Search

Background Adequate neuromuscular control of the knee could be one element to prevent secondary injuries after an anterior cruciate ligament (ACL) injury. To assess neuromuscular control in terms of time, amplitude and activity, electromyography (EMG) is used. However, it is unclear which assessments using EMG could be used for a safe return to sports (RTS). Therefore, we aimed to summarize EMG-related assessments for neuromuscular control of the knee in adult patients after an ACL injury to decide upon readiness for RTS. Methods This systematic review followed guidelines of Preferred Reporting of Items for Systematic Reviews and Meta-Analyses (PRISMA) and Cochrane recommendations. MEDLINE/PubMed, EMBASE, CINAHL, Cochrane Library, Physiotherapy Evidence Database (PEDro), SPORTDiscus and the Web of Science were searched from inception to March 2019 and updated in November 2020. Studies identifying electromyographic assessments for neuromuscular control during dynamic tasks in adult, physically active patients with an anterior cruciate ligament injury were eligible and qualitatively synthesized. Two independent reviewers used a modified Downs and Black checklist to assess risk of bias of included studies. Results From initially 1388 hits, 38 mainly cross-sectional, case-controlled studies were included for qualitative analysis. Most studies provided EMG outcomes of thigh muscles during jumping, running or squatting. Outcomes measures described neuromuscular control of the knee in domains of time, amplitude or activity. Risk of bias was medium to high due to an unclear description of participants and prior interventions, confounding factors and incompletely reported results. Conclusions Despite a wide range of EMG outcome measures for neuromuscular control, none was used to decide upon return to sports in these patients. Additional studies are needed to define readiness towards RTS by assessing neuromuscular control in adult ACL patients with EMG. Further research should aim at finding reliable and valid, EMG-related variables to be used as diagnostic tool for neuromuscular control. Moreover, future studies should aim at more homogenous groups including adequately matched healthy subjects, evaluate gender separately and use sport-specific tasks. Registration The protocol for this systematic review was indexed beforehand in the International Prospective Register of Systematic Reviews (PROSPERO) and registered as CRD42019122188.

Background: Mastication is one of the most fundamental functions for the conservation of human life. To clarify the pathogenetic mechanism of various oral dysfunctions, the demand for devices for evaluating stomatognathic function has been increasing. The aim of the present study was to develop a system to reconstruct and visualize 3-dimensional (3D) mandibular movements relative to the maxilla, including dynamic transition of occlusal contacts between the upper and lower dentitions during mastication in mice. Methods: First, mandibular movements with six degrees of freedom were measured using a motion capture system comprising two high-speed cameras and four reflective markers. Second, 3D models of maxillofacial structure were reconstructed from micro-computed tomography images. Movement trajectories of anatomical landmark points on the mandible were then reproduced by integrating the kinematic data of mandibular movements with the anatomical data of maxillofacial structures. Lastly, 3D surface images of the upper dentition with the surrounding maxillofacial structures were transferred to each of the motion capture images to reproduce mandibular movements relative to the maxilla. We also performed electromyography (EMG) of masticatory muscles associated with mandibular movements. Results: The developed system could reproduce the 3D movement trajectories of arbitrary points on the mandible, such as incisor, molars and condylar points with high accuracy and could visualize dynamic transitions of occlusal contacts between upper and lower teeth associated with mandibular movements. Conclusions: The proposed system has potential to elucidate the mechanisms underlying motor coordination of masticatory muscles and to clarify their roles during mastication by taking advantage of the capability to record EMG data synchronously with mandibular movements. Such insights will enhance our understanding of the pathogenesis and diagnosis of oral motor disorders by allowing comparisons between normal mice and genetically modified mice with oral behavioral dysfunctions., BMC Oral Health, 21, art. no. 527; 2021

The integration of electromyography (EMG) and ultrasound imaging has provided important information about the mechanisms of muscle activation and contraction. Unfortunately, EMG does not allow an accurate assessment of the interplay between the neural drive received by muscles, changes in fascicle length (FL) and the force/torque produced. We aimed to assess the relationship between modulations in tibialis anterior (TA) motor unit (MU) firing rate, FL and dorsiflexion torque (DT) using ultrasound-transparent high-density EMG electrodes. EMG and ultrasound images were recorded simultaneously from TA, using a 32-electrode silicon matrix, while performing isometric dorsiflexion, at diverse ankle joint positions (0° and 30° plantar flexion) and torques (20% and 40% of maximum). EMG signals were decomposed into individual MUs and changes in FL were assessed with a fascicle-tracking algorithm. MU firings were converted into a cumulative spike train (CST) that was cross-correlated with DT (CST-DT) and FL (CST-FL). High cross-correlations were found for CST-FL, 0.60 (range: 0.31-0.85) and CST-DT 0.71 (range: 0.31-0.88). Cross-correlation lags revealed that the delay between CST-FL (~75ms) was significantly smaller than CST-DT (~150ms, pNEW AND NOTEWORTHYBy employing ultrasound-transparent high-density surface EMG electrodes, we show that modulations in tibialis anterior motor unit discharge rate were closely related to both changes in its fascicle length and resultant torque. These relationships allowed quantifying delays between neural drive and muscle shortening as well as muscle shortening and torque during submaximal isometric contractions, providing an accurate estimation of the time required to generate muscle force and subsequent production of torque via the tendon.

Maneuvers to activate the equine's core can make a difference in their physical and psychic health. Although these activities are recommended and practiced, there is little research proving their effectiveness. This article aims to describe, through surface electromyography, the occurrences, durations and sequences activity of longissimus dorsi, rectus abdominis and gluteus medius during thoracolumbar flexion (TLF), lumbar and lumbosacral flexion (LLSF), global flexion (GF), which is the combination of TLF and LLSF, and tail traction (TT). Seven healthy adult horses of three different breeds performed five repetitions of these movements for five seconds (sec). Electromyographic activity was captured with non-invasive superficial sensors positioned in the skin regions covering these muscles. The sequence was performed once per animal, muscle activity captured by surface electromyography, data from two replicates of each animal were selected, analyzed on matLab software and data tabulation were described during each maneuver. These maneuvers provoked punctual and transient activation of muscles mentioned above, confirming the ability to activate equine core muscles. However, responses were not standardized, which means there were variations of occurrence, duration and sequence, suggesting that for practical application of those maneuvers it is necessary to perform more repetitions with longer durations to activate more muscles.

Background: Deep squatting, as part of postural ontogenesis, is an integral part of every athlete's training. Squats performed with the correct kinesiological pattern can ensure optimal loading of the musculoskeletal system, affect the function of the diaphragm and thus breathing in addition to positively affect the pelvic floor muscles. On the contrary, in the case of insufficient coordination, we can detect a failure in the stabilization of individual segments. Aim: The aim of the study was to find out the difference in the quality of muscle involvement in two variants of squats. The first squat was natural for an athlete without the intervention of a therapist, and in the second one we tried to adjust the individual segments biomechanically correctly. Methods: The group included 20 athletes, with an average age of 21.85 years. The measurement took place in the MSC Dukla Banská Bystrica building at a uniform time from 10:00AM to 12:30PM. We used a biomedical telemetry system with surface EMG. M. biceps femoris, m. semitendinosus, m. vastus medialis and m. erector spinae were measured. Results: The activity of the muscles on the back of the thigh showed lower average values after squat correction by physiotherapist instructions (significant in one case). Differences in activity of all muscles: m. biceps femoris dx (p = 0.16005), sin (p = 0,00268), m. semitendinosus dx (p = 0.838), sin (p = 0.0852). m. vastus medialis dx (p= 0.35), sin (p = 0.0066), m erector spinalis dx (p = 0.118), sin (p = 0.0632). Conclusion: Our measurements showed that the correction of individual segments to the correct biomechanical position was statistically confirmed in two cases (vastus medialis sin. and m. biceps femoris sin.), But from a practical point of view we recorded a positive effect on average muscle activity. and overall squat execution efficiency. DOI: https://doi.org/10.24040/sjss.2021.7.1.37-47

Introduction Compressive ulnar neuropathy at the elbow is the second most common compressive neuropathy. Nerve transfers are used for severe ulnar neuropathies as a means of facilitating recovery. Hand therapy and rehabilitation after nerve transfers have not been extensively explored. Purpose of the Study The aim of this repeated case study was to describe the responses, functional outcome, and neuromuscular health of three participants after the supercharged end-to-side (SETS) anterior interosseous nerve (AIN) to ulnar motor nerve transfer do describe the hand therapy and recovery of 3 cases reflecting different recovery potential mediators, trajectories, and outcomes. Study Design Repeated case study. Methods Three participants of similar age (76-80 years) that had severe ulnar neuropathy who underwent surgical treatment including a SETS AIN to ulnar motor nerve surgery were purposively selected from an ongoing clinical trial, based on their response to the surgical and the rehabilitation intervention (large, moderate, and small improvements). Clinical evaluations included measuring range of motion, strength testing, and clinical tests (ie, Egawa's sign) and, subjective assessment of rehabilitation adherence., Quick Disability of Arm, Shoulder and Hand and decomposition-based quantitative electromyography were performed at >23 months to evaluate patients. Results All the three participants completed the surgical and hand therapy interventions, demonstrating a variable course of recovery and functional outcomes. The Quick Disability of Arm, Shoulder and Hand scores (>23 months) for participants A, B, and C were 68, 30, and 18, respectively. The person with the least improvement had idiopathic Parkinson's disease, dyslipidemia, history of depression, and gout. Comparison across cases suggested that the comorbidities, longer time from neuropathy to the surgical intervention, and psychosocial barriers to exercise and rehabilitation adherence influenced the recovery process. The participants with the best outcomes demonstrated improvements in his lower motor neurons or motor unit counts (109 and 18 motor units in the abductor digiti minimi (ADM) and first dorsal interosseous, respectively) and motor unit stability (39.5% and 37.6% near-fiber jiggle in the ADM and first dorsal interosseous, respectively). The participant with moderate response to the interventions had a motor unit count of 93 for the ADM muscle. We were unable to determine motor unit counts and measurements from the participant with the poorest outcomes due to his physical limitations. Conclusions SETS AIN to ulnar motor nerve followed by multimodal hand therapy provides measurable improvements in neurophysiology and function, although engagement in hand therapy and outcomes appear to be mediated by comorbid physical and psychosocial health.

The clinical benefit of Deep Brain Stimulation (DBS) is associated with electrode positioning accuracy. Intraoperative assessment of clinical effect is therefore key. Evaluating this clinical effect in patients with dystonic head tremor, as opposed to limb tremor, is challenging because the head is fixed in a stereotactic frame. To clinically assess head tremor during surgery, surface electromyography (EMG) electrodes were bilaterally applied to the sternocleidomastoid and cervical paraspinal muscles. This case shows that intraoperative polymyography is an easy and useful tool to assess the clinical effect of DBS electrode positioning.

Resistance-training exercises can be classified as either single- or multi-joint exercises and differences in surface electromyography (EMG) amplitude between the two training methods may identify which muscles can benefit from either training modality. This study aimed to compare the surface EMG amplitude of five hip- and knee extensors during one multi-joint (leg press) and two single-joint exercises (knee extension and kickback). Fifteen resistance-trained men completed one familiarization session to determine their unilateral six repetitions maximum (6RM) in the three exercises. During the following experimental session, EMG amplitudes of the vastus lateralis, vastus medialis, rectus femoris, gluteus maximus and biceps femoris of the left leg were measured while performing three repetitions on their respective 6RM loads. The multi-joint exercise leg press produced higher EMG amplitude of the vastus lateralis (ES = 0.92, p = 0.003) than the single-joint exercise knee extension, whereas the rectus femoris demonstrated higher EMG amplitude during the knee extension (ES = 0.93, p = 0.005). The biceps femoris EMG amplitude was higher during the single-joint exercise kickback compared to the leg press (ES = 2.27, p < 0.001), while no significant differences in gluteus maximus (ES = 0.08, p = 0.898) or vastus medialis (ES = 0.056, p = 0.025 were observed between exercises. The difference in EMG amplitude between single- and multi-joint exercises appears to vary depending on the specific exercises and the muscle groups tested. Leg press is a viable and time-efficient option for targeting several hip- and knee extensors during resistance training of the lower limbs, but the single-joint exercises may be preferable for targeting the rectus femoris and biceps femoris.

Key points Gait‐related arm swing in humans supports efficient lower limb muscle activation, indicating a neural coupling between the upper and lower limbs during gait.Intermuscular coherence analyses of gait‐related electromyography from upper and lower limbs in 20 healthy participants identified significant coherence in alpha and beta/gamma bands indicating that upper and lower limbs share common subcortical and cortical drivers that coordinate the rhythmic four‐limb gait pattern.Additional directed connectivity analyses revealed that upper limb muscles drive and shape lower limb muscle activity during gait via subcortical and cortical pathways and to a lesser extent vice versa.The results provide a neural underpinning that arm swing may serve as an effective rehabilitation therapy concerning impaired gait in neurological diseases. Abstract Human gait benefits from arm swing, as it enhances efficient lower limb muscle activation in healthy participants as well as patients suffering from neurological impairment. The underlying neuronal mechanisms of such coupling between upper and lower limbs remain poorly understood. The aim of the present study was to examine this coupling by intermuscular coherence analysis during gait. Additionally, directed connectivity analysis of this coupling enabled assessment of whether gait‐related arm swing indeed drives lower limb muscles. To that end, electromyography recordings were obtained from four lower limb muscles and two upper limb muscles bilaterally, during gait, of 20 healthy participants (mean (SD) age 67 (6.8) years). Intermuscular coherence analysis revealed functional coupling between upper and lower limb muscles in the alpha and beta/gamma band during muscle specific periods of the gait cycle. These effects in the alpha and beta/gamma bands indicate involvement of subcortical and cortical sources, respectively, that commonly drive the rhythmic four‐limb gait pattern in an efficiently coordinated fashion. Directed connectivity analysis revealed that upper limb muscles drive and shape lower limb muscle activity during gait via subcortical and cortical pathways and to a lesser extent vice versa. This indicates that gait‐related arm swing reflects the recruitment of neuronal support for optimizing the cyclic movement pattern of the lower limbs. These findings thus provide a neural underpinning for arm swing to potentially serve as an effective rehabilitation therapy concerning impaired gait in neurological diseases., Key points Gait‐related arm swing in humans supports efficient lower limb muscle activation, indicating a neural coupling between the upper and lower limbs during gait.Intermuscular coherence analyses of gait‐related electromyography from upper and lower limbs in 20 healthy participants identified significant coherence in alpha and beta/gamma bands indicating that upper and lower limbs share common subcortical and cortical drivers that coordinate the rhythmic four‐limb gait pattern.Additional directed connectivity analyses revealed that upper limb muscles drive and shape lower limb muscle activity during gait via subcortical and cortical pathways and to a lesser extent vice versa.The results provide a neural underpinning that arm swing may serve as an effective rehabilitation therapy concerning impaired gait in neurological diseases.

Purpose The present study investigated whether or not passive stretching increases the force-generating capacity of the antagonist muscle, and the possible neuromuscular mechanisms behind. Methods To this purpose, the neuromuscular function accompanying the force-generating capacity was assessed in 26 healthy male volunteers after passive stretching and in a control session. Before and after passive intermittent static stretching of the plantar flexors consisting of five sets × 45 s + 15 s-rest, maximum voluntary isometric contraction (MVC) and surface electromyographic root mean square (sEMG RMS) were measured in the tibialis anterior (the antagonist muscle). Additionally, evoked V wave, H-reflex, and M wave were elicited by nerve stimulation at rest and during MVC. Ankle range of motion (ROM) and plantar flexors MVC and EMG RMS were measured to check for the effectiveness of the stretching manoeuvre. Results No change in MVC [p = 0.670; effect size (ES) − 0.03] and sEMG RMS/M wave during MVC (p = 0.231; ES − 0.09) was observed in the antagonist muscle after passive stretching. Similarly, no change in V wave (p = 0.531; ES 0.16), H-reflex at rest and during MVC (p = 0.656 and 0.597; ES 0.11 and 0.23, respectively) and M wave at rest and during MVC (p = 0.355 and 0.554; ES 0.04 and 0.01, respectively) was observed. An increase in ankle ROM (p p p Conclusion No change in the force-generating capacity and neuromuscular function of the antagonist muscle after passive stretching was observed.

Background Post-operative pulmonary complications are common after exploratory laparotomy. Good abdominal muscle functioning is essential for forced exhalation and effective coughing. However, the impact of a laparotomy on abdominal muscle activity remains uncertain. The study aimed to assess abdominal muscle activity during forced exhalation following elective laparotomy. Materials and methods A was carried out on those undergoing (n = 30) their first elective laparotomy. Abdominal muscle activity, as percentage maximal voluntary contraction (%MVC), was assessed during forced exhalation using surface electromyography (EMG) for transverse abdominis (TrAb), external oblique (EO), and rectus abdominis (RA) pre-operatively and up to seven days post-operatively. Peak expiratory flow rate (PEFR) was assessed during the forced exhalation maneuver. Median %MVC was used to represent the trends and Z-scores to report the change from the baseline activity. Spearman's correlation was used for the correlation between %MVC and PEFR. Results Pre-operatively, we observed the %MVC of TrAb (75.58%) to be the highest followed by RA (66.28%) and EO (62.12%). Post-operatively, all the muscles demonstrated increased activity wherein EO (84.33%) was most active on post-op day1, and for the rest of the days TrAb was the most active. However, as observed from Z-scores of all the three muscles the activity of EO was raised significantly from the baseline. No correlation was observed between %MVC and PEFR. Conclusion TrAb is the most active muscle that contributes to forced exhalation. Following an elective laparotomy, TrAb is no longer the most active muscle, rather it is the EO that primarily contributes to forced exhalation. This should be considered while providing post-operative respiratory care. However, more research is required in this area to better understand the role of expiratory muscle training for those undergoing elective laparotomies., Highlights • Transverse abdominis muscle contributes the most while forceful exhalation normally. • Coupling of the muscles exists during forced exhalation prior to abdominal surgery. • Abdominal surgery uncouples the abdominal muscles that sustains up to 7 days.

The surface electromyogram (sEMG) contains a wealth of motion information, which can reflect user's muscle motion intentions. The decoding based on sEMG has been widely used to provide a safe and effective human-computer interaction (HCI) method for neural prosthesis and exoskeleton robot control. The motor intention decoding based on low sampling frequency sEMG may promote the application of wearable low-cost EMG sensors in HCI. Therefore, a motor intention decoding scheme suitable for low frequency EMG signal is proposed in this paper, that is, transfer learning based on Alexnet. Moreover, the effects of different feature extraction methods and data augmentation with Gaussian white noise are fully analyzed. The proposed algorithm is evaluated with the NinaPro database 5. The highest accuracy can reach 70.4%±4.36% in 53 gestures identification of 10 subjects. Some classical machine learning algorithms such as support vector machine (SVM), linear discriminant analysis (LDA) and K Nearest Neighbor (KNN) are chosen to make comparison, where the SVM with Gaussian kernel function reaches to the maximum accuracy of 67.98%±4.56%. Two-way variance results show significant differences between each other. The experiment results show that the transfer learning is effective for decoding low-frequency sEMG for a large number of gestures.

The biological and pharmacological properties of natural polyphenols of the extract of Euterpe oleracea stone (EEOS) are associated with the central nervous system (CNS). To investigate the sedative and myorelaxant activity of EEOS in vivo, this study aimed to present the myorelaxant and sedative effects of EEOS in Wistar rats using spontaneous locomotor activity and motor electrophysiology. A total of 108 animals were used in the following experiments: a) behavioral tests (n = 27); b) electromyographic recordings of skeletal muscle (n = 27); c) respiratory muscle activity recordings (n = 27); d) cardiac muscle activity recordings (n = 27). The behavioral characteristics were measured according to the latency time of onset, the transient loss of posture reflex and maximum muscle relaxation. Electrodes were implanted in the gastrocnemius muscle and in the tenth intercostal space for electromyographic (EMG) signal capture to record muscle contraction, and in the D2 lead for electrocardiogram acquisition. After using the 300 mg/kg dose of EEOS intraperitoneally, a myorelaxant activity exhibited a lower frequency of contractility with an amplitude pattern of low and short duration at gastrocnemius muscle and intercostal muscle, which clearly describes a myorelaxant activity and changes in cardiac activity. The present report is so far the first study to demonstrate the myorelaxant activity of this extract, indicating an alternative route for acai stone valorization and its application in pharmaceutical fields.

In the study of muscle synergies during the maintenance of single-leg stance there are several methodological issues that must be taken into account before muscle synergy extraction. In particular, it is important to distinguish between epochs of surface electromyography (sEMG) signals corresponding to “ well-balanced ” and “ unbalanced ” single-leg stance, since different motor control strategies could be used to maintain balance. The aim of this work is to present and define a robust procedure to distinguish between “ well-balanced ” and “ unbalanced ” single-leg stance to be chosen as input for the algorithm used to extract muscle synergies. Our results demonstrate that the proposed approach for the selection of sEMG epochs relative to “ well-balanced ” and “ unbalanced ” single-leg stance is robust with respect to the selection of the segmentation threshold, revealing a high consistency in the number of muscle synergies and high similarity among the weight vectors (correlation values range from 0.75 to 0.97). Moreover, differences in terms of average recruitment levels and balance control strategies were detected, suggesting a slightly different modular organization between “ well-balanced ” and “ unbalanced ” single-leg stance. In conclusion, this approach can be successfully used as a pre-processing step before muscle synergy extraction, allowing for a better assessment of motor control strategies during the single-leg stance task.

In this paper we present the development and preliminary validation of a wearable system which is combined with an algorithm interfacing the MYO gesture armband with a Sphero BB-8 robotic device. The MYO armband is a wearable device which measures real-time EMG signals of the end user’s forearm muscles as the user is executing a set of upper limb gestures. These gestures are interpreted and transmitted to a computing hardware via a Bluetooth Low Energy IEEE 802.15.1 wireless protocol. The algorithm analyzes and sorts the data and sends a set of commands to the Sphero robotic device while performing navigation movements. After designing and integrating the software and hardware architecture, we have validated the system with two sets of trials involving a series of commands performed in multiple iterations. The consequent reactions of the robots, due to these commands, were recorded and the performance of the system was analyzed in a confusion matrix to obtain an average accuracy of the system outcome vs. the expected and desired actions. Results show that our integrated system can satisfactorily interface with the system in an intuitive way with an accuracy rating of 85.7 % and 92.9 % for the two tests, respectively. Doi: 10.28991/HIJ-2020-01-04-05 Full Text: PDF

The analysis of movement patterns through EMG activity provides the opportunity to identify the muscle groups most involved in a particular exercise, and to determine the scope of inter-limb deficiencies. The aim of the present study was to investigate the effects of a side-to-side muscle activity asymmetry between the left and the right lower limb during sprinting in soccer players. Sixteen professional soccer players took part in the study. Their age, body mass and body height equaled 23.7 ± 7.6 years, 81.2 ± 10.8 kg and 179.3 ± 12.2 cm, respectively. The sprint test consisted of two maximal sprints over 30 m with a 5-min rest interval between each sprint. EMG was recorded bilaterally from the quadriceps, hamstrings and gluteal muscles. Regression analysis revealed a significant effect of a side-to-side average muscle activity asymmetry between the left and right hamstring (LH/RH) muscles during the speed tests at 5 m (p = 0.044), and 30 m (p = 0.045), as well as the left and right glutes (LG/RG) at 5 m (p = 0.044) and 30 m (p = 0.043). Our results indicate that hamstring and glute muscles should be selectively and additionally activated during resistance training in soccer players to prevent injuries and improve sprint performance.

The aims of this study were to compare muscle activity of the anterior deltoid, medial deltoid, and posterior deltoid in the bench press, dumbbell fly, shoulder press, and lateral raise exercises. Thirteen men experienced in strength training volunteered for the study. Muscle activation was recorded during maximum isometric voluntary contraction (MVIC) for data normalization, and during one set of 12 repetitions with the load of 60% 1RM in all exercises proposed. One-way repeated-measures ANOVA with Bonferroni’s posthoc was applied using a 5% significance level. For anterior deltoid, the shoulder press (33.3% MVIC) presented a significantly higher level of activation when compared to other exercises. Also, no significant difference was found between the bench press (21.4% MVIC), lateral raise (21.2% MVIC), and dumbbell fly (18.8% MVIC). For the medial deltoid, the lateral raise (30.3% MVIC) and shoulder press (27.9% MVIC) presented a significantly higher level of activity than the bench press (5% MVIC) and dumbbell fly (3.4% MVIC). Besides, no significant difference was found between the bench press and the dumbbell fly. For the posterior deltoid, the lateral raise (24% MVIC) presented a significantly higher level of activation when compared to other exercises. For the posterior deltoid portion, the shoulder press (11.4% MVIC) was significantly more active than the bench press (3.5% MVIC) and dumbbell fly (2.5% MVIC). Moreover, no significant difference was found between the bench press and the dumbbell fly. In conclusion, the shoulder press and lateral raise exercises showed a higher level of muscle activation in the anterior deltoid and medial deltoid when compared to the bench press and dumbbell fly exercises.

The paper presents the research methodology and the analysis of the results of the comparison test of two methods of controlling the exoskeleton of the upper limb using signals of muscle activity and manual control devices. The results show the advantage of the joystick method over EMG in terms of usability, task execution time, ease of use and comfort.

We tested the hypothesis that static stretching, an acute, nonmetabolic fatiguing intervention, reduces exercise tolerance by increasing muscle activation and affecting muscle bioenergetics during cycling in the “severe” intensity domain. Ten active men (age, 24 ± 2 years; body mass, 74 ± 11 kg; height, 176 ± 8 cm) participated in identical constant-load cycling tests of equal intensity, of which 2 tests were carried out under control conditions and 2 were done after stretching. This resulted in a 5% reduction of maximal isokinetic sprinting power output. We measured (i) oxygen consumption, (ii) electromyography, (iii) deoxyhemoglobin, (iv) blood lactate concentration; (v) time to exhaustion, and (vi) perception of effort. Finally, oxygen consumption and deoxyhemoglobin kinetics were determined. Force reduction following stretching was accompanied by augmented muscle excitation at a given workload (p = 0.025) and a significant reduction in time to exhaustion (p = 0.002). The time to peak oxygen consumption was reduced by stretching (p = 0.034), suggesting an influence of the increased muscle excitation on the oxygen consumption kinetics. Moreover, stretching was associated with a mismatch between O2 delivery and utilization during the isokinetic exercise, increased perception of effort, and blood lactate concentration; these observations are all consistent with an increased contribution of the glycolytic energy system to sustain the same absolute intensity. These results suggest a link between exercise intolerance and the decreased ability to produce force. Novelty - We provided the first characterization of the effects of prolonged stretching on the metabolic response during severe cycling. - Stretching reduced maximal force and augmented muscle activation, which in turn increased the metabolic response to sustain exercise. Nous testons l’hypothèse selon laquelle l’étirement statique, qui est une intervention ponctuelle fatigante mais non métabolique, réduit la tolérance à l’exercice en augmentant l’activation musculaire et en influant sur la bioénergétique musculaire au cours d’un exercice de pédalage dans le domaine d’intensité « sévère ». Dix hommes actifs (24 ± 2 ans, 74 ± 11 kg, 176 ± 8 cm) participent à des tests de pédalage à intensité constante identique dont deux sont effectués dans des conditions de contrôle et deux après l’étirement, ce qui suscite une réduction de 5 % de la puissance maximale de sprint isocinétique. Nous mesurons : (i) la consommation d’oxygène, (ii) l’électromyogramme, (iii) la désoxyhémoglobine, (iv) la concentration sanguine de lactate, (v) le délai d’épuisement et (vi) la perception de l’effort. Enfin, la cinétique de la consommation d’oxygène et de la désoxyhémoglobine est évaluée. La réduction de la force après l’étirement est accompagnée d’une activation musculaire accrue à une charge de travail donnée (p = 0,025) et d’une réduction significative de délai d’épuisement (p = 0,002). Le délai jusqu’au pic de la consommation d’oxygène est réduit par l’étirement (p = 0,034), ce qui suggère une influence de l’augmentation de l’activation musculaire sur la cinétique de la consommation d’oxygène. De plus, l’étirement est associé à un décalage entre la livraison et l’utilisation d’O2 pendant l’exercice isocinétique, à un accroissement de la perception de l’effort et de la concentration sanguine de lactate; ces observations sont toutes compatibles avec une contribution accrue du système d’énergie glycolytique pour maintenir la même intensité absolue. Ces résultats suggèrent un lien entre l’intolérance à l’exercice et la diminution de la capacité à produire de la force. [Traduit par la Rédaction] Les nouveautés - Nous présentons la première caractérisation des effets d’un étirement prolongé sur la réponse métabolique lors de séances sévères de pédalage. - L’étirement a réduit la force maximale et augmenté l’activation musculaire, ce qui a augmenté la réponse métabolique pour soutenir l’exercice.

3D printing of soft EMG sensing structures enables the creation of personalized sensing structures that can be potentially integrated in prosthetic, assistive and other devices. We developed and characterized flexible carbon-black doped TPU-based sEMG sensing structures. The structures are directly 3D-printed without the need for an additional post-processing step using a low-cost, consumer grade multi-material FDM printer. A comparison between the gold standard Ag/AgCl gel electrodes and the 3D-printed EMG electrodes with a comparable contact area shows that there is no significant difference in the EMG signals&rsquo, amplitude. The sensors are capable of distinguishing a variable level of muscle activity of the biceps brachii. Furthermore, as a proof of principle, sEMG data of a 3D-printed 8-electrode band are analyzed using a patten recognition algorithm to recognize hand gestures. This work shows that 3D-printed sEMG electrodes have great potential in practical applications.

Introduction Peripheral neuropathy represents a spectrum of diseases with different etiologies. The most common causes are diabetes, exposure to toxic substances including alcohol and chemotherapeutics, immune-mediated conditions, and gene mutations. A thorough workup including clinical history and examination, nerve conduction studies, and comprehensive laboratory tests is warranted to identify treatable causes. First steps The variability of symptoms allows distinguishing characteristic clinical phenotypes of peripheral neuropathy that should be recognized in order to stratify the diagnostic workup accordingly. Nerve conduction studies are essential to determine the phenotype (axonal versus demyelinating) and severity. Laboratory tests, including genetic testing, CSF examination, nerve imaging, and nerve biopsy, represent additional clinical tests that can be useful in specific clinical scenarios. Comments We propose a flow chart based on five common basic clinical patterns of peripheral neuropathy. Based on these five clinical phenotypes, we suggest differential diagnostic pathways in order to establish the underlying cause. Conclusions The recognition of characteristic clinical phenotypes combined with nerve conduction studies allows pursuing subsequent diagnostic pathways that incorporate nerve conduction studies and additional diagnostic tests. This two-tiered approach promises higher yield and better cost-effectiveness in the diagnostic workup in patients with peripheral neuropathy.

In this paper, a new CNN architecture is introduced for classification of six different hand gestures using surface electromyography (EMG) data collected from the forearm. At first, two different deep neural networks produced based on Slow Fusion and Inception models separately. Then, the average of accuracy values and standard deviations were calculated for each type of network. The average accuracy was 80.88% and standard deviation was 0.030 for the Slow Fusion based network. For the Inception based network, average accuracy was 82.64% and standard deviation was 0.028. In addition to these two networks, a new CNN architecture is introduced using Slow fusion and Inception models in combination. The architecture has two parallel Inception modules in parallel. Each parallel module is fed by the half of the 3D feature map. The proposed model slowly fuses the information of the parallel modules throughout the network as in Slow-Fusion architecture. The average accuracy achieved with this model was 83.97% and the standard deviation was 0.027. Despite the small data set, the accuracy had increased with the proposed hybrid model. The smaller standard deviation indicates that it is less affected by variations in the training dataset. Our experimental results show that the proposed method gives the best results among the Slow Fusion based and Inception based models.

Background Mobile rehabilitation systems for patients with gait disorder are being developed. Safety functions to prevent patients from falling are considered during product development; however, few studies have been conducted on systems that have been prevalidated for healthy adults prior to application to patients. Objective This study analyzed the characteristics of lower extremity muscles and foot pressure in healthy adults during unbalanced walking with differences in the speed of left and right speed using a two-belt treadmill. Methods Twenty subjects performed gait motions with a difference in the weight support conditions (0% and 30%) and the left and right lower limb speeds (1-3 km/h). Each subject's muscular activities and foot pressure signals were collected. The gait patterns of the faster side exhibit similar characteristics to the paralyzed leg, and the slower side is similar to the non-paralyzed leg. Results Weight-supporting healthy subjects showed asymmetric gait patterns, similar to hemiplegic patients, because of the difference in the speed of the left and right side. Conclusions The quantitative results can be used to develop a training protocol for two-belt treadmills with differently controlled left and right speeds for gait rehabilitation in hemiplegic patients.

Objective Human research on the cremaster muscle (CM), cremasteric reflex (CMR) and genitofemoral nerve (GFN) and reports on their clinical applications using electrophysiological and histological techniques are rare. We aimed to present a detailed review of the human CM and CMR based on our earlier publications and relevant literature. Methods Electromyography (EMG) of the CM was recorded using disposable needle electrodes. CMR was obtained with tactile and/or electrical stimulation of the inner thigh. Transcranial magnetic stimulation (TMS) and magnetic stimulation of the upper lumbar roots were applied; GFN was stimulated using a surface electrode at the anterior superior iliac spine. Results CM striated fibers comprised multiple motor end plates. CM needle EMG results were similar to those of the limb muscles in chronic neurogenic disorders. TMS produced clear-cut evoked motor responses from CM. GFN motor conduction time to CM was absent or delayed in patients with inguinal hernia. EMG of CM was abnormal in 40% of patients with premature ejaculation. Conclusion CM is different from other skeletal muscles both morphologically and physiologically. Intersegmental sacrolumbar reflexes are useful for evaluating ejaculatory dysfunction. Significance CM is an important muscle for testis thermoregulation and sexual reflexes. Neurophysiological techniques are available for physiological and clinical studies., Scientific and Technological Research Council of Turkey (TUBITAK)Turkiye Bilimsel ve Teknolojik Arastirma Kurumu (TUBITAK) [SBAG 3119], The Scientific and Technological Research Council of Turkey (TUBITAK); Grant number: SBAG 3119.

Highlights • These guidelines provide orientation to perform clinical neurophysiological studies during COVID-19 pandemic. • Guide to perform protective procedures for healthcare personal doing clinical neurophysiological studies. • Offer a protocol for the disinfection of equipment and supplies in clinical neurophysiological studies., On 31st December 2019, China notified the World Health Organization of an outbreak of atypical pneumonia from patients at a local seafood market in Wuhan, Hubei, China, responsible for a new coronavirus called Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) that caused COVID-19 disease, which spread rapidly around the world. WHO declared a state of pandemic (11th March, 2020), which has caused more than 1 million infected and more than 110,000 deaths; it was observed that up to 29% of those infected were health care personnel. The main route of transmission of SARS-CoV2 is through respiratory secretions and direct contact with contaminated surfaces and material. The pandemic induced an international saturation of health care services and a rupture in the supply chain of protective equipment for healthcare personnel, which poses a high occupational risk to all. Based on the different healthcare systems, human resources, infrastructure and medical emergencies that will warrant the conduct of clinical neurophysiology studies and the lack of a guide for the management of the situation, it was decided by an expert task force of the Latin American Chapter of the International Federation of Clinical Neurophysiology to carry out these guidelines for the protection of patient and healthcare professionals conducting clinical neurophysiological studies.

Study Design: Narrative review. Objective: To summarize relevant studies regarding the utilization of intraoperative neurophysiological monitoring (IONM) techniques in spine surgery implemented in recent years. Methods: A literature search of the Medline database was performed. Relevant studies from all evidence levels have been included. Titles, abstracts, and reference lists of key articles were included. Results: Multimodal intraoperative neurophysiological monitoring (MIONM) has the advantage of compensating for the limitations of each individual technique and seems to be effective and accurate for detecting perioperative neurological injury during spine surgery. Conclusion: Although there are no prospective studies validating the efficacy of IONM, there is a growing body of evidence supporting its use during spinal surgery. However, the lack of validated protocols to manage intraoperative alerts highlights a critical knowledge gap. Future investigation should focus on developing treatment methodology, validating practice protocols, and synthesizing clinical guidelines.

The purpose of the present study was to examine acute changes in active muscle stiffness with and without the stretch reflex following static stretching. Before and after static stretching for 10 min, active muscle stiffness was measured according to changes in exerted torque and fascicle length during short-range stretch of faster (peak angular velocity of 250 deg·s-1; without the stretch reflex) and slower (peak angular velocity of 100 deg·s-1; with the stretch reflex) angular velocities. During the measurement of active muscle stiffness, the electromyographic activities of plantar flexor muscles were recorded and averaged over two different phases: just before (mEMGa) and after (mEMGb) stretch. In addition, the mEMGb/mEMGa ratio was used to evaluate the effects of stretch reflex. After 10 min of stretching, the mEMGb/mEMGa ratio tended to decrease under the 100 deg·s-1 condition, but not 250 deg·s-1. Under both conditions, active muscle stiffness did not change after 10 min of static stretching. In conclusion, the prolonged static stretching did not affect active muscle stiffness with or without the stretch reflex, but tended to decrease the stretch reflex. In addition, these results imply that active muscle stiffness measured during contractions was not influenced by the stretch reflex.

In this work, we show the success of unsupervised transfer learning between Electroencephalographic (brainwave) classification and Electromyographic (muscular wave) domains with both MLP and CNN methods. To achieve this, signals are measured from both the brain and forearm muscles and EMG data is gathered from a 4-class gesture classification experiment via the Myo Armband, and a 3-class mental state EEG dataset is acquired via the Muse EEG Headband. A hyperheuristic multi-objective evolutionary search method is used to find the best network hyperparameters. We then use this optimised topology of deep neural network to classify both EMG and EEG signals, attaining results of 84.76% and 62.37% accuracy, respectively. Next, when pre-trained weights from the EMG classification model are used for initial distribution rather than random weight initialisation for EEG classification, 93.82%(+29.95) accuracy is reached. When EEG pre-trained weights are used for initial weight distribution for EMG, 85.12% (+0.36) accuracy is achieved. When the EMG network attempts to classify EEG, it outperforms the EEG network even without any training (+30.25% to 82.39% at epoch 0), and similarly the EEG network attempting to classify EMG data outperforms the EMG network (+2.38% at epoch 0). All transfer networks achieve higher pre-training abilities, curves, and asymptotes, indicating that knowledge transfer is possible between the two signal domains. In a second experiment with CNN transfer learning, the same datasets are projected as 2D images and the same learning process is carried out. In the CNN experiment, EMG to EEG transfer learning is found to be successful but not vice-versa, although EEG to EMG transfer learning did exhibit a higher starting classification accuracy. The significance of this work is due to the successful transfer of ability between models trained on two different biological signal domains, reducing the need for building more computationally complex models in future research.

Köklü, Y, Köklü, Ö, Işıkdemir, E, and Alemdaroğlu, U. Effect of varying recovery duration on postactivation potentiation of explosive jump and short sprint in elite young soccer players. J Strength Cond Res 36(2): 534-539, 2022-The purpose of this study was to investigate the effects of postactivation potentiation (PAP) on vertical jump and sprint performances with different recovery durations. Twelve elite young soccer players (average age: 17.0 ± 0.6 years; body mass: 67.0 ± 5.4 kg; height: 175.0 ± 3.5 cm) voluntarily performed countermovement jump (CMJ) and 30-m sprints (with 10-m split times) under unloaded and 4 different recovery duration conditions (R1: 1 minute, R2: 2 minutes, R3: 3 minutes, and R4: 4 minutes) after a set of 3 repetitions of half-squat exercises at 90% of 1-repetition maximum. Electromyographic assessments of both limbs' vastus lateralis (VL) and semitendinosus (ST) muscle activity were also made during the tests. Vertical jump height, sprint time, and VL and ST muscle activity root mean square (RMS) values were analyzed. The results show that players demonstrated significantly better CMJ, 10-, and 30-m sprint performances in the R4 condition compared with the unloaded condition (p0.05). The players also showed significantly higher RMS values for VL and ST muscle activity in the CMJ and 30-m test performances for both legs in the R4 condition compared with the unloaded, R1, R2, and R3 conditions (p0.05). According to these results, if sports scientists and coaches desire to increase the PAP effect after heavy resistance training, 4 minutes of recovery time instead of 1, 2, or 3 minutes for CMJ, 10-, and 30-m sprint performances is recommended.

Diabetic neuropathy (DN) is the most common degenerative complication associated with Diabetes Mellitus. Despite widespread awareness about DN, the only effective treatments are blood glucose control and pain management. The aim of the current study was to determine the effect of intramuscular adipose-derived mesenchymal stem cell (AMSC) transplantation on sciatic nerves in DN using EMG and histological analyses. A total of 27 mice were randomly divided into three groups: control group, DN group and AMSC group. In EMG, CMAP amplitude in the sciatic nerves was lower, but distal latency was higher in the DN group compared with the control group. CMAP amplitude in the sciatic nerves was higher in the AMSC group compared with the DN group. Distal latency in the sciatic nerve was lower in the AMSC group compared with the DN group. Histologic examination of the tissues in the animals treated with AMSC showed a remarkable improvement in microscopic morphology. Fluorescence microscopy analyses demonstrated that intramuscularly transplanted AMSC was selectively localized in the sciatic nerves. Transplantation of AMSC increased protein expression of S100, cdk2, NGF and DHH, all of which, interfered with DN onset in sciatic nerves. The findings of the present study suggest that AMSC transplantation improved DN through a signal-regulatory effect on Schwann cells, neurotrophic actions and restoration of myelination., Ege University Faculty of Medicine Histology and Embryology Laboratories, Ege University Faculty of Medicine Histology and Embryology Laboratories.

Delivering health care at home emerged as a key advancement to reduce healthcare costs and infection risks, as during the SARS-Cov2 pandemic. In particular, in motor training applications, wearable and portable devices can be employed for movement recognition and monitoring of the associated brain signals. This is one of the contexts where it is essential to minimize the monitoring setup and the amount of data to collect, process, and share. In this paper, we address this challenge for a monitoring system that includes high-dimensional EEG and EMG data for the classification of a specific type of hand movement. We fuse EEG and EMG into the magnitude squared coherence (MSC) signal, from which we extracted features using different algorithms (one from the authors) to solve binary classification problems. Finally, we propose a mapping-and-aggregation strategy to increase the interpretability of the machine learning results. The proposed approach provides very low mis-classification errors ($$ < 0.1 ), with very few and stable MSC features ($$ < 10 % of the initial set of available features). Furthermore, we identified a common pattern across algorithms and classification problems, i.e., the activation of the centro-parietal brain areas and arm’s muscles in 8-80 Hz frequency band, in line with previous literature. Thus, this study represents a step forward to the minimization of a reliable EEG-EMG setup to enable gesture recognition.

Objective: This study aimed to examine the effect of fatigue on postural balance of young women using Electromyography (EMG) of lower extremity muscles and measuring the foot plantar Center of Pressure (COP) displacement. Methods: Participants were 10 young women (mean age, 26.4±3.01 years; mean weight, 65.5±5.75 kg; mean height, 165±2.61; BMI, 24.08±2.08 kg/m2) with no history of lower limb injury or balance problems. To evaluate their static balance, the stork test was used and the foot plantar COP was measured by force plates. To measure fatigue, three parameters of muscle power (P), median frequency of muscle (F) and Root Mean Square (RMS) of raw EMG signals were calculated. Data were analyze din SPSS V. 16 and MATLAB software using Mann-Whitney U test. Results: fatigue had a significant effect on P and RMS parameters (P

The unusual and tiring physical activity of bovine transrectal palpation (TRP) requires a novel approach to improve students’ TRP and pregnancy diagnosis (PD) skills. It has been shown that students who participated in an exercise program and students who had a grip strength (GS) of more than 30 kilograms performed better in bovine PDs. Participation in the exercise program increased students’ sensitivity (ability to identify pregnant cows) but did not increase total arm muscle strength. To identify which muscles are used during TRPs and to improve the exercise program, an electromyographic (EMG) analysis was used to identify muscle activation patterns and muscle activity levels during bovine TRPs. Eight subject matter experts (SMEs) each palpated two live cows and one Breed’n Betsy® rectal examination simulator while an EMG Triggered Stimulator recorded muscle activity. Muscle activation was higher for forearm muscles compared with all other examined muscle groups ( p < .001); was higher during retraction of the uterus and palpation of left and right uterine horn, compared with palpation of cervix, uterine body, left ovary, and right ovary ( p < .001); and showed an endurance pattern. Findings have been used to modify the previously developed exercise program in effort to improve students’ TRP and PD skills. The Bovine PD Improvement Exercise Program is available to students through an online application (http://icarus.up.ac.za/vetmlp/) and aims to not only improve GS and TRP accuracy but also stamina and well-being while adding fun to busy study schedules.

The complexity of concurrent cerebral processes underlying driving makes such human behavior one of the most studied real-world activities in neuroergonomics. Several attempts have been made to decode, both offline and online, cerebral activity during car driving with the ultimate goal to develop brain-based systems for assistive devices. Electroencephalography (EEG) is the cornerstone of these studies providing the highest temporal resolution to track those cerebral processes underlying overt behavior. Particularly when investigating real-world scenarios as driving, EEG is constrained by factors such as robustness, comfortability, and high data variability affecting the decoding performance. Hence, additional peripheral signals can be combined with EEG for increasing replicability and the overall performance of the brain-based action decoder. In this regard, hybrid systems have been proposed for the detection of braking and steering actions in driving scenarios to improve the predictive power of the single neurophysiological measurement. These recent results represent a proof of concept of the level of technological maturity. They may pave the way for increasing the predictive power of peripheral signals, such as electroculogram (EOG) and electromyography (EMG), collected in real-world scenarios when informed by EEG measurements, even if collected only offline in standard laboratory settings. The promising usability of such hybrid systems should be further investigated in other domains of neuroergonomics.

Introduction: Recent studies have examined the risk factors associated with lower limb injuries. This study aimed to explore the effect of 12 sessions of feedback corrective exercises on the kinematic indicators of the knee and the Electromyography Activity (EMG) of the muscles of the lower limbs of female wushu players. The present study has a quasi-experimental design with a pre-test/post-test design and a control group. Materials and Methods: In this study, 16 female wushu players were selected by the available sampling method and placed in two groups of exercise and control. The exercise group performed feedback correction exercises for 12 sessions. Before and after the knee varus exercises, we measured, pelvic drop, and EMG of the lower limb muscles of both groups in the SLS movement. The independent two-sample t-test was used to examine intergroup differences and the two-group correlated t-test was used to compare intra group sizes. To analyze the statistical data, SPSS V. 23 was used (P≤0.05) Results: The results showed a significant difference in knee varus between the experiment group and the control group in the pre-test and there was a significant difference between the pelvic drop in the pre-test and post-test of the experiment group compared with the control. The angle of the knee varus in the exercise group showed a significant difference with the control group. The EMG results of the muscles in the pre-test and post-test were significantly different. Conclusion: Based on the findings of the present study, the feedback correction exercise may improve motion control in wushu players. It also improved neuromuscular weakness in the subjects. According to the results and based on less muscle activity during movements, this exercise will reduce fatigue and the risk of injury.

Kinesio taping has been used to improve sensorimotor control performance. In this study, we explored the effect of Kinesio taping with different tensions on hand force control, joint proprioception, reaction time and brain activity. This was an observational study with a single-group, repeated-measures design. Twenty-four healthy participants (12 women) randomly assigned to three wrist/finger flexor taping conditions: (1) taping with 20% additional tension (taping20), (2) taping with neutral tension (tapingN), and (3) without taping (control). Grip force and wrist joint proprioceptive senses, reaction time, and force control performance were recorded in each of the taping conditions. An EEG of the bilateral sensorimotor cortex and an EMG of the right finger flexors were recorded to investigate changes in brain activity and functional connectivity between the brain and muscles (coherence). Our results indicated that taping significantly improved the joint position sense for participants with an error &gt, 3° (control vs. tapingN vs. taping20: 4.1° ± 1.04° vs. 2.6° ± 0.97° vs. 2.1° ± 0.91°, p = 0.001). In addition, Kinesio taping-induced improvements in force control were moderately correlated with decreases in the EEG beta band power. In conclusion, Kinesio taping could improve the joint proprioceptive sense, and taping-induced improvement in force control is likely due to neural desynchronization in motor cortex.

Human motion intention detection is an essential part of the control of upper-body exoskeletons. While surface electromyography (sEMG)-based systems may be able to provide anticipatory control, they typically require exact placement of the electrodes on the muscle bodies which limits the practical use and donning of the technology. In this study, we propose a novel physical interface for exoskeletons with integrated sEMG- and pressure sensors. The sensors are 3D-printed with flexible, conductive materials and allow multi-modal information to be obtained during operation. A K-Nearest Neighbours classifier is implemented in an off-line manner to detect reaching movements and lifting tasks that represent daily activities of industrial workers. The performance of the classifier is validated through repeated experiments and compared to a unimodal EMG-based classifier. The results indicate that excellent prediction performance can be obtained, even with a minimal amount of sEMG electrodes and without specific placement of the electrode.

Background The accurate temporal analysis of muscle activation is of great interest in many research areas, spanning from neurorobotic systems to the assessment of altered locomotion patterns in orthopedic and neurological patients and the monitoring of their motor rehabilitation. The performance of the existing muscle activity detectors is strongly affected by both the SNR of the surface electromyography (sEMG) signals and the set of features used to detect the activation intervals. This work aims at introducing and validating a powerful approach to detect muscle activation intervals from sEMG signals, based on long short-term memory (LSTM) recurrent neural networks. Methods First, the applicability of the proposed LSTM-based muscle activity detector (LSTM-MAD) is studied through simulated sEMG signals, comparing the LSTM-MAD performance against other two widely used approaches, i.e., the standard approach based on Teager–Kaiser Energy Operator (TKEO) and the traditional approach, used in clinical gait analysis, based on a double-threshold statistical detector (Stat). Second, the effect of the Signal-to-Noise Ratio (SNR) on the performance of the LSTM-MAD is assessed considering simulated signals with nine different SNR values. Finally, the newly introduced approach is validated on real sEMG signals, acquired during both physiological and pathological gait. Electromyography recordings from a total of 20 subjects (8 healthy individuals, 6 orthopedic patients, and 6 neurological patients) were included in the analysis. Results The proposed algorithm overcomes the main limitations of the other tested approaches and it works directly on sEMG signals, without the need for background-noise and SNR estimation (as in Stat). Results demonstrate that LSTM-MAD outperforms the other approaches, revealing higher values of F1-score (F1-score > 0.91) and Jaccard similarity index (Jaccard > 0.85), and lower values of onset/offset bias (average absolute bias Conclusions The presented approach LSTM-MAD revealed excellent performances against TKEO and Stat. The validation carried out both on simulated and real signals, considering normal as well as pathological motor function during locomotion, demonstrated that it can be considered a powerful tool in the accurate and effective recognition/distinction of muscle activity from background noise in sEMG signals.

Numerous studies indicated the physical benefits of regular exercise, but the neurophysiological mechanisms of regular exercise in elders were less investigated. We aimed to compare changes in brain activity during exercise in elderly people and in young adults with and without regular exercise habits. A total of 36 healthy young adults (M/F:18/18) and 35 healthy elderly adults (M/F:20/15) participated in this study. According to exercise habits, each age group were classified into regular and occasional exerciser groups. ECG, EEG, and EMG signals were recorded using V-AMP with a 1-kHz sampling rate. The participants were instructed to perform three 5-min bicycle rides with different exercise loads. The EEG spectral power of elders who exercised regularly revealed the strongest positive correlation with their exercise intensity by using Pearson correlation analysis. The results demonstrate that exercise-induced significant cortical activation in the elderly participants who exercised regularly, and most of the p-values are less than 0.001. No significant correlation was observed between spectral power and exercise intensity in the elders who exercised occasionally. The young participants who exercised regularly had greater cardiac and neurobiological efficiency. Our results may provide a new exercise therapy reference for adult groups with different exercise habits, especially for the elders.

In myo-control, for computational and setup constraints, the measurement of a high number of muscles is not always possible: the choice of the muscle set to use in a myo-control strategy depends on the desired application scope and a search for a reduced muscle set, tailored to the application, has never been performed. The identification of such set would involve finding the minimum set of muscles whose difference in terms of intention detection performance is not statistically significant when compared to the original set. Also, given the intrinsic sensitivity of muscle synergies to variations of EMG signals matrix, the reduced set should not alter synergies that come from the initial input, since they provide physiological information on motor coordination. The advantages of such reduced set, in a rehabilitation context, would be the reduction of the inputs processing time, the reduction of the setup bulk and a higher sensitivity to synergy changes after training, which can eventually lead to modifications of the ongoing therapy. In this work, the existence of a minimum muscle set, called optimal set, for an upper-limb myoelectric application, that preserves performance of motor activity prediction and the physiological meaning of synergies, has been investigated. Analyzing isometric contractions during planar reaching tasks, two types of optimal muscle sets were examined: a subject-specific one and a global one. The former relies on the subject-specific movement strategy, the latter is composed by the most recurrent muscles among subjects specific optimal sets and shared by all the subjects. Results confirmed that the muscle set can be reduced to achieve comparable hand force estimation performances. Moreover, two types of muscle synergies namely “Pose-Shared” (extracted from a single multi-arm-poses dataset) and “Pose-Related” (clustering pose-specific synergies), extracted from the global optimal muscle set, have shown a significant similarity with full-set related ones meaning a high consistency of the motor primitives. Pearson correlation coefficients assessed the similarity of each synergy. The discovering of dominant muscles by means of the optimization of both muscle set size and force estimation error may reveal a clue on the link between synergistic patterns and the force task.

ObjectiveSpinal muscular atrophy (SMA) is a motor neuron disease caused by low levels of survival motor neuron (SMN) protein. Prior work in models and patients has demonstrated electrophysiological and morphological defects at the neuromuscular junction (NMJ). Therapeutic development has resulted in clinically available therapies to increase SMN protein levels in patients and improve muscle function. Here we aimed to investigate the effect of SMN restoration (via nusinersen) on NMJ transmission in adults with SMA.MethodsParticipants undergoing nusinersen treatment underwent 3 Hz repetitive nerve stimulation (RNS) of the spinal accessory nerve to assess compound muscle action potential amplitude decrement. Maximum voluntary isometric contraction (MVICT), Revised Upper Limb Module (RULM), and 6 min walk test (6MWT) were assessed for correlations with decrement.ResultsData from 13 ambulatory (7 men/6 women, mean age 40±11 years) and 11 non-ambulatory (3 men/8 women, mean age 38±12 years) participants were analysed. Cross-sectional analyses of RNS decrement were similar at 14 months of nusinersen (−14.2%±11.5%, n=17) vs baseline (−11.9%±8.3%, n=15) (unpaired t-test, p=0.5202). Longitudinal comparison of decrement in eight participants showed no change at 14 months (−13.9%±6.7%) vs baseline (−16.9%±13.4%) (paired t-test, p=0.5863). Decrement showed strong correlations with measures of MVICT, RULM and 6MWT but not age or disease duration.ConclusionAdults with SMA had significant NMJ transmission defects that were not corrected with 14 months of nusinersen treatment. NMJ defects were negatively associated with physical function, and thus may represent a promising target for additive or combinatorial treatments.

Gait analysis applications in clinics are still uncommon, for three main reasons: (1) the considerable time needed to prepare the subject for the examination, (2) the lack of user-independent tools, (3) the large variability of muscle activation patterns observed in healthy and pathological subjects. Numerical indices quantifying the muscle coordination of a subject could enable clinicians to identify patterns that deviate from those of a reference population and to follow the progress of the subject after surgery or completing a rehabilitation program. In this work, we present two user-independent indices. First, a muscle-specific index (MFI) that quantifies the similarity of the activation pattern of a muscle of a specific subject with that of a reference population. Second, a global index (GFI) that provides a score of the overall activation of a muscle set. These two indices were tested on two groups of healthy and pathological children with encouraging results. Hence, the two indices will allow clinicians to assess the muscle activation, identifying muscles showing an abnormal activation pattern, and associate a functional score to every single muscle as well as to the entire muscle set. These opportunities could contribute to facilitating the diffusion of surface EMG analysis in clinics.

One major challenge limiting the use of dexterous robotic hand prostheses controlled via electromyography and pattern recognition relates to the important efforts required to train complex models from scratch. To overcome this problem, several studies in recent years proposed to use transfer learning, combining pre-trained models (obtained from prior subjects) with training sessions performed on a specific user. Although a few promising results were reported in the past, it was recently shown that the use of conventional transfer learning algorithms does not increase performance if proper hyperparameter optimization is performed on the standard approach that does not exploit transfer learning. The objective of this paper is to introduce novel analyses on this topic by using a random forest classifier without hyperparameter optimization and to extend them with experiments performed on data recorded from the same patient, but in different data acquisition sessions. Two domain adaptation techniques were tested on the random forest classifier, allowing us to conduct experiments on healthy subjects and amputees. Differently from several previous papers, our results show that there are no appreciable improvements in terms of accuracy, regardless of the transfer learning techniques tested. The lack of adaptive learning is also demonstrated for the first time in an intra-subject experimental setting when using as a source ten data acquisitions recorded from the same subject but on five different days.

Adopting telemonitoring services during the pandemic for people affected by chronic disease is fundamental to ensure access to health care services avoiding the risk of COVID-19 infection. Among chronic diseases, Amyotrophic Lateral Sclerosis (ALS), also known as Lou Gehrig’s disease, is a progressive neurodegenerative disease of adulthood, caused by the loss of spinal, bulbar and cortical motor neurons, which leads to paralysis of the voluntary muscles and, also, involves respiratory ones. Therefore, remote monitoring and teleconsulting are essential services for ALS patients with limited mobility, as the disease progresses, and for those living far from ALS centres and hospitals. In addition, the COVID 19 pandemic has increased the need to remotely provide the best care to patients, avoiding infection during ALS centre visits. The paper illustrates an innovative, secure medical monitoring and teleconsultation mobile cloud-based system for disabled people, such as those with ALS (Amyotrophic Lateral Sclerosis). The design aims to remotely monitor biosignals, such as ECG (electrocardiographic) and EMG (electromyographic) signals of ALS patients in order to prevent complications related to the pathology.

Due to a sedentary lifestyle, the amount of people suffering from musculoskeletal back diseases has increased over the last few decades. To monitor and cure these disabilities, sensors able to monitor the patient for long-term measurement during daily life and able to provide real-time feedback are required. There are only a few wearable systems that are capable to acquire muscle activity (sEMG) and posture at the same time. Moreover, previously reported systems do not target back sensor and typically comprise bulky uncomfortable solutions. In this paper, we present a new wearable sensor network that is designed to measure muscle activity and posture specialized for back measurement. Special care was taken to propose a discrete and comfortable solution. The prototype only measures 3.1 mm in thickness on the spine, making this sensor system the thinnest and lightest one in the literature to our best knowledge. After testing, it was shown that the sensor system is able to acquire two surface electromyography signals concurrently, to gather acceleration and rotation speed from the patient's lower back, and to transmit data to a computer or a smartphone via serial communication or Bluetooth low energy for a few hours for later processing and analysis. ispartof: SENSORS vol:21 issue:19 ispartof: location:Switzerland status: published

This work investigates elimination methods for cardiogenic artifacts in respiratory surface electromyographic (sEMG) signals and compares their performance with respect to subsequent fatigue detection with different fatigue algorithms. The analysis is based on artificially constructed test signals featuring a clearly defined expected fatigue level. Test signals are additively constructed with different proportions from sEMG and electrocardiographic (ECG) signals. Cardiogenic artifacts are eliminated by high-pass filtering (HP), template subtraction (TS), a newly introduced two-step approach (TSWD) consisting of template subtraction and a wavelet-based damping step and a pure wavelet-based damping (DSO). Each method is additionally combined with the exclusion of QRS segments (gating). Fatigue is subsequently quantified with mean frequency (MNF), spectral moments ratio of order five (SMR5) and fuzzy approximate entropy (fApEn). Different combinations of artifact elimination methods and fatigue detection algorithms are tested with respect to their ability to deliver invariant results despite increasing ECG contamination. Both DSO and TSWD artifact elimination methods displayed promising results regarding the intermediate, “cleaned” EMG signal. However, only the TSWD method enabled superior results in the subsequent fatigue detection across different levels of artifact contamination and evaluation criteria. SMR5 could be determined as the best fatigue detection algorithm. This study proposes a signal processing chain to determine neuromuscular fatigue despite the presence of cardiogenic artifacts. The results furthermore underline the importance of selecting a combination of algorithms that play well together to remove cardiogenic artifacts and to detect fatigue. This investigation provides guidance for clinical studies to select optimal signal processing to detect fatigue from respiratory sEMG signals.

International audience; Crosstalk is an important source of error in interpreting surface electromyography (EMG) signals. Here, we aimed at characterizing crosstalk for three groups of synergistic muscles by the identification of individual motor unit action potentials. Moreover, we explored whether spatial filtering (single and double differential) of the EMG signals influences the level of crosstalk. Three experiments were conducted. Participants (total twenty-five) performed isometric contractions at 10% of the maximal voluntary contraction (MVC) with digit muscles and knee extensors, and at 30% MVC with plantar flexors. High-density surface EMG signals were recorded and decomposed into motor unit spike trains. For each muscle, we quantified the crosstalk induced to neighboring muscles and the level of contamination by the nearby muscle activity. We also estimated the influence of crosstalk on the EMG power spectrum and intermuscular correlation. Most motor units (80%) generated significant crosstalk signals to neighboring muscle EMG in monopolar recording mode, but this proportion decreased with spatial filtering (50% and 42% for single and double differential, respectively). Crosstalk induced overestimations of intermuscular correlation and has a small effect on the EMG power spectrum, which indicates that crosstalk is not reduced with high-pass temporal filtering. Conversely, spatial filtering diminished the crosstalk magnitude and the overestimations of intermuscular correlation, confirming to be an effective and simple technique to reduce crosstalk. This paper presents a new method for the identification and quantification of crosstalk at the motor unit level and clarifies the influence of crosstalk on EMG interpretation for muscles with different anatomy.

Incremental and quantitative improvements of two-way interactions with e x tended realities (XR) are contributing toward a qualitative leap into a state of XR ecosystems being efficient, user-friendly, and widely adopted. However, there are multiple barriers on the way toward the omnipresence of XR; among them are the following: computational and power limitations of portable hardware, social acceptance of novel interaction protocols, and usability and efficiency of interfaces. In this article, we overview and analyse novel natural user interfaces based on sensing electrical bio-signals that can be leveraged to tackle the challenges of XR input interactions. Electroencephalography-based brain-machine interfaces that enable thought-only hands-free interaction, myoelectric input methods that track body gestures employing electromyography, and gaze-tracking electrooculography input interfaces are the examples of electrical bio-signal sensing technologies united under a collective concept of ExG. ExG signal acquisition modalities provide a way to interact with computing systems using natural intuitive actions enriching interactions with XR. This survey will provide a bottom-up overview starting from (i) underlying biological aspects and signal acquisition techniques, (ii) ExG hardware solutions, (iii) ExG-enabled applications, (iv) discussion on social acceptance of such applications and technologies, as well as (v) research challenges, application directions, and open problems; evidencing the benefits that ExG-based Natural User Interfaces inputs can introduce to the area of XR.