Wearable Device Wear Detection Using Dual Transducer Signal Correlation
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Wearable electronic devices continue to consume power unnecessarily when not being worn, as they lack an effective method to detect whether they are in use or not.
Innovation Solution
A method and device utilizing two transducers, such as microphones or accelerometers, to differentiate between ambient and body-conducted sound signals, generating correlation signals to determine if the device is being worn by comparing signal energies and correlations during voiced and unvoiced speech periods, with thresholds determining the device's wear status.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If the device continues to operate without wear detection, then the device remains ready for immediate use, but unnecessary battery power is consumed when not being worn
Solution Approach 1:
The device automatically detects its own wear status using onboard transducers and signal processing algorithms, eliminating the need for manual user input. The system monitors acoustic and vibration signals to determine whether it is being worn, and autonomously adjusts its operational state accordingly, enabling it to serve itself in wear detection and power management.
Solution Approach 2:
The device performs periodic wear detection by analyzing speech signals at specific intervals (e.g., during voiced and unvoiced speech periods). Instead of continuous monitoring, the system uses periodic correlation analysis between transducer signals to determine wear status, reducing overall power consumption while maintaining effective detection capability.
2Measurement precision
If wear detection is implemented using multiple transducers and signal processing, then accurate wear status determination is achieved, but device complexity increases
Solution Approach 1:
The wear detection process is segmented into distinct phases: voiced speech detection, unvoiced speech detection, and correlation analysis. Each phase processes specific signal characteristics separately, allowing the system to achieve high detection accuracy through structured analysis while managing complexity by breaking down the overall task into manageable segments with clear boundaries.
Data Source
AI summary
A method is used for detecting whether a device is being worn, when the device comprises a first transducer and a second transducer. It is determined when a signal detected by at least one of the first and second transducers represents speech. It is then determined when said speech contains speech of a first acoustic class and speech of a second acoustic class. A first correlation signal is generated, representing a correlation between signals generated by the first and second transducers during at least one period when said speech contains speech of the first acoustic class. A second correlation signal is generated, representing a correlation between signals generated by the first and second transducers during at least one period when said speech contains speech of the second acoustic class. It is then determined from the first correlation signal and the second correlation signal whether the device is being worn.