A Control Method for Transtibial Prostheses with Bilateral Leg Data.

Area of Science:

• Biomedical Engineering
• Robotics
• Neuroscience

Background:

• Micro-controlled lower limb prosthetics traditionally rely on sensors from the amputated side.
• Balanced walking requires coordinated neural control of both limbs for proper positioning and orientation.
• Existing prosthetic control systems may not fully capture the user's complete gait dynamics.

Purpose of the Study:

• To develop and evaluate a new control architecture for a transtibial prosthesis prototype.
• To investigate the use of bilateral limb data for improved prosthetic control.
• To enhance the precision and adaptability of prosthetic devices through a comprehensive understanding of gait states.

Main Methods:

• A control architecture was designed to integrate data from sensors on both the intact and amputated limbs.
• Two inertial measurement units (IMUs) were utilized: one on the left shank and one on the right thigh.
• A healthy subject performed walking trials on level ground at various speeds and an obstacle avoidance task with the transtibial prosthesis prototype.

Main Results:

• Bilateral sensor data provided comprehensive information on limb positioning and orientation.
• The controller effectively managed actuation timing for the prosthesis.
• The system demonstrated the ability to assist in precise prosthesis control by interpreting user gait states.

Conclusions:

• Incorporating data from both limbs significantly enhances the control capabilities of lower limb prosthetics.
• This bilateral approach offers a more holistic understanding of gait, leading to improved prosthetic function.
• The developed control architecture shows promise for more intuitive and responsive prosthetic limb control.