Redesign of a Biomechanical Energy Regeneration-based Robotic Ankle Prosthesis using Indonesian Gait Data

Edgar Buwana Sutawika (Mechanical Design Research Group, Faculty of Mechanical and Aerospace Engineering, Institut Teknologi Bandung)
I. Indrawanto (Mechanical Production Engineering Research Group, Faculty of Mechanical and Aerospace Engineering, Institut Teknologi Bandung, Jalan Ganesa No.10, Bandung 40132,)
F. Ferryanto (Mechanical Design Research Group, Faculty of Mechanical and Aerospace Engineering, Institut Teknologi Bandung)
Sandro Mihradi (Mechanical Design Research Group, Faculty of Mechanical and Aerospace Engineering, Institut Teknologi Bandung, Jalan Ganesa No.10, Bandung 40132)
Andi Isra Mahyuddin (Mechanical Design Research Group, Faculty of Mechanical and Aerospace Engineering, Institut Teknologi Bandung, Jalan Ganesa No.10, Bandung 40132)

Journal of Engineering and Technological Sciences
Vol. 53 No. 4 (2021)

In this research, the robotic ankle design from Arizona State University (ASU) known as SPARKy was redesigned to accommodate the specific needs of Indonesian people. Most active prosthetic legs are designed based on gait parameters for people from Western countries, which may differ for people from other cultures that have a different anthropometry and economic background. Indonesians have smaller actuating power characteristics compared to people from Western cultures due to their smaller average weight and body height. Thus, the applied design strategy took advantage of a biomechanical energy regeneration scheme to reduce the actuator input power requirement and the relatively smaller mechanical power of the typical Indonesian ankle to create a potentially affordable robotic ankle with a smaller actuator that meets the technical specifications. The specifications of the powered prosthetic ankle were determined through the same methods used by SPARKy. Only one low-level control system, to actuate normal walking, was designed and tested on a fully assembled robotic ankle. The test results indicated a promising low-level control, where the robotic ankle can follow the predetermined trajectory required to actuate normal walking based on Indonesian gait data.