位置制御メカニズムの解明を目指した肘関節トルク—角度
—筋活動度関係の解析—

抄録

It is well known that contracting muscles have elastic and viscous properties, which change widely with the level of muscle activation. Zeffiro reported that the torque generated by contraction of the triceps brachii muscle in a monkey increased with an increase in elbow angle, just as does an elastic spring. Recently we have investigated torque-angle relations in flexor and extensor muscles of the human elbow under static conditions. The properties of the extensor were similar to Zeffiro’s results. The properties of the flexor, however, did not show a simple elastic property; torque increased and then decreased with increasing elbow angle.
The viscous property of the muscle could be explained in terms of a force-velocity relation. We estimated the torque-angular velocity relation in elbow extensor muscles; torque decreased with increasing angular velocity of extension, which was in agreement with common force-velocity relations of the muscle.
There were few previous investigations of torque-angle relations of the flexor muscle in voluntary flexion movements. The relation would be a key for understanding the control mechanism of upper arm posture.
The purpose of the present study was to obtain and to examine the relations with the constant muscle activation. It is almost impossible for the subject to maintain constant muscle activation during flexion movements. We have utilized a new artificial network technique to overcome this difficulty. In the present study, the torque-angle relations of the elbow flexor muscles showed very fascinating aspects; the stiffness (torque/angle) was negative at the zero velocity and positive at non-zero velocity of flexion.
The experiments were performed with three normal subjects (male, aged 22-25). The task was isovelocity flexion of the elbow joint in a horizontal plane at the height of the shoulder. The subject was asked to hold the elbow joint at a fully extended position (elbow angle was almost zero) against the load torque, and then to flex the elbow joint at a constant velocity to about 120 degrees. In the holding experiments, he was asked to hold the forearm at the desired angle against the load torque. Surface electromyograms (EMGs), elbow joint angle, and torque were measured. Applied torques were approximately 0, 5, 10, and 15% of MVC (maximum voluntary contraction at an angle of about 90 degrees). The flexion velocities were 30, 60, and 90 deg/s. The measurements were repeated at least 10 times for one experimental condition. EMGs were recorded from six muscles: brachialis, caput longum bicipitis brachii, caput breve bicipitis brachii, brachioradialis, caput laterale triceps brachii, and caput longum triceps brachii. A pair of Ag-AgCl surface electrodes (10 mmφ) were put on the skin over each muscle. EMGs were full-wave rectified and then low-pass filtered with a cutoff frequency of 35 Hz. In order to obtain IEMG, this filtered signal was further running averaged over the time span during which the joint angle changed approximately 0.5 degree. Note that in the present study, steady state behaviors were examined.
A three-layer artificial neural network was constructed with inputs of the elbow joint angle, flexion velocity, and six-channel IEMGs, and the output was elbow joint torque. The activation function of the input units was linear, and that of the hidden and output units was sigmoid. The appropriate number of hidden units was determined by varying both the number and the initial connection weight with back propagation learning.
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