Search Results (5)

Background/Objectives: This study examined the effects of a six-week eccentric–reactive training program on neuromechanical markers of lateral explosiveness, asymmetry, and stretch-shortening cycle (SSC) efficiency in elite male youth table tennis players. Fourteen national-level athletes (mean age = 16.6 years) were assigned to either an experimental group (EG, n = 7) or a control group (CG, n = 7). EG performed flywheel squats and lateral depth jumps three times per week, while CG maintained regular training. Pre- and post-intervention testing included countermovement jumps, reactive strength index (RSI_DJ), force asymmetry, time-to-stabilization, SSC efficiency, and energy transfer ratio (ETR), measured via force plates, EMG, and inertial sensors. Methods: Multi-dimensional statistical analysis revealed coordinated improvements in explosive power and movement efficiency following eccentric training that were not visible when examining individual measures separately. Athletes in the training group showed enhanced neuromechanical control and developed more efficient movement patterns compared to controls. The analysis successfully identified distinct performance profiles and demonstrated that the training program improved explosive characteristics in elite table tennis players. Results: Univariate ANOVAs showed no significant Group × Time effects for RSI_DJ, ETR, or SSC_Eff, although RSI_DJ displayed a moderate effect size in EG (d = 0.47, 95% CI [0.12, 0.82], p = 0.043). In contrast, MANOVA confirmed a significant multivariate Group × Time interaction (p = 0.013), demonstrating integrated neuromechanical adaptations. Regression analysis indicated lower baseline CMJ and RSI_DJ predicted greater RSI improvements. Conclusions: In conclusion, eccentric–reactive training promoted multidimensional neuromechanical adaptations in elite racket sport athletes, supporting the use of integrated monitoring and targeted eccentric loading to enhance lateral explosiveness and efficiency. Full article

The functional status of the plantaris muscle (PM) remains controversial and is historically dismissed as vestigial; yet, it is increasingly recognized for its structural and clinical complexity. This narrative review synthesizes current evidence from embryological development, adult morphological studies, comparative mammalian anatomy, and clinical case reports to reassess the role of the PM in humans. Developmental data reveal that the PM is consistently present during fetal life, with tendon morphology and insertion patterns emerging early and resembling adult anatomical variants. Rather than indicating postnatal regression, it suggests a stable polymorphism rooted in prenatal development. Across mammalian species, the PM varies in presence and function, correlating with locomotor specialization from proprioception in primates to propulsion in carnivores, and absence in ungulates. In humans, high proprioceptive fiber density and anatomical variability support the hypothesis that the PM may be undergoing functional repurposing from a contractile to a sensorimotor role. Clinically, its relevance is evident in imaging interpretation, surgical tendon harvesting, and the pathophysiology of Achilles tendinopathy. Recent discoveries, including the identification of the plantaris ligamentous tendon (PLT), further underscore the complexity of this region and support the need to reassess its structural and clinical significance. We conclude that the PM should not be regarded as a regressing remnant but as a dynamically adapting structure with potential neuromechanical function. Future studies involving electromyography and neuroanatomical mapping are essential to elucidate its evolving role. Full article

The accurate, repeatable, and cost-effective quantitative characterization of mild traumatic brain injuries (mTBIs) is crucial for safeguarding the long-term health and performance of high-risk groups, including athletes, emergency responders, and military personnel. However, gaps remain in optimizing mTBI assessment methods, especially regarding the integration of neuromechanical metrics such as reaction time (RT) in predictive models. Background/Objectives: This review synthesizes existing research on the use of neuromechanical probabilistic models as tools for assessing mTBI, with an emphasis on RT’s role in predictive diagnostics. Methods: We examined 57 published studies on recent sensing technologies such as advanced electromyographic (EMG) systems that contribute data for probabilistic neural imaging, and we also consider measurement models for real-time RT tracking as a diagnostic measure. Results: The analysis identifies three primary contributions: (1) a comprehensive survey of probabilistic approaches for mTBI characterization based on RT, (2) a technical examination of these probabilistic algorithms in terms of reliability and clinical utility, and (3) a detailed outline of experimental requirements for using RT-based metrics in psychomotor tasks to advance mTBI diagnostics. Conclusions: This review provides insights into implementing RT-based neuromechanical metrics within experimental frameworks for mTBI diagnosis, suggesting that such metrics may enhance the sensitivity and utility of assessment and rehabilitation protocols. Further validation studies are recommended to refine RT-based probabilistic models for mTBI applications. Full article

Neuronal circuits in the spinal cord are essential for the control of locomotion. They integrate supraspinal commands and afferent feedback signals to produce coordinated rhythmic muscle activations necessary for stable locomotion. For several decades, computational modeling has complemented experimental studies by providing a mechanistic rationale for experimental observations and by deriving experimentally testable predictions. This symbiotic relationship between experimental and computational approaches has resulted in numerous fundamental insights. With recent advances in molecular and genetic methods, it has become possible to manipulate specific constituent elements of the spinal circuitry and relate them to locomotor behavior. This has led to computational modeling studies investigating mechanisms at the level of genetically defined neuronal populations and their interactions. We review literature on the spinal locomotor circuitry from a computational perspective. By reviewing examples leading up to and in the age of molecular genetics, we demonstrate the importance of computational modeling and its interactions with experiments. Moving forward, neuromechanical models with neuronal circuitry modeled at the level of genetically defined neuronal populations will be required to further unravel the mechanisms by which neuronal interactions lead to locomotor behavior. Full article

The purpose of this work is to better understand how animals control locomotion. This knowledge can then be applied to neuromechanical design to produce more capable and adaptable robot locomotion. To test hypotheses about animal motor control, we model animals and their nervous systems with dynamical simulations, which we call synthetic nervous systems (SNS). However, one major challenge is picking parameter values that produce the intended dynamics. This paper presents a design process that solves this problem without the need for global optimization. We test this method by selecting parameter values for SimRoach2, a dynamical model of a cockroach. Each leg joint is actuated by an antagonistic pair of Hill muscles. A distributed SNS was designed based on pathways known to exist in insects, as well as hypothetical pathways that produced insect-like motion. Each joint’s controller was designed to function as a proportional-integral (PI) feedback loop and tuned with numerical optimization. Once tuned, SimRoach2 walks through a simulated environment, with several cockroach-like features. A model with such reliable low-level performance is necessary to investigate more sophisticated locomotion patterns in the future. Full article