An EMG-Driven Weight Support System With Pneumatic Artificial Muscles

In this paper, we introduce our newly developed biosignal-based vertical weight support system that is composed of pneumatic artificial muscles (PAMs) and an electromyography (EMG) measurement device. By using our developed weight support system, assist force can be varied based on measured muscle activities; most existing systems can only generate constant assist forces. In this paper, we estimated knee and ankle joint torques from measured EMGs using floating base inverse dynamics. Knee and ankle joint estimated torques are converted to vertical forces by the kinematic model of a subject. The converted vertical forces are used as force inputs for the PAM actuator system. To validate our system's control performance, four healthy subjects performed a one-leg squat with his left leg while his right leg was assisted by our proposed system. We used the vertical force estimated from the measured EMG signals as a control input to the weight support system. We compared EMG magnitudes with four different experimental conditions: 1) normal two-leg squat; 2) one-leg squat without the assist system; 3) one-leg squat with EMG-based weight support; and 4) one-leg squat with constant force support. The EMG magnitude with the proposed weight support system was much closer to that with normal two-leg squat than that with one-leg squat without the assist system and than that with one-leg squat with constant force support.

[1]  H. Hatze,et al.  A myocybernetic control model of skeletal muscle , 1977, Biological Cybernetics.

[2]  Jun Morimoto,et al.  XoR: Hybrid drive exoskeleton robot that can balance , 2011, 2011 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[3]  Takahiro Kagawa,et al.  Gait pattern generation for a power-assist device of paraplegic gait , 2009, RO-MAN 2009 - The 18th IEEE International Symposium on Robot and Human Interactive Communication.

[4]  Goro Obinata,et al.  Biomechanical analysis and muscle tension estimation of the lower extremities using EMG data , 2010, 2010 International Symposium on Micro-NanoMechatronics and Human Science.

[5]  D. Lloyd,et al.  An EMG-driven musculoskeletal model to estimate muscle forces and knee joint moments in vivo. , 2003, Journal of biomechanics.

[6]  Günter Hommel,et al.  Calibration of an EMG-Based Body Model with six Muscles to control a Leg Exoskeleton , 2007, Proceedings 2007 IEEE International Conference on Robotics and Automation.

[7]  J Ueda,et al.  Individual Muscle Control Using an Exoskeleton Robot for Muscle Function Testing , 2010, IEEE Transactions on Neural Systems and Rehabilitation Engineering.

[8]  Sybert H. Stroeve,et al.  Learning combined feedback and feedforward control of a musculoskeletal system , 1996, Biological Cybernetics.

[9]  O. Schmitt The heat of shortening and the dynamic constants of muscle , 2017 .

[10]  C. Kinnaird,et al.  Medial Gastrocnemius Myoelectric Control of a Robotic Ankle Exoskeleton , 2009, IEEE Transactions on Neural Systems and Rehabilitation Engineering.

[11]  Daniel P. Ferris,et al.  Learning to walk with a robotic ankle exoskeleton. , 2007, Journal of biomechanics.

[12]  K. Kiguchi,et al.  A Study on EMG-Based Control of Exoskeleton Robots for Human Lower-limb Motion Assist , 2007, 2007 6th International Special Topic Conference on Information Technology Applications in Biomedicine.

[13]  Daniel P. Ferris,et al.  A pneumatically powered knee-ankle-foot orthosis (KAFO) with myoelectric activation and inhibition , 2009, Journal of NeuroEngineering and Rehabilitation.

[14]  Stefan Schaal,et al.  Inverse dynamics control of floating base systems using orthogonal decomposition , 2010, 2010 IEEE International Conference on Robotics and Automation.

[15]  Kanji Inoue,et al.  Rubbertuators and applications for robots , 1988 .

[16]  Yasuhisa Hasegawa,et al.  Intention-based walking support for paraplegia patients with Robot Suit HAL , 2007, Adv. Robotics.

[17]  Günter Hommel,et al.  A Human--Exoskeleton Interface Utilizing Electromyography , 2008, IEEE Transactions on Robotics.

[18]  Darwin G. Caldwell,et al.  Braided Pneumatic Muscle Actuators , 1993 .

[19]  O. Sawodny,et al.  Cascaded control concept of a robot with two degrees of freedom driven by four artificial pneumatic muscle actuators , 2005, Proceedings of the 2005, American Control Conference, 2005..

[20]  Kazuo Kiguchi,et al.  EMG-based control for lower-limb power-assist exoskeletons , 2009, 2009 IEEE Workshop on Robotic Intelligence in Informationally Structured Space.

[21]  Yoshiyuki Sankai,et al.  Power assist control for walking aid with HAL-3 based on EMG and impedance adjustment around knee joint , 2002, IEEE/RSJ International Conference on Intelligent Robots and Systems.

[22]  Takayuki Koizumi,et al.  Development and control of pneumatic robot arm for industrial fields , 2011, IECON 2011 - 37th Annual Conference of the IEEE Industrial Electronics Society.

[23]  H. Kobayashi Development on wearable robot for human power support , 2002, IEEE 2002 28th Annual Conference of the Industrial Electronics Society. IECON 02.

[24]  Jun Morimoto,et al.  Brain-controlled exoskeleton robot for BMI rehabilitation , 2012, 2012 12th IEEE-RAS International Conference on Humanoid Robots (Humanoids 2012).

[25]  Hugh M. Herr,et al.  An ankle-foot emulation system for the study of human walking biomechanics , 2006, Proceedings 2006 IEEE International Conference on Robotics and Automation, 2006. ICRA 2006..

[26]  Youngho Kim,et al.  An EMG-based muscle force monitoring system , 2010 .

[27]  Yoshiyuki Sankai,et al.  Control method of robot suit HAL working as operator's muscle using biological and dynamical information , 2005, 2005 IEEE/RSJ International Conference on Intelligent Robots and Systems.