Single-Sensor Gait Waveform Extraction for Bilateral Event Detection
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Solution Overview
Problem
Existing gait detection methods struggle to accurately detect detailed gait events, particularly in the swing phase, using a single sensor, and require multiple sensors for precise analysis, limiting their ability to provide comprehensive gait information.
Innovation Solution
A detection device that generates time-series data from sensor data related to foot movement and extracts a gait waveform, allowing for the detection of gait events in both feet using a sensor attached to one foot, enabling detailed gait event detection without the need for multiple sensors.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If multiple sensors are used to detect gait events in both feet, then measurement precision is improved, but device complexity increases
Solution Approach 1:
The patent uses signal processing to create a virtual copy of the gait waveform from a single sensor, allowing inference of the other foot's gait events without physical duplication of sensors. The processed signal mimics what would be detected by a second sensor, enabling comprehensive bilateral gait analysis with minimal hardware.
Solution Approach 2:
A single sensor is designed to perform multiple functions: detecting gait events for both feet, identifying stance and swing phases, and providing data for gait analysis. The sensor system is engineered to extract comprehensive gait information from one location, eliminating the need for separate sensors on each foot.
2Measurement precision
If pressure-sensitive sensors are used in insoles, then stance phase data is acquired, but swing phase data cannot be obtained
Solution Approach 1:
The system performs preliminary signal processing on the single sensor's output to predict and identify swing phase events before they are directly measurable. By analyzing the temporal patterns and characteristics of the gait waveform, the system proactively determines swing phase timing and characteristics without requiring direct measurement during this phase.
Solution Approach 2:
The patent introduces an intermediary signal processing layer that transforms the limited single-sensor data into comprehensive gait information. This intermediary processing layer infers swing phase characteristics from the stance phase signal patterns, acting as a mediator that bridges the measurement gap and restores complete gait cycle information.
3Adaptability or versatility
If uniaxial acceleration sensors are attached to body parts, then walking motion analysis is possible, but detailed gait event information cannot be obtained
Solution Approach 1:
The patent segments the gait cycle into distinct phases (stance and swing) and identifies specific gait events within each phase by analyzing characteristic patterns in the acceleration signal. This segmentation allows detailed examination of individual events such as heel strike, mid-stance, and toe-off, providing granular gait information from the general motion data.
Solution Approach 2:
The system changes the analysis parameters by transforming raw acceleration data into normalized gait waveforms and identifying specific temporal patterns. By adjusting the parameter extraction method to focus on characteristic acceleration patterns during different gait phases, the system reveals detailed event information that is not immediately apparent in the raw signal.
Data Source
AI summary
In order to detect a detailed walking event in both legs on the basis of a physical quantity that relates to leg motion measured by a sensor mounted on one leg, there is provided a detection device including: an extraction unit for generating time-series data that accompany walking, using sensor data based on a physical quantity that relates to leg motion measured by a sensor installed on one leg part of a walking person, and extracting a walking waveform from the generated time-series data; and a detection unit for detecting a walking event in both legs of the walking person from the walking waveform extracted by the extraction unit.