Search Results (146)

The half-sitting posture is essential for many functional tasks performed by industrial workers. Thus, passive lower-limb exoskeletons, known as wearable chairs, are increasingly used to relieve lower-limb loading in such scenarios. However, although these devices lighten muscle effort during half-sitting tasks, they can disrupt walking mechanics and balance. Moreover, rigorous biomechanical data on joint moments and contact forces during walking with such a device remain scarce. Therefore, this study conducted a biomechanical evaluation of level walking with a wearable chair to quantify its effects on gait and joint loading. Participants performed walking experiments with and without the wearable chair. An optical motion capture system and force plates collected kinematic and ground reaction data. Six-axis force sensors measured contact forces and moments. These measurements were fed into a Newton–Euler inverse dynamics model to estimate lower-limb joint moments and assess joint loading. The contact measurements showed that nearly all rotational load was absorbed at the thigh attachment, while the ankle attachment served mainly as a positional guide with minimal moment transfer. The inverse dynamics analysis revealed that the wearable chair introduced unintended rotational stresses at lower-limb joints, potentially elevating musculoskeletal risk. This detailed biomechanical evidence underpins targeted design refinements to redistribute loads and better protect lower-limb joints. Full article

Background: Short-stem hip replacements are designed to provide improved load distribution and to mimic natural biomechanics. The interplay between implant design, positioning, and resulting bone biomechanics in individual patients remains underexplored, and the relationship between radiographically assessed bone remodeling around short stems and biomechanical predictions has not been previously reported. Methods: This study evaluated three short-stem hip implant designs: Proxima, Collo-MIS, and Minima. Postoperative bone remodeling patterns were analyzed, categorizing remodeling as bone gain, bone loss, or no observable activity, with changes tracked over time. Patient-specific biomechanical models were generated from 6-week postoperative radiographs. Finite element simulations incorporated body weight and gluteal muscle forces to estimate stress and strain distributions within the proximal femur. Strain energy was then applied to a mechanostat-based remodeling algorithm to predict bone remodeling patterns. These biomechanical predictions were compared to observed radiographic remodeling at 2 years post-surgery. A validated biomechanical model was further used to simulate different postoperative positions of the three types of stems. Results: No differences in bone remodeling patterns were observed among the three short-stem designs. Computational modeling demonstrated a statistically significant correlation between predicted remodeling and radiographic measurements at 2 years (p < 0.001). Proxima stems showed a tendency towards increased cortical bone loading under pronounced varus or valgus position in comparison to other two stems, although this observation requires further validation. Conclusions: This exploratory study demonstrates the feasibility of using biomechanical modeling to estimate bone remodeling around short-stem hip implants based on early postoperative radiographs. While the results are promising, they should be interpreted with caution due to the limited cohort size. The proposed modeling approach may offer clinical value in evaluating implant behavior and informing patient-specific treatment strategies. However, further research with larger populations is necessary to refine and validate these predictive tools. Full article

This paper proposes an adaptive human–robot concurrent control scheme that achieves the appropriate gait trajectory for a robotic leg prosthesis to improve the wearer’s comfort in various tasks. To accommodate different wearers, a neuromuscular-force-based impedance method was developed using muscle activation to reshape gait trajectory. To eliminate the use of sensors for torque measurement, a disturbance observer was established to estimate the interaction force between the human residual limb and the prosthetic receptacle. The cost function was combined with the interaction force and tracking errors of the joints. We aim to reduce the cost function by minimally changing the control weight of the gait trajectory generated by the Central Pattern Generator (CPG). The control scheme was primarily based on human-in-the-loop optimization to search for a suitable control weight to regenerate the appropriate gait trajectory. To handle the uncertainties and unknown coupling of the motors, an adaptive law was designed to estimate the unknown parameters of the system. Through a stability analysis, the control framework was verified by semi-globally uniformly ultimately bounded stability. Experimental results are discussed, and the effectiveness of the adaptive control framework is demonstrated. In Case 1, the mean error (MEAN) of the tracking performance was $3.6°$ and $3.3°$, respectively. And the minimized mean square errors (MSEs) of the tracking performance were $2.3°$ and $2.8°$, respectively. In Case 2, the mean error (MEAN) of the tracking performance is $2.7°$ and $3.1°$, respectively. And the minimized mean square errors (MSEs) of the tracking performance are $1.8°$ and $2.4°$, respectively. In Case 3, the mean errors (MEANs) of the tracking performance for subject1 and 2 are $2.4°$, $2.9°$, $3.4°$, and $2.2°$, $2.8°$, $3.1°$, respectively. The minimized mean square errors (MSEs) of the tracking performance for subject1 and 2 were $1.6°$, $2.3°$, $2.6°$, and $1.3°$, $1.7°$, $2.2°$, respectively. Full article

Monitoring forearm muscle contraction force in home-based rehabilitation remains challenging. Electromyography (EMG), as a standard technique, is considered impractical and complex for independent use by patients at home, which poses a risk of device misattachment and inaccurate recorded data. Considering the muscle-related modality, several studies have demonstrated an excellent correlation between stretch sensors and EMG, which provides significant potential for addressing the monitoring issue at home. Additionally, due to its flexible nature, it can be attached to the finger, which facilitates the logging of the kinematic mechanisms of a finger. This study proposes a method for estimating forearm muscle contraction in a cylinder grasping environment during home-based rehabilitation using a stretch-sensor glove. This study employed support vector machine (SVM), multi-layer perceptron (MLP), and random forest (RF) to construct the estimation model. The root mean square (RMS) of the EMG signal, representing the muscle contraction force, was collected from 10 participants as the target learning for the stretch-sensor glove. This study constructed an experimental design based on a home-based therapy protocol known as the graded repetitive arm supplementary program (GRASP). Six cylinders with varying diameters and weights were employed as the grasping object. The results demonstrated that the RF model achieved the lowest root mean square error (RMSE) score, which differed significantly from the SVM and MLP models. The time series waveform comparison revealed that the RF model yields a similar estimation output to the ground truth, which incorporates the contraction–relaxation phases and the muscle’s contraction force. Additionally, despite the subjectivity of the participants’ grasping power, the RF model could produce similar trends in the muscle contraction forces of several participants. Utilizing a stretch-sensor glove, the proposed method demonstrated great potential as an alternative modality for monitoring forearm muscle contraction force, thereby improving the practicality for patients to self-implement home-based rehabilitation. Full article

Climbing demands exceptional isometric finger flexor strength and neuromuscular efficiency. This study aimed to compare maximum isometric strength and muscle quality (MQ) between climbers and non-climbers and examine the influence of sex and specific grip types. Methods: 33 climbers (14 women) and 29 non-climbers (15 women) volunteered in this study. Maximum isometric strength was measured for handgrip, three-finger drag, and half-crimp grips, while forearm muscle mass was estimated using DXA. MQ was calculated as the ratio of peak isometric force to forearm muscle mass. Results: Climbers demonstrated significantly higher isometric strength in both the three-finger drag and half-crimp grips compared to non-climbers (p < 0.01); however, non-significant differences were observed in handgrip strength. Despite similar forearm muscle mass, climbers exhibited greater MQ. Notably, female non-climbers showed higher MQ than their male counterparts (p < 0.05), a sex difference that was not evident among climbers. All tests exhibited high repeatability (ICC > 0.93, CV < 5.81%) with low SEM and MDC95 values. Conclusions: The findings underscore the necessity of employing climbing-specific strength assessments to capture the unique neuromuscular adaptations induced by climbing training. Muscle quality emerges as a sex-neutral biomarker for strength performance evaluation, with potential applications in the optimization of training programs. Future research should further explore the predictive value of MQ and strive for standardized testing protocols. Full article

The purpose of this study was to determine the power produced by knee muscles in normal adults when performing self-selected walking. The power of a single knee muscle is not directly measurable without invasive methods. An EMG-to-force processing (EFP) model was developed, which scaled muscle–tendon unit (MTU) power output to gait EMG. Positive power by each muscle occurred when force was developed during concentric contractions, and negative power occurred with lengthening contractions. The sum of EFP power produced by knee muscles was compared with the kinematics plus kinetics (KIN) knee power at percent gait cycle intervals. Closeness-of-fit of the EFP and KIN power curves (during active muscle forces) was used to validate the model. Key findings were that most knee muscles have a characteristic eccentric-then-concentric contraction pattern, and greatest power was produced by the Semimembranosis, with peak magnitude nearly matched by two vastus muscles (VL, VMO). The EMG-to-force processing approach provides reasonable estimates of active individual knee muscle power in self-selected speed walking in neurologically intact adults. Further, a prolonged period of the gait cycle showed substantial knee flexion or extension in the absence of power produced by muscles acting at the knee. Full article

This study aims to develop and evaluate a cycling-specific marker protocol that minimises the number of markers while accounting for the unique biomechanics of cycling. Although movements in the frontal and transverse planes during cycling are limited, they are clinically relevant due to their association with overuse injuries. Existing gait-based marker protocols often fail to consider cycling-specific factors such as posture, range of motion, marker occlusion, and muscle-induced artifacts. The proposed protocol (PP) uses 15 physical and 8 virtual markers. In the absence of a gold standard for 3D pedalling kinematics, the PP was evaluated by comparing it with established gait analysis protocols. The protocol demonstrated high correlation in gait (CCC > 0.98 for hip and knee in the sagittal plane), low intra-subject variability (CV < 15% for hip, knee, and ankle), and high repeatability. During pedalling, position, velocity, and acceleration were measured in all three spatial directions. Notably, angular velocity and linear acceleration showed significant components outside the sagittal plane, particularly for angular velocity. These findings highlight the importance of considering 3D motion when estimating forces, joint moments, and joint-specific powers in cycling biomechanics. Full article

Objectives: Soccer is the most practiced sport around the world. The injury incidence has an estimated rate of up to 70 injuries per 1000 h of play. FIFA 11+ is a program designed to prevent injuries and optimize performance. The purpose of this study was to analyze the acute effects of this program as a warm-up on different functional, physiological, and mechanical properties of various knee tissues and whether there were differences between genders. Methods: The sample included 45 recreational soccer players. Several muscular and tendon mechanical properties, muscular oxygen saturation, electromyography, maximum voluntary contraction, and rate of force development were analyzed, before and after performing the FIFA 11+. Results: Only a moderate significant increase in muscle oxygen saturation in men from pre- to post-test was reported. No other parameters showed statistically significant differences between groups, suggesting that the intervention may lack clinical relevance. The reported effect sizes were mostly trivial, so differences are unlikely to have significant practical relevance. Statistical analyses were performed using a 2 × 2 factorial repeated measures factorial ANOVA with Bonferroni post hoc comparisons. Conclusions: FIFA 11+ warm-up does not provide a sufficient stimulus to elicit mechanical or metabolic responses in the per-knee structures. Other warm-up designs may be more appropriate for finding these effects. Full article

With the growing demand for personalized and flexible production, human–robot collaboration technology receives increasing attention. However, enabling robots to accurately perceive and align with human motion intentions remains a significant challenge. To address this, a novel human–robot collaborative control framework is proposed, which utilizes electromyography (EMG) signals as an interaction interface and integrates human skill imitation with reinforcement learning. Specifically, to manage the dynamic variation in muscle coordination patterns induced by joint angle changes, a temporal graph neural network enhanced with an Angle-Guided Attention mechanism is developed. This method adaptively models the topological relationships among muscle groups, enabling high-precision three-dimensional dynamic arm force estimation. Furthermore, an expert reward function and a fuzzy experience replay mechanism are introduced in the reinforcement learning model to guide the human skill learning process, thereby enhancing collaborative comfort and smoothness. The proposed approach is validated through a collaborative assembly task. Experimental results show that the proposed arm force estimation model reduces estimation errors by 10.38%, 8.33%, and 11.20% across three spatial directions compared to a conventional Deep Long Short-Term Memory (Deep-LSTM). Moreover, it significantly outperforms state-of-the-art methods, including traditional imitation learning and adaptive admittance control, in terms of collaborative comfort, smoothness, and assembly accuracy. Full article

To enhance wrist impairment rehabilitation efficiency, self-rehabilitation training using healthy-side forearm sEMG was introduced, improving patient engagement and proprioception. A sEMG-based movement recognition and muscle force estimation algorithm was proposed to transmit the estimated results to a wrist rehabilitation robot. Dominant eigenvalues of raw forearm EMG signals were selected to construct a movement recognition model that included a BPNN, a voting decision, and an intensified algorithm. An experimental platform for muscle force estimation was established to measure sEMG under various loads. The linear fitting was performed between mean absolute values (MAVs) and external loads to derive static muscle force estimation models. A dynamic muscle force estimation model was established through linear fitting average MAVs. Volunteers wore EMG sensors and performed six typical movements to complete the verification experiment. The average accuracy of only BPNN was 90.7%, and after the addition of the voting decision and intensified algorithm, it was improved to 98.7%. In the resistance training, the measured and estimated muscle forces exhibited similar trends, with RMSE of 4.2 N for flexion/extension and 5.8 N for ulnar/radial deviation. Under two different speeds and loads, the theoretical and estimated values of dynamic muscle forces showed similar trends with almost no phase difference, and the estimation accuracy was better during flexion movements compared to radial deviations. The proposed algorithms had strong versatility and practicality, aiming to realize the self-rehabilitation trainings of patients. Full article

Background: Muscle strength plays a critical role in the performance of middle- and long-distance athletes. However, the vertical force–velocity (F–V) profile has not been studied in this population. The objectives of this study were twofold: (i) to characterize the F–V profile in middle- and long-distance athletes and (ii) to explore its relationship with physiological and biomechanical performance variables. Methods: Thirty-nine highly trained athletes (13 middle-distance and 26 long-distance athletes), comprising men (18) and women (21), participated in this study. Each athlete performed a squat-jump to determine their F–V profile, followed by two 5 min bouts of low-intensity running and a graded exercise test to assess physiological and kinematic parameters. Results: Significant differences (p ≤ 0.05) were observed in maximal estimated power (P_max) and jump height between middle- and long-distance female athletes (21.20 ± 4.78 W·kg⁻¹ vs. 15.80 ± 2.83 W·kg⁻¹; 26.00 ± 0.05 cm vs. 19.50 ± 0.03 cm), and between male and female long-distance athletes (19.70 ± 2.87 W·kg⁻¹; 24.10 ± 0.02 cm). Stride length during low intensity running showed significant correlations with P_max (r = 0.340) and jump height (r = 0.374). P_max was positively associated with running economy (RE) (r = 0.396) and VO_2max (r = 0.346), and negatively correlated with F–V imbalance (FV_imb) (r = −0.531). Conclusions: Middle- and long-distance athletes demonstrate similar F–V profiles; however, middle-distance athletes exhibit a rightward shift, resulting in higher P_max and jump height, particularly among women. Nevertheless, F–V profile characteristics display only weak associations with physiological and kinematic variables which directly influence performance. Full article

Background: Assessments of muscle strength help prescribe and monitor training loads in cyclists (e.g., triathletes). Some methods include repetition maximum, joint isokinetic tests, and indirect estimates. However, their specificity for cycling’s dynamic force application and competitive cadences is lacking. This study aims to determine the influence of the cycling isokinetic peak force (cIPF) at different cadences on aerobic performance-related variables in trained triathletes. Methods: Eleven trained male athletes (33 ± 9.8 years, 173.1 ± 5.0 cm height, 73.9 ± 6.8 kg body mass, and ≥5 years of triathlon experience) were recruited. Maximal oxygen consumption (VO₂ max), ventilatory thresholds (i.e., VT1 and VT2), and cIPF were assessed. cIPF testing involved 10 s sprints at varied cadences with 4 min rest intervals. Pedaling cadences were set at low (60 rpm), moderate (80 and 100 rpm), and high (120 and 140 rpm) cadences. A regression model approach identified cIPF related to aerobic performance. Results: IPF at 80 and 120 rpm explained 49% of the variability in power output at VT1, 55% of the variability in power output at VT2, 65% of the variability in power output at maximal aerobic power (MAP), and 39% of the variability in VO₂ max. The cycling economy was not explained by cIPF. Conclusions: This study highlights the significance of cIPF, particularly at moderate to high cadences, as a determinant of aerobic-related variables in trained triathletes. Cycling cIPF should be tested to understand an athlete’s profile during crank cycling, informing better practice for training specificity and ultimately supporting athletes in achieving optimal performance outcomes in competitive cycling events. Full article

The volitional control of powered assistive devices is commonly performed by mapping the electromyographic (EMG) activity of the lower limb to joints’ angular kinematics, which are then used as the input for regulation. However, during walking, the ground reaction force (GRF) plays a central role in the modulation of the gait, providing dynamic stability and propulsion during the stance phase. Including this information within the control loop of prosthetic devices can improve the quality of the final output, providing more physiological walking dynamics that enhances the usability and patient comfort. In this work, we explored the feasibility of the estimation of the ground reaction force vertical component (VGRF) by using only the EMG activities of the thigh and shank muscles. We compared two deep learning models in three experiments that involved different muscular configurations. Overall, the outcomes show that the EMG signals could be leveraged to obtain a reliable estimation of the VGRF during walking, and the shank muscles alone represent a viable solution if a reduced recording setup is needed. On the other hand, the thigh muscles failed in providing performance enhancements, either when used alone or together with the shank muscles. The results outline the feasibility of including GRF information within an EMG-driven control scheme for prosthetic and assistive devices. Full article

Custom implants used for pelvic reconstruction in pelvic sarcoma surgery face a high complication rate due to mechanical failures of fixation screws. Consequently, patient-specific finite element (FE) models have been employed to analyze custom pelvic implant durability. However, muscle forces have often been omitted from FE studies of the post-operative pelvis with a custom implant, despite the lack of evidence that this omission has minimal impact on predicted bone, implant, and fixation screw stress distributions. This study investigated the influence of muscle forces on FE predictions of fixation screw pullout and fatigue failure in a custom pelvic implant. Specifically, FE analyses were conducted using a patient-specific FE model loaded with seven sets of personalized muscle and hip joint contact force loading conditions estimated using a personalized neuromusculoskeletal (NMS) model. Predictions of fixation screw pullout and fatigue failure—quantified by simulated screw axial forces and von Mises stresses, respectively—were compared between analyses with and without personalized muscle forces. The study found that muscle forces had a considerable influence on predicted screw pullout but not fatigue failure. However, it remains unclear whether including or excluding muscle forces would yield more conservative predictions of screw failures. Furthermore, while the effect of muscle forces on predicted screw failures was location-dependent for cortical screws, no clear location dependency was observed for cancellous screws. These findings support the combined use of patient-specific FE and NMS models, including loading from muscle forces, when predicting screw pullout but not fatigue failure in custom pelvic implants. Full article

Background: Although supervised exercise therapy (SET) is a primary treatment for peripheral artery disease (PAD), the current literature is limited regarding the mechanisms contributing to increased walking distances, including how lower extremity muscle function is altered after SET. This study aimed to investigate the effects of SET on lower extremity muscle function during walking in patients with PAD. Methods: Twelve patients with PAD participated in a 6-month SET program consisting of three weekly exercise sessions (a total of 72 sessions) and adhered to the American College of Sports Medicine’s (ACSM) recommendations. Each session started with a 5 min warm-up of mild walking and static stretching of upper and lower body muscles, followed by 50 min of intermitted exercise on a treadmill, and then finished with 5 min of cool-down activities similar to the warm-up. Each patient walked across a 10 m pathway with reflective markers on their lower limbs twice: before (baseline) and after six months of participation in SET (post-exercise). Marker coordinates and ground reaction forces were recorded and imported to OpenSim software (version 4.0) for gait simulations. Muscle force, muscle power, and metabolic rate were estimated from OpenSim and compared between the baseline and post-exercise. Results: The mean plantar flexor force was not altered after SET. However, individuals’ plantar flexor muscles demonstrated improvements in force production (lateral gastrocnemius: 75–80% of stance, Cohen’s d = 0.20–0.43; medial gastrocnemius: 65–85% of stance, Cohen’s d = 0.20–0.71; soleus: 90–95% of stance, Cohen’s d = 0.20–0.26). Furthermore, plantar flexor power increased (80–95% of stance, Cohen’s d = 0.20–0.39) and this was attributed to increased power in the lateral gastrocnemius (80–85% of stance, Cohen’s d = 0.20–0.47), medial gastrocnemius (80–90% of stance, Cohen’s d = 0.22–0.60), and soleus muscles (85–95% of stance, Cohen’s d = 0.20–0.49). Similarly, other muscle groups (knee extensors, knee flexors, hip abductors, hip adductors, hip extensors, and hip flexors) also exhibited force and power increases after SET. Additionally, force and power variances were significantly decreased in several muscle groups (plantar flexors, knee extensors, hip abductors, hip external rotators, hip extensors, and hip flexors). Total metabolic rate also increased during the stance period where muscle force and power were elevated after SET (early stance: 5–25%, Cohen’s d = 0.20–0.82; mid stance: 35–45%, Cohen’s d = 0.20–0.47; late stance: 75–80%, Cohen’s d = 0.20–0.36). Conclusions: Our results suggest that from a biomechanics perspective, muscle functions during walking are improved in patients with PAD after SET; however, the improvements were generally small and were not reflected by all muscle groups. Full article