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Multiple myeloma (MM) patients complain of pain and stiffness limiting motility. To determine if patients can benefit from vertebroplasty, we assessed muscle activation and co-activation before and after surgery. Five patients with MM and five healthy controls performed sitting-to-standing and lifting tasks. Patients performed the task before and one month after surgery. Surface electromyography (sEMG) was recorded bilaterally over the erector spinae longissimus and rectus abdominis superior muscles to evaluate the trunk muscle activation and co-activation and their mean, maximum, and full width at half maximum were evaluated. Statistical analyses were performed to compare MM patients before and after the surgery, MM and healthy controls and to investigate any correlations between the muscle's parameters and the severity of pain in patients. The results reveal increased activations and co-activations after vertebroplasty as well as in comparison with healthy controls suggesting how MM patients try to control the trunk before and after vertebroplasty surgery. The findings confirm the beneficial effects of vertebral consolidation on the pain experienced by the patient, despite an overall increase in trunk muscle activation and co-activation. Therefore, it is important to provide patients with rehabilitation treatment early after surgery to facilitate the CNS to correctly stabilize the spine without overloading it with excessive co-activations.

Malocclusion during childhood may affect both morphology and masticatory function and could greatly affect the subsequent growth and development of the jaws and face. The purpose of this study was to evaluate the efficiency of surface electromyography in describing the effects of the rapid palatal expansion (RPE) on Masseter (M) and Temporalis Anterior (T) muscles' activity in 53 children with different types of malocclusion: bilateral posterior crossbite (BPcb), underdeveloped maxillary complex without crossbite (NOcb) and unilateral posterior crossbite on the right (UPCBr) and on the left (UPCBl). The muscular activities during chewing tasks were assessed bilaterally before and after RPE application and three months after removal. Both the envelope's peak (µV) and its occurrence (% of chewing task) were extracted from the surface electromyography signal. Our results showed the presence of statistically significant differences (p < 0.05) on temporomandibular joint muscles, across different assessments, in all the tested populations of subjects. Surface electromyography demonstrated a relationship between the correction of a maxillary transverse discrepancy and the restoration of a muscle's activation patterns comparable to healthy subjects for both T and M.

This work aims at estimating the musculoskeletal forces acting in the human lower extremity during locomotion on rough terrains. We employ computational models of the human neuro-musculoskeletal system that are informed by multi-modal movement data including foot-ground reaction forces, 3D marker trajectories and lower extremity electromyograms (EMG). Data were recorded from one healthy subject locomoting on rough grounds realized using foam rubber blocks of different heights. Blocks arrangement was randomized across all locomotion trials to prevent adaptation to specific ground morphology. Data were used to generate subject-specific models that matched an individual's anthropometry and force-generating capacity. EMGs enabled capturing subject- and ground-specific muscle activation patterns employed for walking on the rough grounds. This allowed integrating realistic activation patterns in the forward dynamic simulations of the musculoskeletal system. The ability to accurately predict the joint mechanical forces necessary to walk on different terrains have implications for our understanding of human movement but also for developing intuitive human machine interfaces for wearable exoskeletons or prosthetic limbs that can seamlessly adapt to different mechanical demands matching biological limb performance.

Background: Under water gait training (UT) has been proposed as an innovative rehabilitative strategy for the treatment of axial disorders in Parkinson Disease (PD) patients, in particular for balance and gait impairment. However, the basis for the improvement is unclear.Research Question: The aim of this study was to evaluate improvements in the muscular activation in the lower limbs in a cohort of PD patients after UT.Methods: Ten PD participants in the "off" state and 10 controls (mean ± standard deviation of age and BMI were respectively: 71 ± 6 years, 28 ± 3 kg/m2; 65.5 ± 7 years, 28 ± 3 kg/m2) were enrolled in the study. After signing informed consent, they walked barefoot at their preferred speed on a 10 m walkway, before and after UT. The electrical activity of four muscles were collected bilaterally by means of a surface electromyography system (sEMG), two force plates and a motion capture system. All signals were synchronized in time with the gait cycle. The sEMG activity of Rectus Femoris (RF), Tibialis Anterior (TA), Biceps Femoris (BF) and Gastrocnemius Lateralis (GL) were acquired. The average from each signal was used to extract the peak of the Envelope (PoE) and its occurrence with respect to the gait cycle (PoPE%). Time and space parameters were determined.Results: Our results showed that UT in PD patients improved the muscle's recruitment pattern towards normal. The PD patients POPE% was comparable with the one of the controls (TA: 20-35 %, 75-80 % of gait cycle; GL: 0-15 %, 25-45 %, 85-100 % of gait cycle) after UT on each muscle with the exception of BF. The muscle co-activation plots failed to show improvement in line with the muscle activation.Significance: These results suggest that the muscle activation improvement with UT in PD participants might be due to a reorganisation at the executive rather than at the command level. [ABSTRACT FROM AUTHOR]

Although model personalization is critical when assessing individuals with morphological or neurological abnormalities, or even non-disabled subjects, its translation into routine clinical settings is hampered by the cumbersomeness of experimental data acquisition and lack of resources, which are linked to high costs and long processing pipelines. Quantifying the impact of neglecting subject-specific information in simulations that aim to estimate muscle forces with surface electromyography informed modeling approaches, can address their potential in relevant clinical questions. The present study investigates how different methods to fine-tune subject-specific neuromuscular parameters, reducing the number of electromyography input data, could affect the estimation of the unmeasured excitations and the musculotendon forces. Three-dimensional motion analysis was performed on 8 non-disabled adult subjects and 13 electromyographic signals captured. Four neuromusculoskeletal models were created for 8 participants: a reference model driven by a large set of sEMG signals; two models informed by four electromyographic signals but calibrated in different fashions; a model based on static optimization. The electromyography-informed models better predicted experimental excitations, including the unmeasured ones. The model based on static optimization obtained less reliable predictions of the experimental data. When comparing the different reduced models, no major differences were observed, suggesting that the less complex model may suffice for predicting muscle forces with a small set of input in clinical gait analysis tasks. Quantitative model performance evaluation in different conditions provides an objective indication of which method yields the most accurate prediction when a small set of electromyographic recordings is available. • Neuromusculoskeletal modeling personalization using few electromyographic signals. • Four different neuromusculoskeletal models with different complexity were compared. • Objective model evaluation applicable when muscle excitation recordings are missing. [ABSTRACT FROM AUTHOR]

Neuro-musculoskeletal (NMS) modeling based on electromyographic (EMG) signals allows for a better understanding of the principles of human movement [1]. Through appropriate modeling software (CEINMS) it is possible to estimate the muscular forces and joint moments calibrated on the single individual. The possibility of having highly subject-specific models allows an improvement in the treatment of a great variety of neurodegenerative diseases and can be fundamental for the general understanding of the neuro-mechanics of human locomotion. Fifteen walking trials of four able body subjects (mean age = 60 ± 2.16, mean BMI = 26.66 ± 4.13) were acquired with a motion capture system (BTS, 60 Hz), synchronized with a force plate (Bertec, 960 Hz) and a 15 channels surface electromyography (sEMG) system (FreePocketEMG, 1000 Hz). The CAST protocol was adopted as marker set, while the following muscles were acquired: Gluteus Maximus, Gluteus Medius, Tensor Fasciae Latae, Sartorius, Adductor Longus, Rectus Femoris, Biceps Femoris, Semitendinosus, Vastus Lateralis, Vastus Medialis, Tibialis Anterior, Peroneus Longus, Gastrocnemius Lateralis, Gastrocnemius Medialis and Soleus. The data were processed in MatLab for the extraction of four muscle synergies by applying the 'Non-negative Matrix Factorization' method [2]. Then, 'Statistical Parametric Mapping' [3] and 'Cosine Similarity' were used as metrics to assign each synergy to the EMG signals of just one muscle for each different muscle groups (Ankle Plantar-flexors, Ankle Dorsi-flexors, Knee Extensors and Knee Flexors). Afterwards data were processed in OpenSim; scaling, inverse kinematics, inverse dynamics, muscle analysis were run. Finally, CEINMS was executed to calculate muscle activations and torques first by informing the model with a complete setup of experimental EMGs data then with a reduced setup (the foru EMGs that best matched with muscle synergies). Activation signals of the muscle-tendon units and the angular moments of the knee and ankle obtain from models developed by CEINMS were compared for different setup with the experimental EMG signals. Comparison was done for both different muscle setups for each subject. In Fig. 1a are shown the values of cosine similarities of the muscles able to better approximate each primitive for one subject. In Fig. 1b-e are displayed the pattern of primitives and the chosen experimental EMG signals for the same subject during one walking trial. The implemented methodology allowed the analysis of the muscular forces developed during walking with an acquisition protocol that includes a reduced number of EMG signals, and a sensitivity analysis for the adoption of NMS models based on a limited number of inputs was conducted. Results seem promising but a validation on a wider sample of subjects including pathological subjects is needed. [ABSTRACT FROM AUTHOR]

Motor impairments are one of the most disabling symptoms related to Parkinson's disease (PD) and negatively affect quality of life [1]. Recently aberrant motor control in this population was investigated by means of surface electromyography (sEMG) in terms of timing of muscle activation [2]. Yet, insights on the recruitment frequency during gait are still lacking. Therefore, this study aims to characterize muscle recruitment frequency in PD with respect to healthy controls during walking. Twenty-five people with PD (age = 64 ± 10 years; BMI =26±3) and ten able bodied subjects (age = 62±6 years; BMI =28±3) were included and underwent sEMG while walking on a 8 m walkaway at BiomovLab (University of Padova, Italy). Three bilateral strides per subject were considered (105 strides in total). Electrical activity of gastrocnemius lateralis (GL) was recorded. To identify onset and offset of the muscle activation, the wavelet-based algorithm presented in [3] was adopted. Then, each signal was digitized in accordance with the detected activation timing (0 = no activation detected, 1 = activation detected) and used to provide activation maps [4] for both the assessed populations. The following Fig. 1 reports the activation map of GL activation for PD and control populations in function of the number of subjects of the specific population where muscular activity is observed. Horizontal bars are grey-level coded, according to the number of subjects of the population where a GL activity is detected; black = activity detected in all subjects, white = activity never detected. PD population presents a very frequent GL activity (close to 100%) between 35% and 55% of the gait cycle, as expected. A relatively poor activity is detected in the other gait cycle phases. Although GL in PD is more frequently recruited in the same gait cycle phase of controls (≈ 70%), healthy subjects displayed more homogeneous GL activity over the whole gait cycle. These outcomes seem to suggest that PD patients are characterized by a reduced ability to adapt to gait-related needs compared to age- matched control subjects. [ABSTRACT FROM AUTHOR]

Gait disorders are one of the cardinal features of Parkinson's Disease (PD) and might be affected by a modified pattern of motor unit activation. This work explores how PD affects the lower limb muscle control and how muscle activity contributes to gait impairment. Using clinical gait analysis data, the onset and the offset of the surface electromyographic (sEMG) signal of four lower limb muscles were determined in 18 people with PD and compared with 10 heathy controls. Different motor patterns were identified in both the populations through a statistical detector algorithm and described in terms of linear envelope, local maxima activation magnitude and occurrence, co-contractions, and bursts duration. Statistical analysis was performed using statistical parametric mapping for the sEMG envelope and linear mixed effects models for the sEMG parameters. An equivalent number of sEMG patterns was detected in PD with respect to controls. Significant differences were highlighted between the two cohorts within the same activation modality. Plantarflexors muscles activation was delayed on time and had different durations and activations peaks, while Biceps Femoris revealed a higher local maximum. These results suggested that functional tibiotarsus joint reeducation coupled with postural rehabilitation might be beneficial for people with PD. [ABSTRACT FROM AUTHOR]