不同目标力矩时距小腿关节肌肉力觉的重测信度**☆

背景：目前对于距小腿关节矢状面内肌肉力觉的研究较为缺乏,距小腿关节肌肉力觉的测试没有统一的标准。 目的：通过分析不同目标力矩时距小腿关节矢状面内运动肌肉力觉的重测信度,探讨距小腿关节肌肉力觉的测量方法。 方法：选取跖屈肌群最大等长峰值力矩值的25%,50%和75%作为距小腿关节肌肉力觉的目标力矩值,测试距小腿关节肌肉对这些目标力矩值的复制能力;运用组内相关系数和测量的标准误来判断肌肉力觉的重复测量结果的一致性程度。 结果与结论：结果显示用来衡量关节肌肉力觉的可变误差和绝对误差的组内相关系数均大于0.75,而且测量的标准误相对较小;常数误差的组内相关系数均小于0.75,而且测量的标准误相对较大。在目标力矩较小时,用来衡量肌肉力觉的可变误差和绝对误差重测信度较好。     

人服系统上肢交互生物力学仿真模型

目的通过建立人-舱外服上肢交互生物力学仿真模型计算穿着舱外服后航天员上肢关节力矩和肌肉力,满足出舱活动风险评估的需求。方法分别建立舱外服手臂的刚体运动学模型和关节阻尼力矩迟滞模型以描述舱外服关节的运动和力学特性。通过对舱外航天服肘部和人体肘部位置进行约束实现人体和舱外服手臂之间的运动学耦合,利用虚拟反作用力元实现两者之间的动力学耦合,在反向运动生物力学架构下建立一体化仿真模型。利用该模型对宇航员穿着加压、未加压舱外服和不穿着舱外服3种工况下肘弯曲/伸展进行仿真案例分析。结果3种工况下肱二头肌的预测肌肉激活和积分肌电的相关性分别为0.86、0.71、0.65,肱三头肌对应的相关性分别为0.75、0.61、0.60,采用预测肌肉激活和积分肌电的一致性定性验证了模型的正确性,利用舱外服肘关节阻尼力矩与人体肘关节肌肉承受力矩之间的一致性验证了模型的合理性。结论该人服系统上肢交互生物力学仿真模型能有效计算航天员穿着舱外服后的上肢关节力矩和肌肉力,且仿真结果和实验表明,加压后舱外服关节阻尼力矩造成较大的人体关节力矩和肌肉负荷,为航天员出舱活动中的体力负荷和骨肌风险评估提供方法学支撑。     

人服系统上肢交互生物力学仿真模型

目的 通过建立人-舱外服上肢交互生物力学仿真模型计算穿着舱外服后航天员上肢关节力矩和肌肉力,满足出舱活动风险评估的需求。方法 分别建立舱外服手臂的刚体运动学模型和关节阻尼力矩迟滞模型以描述舱外服关节的运动和力学特性。通过对舱外航天服肘部和人体肘部位置进行约束实现人体和舱外服手臂之间的运动学耦合,利用虚拟反作用力元实现两者之间的动力学耦合,在反向运动生物力学架构下建立一体化仿真模型。利用该模型对宇航员穿着加压、未加压舱外服和不穿着舱外服3种工况下肘弯曲/伸展进行仿真案例分析。结果 3种工况下肱二头肌的预测肌肉激活和积分肌电的相关性分别为0.86、0.71、0.65,肱三头肌对应的相关性分别为0.75、0.61、0.60,采用预测肌肉激活和积分肌电的一致性定性验证了模型的正确性,利用舱外服肘关节阻尼力矩与人体肘关节肌肉承受力矩之间的一致性验证了模型的合理性。结论 该人服系统上肢交互生物力学仿真模型能有效计算航天员穿着舱外服后的上肢关节力矩和肌肉力,且仿真结果和实验表明,加压后舱外服关节阻尼力矩造成较大的人体关节力矩和肌肉负荷,为航天员出舱活动中的体力负荷和骨肌风险评估提供方法学支撑。     

人服系统上肢交互生物力学仿真模型

目的 通过建立人-舱外服上肢交互生物力学仿真模型计算穿着舱外服后航天员上肢关节力矩和肌肉力，满足出舱活动风险评估的需求。方法 分别建立舱外服手臂的刚体运动学模型和关节阻尼力矩迟滞模型以描述舱外服关节的运动和力学特性。通过对舱外航天服肘部和人体肘部位置进行约束实现人体和舱外服手臂之间的运动学耦合，利用虚拟反作用力元实现两者之间的动力学耦合，在反向运动生物力学架构下建立一体化仿真模型。利用该模型对宇航员穿着加压、未加压舱外服和不穿着舱外服3种工况下肘弯曲/伸展进行仿真案例分析。结果 3种工况下肱二头肌的预测肌肉激活和积分肌电的相关性分别为0.86、0.71、0.65，肱三头肌对应的相关性分别为0.75、0.61、0.60，采用预测肌肉激活和积分肌电的一致性定性验证了模型的正确性，利用舱外服肘关节阻尼力矩与人体肘关节肌肉承受力矩之间的一致性验证了模型的合理性。结论 该人服系统上肢交互生物力学仿真模型能有效计算航天员穿着舱外服后的上肢关节力矩和肌肉力，且仿真结果和实验表明，加压后舱外服关节阻尼力矩造成较大的人体关节力矩和肌肉负荷，为航天员出舱活动中的体力负荷和骨肌风险评估提供方法学支撑。     

肘关节矢状面内生物动力模型及其优化解

目的建立肘关节矢状面内的动力学模型,寻求有效方法进行求解。方法利用Matlab的优化工具箱对所建立的模型进行优化求解。结果求解出了肘关节在不同屈伸角速度下,受到不同外力时的关节反力、各肌肉力以及力矩,得出了与文献相一致的结论。结论利用Matlab的优化工具箱可以合理地求解该模型,并且该模型可以用来计算肘关节在受到不同外力时的关节反力、肌肉力以及相应力矩。     

脑卒中患者运动过程中动力学特征的智能预测

目的 使用主成分分析（principal component analysis,PCA）和反向传播(back propagation,BP)神经网络预测脑卒中患者行走时患侧髋、膝、踝的关节力矩。方法 30例脑卒中患者通过8镜头Qualisys红外光点高速运动捕捉系统和Kistler三维测力台同步采集运动学和动力学数据。通过OpenSim计算脑卒中患者髋、膝、踝患侧关节力矩,采用PCA来筛选累积贡献率达到99%的初始变量,采用标准均方根误差（normalized root mean squared error,NRMSE）、均方根误差（root mean squared error,RMSE）、平均绝对百分比误差（mean absolute percentage error,MAPE）和平均绝对误差（mean absolute error,MAE）、R2作为PCA-BP模型的评价指标。使用肯德尔W系数评价计算关节力矩与预测力矩之间的一致性。结果 PCA数据显示躯干、骨盆、患侧髋、膝和踝关节在x、y、z轴（矢状、冠状、垂直轴）对患侧髋、膝、踝关节力矩具有显著影响。预测值与测量值间NRMSE为5.14%~8.86%,RMSE为0.184~0.371,MAPE为3.5%~4.0%,MAE为0.143~0.248,R2为0.998~0.999。结论 建立的PCA-BP模型可准确预测脑卒中患者行走时的髋膝踝关节力矩,显著缩短测量时间。在脑卒中患者的步态分析中本模型可代替传统的关节力矩计算,为获得脑卒中患者生物力学数据提供新途径,以及为脑卒中患者临床治疗提供有效的方法。     

基于深度相机和神经网络的下肢关节力矩估计

目的 通过深度相机和神经网络估计人在直线行走时髋、膝和踝关节的屈伸力矩。方法 利用光学运动捕捉系统、测力板和Azure Kinect深度相机采集20个人的步态信息,受试者被要求以其偏好的步行速度直线行走,同时踏在测力板上。并利用Visual 3D仿真得到关节力矩作为参考值,分别训练人工神经网络（artificial neural network,ANN）模型与长短期记忆（long short-term memory,LSTM）模型进行关节力矩估计。结果 ANN模型估计髋、膝和踝关节的关节力矩的相对均方根误差（relative root mean square error,rRMSE）分别为15.87%~17.32%、18.36%~25.34%和14.11%~16.82%,相关系数分别为0.81~0.85、0.69~0.74和0.76~0.82。LSTM模型具有更好的估计效果,rRMSE分别为8.53%~12.18%、14.32%~18.78%和6.51%~11.83%,相关系数分别达到了0.89~0.95、0.85~0.91和0.90~0.97。结论 本文证实了利用深度相机和神经网络无接触估计人体下肢关节力矩方案的可行性,其中LSTM模型具有更佳的表现。关节力矩估计结果与现有研究相比具有更好的精度,潜在应用场景包含远程医疗、个性化康复方案制定以及矫形器辅助设计等。     

躯干等速向心屈伸运动时屈伸肌肌力的变化:脊柱最易受损伤的角度范围

背景:目前对躯干肌肌力的研究主要集中于腰痛患者肌力变化方面,而对脊柱容易损伤的角度范围的研究不多。目的:探讨躯干等速向心屈伸动作时屈伸肌肌力变化的特征及脊柱最容易损伤的角度范围。方法:苏州大学2005/2007级研究生,健康男性14名,自愿参加测试。选用瑞士产CON-TREX人体肌力评估和训练系统,测量受试者等速向心运动时的屈伸肌肌力及脊柱角度。测试速度分别为30,60,90,120,180(°)/s,每种速度下,受试者尽自己最大力量屈伸躯干4次,组间休息5min。主要观察:①受试者躯干运动的关节活动范围。②等速向心运动屈伸峰值力矩、屈伸肌峰值力矩比及到达峰值力矩的平均角度的变化。③等速向心运动屈伸肌总功、平均功率。结果与结论:①等速向心运动时,伸肌的峰值力矩值随角速度的增加而减少(P0.05),屈肌峰值力矩值未见规律性的变化;屈、伸肌的峰值力矩比随角速度的加快而增大,但差异无显著性意义(P0.05)。②慢速等速向心运动时,不同角速度下屈、伸肌到达峰值力矩角度分布离散,30(°)/s时为-48.56°,90(°)/s时为-46.18°;快速运动时,屈、伸肌出现最大峰值力矩角度基本接近,120(°)/s时分别为-48.71°,-51.61°,180(°)/s分别-54.86,-53.11°。③等速向心运动时,在不同角速度下,屈、伸肌的总功均随角速度的增加而减少,伸肌总功大于屈肌,伸肌总功的变化差异有显著性意义(P0.05);屈、伸肌的平均功率随角速度的增加呈线性上升,屈肌平均功率始终小于伸肌(P0.01)。结果提示:①等速向心运动时,躯干屈伸肌群的肌力随角速度的增加而减小,躯干在慢速屈伸运动时稳定性较好。②快速等速向心运动时,突受外力打击后容易引起肌肉损伤和脊柱不稳。③等速运动时屈伸肌做功随运动速度下降而降低,但肌肉的爆发力随运动速度的增快而加大。     

髋关节屈伸肌力等速测试:体育学院大学生的特点

背景:等速测试系统作为一种评价人体肌肉功能水平的研究方法和手段,在研究中得到了越来越广泛的应用,但运用等速肌力测试研究大学生髋关节屈伸肌群发展影响的报道并不多见。目的:采用等速肌力测试系统评估大学生髋关节屈伸肌力。方法:志愿参加测试的大学生男女各20名。采用澳大利亚Kylingk公司生产的"Kinitech"等速肌力测试系统,按照测试要求对参试者髋关节进行测试,测试顺序为先向心后离心。测试速度为慢速60(°)/s,中速120(°)/s,快速240(°)/s。观察髋关节屈伸肌群的峰力矩、相对峰力矩、总功、相对总功。结果与结论:在相对应的角速度下,男性峰力矩和相对峰力矩均大于女性(P0.01)。角速度为60,120,240(°)/s时,男性屈肌峰力矩均小于伸肌峰力矩,而女性屈肌峰力矩大于伸肌,但差异无显著性意义(P0.05)。在相对应的角速度下,男性总功及相对总功均大于女性(P0.01)。男性屈肌总功及相对总功均小于伸肌[角速度为60,120(°)/s时,P0.01;角速度为240(°)/s时,P0.05)];女性屈肌总功及相对总功也均小于伸肌[角速度为60(°)/s时,P0.01);角速度为120,240(°)/s时,P0.05)]。提示髋关节屈伸肌群在相对应的角速度下,男性峰力矩、相对峰力矩、总功、相对总功均大于女性;男女峰力矩、相对峰力矩、总功、相对总功随着测试角速度的增大而减小;在对应的指标下,男性的值大于女性。     

穿戴式下肢外骨骼对人体步态特性的影响研究

本文拟探明穿戴式下肢外骨骼对人体下肢相应关节参数与肌肉运动学、动力学参数的影响变化,进而为优化其结构、提高其系统性能提供科学依据。本文通过采集受试者的行走数据,以人体下肢各关节在矢状面上的关节角度作为下肢外骨骼仿真分析的驱动数据,运用人体生物力学分析软件Anybody分别建立了人体模型(即未穿戴下肢外骨骼的人体模型)和人-机系统模型(即穿戴下肢外骨骼后的模型),并对比分析了两种情况下人体下肢运动时的运动学参数(关节力、关节力矩)及肌肉参数(肌肉力、肌肉激活程度、肌肉收缩速度、肌肉长度)的变化情况。实验结果表明,人体穿戴下肢外骨骼后行走的步态满足正常步态,但会出现个别肌肉力突增的现象;下肢主要肌肉的最大肌肉激活程度均未超过1,说明肌肉均未出现疲劳或损伤状况;股直肌的最大肌肉激活程度增加最多(0.456),半腱肌的最大肌肉激活程度增加最少(0.013),提示下肢外骨骼最容易引起股直肌疲劳或损伤。通过本文研究结果说明,为避免出现个别肌肉力突增导致人体下肢损伤,在设计下肢外骨骼时,要特别注意人体体段长与下肢外骨骼杆长的一致性和运动的平稳性。     

An EMG-driven model to estimate muscle forces and joint moments in stroke patients

Individuals following stroke exhibit altered muscle activation and movement patterns. Improving the efficiency of gait can be facilitated by knowing which muscles are affected and how they contribute to the pathological pattern. In this paper we present an electromyographically (EMG) driven musculoskeletal model to estimate muscle forces and joint moments. Subject specific EMG for the primary ankle plantar and dorsiflexor muscles, and joint kinematics during walking for four subjects following stroke were used as inputs to the model to predict ankle joint moments during stance. The model's ability to predict the joint moment was evaluated by comparing the model output with the moment computed using inverse dynamics. The model did predict the ankle moment with acceptable accuracy, exhibiting an average R² value ranging between 0.87 and 0.92, with RMS errors between 9.7% and 14.7%. The values are in line with previous results for healthy subjects, suggesting that EMG-driven modeling in this population of patients is feasible. It is our hope that such models can provide clinical insight into developing more effective rehabilitation therapies and to assess the effects of an intervention.     

Quantification of functional knee flexor to extensor moment ratio using isokinetics and electromyography

CONTEXT: Evaluating moment balance around the knee helps athletic trainers set appropriate targets for injury prevention and rehabilitation programs. OBJECTIVE: To examine the knee flexor (KF) to knee extensor (KE) moment ratios using the moments when each muscle group acts as an agonist and using the moments when the KE acts as an agonist and the KF acts as an antagonist. DESIGN: Cross-sectional. SETTING: University research laboratory. PATIENTS OR OTHER PARTICIPANTS: Seventeen pubertal males (age = 13.7 +/- 0.2 years, height = 1.61 +/- 0.04 m, mass = 51.3 +/- 2.7 kg). INTERVENTION(S): The subjects performed maximal isokinetic concentric KE (KE(CON)) and eccentric KF (KF(ECC)) efforts and performed eccentric KE (KE(ECC)) and concentric KF efforts at 60 degrees /s and 180 degrees /s while we recorded the bipolar surface electromyographic (EMG) signal of the involved muscles. The KF antagonist moment was estimated from EMG-moment relationships determined during calibration KF efforts. Maximal moments were used to estimate the KF:KE ratios, and EMG-based moments were used to estimate the antagonist to agonist ratios. MAIN OUTCOME MEASURE(S): We calculated KF:KE ratios for various angular positions, velocities, and movement directions. RESULTS: The KF(ECC):KE(CON) ratio significantly increased as the knee extended (P < .05) at increased angular velocity (P < .05), reaching a value of 3.14 +/- 1.95 at full extension. The estimated knee flexor antagonist to knee extensor agonist ratio also increased near full extension (0.32 +/- 0.21). CONCLUSIONS: Although the KFs have a higher capacity to produce maximal moment near knee extension and at increased angular velocities, knee joint movement is achieved through a balanced coactivation of the 2 antagonistic muscle groups to maintain joint stability and movement efficiency. The combined use of moment and EMG data can provide additional useful information regarding muscle balance around the knee.     

Human skeletal muscle fibre types and force: velocity properties

It has been reported that there is a relationship between power output and fibre type distribution in mixed muscle. The strength of this relationship is greater in the range of 3–8 rad · s^–1 during knee extension compared to slower or faster angular knee extensor speeds. A mathematical model of the force: velocity properties of muscle with various combinations of fast- and slow-twitch fibres may provide insight into why specific velocities may give better predictions of fibre type distribution. In this paper, a mathematical model of the force: velocity relationship for mixed muscle is presented. This model demonstrates that peak power and optimal velocity should be predictive of fibre distribution and that the greatest fibre type discrimination in human knee extensor muscles should occur with measurement of power output at an angular velocity just greater than 7 rad · s^–1. Measurements of torque: angular velocity relationships for knee extension on an isokinetic dynamometer and fibre type distribution in biopsies of vastus lateralis muscles were made on 31 subjects. Peak power and optimal velocity were determined in three ways: (1) direct measurement, (2) linear regression, and (3) fitting to the Hill equation. Estimation of peak power and optimal velocity using the Hill equation gave the best correlation with fibre type distribution (r > 0.5 for peak power or optimal velocity and percentage of fast-twitch fibres). The results of this study confirm that prediction of fibre type distribution is facilitated by measurement of peak power at optimal velocity and that fitting of the data to the Hill equation is a suitable method for evaluation of these parameters.     

Control of 3D limb dynamics in unconstrained overarm throws of different speeds performed by skilled baseball players

This study investigated how the human CNS organizes complex three-dimensional (3D) ball-throwing movements that require both speed and accuracy. Skilled baseball players threw a baseball to a target at three different speeds. Kinematic analysis revealed that the fingertip speed at ball release was mainly produced by trunk leftward rotation, shoulder internal rotation, elbow extension, and wrist flexion in all speed conditions. The study participants adjusted the angular velocities of these four motions to throw the balls at three different speeds. We also analyzed the dynamics of the 3D multijoint movements using a recently developed method called "nonorthogonal torque decomposition" that can clarify how angular acceleration about a joint coordinate axis (e.g., shoulder internal rotation) is generated by the muscle, gravity, and interaction torques. We found that the study participants utilized the interaction torque to generate larger angular velocities of the shoulder internal rotation, elbow extension, and wrist flexion. To increase the interaction torque acting at these joints, the ball throwers increased muscle torque at the shoulder and trunk but not at the elbow and wrist. These results indicates that skilled ball throwers adopted a hierarchical control in which the proximal muscle torques created a dynamic foundation for the entire limb motion and beneficial interaction torques for distal joint rotations.     

A Model of the Upper Extremity for Simulating Musculoskeletal Surgery and Analyzing Neuromuscular Control

Biomechanical models of the musculoskeletal system are frequently used to study neuromuscular control and simulate surgical procedures. To be broadly applicable, a model must be accessible to users, provide accurate representations of muscles and joints, and capture important interactions between joints. We have developed a model of the upper extremity that includes 15 degrees of freedom representing the shoulder, elbow, forearm, wrist, thumb, and index finger, and 50 muscle compartments crossing these joints. The kinematics of each joint and the force-generating parameters for each muscle were derived from experimental data. The model estimates the muscle–tendon lengths and moment arms for each of the muscles over a wide range of postures. Given a pattern of muscle activations, the model also estimates muscle forces and joint moments. The moment arms and maximum moment-generating capacity of each muscle group (e.g., elbow flexors) were compared to experimental data to assess the accuracy of the model. These comparisons showed that moment arms and joint moments estimated using the model captured important features of upper extremity geometry and mechanics. The model also revealed coupling between joints, such as increased passive finger flexion moment with wrist extension. The computer model is available to researchers at .     

Vector-based forearm rotation moment arms – A sensitivity analysis

All existing moment arm data for muscles of the forearm derive from tendon excursion experiments. Moment arms determined this way are only valid for movement about the same generalised coordinate system as was used during the tendon excursion, which makes their implementation in more complex or realistic joint models problematic. This study used a vector-based method to calculate muscle moment arms in a three dimensional model of forearm rotation. It also evaluated the sensitivity of this method to errors in the input data. There was reasonably close agreement between the moment arms calculated in this study and those published using tendon excursion methods. Six out of eight muscles had moment arms within the range of values reported previously. However, the vector-based method was sensitive to the accuracy of the input data. This sensitivity varied between muscles and input variables. Generally, the calculations were more robust to the point of force application than the muscle lines of action and the joint's axis of rotation. A small change in these variables could produce substantial changes in the calculated moment arms. Consequently, accurate input data is important when using the vector-based method in a joint model.     

Reliability of a practicable EMG-moment model for antagonist moment prediction

Although the use of practicable EMG-moment models for knee joint moment prediction appears promising, the repeatability of the estimated forces remains unclear. The purpose of this study was to apply an EMG-moment model to predict the antagonist moment of the knee flexors (Mflx) during maximal isometric knee extension efforts. Nine healthy males performed maximal isometric knee extension and flexion contractions at 0 degrees , 45 degrees and 90 degrees angles with recordings of the net moment and EMG of thigh muscles. Calibration knee flexion efforts were performed at different levels of intensity and the resulting EMG-moment curves were fitted using second-order polynomials. The polynomials were then used to predict Mflx. This procedure was repeated a week after. The results indicated non-significant differences in test-retest Mflx. Intraclass correlation coefficients ranged from 0.852 to 0.912 indicating high test-retest reliability of the estimated Mflx. For isometric contractions, the present model is suitable as a method to estimate antagonist muscle moments.     

Accuracy of a practicable EMG to force model for knee muscles

A practicable EMG-force model is evaluated for muscles about the knee. The model included envelope signal processing and a gain-dependency of knee angle and angular velocity. Six healthy subjects participated in the experiments. For calibration, maximal isokinetic contractions about the knee were performed on a dynamometer with recordings of knee joint movement, net moment and EMG of thigh muscles. The model parameters were fitted on these calibration experiments. For validation, estimated moments from the EMG levels were compared to the actual exerted moments of two independent isokinetic contractions. Averaged RMS values of the difference ranged from 11 to 20% of the actual exerted moment. For isokinetic concentric contractions, the present model is suitable as a method to estimate muscle moments.     

Probabilistic Modeling of Knee Muscle Moment Arms: Effects of Methods,Origin–Insertion,and Kinematic Variability

In musculoskeletal modeling, reliable estimates of muscle moment arms are an important step in accurately predicting muscle forces and joint moments. The degree of agreement between the two common methods of calculating moment arms—tendon excursion (TE) and geometric origin–insertion, is currently unknown for the muscles crossing the knee joint. Further, measured moment arm data are subject to variability in estimation of attachment sites as points from irregular surfaces on the bones, and due to differences in joint kinematics observed in vivo. Thus, the objectives of the present study were to compare moment arms of major muscles crossing the knee joint obtained from TE and geometric methods using a finite element-based lower extremity model, and to quantify the effects of potential muscle origin–insertion and tibiofemoral kinematic variability on the predicted moment arms using probabilistic methods. A semiconstrained, fixed bearing, posterior cruciate-retaining total knee arthroplasty was included due to available in vivo kinematic data. In this study, muscle origin and insertion locations and kinematic variables were represented as normal distributions with standard deviations of 5 mm for origin–insertion locations and up to 1.6 mm and 3.0° for the kinematic parameters. Agreement between the deterministic moment arm calculations from the two methods was excellent for the flexors, while differences in trends and magnitudes were observed for the extensor muscles. Model-predicted deterministic moment arms from both methods agreed reasonably with the experimental values from available literature. The uncertainty in input parameters resulted in substantial variability in predicted moment arms, with the size of 1–99% confidence interval being up to 41.3 and 35.8 mm for the TE and geometric methods, respectively. The sizeable range of moment arm predictions and associated excursions has the potential to affect a muscle’s operating range on the force–length curve, thus affecting joint moments. In this study, moment arm predictions were more dependent on muscle origin–insertion locations than the kinematic variables. The important parameters from the TE method were the origin and insertion locations in the sagittal plane, while the insertion location in the sagittal plane was the dominant parameter using the geometric method.     

Monte Carlo simulation of a planar shoulder model

Although variability of anthropometric measures within a population is a well established phenomenon, most biomechanical models are based on average parameter values. For example, optimisation models for predicting muscle forces from net joint reaction moments typically use average muscle moment arms. However, understanding the distribution of musculoskeletal morbidity within a population requires information about the variation of tissue loads within the population. This study investigated the use of Monte Carlo simulation techniques to predict the statistical distribution of deltoid and rotator cuff muscle forces during static arm elevation. Muscle moment arms were modelled either as independent random variables or jointly distributed random variables. Moment arm data was collected on 22 cadaver specimens. The results demonstrated the use of Monte Carlo techniques to describe the statistical distribution of muscle forces. Although assuming statistically independent moment arms did affect the statistical distribution shape, that assumption did not affect the median predicted forces. The standard deviations of muscle forces predicted using Monte Carlo techniques were similar to the standard deviation of muscle force predictions using the whole sample of specimens. It is concluded that Monte Carlo simulation techniques are a useful tool to analyse the interindividual variability of rotator cuff muscle forces.