• Transactions of the Korean Society of Mechanical Engineers A
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• v.35 no.7
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• pp.785-790
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• 2011

The goal of this study is to estimate the force acting on the knee joint in the human body by using the Hilltype muscle model based on a musculoskeletal model of the human lower extremity in the sagittal plane. For estimating the force applied, the human leg is modeled using multi-body modeling. This leg model comprises biarticular muscles acting on two joints of the upper and lower limbs, and the muscles include some of the major muscles such as the hamstring. In order to analyze the uncertainty of the applied forces acting on the knee joint, statistical distributions of human body, leg part, parameters are required and to obtain the parameter's statistical characteristic of the part sample survey method is employed. Finally, by using the sensitivity information of the parameters, the force acting on the knee joint can be estimated.

• Proceedings of the KIEE Conference
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• 1998.07b
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• pp.611-613
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• 1998

A structure of musculotendon model with a fatigue profile is investigated. The Hill-type musculotendon model can predicts the decline in muscle force for a given fatigue profile. It consists of nonlinear activation and contraction dynamics based on the physiological concepts. It is normalized for generalization to deal with the various muscles. Muscle force generated by continuous tetanic electrical monophasic pulsewidth modulation stimulation is decreased in time. A fatigue profile is expressed by a function of intramuscular acidification and applied to the relationship between muscle force and shortening velocity in contraction dynamics. The results of computer simulation are well matched with data in a literature which are isometrically performed for knee extension muscles. Also change in optimal fiber length has an effect only on muscle time, constant not on the steady-state tetanic force.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.22 no.6
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• pp.502-508
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• 2012

An analytical model for a human body is important to predict muscle and joint forces. Because it is difficult to estimate muscle or joint forces from a human body, the objective of this study is the development of a reliable analytical model for a human body to evaluate the lower extremity muscle and joint forces. The musculoskeletal system of the human lower extremity is modeled as a multibody system employing the Hill-type muscle model. Muscle forces are determined to minimize energy consumption, and we assume that motion is constrained in the sagittal plane. Muscle forces are calculated through an equilibrium analysis while rising from a seated position. The musculoskeletal model consists of four segments. Each segment is a rigid body and connected by frictionless revolute joints. Muscles of the lower extremity are simplified to seven muscles with those that are not related to the sagittal plane motion are ignored. Muscles that play a similar role are combined together. The results of the present study are compared with experimental results to validate the lower extremity model and the assumptions of the present study.

• Journal of the Korean Society for Precision Engineering
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• v.30 no.6
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• pp.650-657
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• 2013

This study uses a muscle activation sensor and elbow joint model to develop an estimation algorithm for human elbow joint torque for use in a human-robot interface. A modular-type MVS (Muscle Volume Sensor) and calibration algorithm are developed to measure the muscle activation signal, which is represented through the normalization of the calibrated signal of the MVS. A Hill-type model is applied to the muscle activation signal and the kinematic model of the muscle can be used to estimate the joint torques. Experiments were performed to evaluate the performance of the proposed algorithm by isotonic contraction motion using the KIN-COM$^{(R)}$ equipment at 5, 10, and 15Nm. The algorithm and its feasibility for use as a human-robot interface are verified by comparing the joint load condition and the torque estimated by the algorithm.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.38 no.10
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• pp.1147-1155
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• 2014

Biomechanical models are often used to predict muscle and joint forces in the human body. For estimation of muscle forces, the body and muscle properties have to be known. However, these properties are difficult to measure and differ from person to person. Therefore, it is necessary to predict the change in muscle forces depending on the body and muscle properties. The objective of the present study is to develop a numerical procedure for estimating the muscle forces in the human lower extremity under uncertainty of body and muscle properties during rising motion from a seated position. The human lower extremity is idealized as a multibody system in which eight Hill-type muscle force models are employed. Each model has four degrees of freedom and is constrained in the sagittal plane. The eight muscle forces are determined by minimizing the metabolic energy consumption during the rising motion. Uncertainty analysis is performed using a first-order reliability method. The one-standard-deviation range of agonistic muscle forces is calculated to be about 150-300 N.