Search Results (155)

Fighting against gravity is a common challenge for all terrestrial animals, including most mammals. It means, in particular, avoiding falls to the ground while performing daily tasks, such as standing up, locomotion, or foraging for food. This means that balance control in humans involves a wide variety of contexts and balance paradigms, such as upright standing, hand standing, tightrope walking, ice-skater spinning, bicycling, whole-body gesturing, and fingertip stick balancing, among others. From the cybernetic point of view, the underlying control problem is to keep the CoP (Center of Pressure) and the CoM (Center of Mass) aligned dynamically on the common vertical axis, and this means that the variety of balance strategies can be reduced to two basic paradigms: the CoP strategy (the CoP is the control variable and the CoM is the controlled variable) and the CoM strategy (the CoM is simultaneously the control and the controlled variable). It is suggested that the two balance strategies are implemented by combining four basic control paradigms, as a function of the task and environmental conditions: • Opportunistic control: exploitation of a physical phenomenon as the gyroscopic effect. • Stiffness control: exploitation of the elastic properties of skeletal muscles. • Feedback control: measuring an incipient fall index and closing the loop in real time. In particular, it is shown that a phase-space-based formulation of intermittent feedback control can compensate for the destabilization effect of conventional continuous control due to the large feedback delay. • Feedforward control: exploitation of an internal body model to generate stable whole-body synergies in an anticipatory manner. Such control paradigms are illustrated by summarizing the results of experimental and simulated data. Full article

Background/Objectives: Industry 5.0 emphasizes the protection and empowerment of human workers. Passive wearables reduce physical strain, but the evaluation of their efficacy remains incomplete when based solely on kinematics or electromyographic (EMG) envelope amplitude, failing to capture the underlying neural “cost” or the compensatory strategies. This paper proposes a computational framework centered on muscle synergy analysis to bridge the gap between laboratory-grade neural assessment and real-world industrial applications. The goal is to move beyond simple biomechanical metrics toward a deeper understanding of neural coordination during device interaction. Methods: Given the practical limitations of high-density EMG in industrial settings, we propose a “streamlining” approach: laboratory-derived synergy models guide the understanding of neural processes and the selection of a minimal set of sensors capable of detecting maladaptive motor compensations and early signs of fatigue. Results: This approach allows for long-term monitoring without compromising natural movement. By decoupling neural strategies from kinematic output, “silent” risk situations can be identified even when movement appears correct but the neural coordination is altered by the passive device. This supports personalized ergonomic indices and predictive prevention protocols, transforming wearables from simple mechanical aids into intelligent, human-centric systems. Conclusions: This framework provides a roadmap for translating complex motor control theories into practical tools for the next generation of safe and sustainable manufacturing. Full article

Turning impairment is a major contributor to falls in Parkinson’s disease (PD), yet the mechanisms linking cortical dysfunction to altered motor behavior remain unclear. In particular, it is unknown whether disrupted cortical communication impairs turning by altering muscle coordination. This study investigates a novel mechanistic pathway: whether muscle synergy complexity mediates the relationship between cortical network connectivity and turning performance in PD. Specifically, electroencephalography (EEG) and electromyography (EMG) were recorded from 12 individuals with PD and 12 age-matched healthy controls during a 180° turning task. Directed cortical connectivity, muscle synergy complexity, and spatiotemporal turning performance were quantified. Mediation analysis was used to determine whether cortical influences on behavior operate indirectly through neuromuscular coordination. Compared to controls, individuals with PD performed slower turns with shorter stride lengths and reduced synergy complexity (p < 0.05), alongside altered frontal cortical connectivity (p < 0.05). Across participants, higher synergy complexity was associated with faster, longer strides (p < 0.04). Cortical connectivity strength strongly predicted synergy complexity (R² = 0.66, p < 0.001) and exerted a significant indirect effect on turning performance (β = 0.312; 95% CI [0.072, 0.605]; p = 0.008). In PD, reliance on this indirect pathway increased with disease severity and poorer turning ability (r > 0.57, p < 0.03). This work establishes how muscle synergy complexity significantly mediates the relationship between cortical connectivity and turning performance in PD. Our findings provide evidence of a cortical–neuromuscular–behavioral pathway underlying turning deficits, highlighting coordination as a key target for neurorehabilitation. Full article

Non-organic (muscle) weakness (NOw) is proposed as a distinct pathological entity characterized by maladaptive neuroplasticity (learning) affecting motor control. Functional deficits are most directly revealed through the manual muscle testing (MMT) break test, which uniquely exposes a muscle’s ability to adapt to increasing external load, potentially serving as an index of motor control integrity. We advance the “muscle-motor-movement PTSD” (mPTSD) model in which learning during pain or stress (trauma) yields chronic avoidance (inhibition) of the associated muscles. In a second stage, compensatory synergies develop, overriding attempts at hypertrophy-oriented training. This non-systematic, integrative review synthesizes clinical reports, learning theories, motor control and pain literature, and objective tests of force and movement over time during MMT. Predictive processing and reinforcement learning offer complementary accounts of how hyper-precise priors and passive avoidance may maintain NOw beyond functional recovery. Unexplained muscle weakness is found in non-specific musculoskeletal disorders and functional motor disorder (functional weakness), but may also contribute to other conditions, such as kinesiophobia. Effective alternative treatments for NOw may act by updating or erasing maladaptive motor learning by disrupting memory reconsolidation, allowing immediate restoration of function. Analogous to psychoneuroimmunology’s role in immune function, we propose “psychoneurokinesiology”, the study of how maladaptive learning affects movement. Full article

Background: Polysubstance use, particularly the combination of opioids and stimulants, represents a growing public health concern due to its high risk of severe multisystem complications and mortality. Here, we present a case illustrating the lethal synergy of opioid–stimulant co-use. Methods: A 37-year-old male with chronic Hepatitis C and documented polysubstance use reported recent use of fentanyl, cocaine, methamphetamine, and cannabis. He presented with generalized weakness, left lower limb pain, tense edema, and anuria. Clinical assessment included monitoring of vital signs, physical examination, capillary blood gas analysis, extended laboratory panels (muscle and cardiac enzymes, electrolytes, and coagulation parameters), urinalysis, and Doppler imaging. Management over five days included intravenous hydration, diuretics, urinary alkalinization, electrolyte correction, anticoagulation, metabolic and vitamin therapy, hemodialysis, and comprehensive supportive care. Results: Laboratory evaluation revealed massive rhabdomyolysis (peak CK 161,050 U/L), severe hyperkalemia (K⁺ 8.4 mmol/L), metabolic acidosis, acute kidney injury with oligoanuria, and left-sided deep vein thrombosis. Despite intensive multidisciplinary interventions, the patient’s repeated refusal of ongoing treatment critically contributed to a fatal outcome. Conclusions: This case underscores the high mortality risk associated with opioid–stimulant co-use and the crucial impact of treatment refusal. Clinicians and public health stakeholders should recognize the rapid progression of multisystem dysfunction in polysubstance users and prioritize early, aggressive interventions combined with patient engagement strategies to mitigate fatal outcomes. Full article

Surface electromyography (sEMG) provides a non-invasive measure of the neural drive transmitted from the central nervous system to muscles by capturing the spatiotemporal summation of motor unit action potentials at the skin surface, and is therefore widely used to study neuromuscular coordination during motor tasks. By reflecting neural drive transmitted from the central nervous system to peripheral muscles, sEMG provides valuable insights for investigating neuromuscular coordination during upper-limb motor tasks. Within the framework of modular motor control, muscle synergy analysis has been increasingly applied to characterize coordinated muscle activation patterns extracted from multi-channel sEMG recordings. In this study, sEMG signals were collected from twelve stroke patients and nine healthy subjects during robot-assisted upper-limb training, involving two movement trajectories (straight and rectangular) and multiple robot-assisted levels. Muscle synergies were extracted using non-negative matrix factorization (NMF). A synergy merging–splitting model, combined with a Functional Driving Ratio (FDR), was employed to characterize both the muscle synergy reorganization and the relative activation contributions of driving versus stabilizing muscle components in terms of motor control strategy. The results showed that healthy subjects maintained consistent muscle coordination patterns across different assistive levels, while making task-dependent adjustments to muscle activation to adapt to variations in movement trajectories. For stroke patients, higher functional status was correlated with more differentiated coordination patterns and relatively higher FDR values, suggesting greater reliance on task-relevant agonist muscles during movement execution. In contrast, lower-function patients exhibited less differentiated coordination patterns accompanied by reduced FDR values, indicating the increased involvement of stabilizing or antagonist muscles. This shift may reflect compensatory control strategies and the reduced efficiency of neuromuscular coordination during assisted upper-limb movements. These findings suggest that sEMG-based muscle synergy features and the FDR may provide quantitative, sensor-derived support for characterizing neuromuscular coordination during robot-assisted rehabilitation. Full article

The aims of this research were to characterize neuromuscular control features within the gait cycle in Parkinson’s disease (PD) from the perspectives of muscle synergies and cross-modal coupling and to propose a joint representation of the relationship between muscle activation patterns and kinematic dynamic outputs. PD participants (n = 19) were included. Lower-limb surface electromyography (EMG) and kinematic dynamic channels, including pelvic/hip, knee, and ankle angular acceleration, were collected during level-ground natural walking. EMG signals were first decomposed using non-negative matrix factorization (NMF) to extract muscle synergies, and the number of synergies was evaluated using reconstruction performance (R²). Multimodal matrix factorization (MMF) was then applied to jointly decompose the EMG and angular-acceleration channels, yielding a cross-modal synergy representation comprising a shared temporal structure (H) and modality-specific weight structures (W): non-negativity was imposed on EMG weights, whereas kinematic weights were allowed to take positive and negative values to encode directional contributions. Under the current task and muscle set, NMF achieved high EMG reconstruction performance with four synergies (R² = 0.882). The synergy weights showed an ankle-dominant pattern: tibialis anterior (TA) consistently carried high weights across multiple synergies, while lateral gastrocnemius (LG) and soleus (SOL) contributed prominently to another synergy. The synergy activation profiles exhibited phase-dependent fluctuations with multiple rises and falls across the gait cycle, suggesting that synergy output was primarily characterized by continuous modulation rather than single-peak recruitment. MMF further identified eight cross-modal synergies, simultaneously capturing the shared contributions of key muscle groups (e.g., RF, TA, and SOL) and pelvic/hip and knee/ankle angular-acceleration channels within the same decomposition framework and summarizing their descriptive co-variation through the shared temporal structure (H). Overall, A low-dimensional synergy analysis combining EMG-only NMF with cross-modal MMF enables simultaneous characterization of cohort-level modular organization of muscle activity during gait and its descriptive association with pelvis-to-lower-limb dynamic output. This joint framework provides a methodological basis for quantitatively describing gait-related modular organization and temporal modulation patterns in this PD cohort under natural level-ground walking and lays the groundwork for subsequent testing of associations between synergy features and gait phenotypes, clinical severity, and rehabilitation responses. Full article

Background: Reconstructing full muscle activation trajectories from sparse measurements is underdetermined: many activation patterns can explain similar joint moments, and purely mechanical inverse formulations can yield non-physiological solutions. Methods: We propose a synergy-informed, physics-constrained framework to reconstruct unmeasured muscle activations when only a subset of muscles is observed. A synergy reconstruction prior (SynRc) is obtained by identifying a synergy basis from proxy activations via non-negative matrix factorization (NMF) and estimating time-varying synergy excitations from measured channels. Unmeasured activations are then solved via bound-constrained multi-objective optimization that jointly minimizes (i) normalized joint-moment error between OpenSim forward-computed moments and inverse-dynamics moments and (ii) deviation from the SynRc prior, with an optional smoothness refinement stage. Results: Verification on synthetic OpenSim Arm26 (2-DOF) cases with known ground truth shows that $J_1$-dominant selections from the stage-I Pareto set reduce normalized joint-moment error from 0.154 (SynRc-only) to ≈0.138, at the cost of larger deviation from the synergy prior. These Pareto diagnostics expose identifiability and selection sensitivity under sparse measurements when ground truth is unavailable. Conclusions: The proposed framework makes mechanics–synergy trade-offs explicit and provides structured diagnostics and selection guidance for sparse-measurement scenarios. Full article

Background/Objectives: Bladder cancer remains a therapeutically challenging malignancy due to high recurrence rates, progression to muscle-invasive disease, and frequent resistance to cisplatin-based chemotherapy. Cold physical plasma (hereafter referred to as plasma) has emerged as a locally applicable modality that generates reactive oxygen species (ROS) and shows preclinical antitumor activity, offering a potential strategy to enhance cisplatin efficacy while enabling dose reduction. Here, we investigated combination treatment with cisplatin and argon plasma generated by the clinically approved kINPen jet in human bladder cancer models. Methods: Three bladder cancer cell lines representing distinct entities were used, namely the urothelial carcinoma lines RT-112 and T24, and the squamous cell carcinoma line SCaBER. IC₂₅ values for plasma and cisplatin monotherapy were established by resazurin assay and used to design combination regimens. Treatment interactions were quantified by coefficient of drug interaction (CDI) analysis and monitored kinetically by long-term live-cell imaging. Plasma-derived ROS were measured in PBS and DMEM, and their functional relevance was assessed in SCaBER cells using catalase and N-acetylcysteine. In ovo validation was performed in the tumor chorioallantoic membrane (TUM-CAM) model, where tumor mass, vascularization, cellular marker expression, and cytokine secretion were analyzed. Results: Plasma and cisplatin exhibited opposing monotherapy sensitivity profiles across cell lines, creating a favorable basis for combination treatment. CDI analysis revealed clear synergy in SCaBER at intermediate cisplatin concentrations, additive effects in RT-112, and additive to mildly synergistic effects in T24. ROS profiling and scavenger experiments identified hydrogen peroxide as a key mediator of plasma and plasma–cisplatin cytotoxicity in SCaBER. In the TUM-CAM model, plasma and cisplatin monotherapies showed notable antitumoral potential. At the same time, plasma–cisplatin combination therapy elicited only modest effects on tumor growth and vascularization compared to monotreatments but induced distinct, cell line-specific alterations in cytokine and marker expression. Conclusions: These findings demonstrate that plasma can potentiate cisplatin cytotoxicity in bladder cancer cells and reshape tumor-associated molecular signatures, supporting further optimization and preclinical evaluation of plasma–cisplatin combination therapy. Full article

Background: Nutritional interventions to mitigate age/disease-related skeletal muscle attrition are much needed given the growing older population. Beta-hydroxy beta-methylbutyrate (HMB), an endogenous metabolite of the essential amino acid leucine, has anabolic properties in skeletal muscle: acutely stimulating muscle protein synthesis and attenuating muscle protein breakdown. While the role of supplemental HMB on muscle protein turnover is established, mechanistic effects on the muscle transcriptome have not been examined. Methods: Total RNA was extracted from m. vastus lateralis muscle biopsies of young males (n = 14) before and ~2.5 h after oral consumption of ~3 g HMB. Global changes in the muscle transcriptome were assessed via RNA sequencing, and differential expression in genes between fasted and ‘fed’ (HMB) conditions was determined. To identify the functional biology of differentially expressed genes, gene set enrichment and active subnetwork-orientated enrichment analyses was performed. Results: Of 15,982 genes detected, 468 were significantly upregulated and 326 were significantly downregulated in response to HMB. These genes were found to be associated with molecular pathways regulating muscle protein turnover, most notably, JAK-STAT signalling (e.g., STAM), circadian rhythm (e.g., NR1D1, NR1D2, PER2, PER3), TNFα signalling (e.g., TNFRSF1A, CCL2, CXCL2), and protein synthesis (e.g., POLR1A, POLR2A, POLR3A, PIK3RR, SGK1). HMB also regulated the expression of AA transporters, evoking a robust increase in SLC36A1 (PAT1) and SLC7A5 (LAT1). Conclusions: HMB evokes transcriptional events important in the homeostasis of muscle, supporting a role in proteostasis and one akin to protein intake, i.e., upregulation of AA transporters. Future work should further define HMB’s transcriptomic/proteomic effects in ageing/disease and synergy with exercise. Full article

Background: This study aimed to explore the effects of neuromuscular electrical stimulation (NMES) combined with water-based resistance training on muscle activation and coordination during freestyle kicking. Methods: Thirty National Level male freestyle swimmers were randomly assigned to an experimental group (NMES + water-based training) or a control group (water-based training only) for a 12-week intervention. The experimental group received NMES pretreatment before each session. Underwater surface electromyography (sEMG) synchronized with high-speed video was used to collect muscle activation data and corresponding kinematic information during the freestyle kick. The sEMG signals were then processed using time-domain analysis, including integrated electromyography (iEMG), which reflects the cumulative electrical activity of muscles, and root mean square amplitude (RMS), which indicates the intensity of muscle activation. Non-negative matrix factorization (NMF) was further applied to extract and characterize muscle synergy patterns. Results: The experimental group showed significantly higher iEMG and RMS values in key muscles during both kicking phases. Within the core propulsion synergy, muscle weighting of vastus medialis and biceps femoris increased significantly, while activation duration of the postural adjustment synergy was shortened. The number of synergies showed no significant difference. Conclusions: NMES combined with water-based resistance training enhances muscle activation and optimizes neuromuscular coordination strategies, offering a novel approach to improving sport-specific performance. Full article

Background: Neuromuscular electrical stimulation (NMES) is an effective exogenous neuromuscular activation method widely used in sports training and rehabilitation. However, existing research primarily focuses on land-based sports or single-joint movements, with limited in-depth exploration of its intervention effects and underlying neuromuscular control mechanisms for complex, multi-joint coordinated aquatic activities like breaststroke swimming. This study aimed to investigate the effects of NMES combined with traditional resistance training on neuromuscular function during sport-specific technical movements in breaststroke athletes. Methods: A randomized controlled trial was conducted with 30 national-level or above breaststroke athletes assigned to either an experimental group (NMES combined with traditional squat resistance training) or a control group (traditional squat resistance training only) for an 8-week intervention. A specialized fully waterproof wireless electromyography (EMG) sensor system (Mini Wave Infinity Waterproof) was used to synchronously collect surface EMG signals from 10 lower limb and trunk muscles during actual swimming, combined with high-speed video for movement phase segmentation. Changes in lower limb explosive power were assessed using a force plate. Non-negative matrix factorization (NMF) muscle synergy analysis was employed to compare changes in muscle activation levels (iEMG, RMS) and synergy patterns (spatial structure, temporal activation coefficients) across different phases of the breaststroke kick before and after the intervention. Results: Compared to the control group, the experimental group demonstrated significantly greater improvements in single-leg jump height (Δ = 0.06 m vs. 0.03 m) and double-leg jump height (Δ = 0.07 m vs. 0.03 m). Time-domain EMG analysis revealed that the experimental group showed more significant increases in iEMG values for the adductor longus, adductor magnus, and gastrocnemius lateralis during the leg-retraction and leg-flipping phases (p < 0.05). During the pedal-clamp phase, the experimental group exhibited significantly reduced activation of the tibialis anterior alongside enhanced activation of the gastrocnemius. Muscle synergy analysis indicated that post-intervention, the experimental group showed a significant increase in the weighting of the vastus medialis and biceps femoris within synergy module 4 (SYN4, related to propulsion and posture) (p < 0.05), a significant increase in rectus abdominis weighting within synergy module 3 (SYN3, p = 0.033), and a significant shortening of the activation duration of synergy module 2 (SYN2, p = 0.007). Conclusions: NMES combined with traditional resistance training significantly enhances land-based explosive power in breaststroke athletes and specifically optimizes neuromuscular control strategies during the underwater breaststroke kick. This optimization is characterized by improved activation efficiency of key muscle groups, more economical coordination of antagonist muscles, and adaptive remodeling of inter-muscle synergy patterns in specific movement phases. This study provides novel evidence supporting the application of NMES in swimming-specific strength training, spanning from macroscopic performance to microscopic neural control. Full article

Hand exoskeletons are increasingly used to support post-stroke reach-to-grasp, yet most intention-detection strategies trigger assistance from local hand events without considering the synergy between proximal arm transport and distal hand shaping. We evaluated whether proximal arm kinematics, alone or fused with EMG, can predict flexor and extensor digitorum activity for synergy-aligned hand assistance. We trained nine models per participant: linear regression (LINEAR), feedforward neural network (NONLINEAR), and LSTM, each under EMG-only, kinematics-only (KIN), and EMG+KIN inputs. Performance was assessed by RMSE on test trials and by a synergy-retention analysis, comparing synergy weights from original EMG versus a hybrid EMG in which extensor and flexor digitorum measure signals were replaced by model predictions. Results have shown that kinematic information can predict muscle activity even with a simple linear model (average RMSE around 30% of signal amplitude peak during go-to-grasp contractions), and synergy analysis indicated high cosine similarity between original and hybrid synergy weights (on average 0.87 for the LINEAR model). Furthermore, the LINEAR model with kinematics input has been tested in a real-time go-to-grasp motion, developing a high-level control strategy for a hand exoskeleton, to better simulate post-stroke rehabilitation scenarios. These results suggest the intrinsic synergistic motion of go-to-grasp actions, offering a practical path, in hand rehabilitation contexts, for timing hand assistance in synergy with arm transport and with minimal setup burden. Full article

Leg dominance has been linked to an increased risk of lower-limb injuries in sports. This study examined bilateral asymmetry in muscle synergy patterns during one-leg stance on stable and multiaxial unstable surfaces. Twenty-five active young adults (25.6 ± 3.9 years) performed unipedal stance tasks on their dominant and non-dominant legs while surface electromyography (EMG) was recorded from seven lower-limb muscles per leg. Muscle synergies were extracted using non-negative matrix factorization (NMF), and structural similarity was assessed via cosine similarity with the Hungarian matching algorithm. Four consistent synergies were identified under both surface conditions, accounting for 88% of the total variance. On the stable surface, significant asymmetry in muscle weightings was observed in the rectus femoris (p = 0.030) for Synergy 1 and in the rectus femoris (p = 0.042), tibialis anterior (p = 0.024), peroneus longus (p = 0.023), and soleus (p = 0.006) for Synergy 2. On the unstable surface, asymmetry was evident in the biceps femoris (p = 0.048) for Synergy 2 and the rectus femoris (p = 0.045) for Synergy 3. Overall, dominance-related asymmetry was more pronounced under stable conditions and became more subtle as postural demand increased, revealing bilateral asymmetry in neuromuscular coordination during unipedal stance. Full article

Setting is a fundamental movement in volleyball. While there are several optimal interpreters of the role in professional play, there is a surprising lack of advanced measurement techniques for the evaluation of the movement from a biomechanical perspective. We proposed a comprehensive motion analysis protocol based on kinematics and motor coordination assessment (muscle synergies) for an in-depth analysis of the setting gesture. We also quantified the test–retest performance and discussed in detail the potential of the method. A single experienced player (age 27) tested and retested the protocol. The protocol was quite rapid to perform (about 30 min, including placement of kinematic and electromyography sensors on the patient’s body); we found high test and re-test consistency in different sessions within this participant (ICC > 0.90). These preliminary results suggest that the protocol could support the use of the state-of-the-art methods for motion analysis and biomechanics in volleyball and sports in general. Full article