Assessment methodology for human-exoskeleton interactions: Kinetic analysis based on muscle activation

Area of Science:

• Biomechanics
• Robotics
• Human-Computer Interaction

Background:

• Exoskeleton development requires kinetic analysis, which traditionally involves complex equipment and lengthy data processing.
• Current methods for kinetic analysis, such as using force plates, are often resource-intensive and can be problematic in certain experimental setups.

Purpose of the Study:

• To present a novel methodology for calculating kinetic parameters (torque and power) without the need for ground reaction force measurements.
• To simplify and reduce the burden of kinetic analysis in exoskeleton development and assessment.
• To introduce new indices, Assistance in Torque (AMI) and Assistance in Power (API), for quantifying exoskeleton assistance.

Main Methods:

• Utilizing data from electromyography (EMG) and motion capture systems.
• Combining literature data with laboratory-collected data to analyze a larger number of cycles.
• Calculating kinetic parameters, including joint torques and powers, without relying on force plate measurements.

Main Results:

• The proposed method significantly reduces the number of instruments required for kinetic analysis.
• It allows for kinetic parameter calculation even when force sensors are not feasible.
• The method demonstrates high statistical validity and enables analysis over a greater number of cycles compared to traditional methods.

Conclusions:

• The new methodology provides an accessible and statistically robust approach to kinetic assessment in exoskeleton research.
• By simplifying the assessment process, this method can positively impact and accelerate exoskeleton development, aligning with User-Center Design principles.
• The introduced AMI and API indices offer valuable quantitative measures of exoskeleton assistance based on user kinematics and muscle activation.