Wearable Robot Gait Phase Estimation Using Discrete Wavelet Transform
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Solution Overview
Problem
Current wearable robots face challenges in accurately estimating gait phase and identifying relevant biomechanical events due to limitations in sensor durability and invasiveness, particularly in real-life applications, where external sensory systems can hinder portability and usability.
Innovation Solution
A gait phase estimation system for wearable robots using Discrete Wavelet Transform (DWT) and adaptive oscillators, which processes hip joint angle signals to identify heel strike and toe-off events, eliminating the need for additional sensors and enhancing the integration of assistive torque profiles.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If external sensory systems (foot switches, pressure-sensitive insoles) are used for gait phase estimation, then measurement precision is improved, but device complexity and loss of portability worsen
Solution Approach 1:
The patent extracts the gait event detection functionality from external sensory systems and relocates it to the wearable robot's onboard processor. The system uses the encoder signals already present in the robot to detect gait events through signal processing algorithms, eliminating the need for separate foot switches or insoles while maintaining measurement precision.
Solution Approach 2:
The patent makes the existing encoder system multi-functional by using it both for robotic actuation control and for gait phase estimation. The same encoder signals that drive the robot's movement are also processed to identify gait events, thereby eliminating the need for dedicated external sensors and reducing overall system complexity.
2Reliability
If repeated calibrations are performed for sensor durability, then reliability is improved, but loss of time increases
Solution Approach 1:
The patent implements a self-calibrating system where the wearable robot automatically adapts to the user's gait pattern without requiring manual calibration. The system uses adaptive oscillators and signal processing to continuously track gait phase, automatically adjusting to different walking speeds and patterns, thereby eliminating the need for repeated manual calibrations and reducing time loss.
3Ease of operation
If integrated sensors are used to minimize invasiveness, then ease of operation is improved, but measurement precision may worsen
Solution Approach 1:
The patent replaces mechanical sensor systems (foot switches, pressure insoles) with an electronic signal processing approach. Instead of using additional physical sensors on the user's body, the system processes existing encoder signals through algorithms including adaptive oscillators and gait event detection, achieving both comfort and precision.
Solution Approach 2:
The patent changes the approach from direct mechanical sensing to signal parameter analysis. By transforming encoder signals into gait phase information through adaptive oscillators and detecting events through signal characteristics changes, the system maintains measurement precision while using minimally invasive integrated sensors.
Data Source
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AI summary
A wearable robot and method for controlling the wearable robot having at least one leg unit involves: (a) obtaining at least one input signal from at least one encoder tracking a hip joint angle versus time with the at least one encoder attached to the wearable robot and corresponding to the at least one leg unit; (b) windowing the at least one input signal within a window size based on time versus the hip joint angle; (c) decomposing the at least one input signal with a Discrete Wavelet Transform (DWT); (d) identifying at least one gait event in a gait cycle by using the DWT; (e) computing temporal gait parameters based on the at least one gait event; (f) generating an assistive force in the at least one leg unit in response to the temporal gait parameters.