Step Detection Swing Compensation in Mobile Devices
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Solution Overview
Problem
Step detection in mobile devices is inaccurate due to the device being carried in various locations, such as a user's hand, leading to combined motion that complicates the detection of steps, especially when the device is swinging.
Innovation Solution
Implementing threshold detection, Eigen analysis, and hybrid frequency analysis to determine if the mobile device is swinging, which adjusts the step count and provides a level of certainty, using acceleration data and potentially gyroscopic data to differentiate between walking and swinging.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If step detection is performed using acceleration data from a mobile device carried in various locations, then the device can be used in multiple scenarios (hand, pocket, purse), but the step detection accuracy deteriorates due to combined motion and swinging
Solution Approach 1:
The system performs preliminary swing detection analysis before final step detection. By analyzing acceleration data patterns, eigenvalues, and frequency characteristics in advance, the system identifies swinging conditions and adjusts step detection parameters accordingly, preventing inaccurate step counts caused by arm swing motion
Solution Approach 2:
The system dynamically changes detection parameters based on detected motion patterns. When swinging is detected through acceleration threshold analysis or eigenvalue calculation, the system adjusts the step detection algorithm to compensate for the swinging motion, thereby maintaining accuracy across different carrying positions
2Ease of operation
If the mobile device is held in the user's hand for convenient access, then ease of operation improves, but step detection accuracy deteriorates due to arm swinging motion
Solution Approach 1:
The system converts the harmful effect of arm swinging into a detectable pattern. By analyzing the characteristic acceleration patterns, eigenvalues, and frequency content of swinging motion, the system identifies when swinging occurs and compensates for it in the step detection algorithm, thereby maintaining accuracy even when the device is held in the hand
3Measurement precision
If swing detection algorithms are implemented to improve step detection accuracy, then measurement precision improves, but device complexity increases due to additional processing requirements
Solution Approach 1:
The system implements a tiered approach to swing detection. It first performs simple acceleration threshold analysis to identify potential swinging conditions, then applies more complex eigenvalue analysis or frequency analysis only when needed. This partial application of complex algorithms reduces overall processing complexity while maintaining detection accuracy
Data Source
AI summary
Step detection accuracy in mobile devices is increased by determining whether swinging is taking place. According to the invention, swinging can be detected using threshold detection, Eigen analysis, hybrid frequency analysis, and/or gyroscope-based analysis, for example. The determination that swinging is (or may be) occurring can impact how the mobile device reports detected steps for step detection. A count of missteps and/or a level of certainty, based on swing detection, can be provided with a step count.