Equations for estimating the static supportive torque provided by upper-limb exoskeletons.

Area of Science:

• Biomechanics
• Human-Robot Interaction
• Ergonomics

Background:

• Industrial upper-limb exoskeletons are increasingly used.
• End-users lack detailed knowledge of exoskeleton support torque across various movements.
• Accurate support torque data is crucial for effective exoskeleton application.

Purpose of the Study:

• To develop and validate a methodology for quantifying the specific supportive torque of passive upper-limb exoskeletons.
• To provide predictive models for exoskeleton support torque based on upper-limb elevation angles.

Main Methods:

• Quantified support torque of four passive upper-limb exoskeletons using an isokinetic dynamometer.
• Conducted tests across all support ranges and levels (n=68) with repeated measures for reliability.
• Developed polynomial regression equations to predict support torque as a function of elevation angle.

Main Results:

• Demonstrated 'Good' to 'Excellent' between-session reliability for the measurement methodology (Intraclass Correlation Coefficients).
• Generated predictive equations for exoskeleton support torque across elevation angles from 10° to 180°.
• Identified one condition with lower reliability, warranting further investigation.

Conclusions:

• The presented methodology accurately quantifies exoskeleton support torque with high reliability.
• Predictive equations enable precise estimation of support for digital human modeling and exoskeleton selection.
• This work enhances the understanding and application of industrial upper-limb exoskeletons.