Optimizing shoulder elevation assist rate in exoskeletal rehabilitation based on muscular activity indices: a clinical feasibility study.

BACKGROUND: Restoring shoulder function is critical for upper-extremity rehabilitation following a stroke. The complex musculoskeletal anatomy of the shoulder presents a challenge for safely assisting elevation movements through robotic interventions. The level of shoulder elevation assistance in rehabilitation is often based on clinical judgment. There is no standardized method for deriving an optimal level of assistance, underscoring the importance of addressing abnormal movements during shoulder elevation, such as abnormal synergies and compensatory actions. This study aimed to investigate the effectiveness and safety of a newly developed shoulder elevation exoskeleton robot by applying a novel optimization technique derived from the muscle synergy index. METHODS: Twelve chronic stroke participants underwent an intervention consisting of 100 robot-assisted shoulder elevation exercises (10 × 10 times, approximately 40 min) for 10 days (4-5 times/week). The optimal robot assist rate was derived by detecting the change points using the co-contraction index, calculated from electromyogram (EMG) data obtained from the anterior deltoid and biceps brachii muscles during shoulder elevation at the initial evaluation. The primary outcomes were the Fugl-Meyer assessment-upper extremity (FMA-UE) shoulder/elbow/forearm score, kinematic outcomes (maximum angle of voluntary shoulder flexion and elbow flexion ratio during shoulder elevation), and shoulder pain outcomes (pain-free passive shoulder flexion range of motion [ROM] and visual analogue scale for pain severity during shoulder flexion). The effectiveness and safety of robotic therapy were examined using the Wilcoxon signed-rank sum test. RESULTS: All 12 patients completed the procedure without any adverse events. Two participants were excluded from the analysis because the EMG of the biceps brachii was not obtained. Ten participants (five men and five women; mean age: 57.0 [5.5] years; mean FMA-UE total score: 18.7 [10.5] points) showed significant improvement in the FMA-UE shoulder/elbow/forearm score, kinematic outcomes, and pain-free passive shoulder flexion ROM (P < 0.05). The shoulder pain outcomes remained unchanged or improved in all patients. CONCLUSIONS: The study presents a method for deriving the optimal robotic assist rate. Rehabilitation using a shoulder robot based on this derived optimal assist rate showed the possibility of safely improving the upper-extremity function in patients with severe stroke in the chronic phase.

Exploration of a machine learning approach for diagnosing sarcopenia among Chinese community-dwelling older adults using sEMG-based data.

BACKGROUND: In the practical application of sarcopenia screening, there is a need for faster, time-saving, and community-friendly detection methods. The primary purpose of this study was to perform sarcopenia screening in community-dwelling older adults and investigate whether surface electromyogram (sEMG) from hand grip could potentially be used to detect sarcopenia using machine learning (ML) methods with reasonable features extracted from sEMG signals. The secondary aim was to provide the interpretability of the obtained ML models using a novel feature importance estimation method. METHODS: A total of 158 community-dwelling older residents (≥ 60 years old) were recruited. After screening through the diagnostic criteria of the Asian Working Group for Sarcopenia in 2019 (AWGS 2019) and data quality check, participants were assigned to the healthy group (n = 45) and the sarcopenic group (n = 48). sEMG signals from six forearm muscles were recorded during the hand grip task at 20% maximal voluntary contraction (MVC) and 50% MVC. After filtering recorded signals, nine representative features were extracted, including six time-domain features plus three time-frequency domain features. Then, a voting classifier ensembled by a support vector machine (SVM), a random forest (RF), and a gradient boosting machine (GBM) was implemented to classify healthy versus sarcopenic participants. Finally, the SHapley Additive exPlanations (SHAP) method was utilized to investigate feature importance during classification. RESULTS: Seven out of the nine features exhibited statistically significant differences between healthy and sarcopenic participants in both 20% and 50% MVC tests. Using these features, the voting classifier achieved 80% sensitivity and 73% accuracy through a five-fold cross-validation. Such performance was better than each of the SVM, RF, and GBM models alone. Lastly, SHAP results revealed that the wavelength (WL) and the kurtosis of continuous wavelet transform coefficients (CWT_kurtosis) had the highest feature impact scores. CONCLUSION: This study proposed a method for community-based sarcopenia screening using sEMG signals of forearm muscles. Using a voting classifier with nine representative features, the accuracy exceeds 70% and the sensitivity exceeds 75%, indicating moderate classification performance. Interpretable results obtained from the SHAP model suggest that motor unit (MU) activation mode may be a key factor affecting sarcopenia.

Is sleep bruxism in obstructive sleep apnea only an oral health related problem?

BACKGROUND: The etiology of sleep bruxism in obstructive sleep apnea (OSA) patients is not yet fully clarified. This prospective clinical study aimed to investigate the connection between probable sleep bruxism, electromyographic muscle tone, and respiratory sleep patterns recorded during polysomnography. METHODS: 106 patients with OSA (74 males, 31 females, mean age: 56.1 ± 11.4 years) were divided into two groups (sleep bruxism: SB; no sleep bruxism: NSB). Probable SB were based on the AASM criteria: self-report of clenching/grinding, orofacial symptoms upon awakening, abnormal tooth wear and hypertrophy of the masseter muscle. Both groups underwent clinical examination for painful muscle symptoms aligned with Temporomandibular Disorders Diagnostic Criteria (DC/TMD), such as myalgia, myofascial pain, and headache attributed to temporomandibular disorder. Additionally, non-complaint positive muscle palpation and orofacial-related limitations (Jaw Functional Limited Scale-20: JFLS-20) were assessed. A one-night polysomnography with electromyographic masseter muscle tone (EMG) measurement was performed. Descriptive data, inter-group comparisons and multivariate logistic regression were calculated. RESULTS: OSA patients had a 37.1% prevalence of SB. EMG muscle tone (N1-N3, REM; P = 0.001) and the number of hypopneas (P = 0.042) were significantly higher in the sleep bruxism group. While measures like apnea-hypopnea-index (AHI), respiratory-disturbance-index (RDI), apnea index (AI), hypopnea-index (HI), number of arousals, and heart rate (1/min) were elevated in sleep bruxers, the differences were not statistically significant. There was no difference in sleep efficiency (SE; P = 0.403). Non-complaint masseter muscle palpation (61.5%; P = 0.015) and myalgia (41%; P = 0.010) were significant higher in SB patients. Multivariate logistic regression showed a significant contribution of EMG muscle tone and JFLS-20 to bruxism risk. CONCLUSION: Increased EMG muscle tone and orofacial limitations can predict sleep bruxism in OSA patients. Besides, SB patients suffer more from sleep disorder breathing. Thus, sleep bruxism seems to be not only an oral health related problem in obstructive apnea. Consequently, interdisciplinary interventions are crucial for effectively treating these patients. TRIAL REGISTRATION: The study was approved by the Ethics Committee of Philipps-University Marburg (reg. no. 13/22-2022) and registered at the "German Clinical Trial Register, DRKS" (DRKS0002959).

The role of electrodiagnosis in focal neuropathies.

Electrodiagnostic (EDX) testing plays an important role in confirming a mononeuropathy, localizing the site of nerve injury, defining the pathophysiology, and assessing the severity and prognosis. The combination of nerve conduction studies (NCS) and needle electromyography findings provides the necessary information to fully assess a nerve. The pattern of NCS abnormalities reflects the underlying pathophysiology, with focal slowing or conduction block in neuropraxic injuries and reduced amplitudes in axonotmetic injuries. Needle electromyography findings, including spontaneous activity and voluntary motor unit potential changes, complement the NCS findings and further characterize chronicity and degree of axon loss and reinnervation. EDX is used as an objective marker to follow the progression of a mononeuropathy over time.

Clinical and genetic characteristics of myotonia congenita in Chinese population.

Myotonia congenita (MC) is a rare hereditary muscle disease caused by variants in the CLCN1 gene. Currently, the correlation of phenotype-genotype is still uncertain between dominant-type Thomsen (TMC) and recessive-type Becker (BMC). The clinical data and auxiliary examinations of MC patients in our clinic were retrospectively collected. Electromyography was performed in 11 patients and available family members. Whole exome sequencing was conducted in all patients. The clinical and laboratory data of Chinese MC patients reported from June 2004 to December 2022 were reviewed. A total of 11 MC patients were included in the study, with a mean onset age of 12.64 ± 2.73 years. The main symptom was muscle stiffness of limbs. Warm-up phenomenon and percussion myotonia were found in all patients. Electromyogram revealed significant myotonic charges in all patients and two asymptomatic carriers, while muscle MRI and biopsy showed normal or nonspecific changes. Fourteen genetic variants including 6 novel variants were found in CLCN1. Ninety-eight Chinese patients were re-analyzed and re-summarized in this study. There were no significant differences in the demographic data, clinical characteristics, and laboratory findings between 52 TMC and 46 BMC patients. Among the 145 variants in CLCN1, some variants, including the most common variant c.892 G>A, could cause TMC in some families and BMC in others. This study expanded the clinical and genetic spectrum of Chinese patients with MC. It was difficult to distinguish between TMC and BMC only based on the clinical, laboratory, and genetic characteristics.

Effects of static exercises on hip muscle fatigue and knee wobble assessed by surface electromyography and inertial measurement unit data.

Hip muscle weakness can be a precursor to or a result of lower limb injuries. Assessment of hip muscle strength and muscle motor fatigue in the clinic is important for diagnosing and treating hip-related impairments. Muscle motor fatigue can be assessed with surface electromyography (sEMG), however sEMG requires specialized equipment and training. Inertial measurement units (IMUs) are wearable devices used to measure human motion, yet it remains unclear if they can be used as a low-cost alternative method to measure hip muscle fatigue. The goals of this work were to (1) identify which of five pre-selected exercises most consistently and effectively elicited muscle fatigue in the gluteus maximus, gluteus medius, and rectus femoris muscles and (2) determine the relationship between muscle fatigue using sEMG sensors and knee wobble using an IMU device. This work suggests that a wall sit and single leg knee raise activity fatigue the gluteus medius, gluteus maximus, and rectus femoris muscles most reliably (p < 0.05) and that the gluteus medius and gluteus maximus muscles were fatigued to a greater extent than the rectus femoris (p = 0.031 and p = 0.0023, respectively). Additionally, while acceleration data from a single IMU placed on the knee suggested that more knee wobble may be an indicator of muscle fatigue, this single IMU is not capable of reliably assessing fatigue level. These results suggest the wall sit activity could be used as simple, static exercise to elicit hip muscle fatigue in the clinic, and that assessment of knee wobble in addition to other IMU measures could potentially be used to infer muscle fatigue under controlled conditions. Future work examining the relationship between IMU data, muscle fatigue, and multi-limb dynamics should be explored to develop an accessible, low-cost, fast and standardized method to measure fatiguability of the hip muscles in the clinic.

Feasibility and safety of dual-console telesurgery with the KangDuo Surgical Robot-1500 System using fifth-generation and wired networks: an animal experiment and sea-spanning clinical study.

BACKGROUND: To evaluate the feasibility and safety of dual-console telesurgery with the new KangDuo system in an animal experiment and clinical study. METHODS: Six canine models were performed radical prostatectomy with dual-console KanDuo surgical robot-1500 (KD-SR-1500-RARP). The perioperative outcomes, physical and mental workload of the surgeon were collected. Physical workload was evaluated with surface electromyography. Mental workload was evaluated with NASA-TLX. After conducting animal experiments to verify safety of dual-console KD-SR-1500-RARP, we conducted the clinical trial using 5G and wired networks. RESULTS: In the animal experiment, all surgeries were performed successfully. The operative time was 80.2±32.1 min. The docking time was 2.4±0.5 min. The console time was 49.7±25.3 min. There were no perioperative complications or equipment related adverse events. All dogs can micturate after catheter removal at one week postoperatively. The mental workload was at a low level (a scale ranging from 0 to 60), which scored 15.7±6.9. Among the eight recorded muscles, the fatigue degree of the right radial flexor and left biceps was the highest two (iEMG, resection, 299.8±344 uV, 109.9±16.9 uV; suture, 849.4±1252.5 uV, 423.1±621.3 uV, respectively). In the clinical study, the console time was 136 min. The mean latency time was ≤200 ms. The data pocket loss was <1%. The operation was successfully completed without malfunctions occurring throughout the entire process. CONCLUSIONS: Dual-console telesurgery with the KD-SR-1500 system was shown to be feasible and safe in radical prostatectomy using 5G and wired networks.

Analysis of pelvic floor muscle electromyography parameters in women with or without sexual dysfunction.

Background To investigate the differences in pelvic floor muscle (PFM) electromyography (EMG) parameters between women with or without sexual dysfunction (FSD) and their correlations. Methods Women who voluntarily participated in a questionnaire-based survey on sexual function and underwent PFM EMG in Weifang People's Hospital during the period from March 2021 to December 2021 were retrospectively enrolled. The female sexual (dys)function was measured using the Female Sexual Function Index. Glazer PFM EMG was performed using a Melander instrument (MLD A2 Deluxe). The differences in PFM EMG parameters between women with or without FSD were compared, and the relationships between PFM EMG parameters and FSD were analysed using multiple linear regression models. Results A total of 305 women were enrolled, with 163 in the FSD group and 142 in the non-FSD group. Comparisons of PFM EMG parameters between these two groups revealed that the FSD group had significantly higher peak EMG amplitude during the phasic (flick) contractions and shorter recovery latency during the tonic contractions than the non-FSD group (both P P Conclusions The results of the pelvic floor EMG in this study suggest that the pelvic floor muscles of women with FSD may be more susceptible to fatigue, and may have poorer coordination of their pelvic floor muscles.

Preliminary Study on Effects of Neck Exoskeleton Structural Design in Patients With Amyotrophic Lateral Sclerosis.

Neck muscle weakness due to amyotrophic lateral sclerosis (ALS) can result in dropped head syndrome, adversely impacting the quality of life of those affected. Static neck collars are currently prescribed to hold the head in a fixed upright position. However, these braces are uncomfortable and do not allow any voluntary head-neck movements. By contrast, powered neck exoskeletons have the potential to enable head-neck movements. Our group has recently improved the mechanical structure of a state-of-the-art neck exoskeleton through a weighted optimization. To evaluate the effect of the structural changes, we conducted an experiment in which patients with ALS were asked to perform head-neck tracking tasks while using the two versions of the neck exoskeleton. We found that the neck muscle activation was significantly reduced when assisted by the structurally enhanced design compared to no assistance provided. The improved structure also improved kinematics tracking performance, allowing users to better achieve the desired head poses. In comparison, the previous design did not help reduce the muscle effort required to perform these tasks and even slightly worsened the kinematic tracking performance. It was also found that biomechanical benefits gained from using the structurally improved design were consistent across participants with both mild and severe neck weakness. Furthermore, we observed that participants preferred to use the powered neck exoskeletons to voluntarily move their heads and make eye contact during a conversation task rather than remain in a fixed upright position. Each of these findings highlights the importance of the structural design of neck exoskeletons in achieving desired biomechanical benefits and suggests that neck exoskeletons can be a viable method to improve the daily life of patients with ALS.

A multifaceted suite of metrics for comparative myoelectric prosthesis controller research.

Upper limb robotic (myoelectric) prostheses are technologically advanced, but challenging to use. In response, substantial research is being done to develop person-specific prosthesis controllers that can predict a user's intended movements. Most studies that test and compare new controllers rely on simple assessment measures such as task scores (e.g., number of objects moved across a barrier) or duration-based measures (e.g., overall task completion time). These assessment measures, however, fail to capture valuable details about: the quality of device arm movements; whether these movements match users' intentions; the timing of specific wrist and hand control functions; and users' opinions regarding overall device reliability and controller training requirements. In this work, we present a comprehensive and novel suite of myoelectric prosthesis control evaluation metrics that better facilitates analysis of device movement details-spanning measures of task performance, control characteristics, and user experience. As a case example of their use and research viability, we applied these metrics in real-time control experimentation. Here, eight participants without upper limb impairment compared device control offered by a deep learning-based controller (recurrent convolutional neural network-based classification with transfer learning, or RCNN-TL) to that of a commonly used controller (linear discriminant analysis, or LDA). The participants wore a simulated prosthesis and performed complex functional tasks across multiple limb positions. Analysis resulting from our suite of metrics identified 16 instances of a user-facing problem known as the "limb position effect". We determined that RCNN-TL performed the same as or significantly better than LDA in four such problem instances. We also confirmed that transfer learning can minimize user training burden. Overall, this study contributes a multifaceted new suite of control evaluation metrics, along with a guide to their application, for use in research and testing of myoelectric controllers today, and potentially for use in broader rehabilitation technologies of the future.

Reciprocal inhibition of the thigh muscles in humans: A study using transcutaneous spinal cord stimulation.

Evaluating reciprocal inhibition of the thigh muscles is important to investigate the neural circuits of locomotor behaviors. However, measurements of reciprocal inhibition of thigh muscles using spinal reflex, such as H-reflex, have never been systematically established owing to methodological limitations. The present study aimed to clarify the existence of reciprocal inhibition in the thigh muscles using transcutaneous spinal cord stimulation (tSCS). Twenty able-bodied male individuals were enrolled. We evoked spinal reflex from the biceps femoris muscle (BF) by tSCS on the lumber posterior root. We examined whether the tSCS-evoked BF reflex was reciprocally inhibited by the following conditionings: (1) single-pulse electrical stimulation on the femoral nerve innervating the rectus femoris muscle (RF) at various inter-stimulus intervals in the resting condition; (2) voluntary contraction of the RF; and (3) vibration stimulus on the RF. The BF reflex was significantly inhibited when the conditioning electrical stimulation was delivered at 10 and 20 ms prior to tSCS, during voluntary contraction of the RF, and during vibration on the RF. These data suggested a piece of evidence of the existence of reciprocal inhibition from the RF to the BF muscle in humans and highlighted the utility of methods for evaluating reciprocal inhibition of the thigh muscles using tSCS.

Machine learning-empowered sleep staging classification using multi-modality signals.

The goal is to enhance an automated sleep staging system's performance by leveraging the diverse signals captured through multi-modal polysomnography recordings. Three modalities of PSG signals, namely electroencephalogram (EEG), electrooculogram (EOG), and electromyogram (EMG), were considered to obtain the optimal fusions of the PSG signals, where 63 features were extracted. These include frequency-based, time-based, statistical-based, entropy-based, and non-linear-based features. We adopted the ReliefF (ReF) feature selection algorithms to find the suitable parts for each signal and superposition of PSG signals. Twelve top features were selected while correlated with the extracted feature sets' sleep stages. The selected features were fed into the AdaBoost with Random Forest (ADB + RF) classifier to validate the chosen segments and classify the sleep stages. This study's experiments were investigated by obtaining two testing schemes: epoch-wise testing and subject-wise testing. The suggested research was conducted using three publicly available datasets: ISRUC-Sleep subgroup1 (ISRUC-SG1), sleep-EDF(S-EDF), Physio bank CAP sleep database (PB-CAPSDB), and S-EDF-78 respectively. This work demonstrated that the proposed fusion strategy overestimates the common individual usage of PSG signals.

Combining enhanced spectral resolution of EMG and a deep learning approach for knee pathology diagnosis.

Knee osteoarthritis (OA) is a prevalent, debilitating joint condition primarily affecting the elderly. This investigation aims to develop an electromyography (EMG)-based method for diagnosing knee pathologies. EMG signals of the muscles surrounding the knee joint were examined and recorded. The principal components of the proposed method were preprocessing, high-order spectral analysis (HOSA), and diagnosis/recognition through deep learning. EMG signals from individuals with normal and OA knees while walking were extracted from a publicly available database. This examination focused on the quadriceps femoris, the medial gastrocnemius, the rectus femoris, the semitendinosus, and the vastus medialis. Filtration and rectification were utilized beforehand to eradicate noise and smooth EMG signals. Signals' higher-order spectra were analyzed with HOSA to obtain information about nonlinear interactions and phase coupling. Initially, the bicoherence representation of EMG signals was devised. The resulting images were fed into a deep-learning system for identification and analysis. A deep learning algorithm using adapted ResNet101 CNN model examined the images to determine whether the EMG signals were conventional or indicative of knee osteoarthritis. The validated test results demonstrated high accuracy and robust metrics, indicating that the proposed method is effective. The medial gastrocnemius (MG) muscle was able to distinguish Knee osteoarthritis (KOA) patients from normal with 96.3±1.7% accuracy and 0.994±0.008 AUC. MG has the highest prediction accuracy of KOA and can be used as the muscle of interest in future analysis. Despite the proposed method's superiority, some limitations still require special consideration and will be addressed in future research.

Electromyographic biofeedback training in a cerebral palsy patient undergoing pronator teres rerouting and brachioradialis to extensor carpi radialis brevis tendon transfer surgery: A case report.

Several surgical procedures are used to treat dynamic pronation position of the forearm and flexion deformity of the wrist in cerebral palsy. Postoperative results of pronator teres rerouting were explored, while specially designed postoperative physiotherapy and its outcomes were limited. Herein, we present a case in whom the outcomes of electromyographic biofeedback (EMG-BF) training were assessed after pronator teres rerouting and brachioradialis tendon to extensor carpi radialis brevis tendon transfer combined with derotation osteotomy. The peak value increased, while the resting value decreased for the muscles after the intervention. Range of motion, hand function, manual ability, functional independence, and quality of life levels were improved. In conclusion, EMG biofeedback training may have a positive effect on neuromuscular control of pronator teres and brachioradialis. Free use of the upper extremity and improved manual ability positively affect the activity and quality of life of the patients.

A comprehensive dataset on biomechanics and motor control during human walking with discrete mechanical perturbations.

Background: Humans have a remarkable capability to maintain balance while walking. There is, however, a lack of publicly available research data on reactive responses to destabilizing perturbations during gait. Methods: Here, we share a comprehensive dataset collected from 10 participants who experienced random perturbations while walking on an instrumented treadmill. Each participant performed six 5-min walking trials at a rate of 1.2 m/s, during which rapid belt speed perturbations could occur during the participant's stance phase. Each gait cycle had a 17% probability of being perturbed. The perturbations consisted of an increase of belt speed by 0.75 m/s, delivered with equal probability at 10%, 20%, 30%, 40%, 50%, 60%, 70%, or 80% of the stance phase. Data were recorded using motion capture with 25 markers, eight inertial measurement units (IMUs), and electromyography (EMG) from the tibialis anterior (TA), soleus (SOL), lateral gastrocnemius (LG), rectus femoris (RF), vastus lateralis (VL), vastus medialis (VM), biceps femoris (BF), and gluteus maximus (GM). The full protocol is described in detail. Results: We provide marker trajectories, force plate data, EMG data, and belt speed information for all trials and participants. IMU data is provided for most participants. This data can be useful for identifying neural feedback control in human gait, biologically inspired control systems for robots, and the development of clinical applications.

Context-informed incremental learning improves both the performance and resilience of myoelectric control.

Despite its rich history of success in controlling powered prostheses and emerging commercial interests in ubiquitous computing, myoelectric control continues to suffer from a lack of robustness. In particular, EMG-based systems often degrade over prolonged use resulting in tedious recalibration sessions, user frustration, and device abandonment. Unsupervised adaptation is one proposed solution that updates a model's parameters over time based on its own predictions during real-time use to maintain robustness without requiring additional user input or dedicated recalibration. However, these strategies can actually accelerate performance deterioration when they begin to classify (and thus adapt) incorrectly, defeating their own purpose. To overcome these limitations, we propose a novel adaptive learning strategy, Context-Informed Incremental Learning (CIIL), that leverages in situ context to better inform the prediction of pseudo-labels. In this work, we evaluate these CIIL strategies in an online target acquisition task for two use cases: (1) when there is a lack of training data and (2) when a drastic and enduring alteration in the input space has occurred. A total of 32 participants were evaluated across the two experiments. The results show that the CIIL strategies significantly outperform the current state-of-the-art unsupervised high-confidence adaptation and outperform models trained with the conventional screen-guided training approach, even after a 45-degree electrode shift (p < 0.05). Consequently, CIIL has substantial implications for the future of myoelectric control, potentially reducing the training burden while bolstering model robustness, and leading to improved real-time control.

Evaluation of functional interaction masseter and sternocleidomastoid muscles affected by TMJ dysfunction.

OBJECTIVE: Aim: To evaluate the functional connection and the bioelectrical state of the m.masseter and m. sternocleidomastoid using functional tests before and after treatment. PATIENTS AND METHODS: Materials and Methods: The sample consisted of 21 individuals with temporomandibular joint dysfunction. Examinations were carried out before and after treatment using repositioning splint therapy and in seated/standing positions. RESULTS: Results: M. masseter - p=0.072 before treatment and p=0.821 after treatment. Symmetry is also maintained after treatment. After treatment, a significant difference is noted at the level of significance p<0.001 for the right chewing muscle. In seated and standing positions before treatment did not reveal a statistically significant difference (p=0.07, p=0.143) and after (p=0.272, p=0.623).M. sternocleidomastoid- p<0.001 when comparing right and left sides. After treatment, there was no difference between the right and left sides (p=0.169). No statistical difference was found when assessing indicators separately for the right and left muscles in seated and standing positions (p=0.304, p=0.611, p=0.089, p=0.869). When comparing the bioelectric potentials of the right muscle before, after treatment, a statistically significant difference was found p=0.001. CONCLUSION: Conclusions: Biostatistical analysis of the indicators of bioelectrical activity of m. masseter and sternocleidomastoid indicates no changes in muscle microvolt indicators with changes in body position in patients. However, repositioning splint therapy is associated with reduced muscle tone in initially more spasmodic muscles. It is worth noting that the symmetry of interaction between muscles improves.

Neurologic Approach to Radiculopathy, Back Pain, and Neck Pain.

Back pain and neck pain are common in clinical practice, but significant challenges and pitfalls exist in their diagnosis, treatment, and management. From the neurologic standpoint, cervical radiculopathy and lumbosacral radiculopathy are characterized by neck pain or back pain accompanied by sensory and motor symptoms in an arm or leg. The basic neurologic examination is vital, but testing like electromyography and MRI is often needed especially in cases that fail conservative management. Oral medications, injection-based therapies, physical therapy, and surgical evaluation all have a place in the comprehensive neurologic management of back and neck pain and associated radiculopathy.

Bichectomy Surgery and EMG Masticatory Muscles Function in Adult Women: A Longitudinal Study.

AIM: This longitudinal study aimed to evaluate the electromyographic activity of the masseter and temporal muscles in adult women who underwent buccal fat removal. MATERIALS AND METHODS: The sample consisted of 20 healthy adult women with no temporomandibular dysfunction and normal occlusion, who were assessed before, 30, and 60 days after the surgery. The electromyographic signal of the masseter and temporal muscles was captured through mandibular tasks including rest, protrusion, right and left laterality, and maximum voluntary contraction with and without parafilm. The results obtained were tabulated and the Shapiro-Wilk normality test was performed, which indicated a normal distribution. Statistical analysis was performed using the repeated measures test (p < 0.05). RESULTS: Significant differences were observed between time periods in maximum voluntary contraction for the left masseter muscle (p = 0.006) and in maximum voluntary contraction with parafilm for the right temporal (p = 0.03) and left temporal (p = 0.03) muscles. CONCLUSION: Bichectomy surgery did not modify the electromyographic activity of the masseter and temporal muscles during the rest task but may have influenced variations in the electromyographic signal during different mandibular tasks after 60 days of surgery, suggesting compensatory adaptations and functional recovery. CLINICAL SIGNIFICANCE: Understanding the impact of buccal fat removal surgery on the stomatognathic system function provides insights into postoperative functional recovery and potential compensatory adaptations, guiding clinical management and rehabilitation strategies for patients undergoing such procedures. How to cite this article: Cardoso AHDLS, Palinkas M, Bettiol NB, et al. Bichectomy Surgery and EMG Masticatory Muscles Function in Adult Women: A Longitudinal Study. J Contemp Dent Pract 2024;25(3):207-212.