Foot Step Counting via Stride Frequency Analysis
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Solution Overview
Problem
Existing wearable sports devices cannot implement foot step counting when worn on the foot, as they rely on wrist and waist placement for step counting functionality.
Innovation Solution
A method and apparatus that collect and process foot acceleration signals to extract stride frequency, allowing for the calculation of steps based on motion time intervals and stride frequency, using combined acceleration processing, state processing, and feature extraction techniques.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If existing step counting methods are used, then step counting can be implemented when worn on wrist or waist, but foot step counting cannot be implemented
Solution Approach 1:
The patent transforms the step counting problem from detecting step occurrences to calculating stride frequency. By changing the measurement parameter from binary step detection to continuous frequency analysis of acceleration signals, the system can accurately count foot steps when worn on the foot. The stride frequency is calculated through spectral analysis of the combined acceleration signal, and steps are derived from this frequency parameter rather than traditional threshold-based detection.
2Measurement precision
If foot acceleration signals are processed using traditional step counting algorithms, then device complexity remains low, but measurement precision deteriorates due to inability to accurately capture foot motion characteristics
Solution Approach 1:
The patent replaces traditional mechanical threshold-based step detection with spectral analysis methods. Instead of using simple acceleration thresholds to detect steps, the system performs Fast Fourier Transform (FFT) on the combined acceleration signal to obtain stride frequency. This substitution of detection methodology significantly improves measurement precision by capturing the periodic nature of foot motion, while the complexity is managed through efficient signal processing algorithms.
Solution Approach 2:
The patent creates a universal step counting algorithm that works for both walking and running scenarios without requiring separate detection mechanisms. The combined acceleration signal processing and spectral analysis approach naturally adapts to different motion patterns, making the system multi-functional for various exercise types while maintaining a unified processing framework that manages complexity.
Data Source
AI summary
A method includes: collecting an original signal in a specified time interval, and performing combined acceleration processing on the original signal to obtain a combined acceleration signal; performing state processing on the combined acceleration signal to obtain a motion time interval, and extracting a plurality of feature groups from the combined acceleration signal according to a preset motion rule; and performing screening on the plurality of feature groups to obtain a first feature group, extracting a median value from the first feature group, and obtaining a stride frequency in the specified time interval based on the median value and a collection frequency, and obtaining a quantity of steps through calculation based on the motion time interval and the stride frequency.