Falls due to disturbances are a common cause of serious cycling injuries, yet evaluation approaches to systematically evaluate interventions aimed at improving balance recovery are lacking. Current ex-post evaluations are hindered by sparse crash data, and existing ex-ante approaches often lack generalizability or rely on surrogate measures that are not validated against fall risk. This study introduces the Maximum Allowable Handlebar Disturbance (MAHD), a novel performance indicator that quantifies the largest handlebar disturbance a cyclist can recover from without falling. The MAHD captures the cyclist’s resilience to disturbances and provides a direct, interpretable measure of intervention effectiveness. We propose two methods for determining MAHD: (1) controlled treadmill experiments with induced handlebar disturbances and safe fall conditions and (2) simulations using bicycle dynamics and cyclist control models. Together, these methods allow quantitative ex-ante evaluation and systematic comparison of interventions targeting cyclist control, bicycle design, and infrastructure features such as curbs and road shoulders. With further validation, the MAHD offers practical value for researchers, engineers, and policymakers seeking to design safer bicycles, training programs, and road environments and improve evidence-based resource allocation. In the future, this could reduce fall-related cycling injuries.

Falls are a significant cause of injury among cyclists, highlighting the need for effective fall prevention interventions. However, ex-ante evaluation of such interventions remains challenging for engineers designing safer infrastructure and bicycles, as well as for safety professionals developing training programs. This study proposes the Maximum Allowable Handlebar Disturbance (MAHD) — the largest external handlebar disturbance a cyclist can recover from — as a performance indicator for evaluating fall prevention interventions. While bicycle dynamics and cyclist control models have the potential to determine this indicator and simulate interventions, their application is currently limited by a lack of validation in predicting the MAHD and the narrow range of interventions that can be incorporated into existing cyclist control models. To address these limitations, we conducted controlled experiments with 24 participants of varying ages and skill levels, exposing them to impulse-like handlebar disturbances that resulted in both recoveries and falls. This dataset, which includes recorded cyclist falls, supports future validation of bicycle dynamics and control models in predicting the MAHD. In addition, using Bayesian Model Averaging, we identified key cyclist factors influencing the MAHD, with forward speed and cyclist balancing skill being critical predictors. Incorporating these predictors into cyclist control models can substantially improve their practical application. These insights were then used to develop a Bayesian multilevel logistic regression model to predict the MAHD for different types of cyclists. Our findings improve the potential for bicycle dynamics and control models to proactively evaluate cyclist fall prevention methods, contributing to safer cycling environments.

Musculoskeletal (MSK) models offer a non-invasive way to understand biomechanical loads on joints and tendons, which are difficult to measure directly. Variations in muscle strength, especially relative differences between muscles, significantly impact model outcomes. Typically, scaled generic MSK models use maximum isometric forces that are not adjusted for different demographics, raising concerns about their accuracy. This review provides an overview on experimentally derived strength parameters, including physiological cross-sectional area (PCSA), muscle mass (Mm), and relative muscle mass (%Mm), which is the relative distribution of muscle mass across the leg. Limited lower extremity PCSA data prevented assessment of differences in PCSA distribution. We analysed differences by age and sex, and compared open-source lower limb MSK model parameters with experimental data from 57 studies. Our dataset, with records dating back to 1884, shows that uniformly increasing all maximum isometric forces in MSK models does not capture key age-and sex-related differences in muscle ratio. Males have a significantly higher proportion of muscle mass in the rectus femoris(12%) and semimembranosus(15%) muscles, while females have a greater relative muscle mass in the pelvic (gluteus maximus(17%) and medius(23%)) and ankle muscles (tibialis anterior(14%) and posterior(15%), and extensor digitorum longus(16%)). Older adults have a higher relative muscle mass in the gluteus medius(37%), while younger individuals show more in the gastrocnemius(31%). Current MSK models do not accurately represent muscle mass distribution for specific age or sex groups. None of them accurately reflect female muscle mass distribution. Further research is needed to explore musculotendon age- and sex differences.

Background: Amyotrophic lateral sclerosis (ALS) is a lethal progressive neurodegenerative disease characterized by upper motor neuron (UMN) and lower motor neuron (LMN) involvement. Their varying degree of involvement results in a clinical heterogenous picture, making clinical assessments of UMN signs in patients with ALS often challenging. We therefore explored whether instrumented assessment using robotic manipulation could potentially be a valuable tool to study signs of UMN involvement. Methods: We examined the dynamics of the wrist joint of 15 patients with ALS and 15 healthy controls using a Wristalyzer single-axis robotic manipulator and electromyography (EMG) recordings in the flexor and extensor muscles in the forearm. Multi-sinusoidal torque perturbations were applied, during which participants were asked to either relax, comply or resist. A neuromuscular model was used to study muscle viscoelasticity, e.g. stiffness (k) and viscosity (b), and reflexive properties, such as velocity, position and force feedback gains (kv, kp and kf, respectively) that dominated the responses. We further obtained clinical signs of LMN (muscle strength) and UMN (e.g. reflexes, spasticity) dysfunction, and evaluated their relation with the estimated neuromuscular model parameters. Results: Only force feedback gains (kf) were elevated in patients (p = 0.033) compared to controls. Higher kf, as well as the resulting reflexive torque (Tref), were both associated with more severe UMN dysfunction in the examined arm (p = 0.040 and p < 0.001). Patients with UMN symptoms in the examined arm had increased kf and Tref compared to controls (both p = 0.037). Neither of these measures was related to muscle strength, but muscle stiffness (k) was lower in weaker patients (p = 0.012). All these findings were obtained from the relaxed test. No differences were observed during the instructions comply and resist. Conclusions: This findings are proof-of-concept that instrumented assessment using robotic manipulation is a feasible technique in ALS, which may provide quantitative, operator-independent measures relating to UMN symptoms. Elevated force feedback gains, driving larger reflexive muscle torques, appear to be particularly indicative of clinically established levels of UMN dysfunction in the examined arm.

Autonomous robots are used to inspect, repair and maintain underwater assets. These tasks require energy-efficient robots, including efficient movement to extend available operational time. To examine the suitability of a propulsion system based on undulating fins, we built two robots with one and two fins, respectively, and conducted a parametric study for combinations of frequency, amplitude, wavenumber and fin shapes in free-swimming experiments, measuring steady-state swimming speed, power consumption and cost of transport. The following trends emerged for both robots. Swimming speed was more strongly affected by frequency than amplitude across the examined wavenumbers and fin heights. Power consumption was sensitive to frequency at low wavenumbers, and increasingly sensitive to amplitude at high wavenumbers. This increasing sensitivity of amplitude was more pronounced in tall rather than short fins. Cost of transport showed a complex relation with fin size and kinematics and changed drastically across the mapped parameter space. At equal fin kinematics as the single-finned robot, the double-finned robot swam slightly faster (>10%) with slightly lower power consumption (<20%) and cost of transport (<40%). Overall, the robots perform similarly to finned biological swimmers and other bio-inspired robots, but do not outperform robots with conventional propulsion systems.

In baseball pitchers the elbow is exposed to high and repetitive loads (i.e. external valgus torque), caused by pitching a high number of balls in a practice session or game. This can result in overuse injuries like the ulnar collateral ligament (UCL) injury. To understand injury mechanisms, the effect of repetitive pitching on the elbow load magnitude and variability was investigated. In addition, we explored whether repetitive pitching affects elbow muscle activation during pitching. Fifteen pitchers threw each 60 to 110 balls. The external valgus torque and electromyography of three elbow muscles were quantified during each pitch. Linear mixed model analyses were performed to investigate the effect of repetitive pitching. On a group level, the linear mixed models showed no significant associations of repetitive pitching with valgus torque magnitude and variability and elbow muscle activity. Significant differences exist between pitchers in their individual trajectories in elbow valgus torque and muscle activity with repetitive pitching. This shows the importance of individuality in relation to repetitive pitching. In order to achieve effective elbow injury prevention in baseball pitching, individual characteristics of changes in elbow load and muscle activity in relation to the development of UCL injuries should be investigated.

Individuals with an upper motor neuron syndrome, e.g., stroke survivors, may have a pathological increase of passive ankle stiffness due to spasticity, that impairs ankle function and activities such as walking. To improve mobility, walking aids such as ankle-foot orthoses and orthopaedic shoes are prescribed. However, these walking aids generally limit the range of motion (ROM) of the foot and may therewith negatively influence activities that require a larger ROM. Here we present a new ankle-foot orthosis 'Hermes', and its first experimental results from four hemiparetic chronic stroke patients. Hermes was designed to facilitate active ankle dorsiflexion by mechanically compensating the passive ankle stiffness using a negative-stiffness mechanism. Four levels of the Hermes' stiffness compensation (0%, 35%, 70% and 100%) were applied to evaluate active ROM in a robotic ankle manipulator and to test walking feasibility on an instrumented treadmill, in a single session. The robotic tests showed that Hermes successfully compensated the ankle joint stiffness in all four patients and improved the active dorsiflexion ROM in three patients. Three patients were able to walk with Hermes at one or more Hermes' stiffness compensation levels and without reducing their preferred walking speeds compared to those with their own walking aids. Despite a small sample size, the results show that Hermes holds great promise to support voluntary ankle function and to benefit walking and daily activities.

Human hands are complex biomechanical systems that allow for dexterous tasks with many degrees of freedom. Coordination of the fingers is essential for many activities of daily living and involves integrating sensory signals. During this sensory integration, the central nervous system deals with the uncertainty of sensory signals. When handling compliant objects, force and position are related. Interactions with stiff objects result in reduced position changes and increased force changes compared to compliant objects. Literature has shown sensory integration of force and position at the shoulder. Nevertheless, differences in sensory requirements between proximal and distal joints may lead to different proprioceptive representations, hence findings at proximal joints cannot be directly transferred to distal joints, such as the digits. Here, we investigate the sensory integration of force and position during pinching. A haptic manipulator rendered a virtual spring with adjustable stiffness between the index finger and the thumb. Participants had to blindly reproduce a force against the spring. In both visual reference trials and blind reproduction trials, the relation between pinch force and spring compression was constant. However, by covertly changing the spring characteristics in catch trials into an adjusted force-position relation, the participants’ weighting of force and position could be revealed. In agreement with previous studies on the shoulder, participants relied more on force sense in trials with higher stiffness. This study demonstrated stiffness-dependent sensory integration of force and position feedback during pinching.

Transcranial direct current stimulation (tDCS) is a promising tool to improve and speed up motor rehabilitation after stroke, but inconsistent clinical effects refrain tDCS from clinical implementation. Therefore, this study aimed to assess the need for individualized tDCS configurations in stroke, considering interindividual variability in brain anatomy and motor function representation. We simulated tDCS in individualized MRI-based finite element head models of 21 chronic stroke subjects and 10 healthy age-matched controls. An anatomy-based stimulation target, i.e. the motor hand knob, was identified with MRI, whereas a motor function-based stimulation target was identified with EEG. For each subject, we simulated conventional anodal tDCS electrode configurations and optimized electrode configurations to maximize stimulation strength within the anatomical and functional target. The normal component of the electric field was extracted and compared between subjects with stroke and healthy, age-matched controls, for both targets, during conventional and optimized tDCS. Electrical field strength was significantly lower, more variable and more frequently in opposite polarity for subjects with stroke compared to healthy age-matched subjects, both for the anatomical and functional target with conventional, i.e. non-individualized, electrode configurations. Optimized, i.e. individualized, electrode configurations increased the electrical field strength in the anatomical and functional target for subjects with stroke but did not reach the same levels as in healthy subjects. Considering individual brain structure and motor function is crucial for applying tDCS in subjects with stroke. Lack of individualized tDCS configurations in subjects with stroke results in lower electric fields in stimulation targets, which may partially explain the inconsistent clinical effects of tDCS in stroke trials.

Recent studies have established the presence of nociceptive steady-state evoked potentials (SSEPs), generated in response to thermal or intra-epidermal electric stimuli. This study explores cortical sources and generation mechanisms of nociceptive SSEPs in response to intra-epidermal electric stimuli. Our method was to stimulate healthy volunteers (n = 22, all men) with 100 intra-epidermal pulse sequences. Each sequence had a duration of 8.5 s, and consisted of pulses with a pulse rate between 20 and 200 Hz, which was frequency modulated with a multisine waveform of 3, 7 and 13 Hz (n = 10, 1 excluded) or 3 and 7 Hz (n = 12, 1 excluded). As a result, evoked potentials in response to stimulation onset and contralateral SSEPs at 3 and 7 Hz were observed. The SSEPs at 3 and 7 Hz had an average time delay of 137 ms and 143 ms respectively. The evoked potential in response to stimulation onset had a contralateral minimum (N1) at 115 ms and a central maximum (P2) at 300 ms. Sources for the multisine SSEP at 3 and 7 Hz were found through beamforming near the primary and secondary somatosensory cortex. Sources for the N1 were found near the primary and secondary somatosensory cortex. Sources for the N2-P2 were found near the supplementary motor area. Harmonic and intermodulation frequencies in the SSEP power spectrum remained below a detectable level and no evidence for nonlinearity of nociceptive processing, i.e. processing of peripheral firing rate into cortical evoked potentials, was found.

Background: Inertial measurement units (IMUs) offer the possibility to capture the lower body motions of players of outdoor team sports. However, various sources of error are present when using IMUs: the definition of the body frames, the soft tissue artefact (STA) and the orientation filter. Methods to minimize these errors are currently being used without knowing their exact influence on the various sources of errors. The goal of this study was to present a method to quantify each of the sources of error of an IMU separately. Methods: An optoelectronic system was used as a gold standard. Rigid marker clusters (RMCs) were designed to construct a rigid connection between the IMU and four markers. This allowed for the separate quantification of each of the sources of error. Ten subjects performed nine different football-specific movements, varying both in the type of movement, and in movement intensity. Results: The error of the definition of the body frames (11.3–18.7 deg RMSD), the STA (3.8–9.1 deg RMSD) and the error of the orientation filter (3.0–12.7 deg RMSD) were all quantified separately for each body segment. Conclusions: The error sources of IMU-based motion analysis were quantified separately. This allows future studies to quantify and optimize the effects of error reduction techniques.

Muscle force analysis can be essential for injury risk estimation and performance enhancement in sports like strength training. However, current methods to record muscle forces including electromyography or marker-based measurements combined with a musculoskeletal model are time-consuming and restrict the athlete's natural movement due to equipment attachment. Therefore, the feasibility and validity of a more applicable method, requiring only a single standard camera for the recordings, combined with a deep-learning model and musculoskeletal model is evaluated in the present study during upper-body strength exercises performed by five athletes. Comparison of muscle forces obtained by the single camera driven model against those obtained from a state-of-the art marker-based driven musculoskeletal model revealed strong to excellent correlations and reasonable RMSD's of 0.4–2.1% of the maximum force (Fmax) for prime movers, and weak to strong correlations with RMSD's of 0.4–0.7% Fmax for stabilizing and secondary muscles. In conclusion, a single camera deep-learning driven model is a feasible method for muscle force analysis in a strength training environment, and first validity results show reasonable accuracies, especially for prime mover muscle forces. However, it is evident that future research should investigate this method for a larger sample size and for multiple exercises.

PURPOSE: Neuromuscular fatigue is considered to be important in the etiology of hamstring strain injuries in football. Fatigue is assumed to lead to decreases in hamstring contractile strength and changes in sprinting kinematics, which would increase hamstring strain injury risk. Therefore, the aim was to examine the effects of football-specific fatigue on hamstring maximal voluntary torque (MVT) and rate of torque development (RTD), in relation to alterations in sprinting kinematics. METHODS: Ten amateur football players executed a 90-min running-based football match simulation. Before and after every 15 min of simulated play, MVT and RTD of the hamstrings were obtained in addition to the performance and lower body kinematics during a 20-m maximal sprint. Linear mixed models and repeated measurement correlations were used to assess changes over time and common within participant associations between hamstring contractile properties and peak knee extension during the final part of the swing phase, peak hip flexion, peak combined knee extension and hip flexion, and peak joint angular velocities, respectively. RESULTS: Hamstring MVT and sprint performance were significantly reduced by 7.5% and 14.3% at the end of the football match simulation. Unexpectedly, there were no indications for reductions in RTD when MVT decrease was considered. Decreases in hamstring MVT were significantly correlated to decreases in peak knee angle (R = 0.342) and to increases in the peak combined angle (R = -0.251). CONCLUSIONS: During a football match simulation, maximal voluntary isometric hamstring torque declines. This decline is related to greater peak knee extension and peak combined angle during sprint running, which indicates a reduced capacity of the hamstrings to decelerate the lower leg during sprint running with fatigue.