Novel soft bending actuator based power augmentation hand exoskeleton controlled by human intention

Al-Fahaam, H; Davis, ST; Nefti-Meziani, S; Theodoridis, T

Abstract

This article presents the development of a soft material power augmentation wearable robot using novel bending soft artificial muscles. This soft exoskeleton was developed as a human hand power augmentation system for healthy or partially hand disabled individuals. The proposed prototype serves healthy manual workers by decreasing the muscular effort needed for grasping objects. Furthermore, it is a power augmentation wearable robot for partially hand disabled or post-stroke patients, supporting and augmenting the fingers’ grasping force with minimum muscular effort in most everyday activities. This wearable robot can fit any adult hand size without the need for any mechanical system changes or calibration. Novel bending soft actuators are developed to actuate this power augmentation device. The performance of these actuators has been experimentally assessed. A geometrical kinematic analysis and mathematical output force model have been developed for the novel actuators. The performance of this mathematical model has been proven experimentally with promising results. The control system of this exoskeleton is created by hybridization between cascaded position and force closed loop intelligent controllers. The cascaded position controller is designed for the bending actuators to follow the fingers in their bending movements. The force controller is developed to control the grasping force augmentation. The operation of the control system with the exoskeleton has been experimentally validated. EMG signals were monitored during the experiments to determine that the proposed exoskeleton system decreased the muscular efforts of the wearer.

Citation

Al-Fahaam, H., Davis, S., Nefti-Meziani, S., & Theodoridis, T. (2018). Novel soft bending actuator based power augmentation hand exoskeleton controlled by human intention. Intelligent Service Robotics, 11(3), 247-268. https://doi.org/10.1007/s11370-018-0250-4

• Journal Article Type: Article
• Acceptance Date: Apr 20, 2018
• Online Publication Date: Apr 28, 2018
• Publication Date: Apr 28, 2018
• Deposit Date: Apr 23, 2018
• Publicly Available Date: May 1, 2018
• Journal: Intelligent Service Robotics
• Print ISSN: 1861-2776
• Electronic ISSN: 1861-2784
• Publisher: Springer Verlag
• Volume: 11
• Issue: 3
• Pages: 247-268
• DOI: https://doi.org/10.1007/s11370-018-0250-4
• Publisher URL: http://dx.doi.org/10.1007/s11370-018-0250-4
• Related Public URLs: https://www.springer.com/engineering/control/journal/11370