Development of a Single Leg Knee Exoskeleton and Sensing Knee Center of Rotation Change for Intention Detection

Area of Science:

• Robotics
• Biomechanics
• Assistive Technology

Background:

• Conventional bilateral exoskeletons may be inefficient for unilateral leg discomfort.
• Existing designs often have high inertia due to bulky actuators.
• Accurate real-time intention detection is crucial for effective exoskeleton control.

Purpose of the Study:

• To develop a single-leg knee joint assistance robot (exoskeleton).
• To reduce the inertial forces experienced by the wearer.
• To improve intention detection for naturalistic movement assistance.

Main Methods:

• Designed a lightweight, wire-driven actuator exoskeleton for the knee.
• Incorporated an adjustable lower frame length to accommodate complex knee movements.
• Utilized length between knee and ankle (LBKA) measurements for intention detection, alongside motor encoder data.
• Trained a neural network to classify user intentions for stair ascending, stair descending, and walking.

Main Results:

• The wire-driven actuator and lightweight materials significantly reduced the exoskeleton's inertia.
• The adjustable frame length allowed for better alignment with knee joint kinematics.
• LBKA measurements provided faster and more responsive data for intention detection compared to motor encoders alone.
• The neural network achieved accurate intention detection across various environments and movements.

Conclusions:

• The developed single-leg knee exoskeleton offers a promising solution for unilateral leg assistance.
• The novel LBKA measurement technique enhances the responsiveness and accuracy of intention detection.
• This approach has the potential to improve user experience and functional mobility for individuals with leg impairments.