate the real-time control performance of iEMG over time. A novel protocol was developed to quantify the robustness of the real-time performance parameters. Intramuscular wires were used to record EMG signals, which were kept inside the muscles for five consecutive days. Tests were performed on multiple days using Fitts’ law. Throughput, completion rate, path efficiency and overshoot were evaluated as performance metrics using three train/test strategies. Each train/test scheme was categorized on the basis of data quantity and the time difference between training and testing data. An artificial neural network (ANN) classifier was trained and tested on (i) data from the same day (WDT), (ii) data collected from the previous day and tested on present-day (BDT) and (iii) trained on all previous days including the present day and tested on present-day (CDT). It was found that the completion rate (91.6 ± 3.6%) of CDT was significantly better (p < 0.01) than BDT (74.02 ± 5.8%) and WDT (88.16 ± 3.6%). For BDT, on average, the first session of each day was significantly better (p < 0.01) than the second and third sessions for completion rate (77.9 ± 14.0%) and path efficiency (88.9 ± 16.9%). Subjects demonstrated the ability to achieve targets successfully with wire electrodes. Results also suggest that time variations in the iEMG signal can be catered by concatenating the data over several days. This scheme can be helpful in attaining stable and robust performance

Feasibility RCT of neuromuscular electrical stimulation; an Intervention to Maintain and improve neuroMuscular function during periods of Immobility (IMMI): Protocol

East Midlands Research into Ageing Network (EMRAN) is a research collaboration across the East Midlands to facilitate collaborative applied clinical research into ageing and the care of older people. EMRAN was set up by NIHR CLAHRC East Midlands and is supported by the NIHR Clinical Research Network

Frailty phenotype and frailty index are associated with distinct neuromuscular electrophysiological characteristics in men

The purpose of this study was to determine whether neuromuscular electrophysiological characteristics that are known to underlie sarcopenia are also associated with the more complex frailty syndrome. Eighty‐six men [mean (SD) age, 74 (8) years] were classed as non‐frail (robust), prefrail or frail using criteria from the frailty phenotype (FP) and the frailty index (FI). The femoral nerve was stimulated maximally and the resulting compound muscle action potential amplitude (CMAP) measured over the vastus lateralis. Motor unit potential (MUP) size was assessed during voluntary contractions using intramuscular electromyography (iEMG). Logistic and negative binomial regression models determined relationships between FP and FI with CMAP and MUP sizes before and after adjustments for age and body mass index. Larger CMAP size was associated with a lower likelihood of frailty in fully adjusted models: a 1SD higher level in vastus lateralis CMAP size was associated with a 0.4 (95% confidence interval: 0.2, 0.6; P < 0.01) unit lower FI (40% of the FI range) and more than halving of the odds [odds ratio: 0.43 (95% confidence interval: 0.21, 0.90)] of having a frail/prefrail phenotype. Greater MUP size was also related to lower FI values using unadjusted and fully adjusted models. However, MUP size was not significantly related to FP in any model. Smaller MUPs and a smaller CMAP were significantly associated with a higher likelihood of frailty, independent of age and body mass index. These results relate neuromuscular electrophysiological characteristics to the complex frailty syndrome and identify motor unit remodelling as a possible contributing factor

Transversus abdominis is part of a global not local muscle synergy during arm movement

The trunk muscle transversus abdominis (TrA) is thought to be controlled independently of the global trunk muscles. Methodological issues in the 1990s research such as unilateral electromyography and a limited range of arm movements justify a re-examination of this theory. The hypothesis tested is that TrA bilateral co-contraction is a typical muscle synergy during arm movement. The activity of 6 pairs of trunk and lower limb muscles was recorded using bilateral electromyography during anticipatory postural adjustments (APAs) associated with the arm movements. The integrated APA electromyographical signals were analyzed for muscle synergy using Principle Component Analysis. TrA does not typically bilaterally co-contract during arm movements (1 out of 6 participants did). APA muscle activity of all muscles during asymmetrical arm movements typically reflected a direction specific diagonal pattern incorporating a twisting motion to transfer energy from the ground up. This finding is not consistent with the hypothesis that TrA plays a unique role providing bilateral, feedforward, multidirectional stiffening of the spine. This has significant implications to the theories underlying the role of TrA in back pain and in the training of isolated bilateral co-contraction of TrA in the prophylaxis of back pain

Investigation of Permanent Tattoos to Increase Myoelectric Signal Connectivity in Prosthetics

Myoelectric prosthetics offer users increased functionality in many facits of their lives. However, maintaining reliable connectivity between sEMG sensors and targeted muscle locations can be problematic. Volume fluctuation of the residual limb, dirt, sweat, and movement of the socket and sensor over the limb can all because of signal disruption leading some users to find the myoelectric prostheses, costing thousands of dollars, to be unreliable, and stop using it. To increase connectivity between the optimal myoelectric sites and sEMG sensors, this paper proposes the use of permanent ink tattoos to create a stable location which a sensor can move over when a prosthetic socket shifts, but still have connectivity to sites with the strongest myoelectric signal. This study proposes to start by testing various permanent bio-compatible tattoo inks for electrical connectivity in skin. Then test for optimal pattern designs in static and dynamic sensor scenarios to determine whether or not levels of myoelectric signals are higher and clearer (less electrical resistance in ohms) than unprepared skin. This technique may provide benefits to those using surface EMG sensor who experience interruptions in myoelectric signals, preventing the performance of intentional prosthetic functions. This could also benefit the development of implanted EMG electrodes or neural implants, as a means to provide efficient signal transmission through the skin

Diverse coordinate frames on sensorimotor areas in visuomotor transformation

The visuomotor transformation during a goal-directed movement may involve a coordinate transformation from visual ‘extrinsic’ to muscle-like ‘intrinsic’ coordinate frames, which might be processed via a multilayer network architecture composed of neural basis functions. This theory suggests that the postural change during a goal-directed movement task alters activity patterns of the neurons in the intermediate layer of the visuomotor transformation that recieves both visual and proprioceptive inputs, and thus influence the multi-voxel pattern of the blood oxygenation level dependent signal. Using a recently developed multi-voxel pattern decoding method, we found extrinsic, intrinsic and intermediate coordinate frames along the visuomotor cortical pathways during a visuomotor control task. The presented results support the hypothesis that, in human, the extrinsic coordinate frame was transformed to the muscle-like frame over the dorsal pathway from the posterior parietal cortex and the dorsal premotor cortex to the primary motor cortex

Recursive decomposition of electromyographic signals with a varying number of active sources: Bayesian modelling and filtering

International audienceThis paper describes a sequential decomposition algorithm for single channel intramuscular electromyography (iEMG) generated by a varying number of active motor neurons. As in previous work, we establish a Hidden Markov Model of iEMG, in which each motor neuron spike train is modeled as a renewal process with inter-spike intervals following a discrete Weibull law and motor unit action potentials are modeled as impulse responses of linear time-invariant systems with known prior. We then expand this model by introducing an activation vector associated to the state vector of the Hidden Markov Model. This activation vector represents recruitment/derecruitment of motor units and is estimated together with the state vector using Bayesian filtering. Non-stationarity of the model parameters is addressed by means of a sliding window approach, thus making the algorithm adaptive to variations in contraction force and motor unit action potential waveforms. The algorithm was validated using simulated and experimental iEMG signals with varying number of active motor units. The experimental signals were acquired from the tibialis anterior and abductor digiti minimi muscles by fine wire and needle electrodes. The decomposition accuracy in both simulated and experimental signals exceeded 90% and the recruitment/derecruitment was successfully tracked by the algorithm. Because of its parallel structure, this algorithm can be efficiently accelerated, which lays the basis for its future real-time applications in human-machine interfaces, e.g. for prosthetic control