Establishing moment-angle equations to predict low back exoskeleton support moment

Abstract

Exoskeletons have emerged as a promising technology for potentially mitigating the risk of injuries by providing mechanical support and reducing loads on the body. There are a variety of low back passive exoskeletons currently available. While manufactures do provide specifications on the peak supportive moment capabilities, little is known about their moment-angle relationship through their full range of motion. This information is valuable when deciding on which exoskeleton best supports the task demands on job. This study aimed to develop moment-angle equations for two passive low back support exoskeletons (SuitX BackX and Laevo V2.5). These equations can provide valuable insights into the mechanical behavior and the extent of supportive moment delivered by passive low-back support exoskeletons during dynamic tasks. These equations can be used from a preventative perspective to help practitioners understand how much support may be provided given task and operator characteristics. For experimental data collection, we secured exoskeletons on a dynamometer (Biodex System 4) and loaded in a full range of motion with five different loading rates, i.e., 5, 10, 20, 30, 45, and 60 deg/sec. Results show polynomial regression equations for each exoskeleton, motion, support setting and angular velocity which were determined based on low mean square error and high-squared values. Implications for this work include integration within digital human modeling technology to help determine the need for exoskeleton implementation as a tool that can reduce the risk of work-related musculoskeletal injury.