Self-Paced Treadmill Belt Speed Control via Force Sensors
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Solution Overview
Problem
Existing self-paced treadmills rely on external devices for feedback, limiting their ability to accurately adjust belt speeds based on user leg motion, which affects stability and adaptation during locomotion, especially in split-belt conditions.
Innovation Solution
A system that combines feedback and feedforward processes using ground reaction force sensors to estimate current step speeds, applying a Kalman filter to generate a time-varying speed command for each treadmill belt, allowing for self-paced adjustment without external instrumentation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If external devices such as ultrasonic range finders or feedback-controlled locomotion interfaces are used to facilitate motion capture, then the ability to adjust belt speeds based on user position is improved, but the device complexity and requirement for additional instrumentation increases
Solution Approach 1:
The treadmill system uses its own built-in force sensors and existing infrastructure to automatically detect user position and adjust belt speeds without requiring external devices. The system serves itself by utilizing the force measurement capability already present in the treadmill structure to capture gait information and control the belts autonomously.
Solution Approach 2:
The force sensors originally designed for measuring ground reaction forces during gait analysis are simultaneously used for controlling the treadmill belt speeds. This multi-functional use of existing sensors eliminates the need for separate external devices, reducing system complexity while maintaining positioning accuracy.
2Extent of automation
If feedback algorithms are used to report on subject position relative to the treadmill, then automation of safety measures is improved, but the ability to accurately adjust belt speeds based on actual leg motion is limited
Solution Approach 1:
The system continuously monitors force sensor data during the gait cycle and uses this feedback to dynamically adjust belt speeds. The feedback algorithm processes real-time force measurements to determine user position and leg motion, automatically modifying belt parameters to match actual user movement rather than relying on pre-programmed safety rules alone.
Solution Approach 2:
The system replaces mechanical or external positioning devices with a computational approach that processes force sensor data to infer user position and leg motion. By substituting physical measurement devices with algorithmic analysis of existing sensor data, the system achieves more accurate leg motion detection while maintaining automation.
3Adaptability or versatility
If split-belt treadmill configurations are used to enable continuous speed adjustment, then adaptability to user performance is improved, but the stability and robustness of turning control during locomotion is compromised
Solution Approach 1:
The system dynamically adjusts belt speeds based on real-time force sensor feedback during the gait cycle. Rather than using fixed split-belt configurations, the belt speeds continuously adapt to match actual user leg motion, providing both the adaptability of variable speeds and the stability of motion-matched control throughout the walking cycle.
Solution Approach 2:
The system changes belt speed parameters in response to detected gait phase and user position. By modulating belt parameters based on real-time force measurements and calculated position, the system achieves continuous adaptation while maintaining turning control stability through coordinated parameter adjustments that match natural locomotion patterns.
Data Source
AI summary
Systems and methods are provided for enabling a split belt treadmill having two belts to self-pace. A feedback process estimates a first current step speed for a user on each belt by measuring stride length and step duration. A feed-forward process estimates a second current step speed for the user on each belt by measuring three forces and three moment components associated with foot contact with the belt. A command speed for each belt is produced by combining the first and second current step speeds with a Kalman filter. A belt speed associated with each belt is adjusted based upon the command speed.