Abstract
The methods described provide for quantitative evaluation of skeletal muscles’ passive resistance, also known as muscle stiffness, muscle myotonia or spasticity. They are employed in the quantitative evaluation of muscle groups responsible for angular movements in the elbow joint. The methods, along with the manually actuated dynamometer, represent an alternative to current evaluation methods which are considered inaccurate and subjective. The function of the electronic dynamometer subsystem is to measure angle and torque in the elbow joint. Stiffness can be evaluated by a graph of the torque moment and joint angle in mutual dependence. Since the curve of dependence demonstrates a relation between the torque moment and joint angle is composed of three parts (small, mean, and high angles), three polynomial equations for three regression lines must be calculated. This means that for three regression lines, three values of joint stiffness are obtained. Angular velocity of the rotational movement in a joint is the result of movement affected by a manually controlled lever of dynamometer. No statistically significant difference in joint stiffness values was identified, when comparing values for individual joint stiffness across three different groups of angular velocities; however, when the same comparison was made for small, mean and high angles, a statistically significant difference was identified for all three angular velocities used. The experiments with healthy subjects confirmed, that the torsional moment is dependent on the elbow angle, not on the velocity of the movement. Finding a correlation between a passive moment of force and kinematic angular parameters allows for the study of a complex movement in a joint.
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This work was done in the framework of research project SGS17/108/OHK4/1T/17.
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Kutilek, P. et al. (2020). Methods of Joint Stiffness Measurement Using a Manually Actuated Dynamometer. In: Szewczyk, R., Krejsa, J., Nowicki, M., Ostaszewska-LiĹĽewska, A. (eds) Mechatronics 2019: Recent Advances Towards Industry 4.0. MECHATRONICS 2019. Advances in Intelligent Systems and Computing, vol 1044. Springer, Cham. https://doi.org/10.1007/978-3-030-29993-4_16
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