A novel human effort estimation method for knee assistive exoskeletons.

Area of Science:

• Biomechanics
• Robotics
• Wearable Technology

Background:

• Accurate estimation of knee joint torques is crucial for developing effective knee assistive devices.
• Existing methods often require extensive instrumentation, limiting wearability and portability.
• Minimizing sensor requirements can significantly improve the user experience and practical application of assistive technologies.

Purpose of the Study:

• To present a novel, low-sensing method for online estimation of knee joint torques.
• To enable the generation of reference signals for knee assistive devices.
• To demonstrate a minimalistic and ergonomic sensory system for torque estimation.

Main Methods:

• The method relies on measuring ground reaction forces and torques at the feet.
• It utilizes shank posture data and a shank biomechanical model to estimate knee torque.
• An equilibrium condition is imposed on the user's shank for torque calculation, independent of upper body or payload data.

Main Results:

• The proposed method accurately estimates knee torques with reduced sensing requirements.
• Experiments demonstrated effectiveness across various postures, motions (squat, foot contact changes), and payloads.
• The system proved effective even with dynamic changes in the center of mass (CoM) of a payload.

Conclusions:

• A novel, low-sensing method for online knee torque estimation has been successfully developed.
• The approach facilitates the creation of easily wearable and portable knee assistive devices.
• This technique offers a practical solution for generating control signals in assistive robotics and rehabilitation.