The design and mathematical modelling of novel extensor bending pneumatic artificial muscles (EBPAMs) for soft exoskeletons

Al-Fahaam, HSH; Davis, ST; Nefti-Meziani, S

Abstract

This article presents the development of a power augmentation and rehabilitation exoskeleton based on a novel actuator. The proposed soft actuators are extensor bending pneumatic artificial muscles. This type of soft actuator is derived from extending McKibben artificial muscles by reinforcing one side to prevent extension. This research has experimentally assessed the performance of this new actuator and an output force mathematical model for it has been developed. This new mathematical model based on the geometrical parameters of the extensor bending pneumatic artificial muscle determines the output force as a function of the input pressure. This model is examined experimentally for different actuator sizes. After promising initial experimental results, further model enhancements were made to improve the model of the proposed actuator. To demonstrate the new bending actuators a power augmentation and rehabilitation soft glove has been developed. This soft hand exoskeleton is able to fit any adult hand size without the need for any mechanical system changes or calibration. EMG signals from the human hand have been monitored to prove the performance of this new design of soft exoskeleton. This power augmentation and rehabilitation wearable robot has been shown to reduce the amount of muscles effort needed to perform a number of simple grasps.

Citation

Al-Fahaam, H., Davis, S., & Nefti-Meziani, S. (2017). The design and mathematical modelling of novel extensor bending pneumatic artificial muscles (EBPAMs) for soft exoskeletons. Robotics and autonomous systems, 99, 63-74. https://doi.org/10.1016/j.robot.2017.10.010

• Journal Article Type: Article
• Acceptance Date: Oct 15, 2017
• Online Publication Date: Nov 1, 2017
• Publication Date: Nov 1, 2017
• Deposit Date: Oct 18, 2017
• Publicly Available Date: Nov 1, 2018
• Journal: Robotics and Autonomous Systems
• Print ISSN: 0921-8890
• Publisher: Elsevier
• Volume: 99
• Pages: 63-74
• DOI: https://doi.org/10.1016/j.robot.2017.10.010
• Publisher URL: http://dx.doi.org/10.1016/j.robot.2017.10.010
• Related Public URLs: https://www.journals.elsevier.com/robotics-and-autonomous-systems