Gait Device Control via Signal Conditioning and Coordinate Transformation
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Solution Overview
Problem
Existing control systems for gait devices, such as prosthetic and robotic systems, face challenges in processing user signals quickly and accurately, leading to inadequate smooth and continuous control.
Innovation Solution
A method involving the measurement of kinematic and loading states, conditioning through integration, differentiation, filtering, and amplification, followed by coordinate transformation, and input into a reference function to calculate a desired reference command for actuators, enabling precise control of gait devices.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional control systems are used for gait devices, then device operation is achieved, but signal processing speed and accuracy are insufficient, resulting in discontinuous and non-smooth control
Solution Approach 1:
The patent applies preliminary action by pre-conditioning the state measurement through filtering, integration, and differentiation operations before the control decision is made. This preprocessing of signals ensures that when the control system processes user signals, they are already optimized for accuracy and speed, eliminating the need for time-consuming real-time corrections during actuation.
Solution Approach 2:
The patent introduces an intermediary conditioning system between the sensor and the actuator. This intermediary layer includes filtering operations that remove noise, integration operations that accumulate signal over time for better accuracy, and differentiation operations that enhance signal changes. This intermediary processing layer resolves the contradiction by improving signal quality without adding significant time delay.
2Stability of the object's composition
If conventional control methods are used, then basic control function is achieved, but smooth and continuous control is not provided
Solution Approach 1:
The patent ensures continuity of useful action by continuously conditioning the state measurement through filtering and integration operations. Rather than discrete control updates, the system maintains continuous signal processing that smooths transitions and eliminates abrupt changes in actuator movement, providing stable and continuous control throughout the gait cycle.
Solution Approach 2:
The patent applies dynamics by making the control system adaptive through conditional processing. The filtering, integration, and differentiation operations dynamically adjust the signal based on the current state, allowing the system to respond smoothly to changing conditions during gait while maintaining overall control stability without requiring overly complex static control structures.
3Measurement precision
If state measurement is used directly without conditioning, then processing is simple, but noise and inaccuracies are present causing sudden jumps and oscillations
Solution Approach 1:
The patent applies preliminary action by pre-conditioning the state measurement through filtering, integration, and differentiation operations before the control decision is made. This preprocessing of signals ensures that when the control system processes user signals, they are already optimized for accuracy and speed, eliminating the need for time-consuming real-time corrections during actuation.
Solution Approach 2:
The patent introduces an intermediary conditioning system between the sensor and the actuator. This intermediary layer includes filtering operations that remove noise, integration operations that accumulate signal over time for better accuracy, and differentiation operations that enhance signal changes. This intermediary processing layer resolves the contradiction by improving signal quality without adding significant time delay.
Data Source
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AI summary
Methods for controlling gait devices include measuring kinematic and/or loading states of limb or robotic segments; conditioning the resulting state measurement by any combination or order of integration, differentiation, filtering, and amplification; transforming conditioned state measurements by coordinate transformation; optionally conditioning the transformed state measurements a second time in a manner similar to the first conditioning step; and using the transformed or conditioned transformed state measurements as independent variables in a predetermined reference function to calculate a desired reference command for any number of actuators.