Reactive lower limb muscle function during walking plays a key role in balance recovery following tripping, and ultimately fall prevention. The objective of this study was to evaluate muscle and ...joint function in the recovery limb during balance recovery after trip-based perturbations during walking. Twenty-four healthy participants underwent gait analysis while walking at slow, moderate and fast speeds over level, uphill and downhill inclines. Trip perturbations were performed randomly during stance, and lower limb kinematics, kinetics, and muscle contribution to the acceleration of the whole-body centre of mass (COM) were computed pre- and post-perturbation in the recovery limb. Ground slope and walking speed had a significant effect on lower limb joint angles, net joint moments and muscle contributions to support and propulsion during trip recovery (p < 0.05). Specifically, increasing walking speed during trip recovery significantly reduced hip extension in the recovery limb and increased knee flexion, particularly when walking uphill and at higher walking speeds (p < 0.05). Gluteus maximus played a critical role in providing support and forward propulsion of the body during trip recovery across all gait speeds and ground inclinations. This study provides a mechanistic link between muscle action, joint motion and COM acceleration during trip recovery, and underscores the potential of increased walking speed and ground inclination to increase fall risk, particularly in individuals prone to falling. The findings of this study may provide guidelines for targeted exercise therapy such as muscle strengthening for fall prevention.
Abstract In order to effectively solve the motor dysfunction of lower limbs in the elderly caused by the degeneration of lower limb muscle function and stroke hemiplegia， the importance of ...rehabilitation exercise for the recovery of lower extremity dysfunction patients is analyzed from the perspective of rehabilitation medicine. Combining with the physiological structure of human body， a human musculoskeletal model is established and the musculoskeletal simulation analysis is carried out. In order to accurately judge the motion intention of patients， three kinds of special sensors for exoskeleton are designed. On this basis， a force sensing joint structure scheme is proposed， and the overall structure of the lower limb power exoskeleton is designed. The human-machine coupling kinematics simulation analysis is carried out. On the basis of structure design， the hardware and electrical system of lower limb exoskeleton are designed. In order to verify the correctness of theoretical research， the exoskeleton proto
A Musculoskeletal model for the lumbar spine Christophy, Miguel; Faruk Senan, Nur Adila; Lotz, Jeffrey C. ...
Biomechanics and modeling in mechanobiology,
01/2012, Letnik:
11, Številka:
1-2
Journal Article
During forward flexion, spine motion varies due to age and sex differences. Previous studies showed that lumbar/pelvis range of flexion (RoF) and lumbo-pelvic ratio (L/P) are age/sex dependent. How ...variation of these parameters affects lumbar loading in a normal population requires further assessment. We aimed to estimate lumbar loads during dynamic flexion-return cycle and the differences in peak loads (compression) and corresponding trunk inclinations due to variation in lumbar/pelvis RoF and L/P.
Based on in vivo L/P (0.11–3.44), temporal phases of flexion (early, middle, and later), the lumbar (45-55°) and hip (60-79°) RoF; full flexion-return cycles of six seconds were reconstructed for three age groups (20–35, 36–50 and 50+ yrs.) in both sexes. Six inverse dynamic analyses were performed with a 50th percentile model, and differences in peak loads and corresponding trunk inclinations were calculated.
Peak loads at L4-L5 were 179 N higher in younger males versus females, but 228 N and 210 N lower in middle-aged and older males, respectively, compared to females. Females exhibited higher trunk inclinations (6°-20°) than males across all age groups. Age related differences in L4-L5 peak loads and corresponding trunk inclinations were found up to 415 N and 19° in males and 152 N and 13° in females. With aging, peak loads were reduced in males but were found non-monotonic in females, whereas trunk inclinations at peak loads were reduced in both sexes from young to middle/old age groups.
In conclusion, lumbar loading and corresponding trunk inclinations varied notably due to age/sex differences. Such data may help distinguishing normal or pathological condition of the lumbar spine.
Objective: Musculoskeletal models provide a noninvasive means to study human movement and predict the effects of interventions on gait. Our goal was to create an open-source 3-D musculoskeletal model ...with high-fidelity representations of the lower limb musculature of healthy young individuals that can be used to generate accurate simulations of gait. Methods: Our model includes bony geometry for the full body, 37 degrees of freedom to define joint kinematics, Hill-type models of 80 muscle-tendon units actuating the lower limbs, and 17 ideal torque actuators driving the upper body. The model's musculotendon parameters are derived from previous anatomical measurements of 21 cadaver specimens and magnetic resonance images of 24 young healthy subjects. We tested the model by evaluating its computational time and accuracy of simulations of healthy walking and running. Results: Generating muscle-driven simulations of normal walking and running took approximately 10 minutes on a typical desktop computer. The differences between our muscle-generated and inverse dynamics joint moments were within 3% (RMSE) of the peak inverse dynamics joint moments in both walking and running, and our simulated muscle activity showed qualitative agreement with salient features from experimental electromyography data. Conclusion: These results suggest that our model is suitable for generating muscle-driven simulations of healthy gait. We encourage other researchers to further validate and apply the model to study other motions of the lower extremity. Significance: The model is implemented in the open-source software platform OpenSim. The model and data used to create and test the simulations are freely available at https://simtk.org/home/full_body/, allowing others to reproduce these results and create their own simulations.
Gait asymmetry and a high incidence of lower back pain are typical for people with unilateral lower limb amputation. A common therapeutic objective is to improve gait symmetry; however, it is unknown ...whether better gait symmetry reduces lower back pain risk. To begin investigating this important clinical question, we examined a preexisting dataset to explore whether L5/S1 vertebral joint forces in people with unilateral lower limb amputation can be improved with better symmetry.
L5/S1 compression and resultant shear forces were estimated in each participant with unilateral lower limb amputation (n = 5) with an OpenSim musculoskeletal model during different levels of guided gait asymmetry. The amount of gait asymmetry was defined by bilateral stance times and guided via real-time feedback. A theoretical lowest L5/S1 force was determined from the minimum of a best-fit quadratic curves of L5/S1 forces at levels of guided asymmetry ranging from −10 to +15%. The forces found at the theoretical lowest force and during the 0% asymmetry level were compared to forces at preferred levels of asymmetry and to those from an able-bodied group (n = 5).
Results indicated that the forces for the people with unilateral lower limb amputation group at the preferred level of asymmetry were not different then at their 0% asymmetry condition, theoretical lowest L5/S1 forces, or the able-bodied group (all p-values > .23).
These preliminary results challenge the premise that restoring symmetric gait in people with unilateral lower limb amputation will reduce risk of lower back pain.
•modifying preferred gait may negatively impact lower back forces.•asymmetric gait may aid amputees.•transtibial amputees have similar L5/S1 demands as non-amputees while walking.
This paper aimed to develop a novel electromyography (EMG)-based neural-machine interface (NMI) that is user-generic for continuously predicting coordinated motion between metacarpophalangeal (MCP) ...and wrist flexion/extension. The NMI requires a minimum calibration procedure that only involves capturing maximal voluntary muscle contraction for the monitored muscles for individual users. At the center of the NMI is a user-generic musculoskeletal model based on the experimental data collected from six able-bodied (AB) subjects and nine different upper limb postures. The generic model was evaluated on-line on both AB subjects and a transradial amputee. The subjects were instructed to perform a virtual hand/wrist posture matching task with different upper limb postures. The on-line performance of the generic model was also compared with that of the musculoskeletal model customized to each individual user (called "specific model"). All subjects accomplished the assigned virtual tasks while using the user-generic NMI, although the AB subjects produced better performance than the amputee subject. Interestingly, compared with the specific model, the generic model produced comparable completion time, a reduced number of overshoots, and improved path efficiency in the virtual hand/wrist posture matching task. The results suggested that it is possible to design an EMG-driven NMI based on a musculoskeletal model that could fit multiple users, including upper limb amputees, for predicting coordinated MCP and wrist motion. The present new method might address the challenges of existing advanced EMG-based NMI that require frequent and lengthy customization and calibration. Our future research will focus on evaluating the developed NMI for powered prosthetic arms.
Objective: electromyogram (EMG)-driven musculoskeletal models have been widely used to investigate human movements while existing EMG-driven models commonly neglect regional heterogeneity in anatomy ...and activation within a skeletal muscle. To consider neuromuscular compartment anatomy and activation, a subject- and compartment-specific EMG-driven model was developed for isometric plantarflexion moment prediction. Methods: the model was hill-type consisting of gastrocnemius medialis, gastrocnemius lateralis, and soleus around the ankle joint, and each muscle was discretised into four compartments. The moment arms of each compartment were determined using magnetic resonance imaging and the compartment activation was calculated based on high-density surface EMG signals. And the hill-type compartment parameters were tuned in a calibration process. The developed compartment-specific model and a generic EMG-driven model were examined by comparing their predicted net ankle moments with measurements obtained while subjects performed isometric plantarflexion tasks at different contraction levels. Results: compared to the generic EMG-driven model, the isometric plantarflexion moment prediction using the compartment-specific model was more accurate at all contraction levels, with the average prediction error decreasing from average 13.81% to 10.11%. The contraction of each compartment was found to be generally non-uniform at all contraction levels. Conclusion: the developed compartment-specific model enabled accurate prediction of isometric plantarflexion moment and the simulation of non-uniform muscular contraction, which is more physiologically appropriate than the existing EMG-driven models. Significance: the proposed compartment-specific formulation opens new perspectives for subject-specific musculoskeletal modelling, which has great potential in understanding regional characteristics of the neuromuscular activities.
The cybertwin-driven 6G that can obtain static and dynamic data stream of users provide an exciting potential for a novel muscular human cybertwin beyond traditonally used artificial neural networks ...(ANNs) and musculoskeletal models (MSMs). In this article, we propose the conceptual design of the muscular human cybertwin and construct a baseline model with an improved generalization ability over ANN and an easier adaptation to new data distributions over MSMs. In particular, we for the first time propose to combine ANN and MSM, which benefits from the combination of learning-based approaches and analytical approaches. We then experimentally compare different manners of the combination and demonstrate the better combining manner on our testing case. Finally, we evaluate our method on an open-sourced dataset and on data from wearable sensors from the aspects of joint moment prediction accuracy, data efficiency, generalization ability, and time efficiency of personalization. Our proposed method achieves accuracy similar with ANN and over 30<inline-formula><tex-math notation="LaTeX">\%</tex-math></inline-formula> better than MSM with sufficient training data. Compared with ANN, the improved data efficiency is presented by the better accuracies with a small amount of training data, and the generalization ability to unseen walking conditions and new subjects are demonstrated by the over 70<inline-formula><tex-math notation="LaTeX">\%</tex-math></inline-formula> accuracy improvements. Moreover, when fine-tuning the model, our algorithm is demonstrated by the time 75<inline-formula><tex-math notation="LaTeX">\%</tex-math></inline-formula> shorter than calibrated MSM and the accuracy improvements.
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