Methodology for Selecting the Appropriate Electric Motor for Robotic Modular Systems for Lower Extremities

Area of Science:

• Biomedical Engineering
• Robotics
• Rehabilitation Technology

Background:

• Hybrid robotic rehabilitation systems combining functional electrical stimulation (FES) and exoskeletons show promise for lower limb motor function recovery.
• Accurate motor selection for robotic exoskeletons is critical for effective walking assistance in individuals with mobility impairments and the elderly.

Purpose of the Study:

• To investigate and present an improved method for calculating joint torques in robotic exoskeletons.
• To propose a mathematical model for precise torque calculation to aid in selecting appropriate servo motors for exoskeleton joints.

Main Methods:

• Developed an extended mathematical model incorporating static and dynamic human body segment parameters (length, mass, center of mass, etc.).
• Integrated previous models (Zatsiorsky BSP, Dempster BSP, forward kinematics) into the new model.
• Presented an analytic method to utilize model results for selecting servo motors based on calculated joint torques.

Main Results:

• The proposed method yielded deviations from typical torque calculation methods, providing a more accurate understanding of motor requirements.
• Enabled better motor selection, avoiding underpowered or oversized actuators for exoskeleton joints.
• The study offers a tool with an embedded library for researchers to replicate findings and configure parameters.

Conclusions:

• The novel mathematical model and analytic method enhance the precision of motor selection for hybrid exoskeleton joints.
• This approach improves the design and functionality of robotic exoskeletons for mobility assistance and rehabilitation.
• Researchers gain a valuable tool for optimizing actuator choices in robotic articulated systems.