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Joint Torque Estimation of Elbow joint using Neural Network Back Propagation Theory

Hye Youn Jang, Wan Soo Kim, Jung Soo Han, Chang Soo Han
JKSPE 2011;28(6):670-677.
Published online: June 1, 2011
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This study is to estimate the joint torques without torque sensor using the EMG (Electromyogram) signal of agonist/antagonist muscle with Neural Network Back Propagation Algorithm during the elbow motion. Command Signal can be guessed by EMG signal. But it cannot calculate the joint torque. There are many kinds of field utilizing Back Propagation Learning Method. It is generally used as a virtual sensor estimated physical information in the system functioning through the sensor. In this study applied the algorithm to obtain the virtual senor values estimated joint torque. During various elbow movement(Biceps isometric contraction, Biceps/Triceps Concentric Contraction (isotonic), Biceps/Triceps Concentric Contraction/Eccentric Contraction (isokinetic) ), exact joint torque was measured by KINCOM equipment. It is input to the (BP)algorithm with EMG signal simultaneously and have trained in a variety of situations. As a result, Only using the EMG sensor, this study distinguished a variety of elbow motion and verified a virtual torque value which is approximately(about 90%) the same as joint torque measured by KINCOM equipment.

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Joint Torque Estimation of Elbow joint using Neural Network Back Propagation Theory
J. Korean Soc. Precis. Eng.. 2011;28(6):670-677.   Published online June 1, 2011
Download Citation

Download a citation file in RIS format that can be imported by all major citation management software, including EndNote, ProCite, RefWorks, and Reference Manager.

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Joint Torque Estimation of Elbow joint using Neural Network Back Propagation Theory
J. Korean Soc. Precis. Eng.. 2011;28(6):670-677.   Published online June 1, 2011
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