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Depth Sensing for Improved Control of Lower Limb Prostheses.

Nili Eliana Krausz1, Tommaso Lenzi2, Levi J Hargrove3

  • 1Center for Bionic Medicine, Rehabilitation Institute of Chicago, Chicago, IL, USA.

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Summary

This study introduces a novel stair segmentation system using depth sensing for powered lower limb prostheses. This technology accurately identifies stairs in real-time, enhancing prosthetic functionality for amputees.

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Area of Science:

  • Robotics
  • Biomedical Engineering
  • Computer Vision

Background:

  • Powered lower limb prostheses aim to improve amputees' quality of life by enabling daily activities.
  • Seamless ambulation mode recognition is crucial for advanced prosthetic function but remains a challenge.
  • Current systems rely on mechanical and EMG sensors, lacking environmental context.

Purpose of the Study:

  • To develop and validate a novel stair segmentation system using depth sensing.
  • To enhance intent recognition for powered lower limb prostheses by incorporating environmental data.
  • To improve prosthetic adaptability to diverse terrains and obstacles.

Main Methods:

  • Design and characterization of a stair segmentation system utilizing Microsoft Kinect depth sensing.
  • Static and dynamic tests to evaluate segmentation speed, accuracy, and robustness across various staircases.
  • Online walking tests to assess real-time performance and accuracy of stair parameter estimation.

Main Results:

  • The depth camera's resolution impacts segmentation speed and accuracy.
  • The algorithm demonstrated robustness across different staircase configurations.
  • Real-time stair segmentation achieved >5 frames/s, estimating distance, angle, step count, height, and depth with high accuracy.
  • Online tests showed approximately 98.8% accuracy in detecting stair approaches.

Conclusions:

  • Integrating depth sensing provides valuable environmental information for prosthetic control.
  • The proposed stair segmentation system enables accurate and real-time estimation of stair parameters.
  • This technology has the potential to significantly improve the safety and functionality of powered lower limb prostheses during ambulation.