MEMS Sensor Motion Detection via Moment Difference Analysis
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Solution Overview
Problem
Microelectromechanical systems (MEMS) sensors in mobile devices are prone to bias and sensitivity errors due to environmental changes, leading to inaccurate data and complicating sensor fusion processes, particularly in devices with limited computational resources and battery constraints.
Innovation Solution
A method involving the computation of differences between pairs of sensor samples, subtraction of expected higher order moments, and comparison to a threshold to determine device motion and calibrate sensors efficiently, allowing for reduced processing overhead and power consumption.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If sensor calibration operations are performed to characterize bias or sensitivity error, then measurement precision is improved, but loss of time increases due to the calibration duration
Solution Approach 1:
The system performs preliminary motion detection analysis using moment calculations to determine whether calibration conditions are met before initiating full calibration operations. By evaluating the fourth order moment difference in advance, the system can quickly identify when the device is stationary and ready for calibration, avoiding unnecessary calibration during motion and thus reducing overall calibration time while maintaining precision.
2Measurement precision
If sensor fusion involving multiple sensor systems is used, then measurement precision is improved, but use of energy increases due to higher computational requirements
Solution Approach 1:
The system applies partial action by using moment-based motion detection as a filtering mechanism before engaging full sensor fusion processing. Instead of continuously running computationally intensive sensor fusion algorithms, the system only activates them when the moment calculation indicates stationary conditions, thereby reducing overall energy consumption while maintaining measurement precision when needed.
3Reliability
If continuous sensor monitoring is performed to detect motion, then reliability of motion detection is improved, but productivity decreases due to increased processing overhead
Solution Approach 1:
The system extracts only the essential information needed for motion detection by calculating moments from sensor data rather than processing the complete raw sensor streams. By focusing computation on the fourth order moment difference, the system achieves reliable motion detection with significantly reduced processing overhead compared to analyzing all sensor data continuously.
Data Source
AI summary
Systems and methods are disclosed for characterizing motion of a device by taking the difference between pairs of sensor signal samples and comparing an expected higher order moment for the differences determined from an observed first order moment for the differences and/or an observed second order moment for the differences and the observed higher order moment for the differences. A determination of whether the device is experiencing motion may be made based on a comparison of the difference of the moments to a threshold.