Promise of a low power mobile CPU based embedded system in artificial leg control

Area of Science:

• Biomedical Engineering
• Computer Engineering
• Robotics

Background:

• Neural-machine interfaces (NMIs) are crucial for advanced prosthetics.
• Existing NMI systems often face power consumption and real-time processing challenges.
• Mobile processor technology offers potential for efficient embedded NMI solutions.

Purpose of the Study:

• To design and implement a low-power embedded system for NMI applications using mobile processor technology.
• To evaluate the system's ability to execute a complex NMI algorithm in real-time.
• To demonstrate the system's effectiveness for controlling artificial limbs.

Main Methods:

• Utilized Intel Atom™ Z530 Processor for a low-power embedded system.
• Implemented a neuromuscular-mechanical fusion and phase-dependent pattern classification NMI algorithm.
• Developed a highly optimized C program for the embedded system.

Main Results:

• The embedded NMI system achieved real-time performance with high accuracy in recognizing locomotion modes.
• The system demonstrated low power consumption (2.2 watts) and low CPU utilization (<4.3%).
• Optimized C implementation on the embedded system outperformed PC-based MATLAB implementations.

Conclusions:

• Mobile-CPU-based embedded systems are highly promising for advanced control of powered lower limb prostheses.
• The developed NMI embedded system meets real-time constraints and offers efficient processing.
• This technology enables more sophisticated and responsive artificial limb control.