Mobile Device Kinematic Parameter Determination Using Wavelet Transforms
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Solution Overview
Problem
Existing methods for determining user dynamics and contextual information, such as satellite-based systems and computer vision, are power-hungry, inaccurate in urban areas, and costly, especially in indoor environments, and require sophisticated setups that are not suitable for real-time applications on mobile devices.
Innovation Solution
A method using adaptable algorithms and sensor fusion techniques on mobile devices to process signals from available sensors like accelerometers, optimizing sampling frequency for performance and power consumption, and applying wavelet transforms to derive user dynamics and localization information, which can be displayed in real-time on the device.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If satellite-based systems are used to determine location and velocity, then location information can be obtained, but power consumption is very high and accuracy is low in urban areas and indoor environments
Solution Approach 1:
The patent replaces satellite-based electromagnetic signal systems with an inertial measurement system using accelerometers, gyroscopes, and magnetometers. This mechanical/sensor-based substitution eliminates dependency on satellite signals, enabling accurate location and velocity determination indoors and in urban canyons without the high power consumption of continuous GPS reception.
Solution Approach 2:
The patent introduces inertial sensors as intermediary devices that measure physical motion parameters (acceleration, orientation, magnetic field) to indirectly determine location and velocity. This intermediary measurement approach provides continuous accurate tracking without requiring external satellite signals, resolving the contradiction between accuracy in denied environments and power consumption.
2Measurement precision
If computer vision based systems with multiple cameras and markers are used, then accurate body movement measurements can be delivered, but the setup is laborious, expensive, space-constrained and difficult to implement in real-time applications
Solution Approach 1:
The patent extracts the essential measurement function from complex computer vision systems by using only inertial sensors embedded in a mobile device. This extraction eliminates the need for multiple cameras, markers, and sophisticated lab environments, retaining measurement capability while dramatically reducing system complexity and enabling real-time portable application.
Solution Approach 2:
The patent makes the mobile device itself the measurement instrument through embedded inertial sensors. The device autonomously captures its own motion data without requiring external observation systems, markers, or complex setup infrastructure, enabling self-contained real-time measurement anywhere the device can be carried.
3Reliability
If sophisticated wearable sensors are used for monitoring human gait, then contextual information can be obtained, but hardware requirements raise the cost of the system
Solution Approach 1:
The patent makes standard mobile device sensors (accelerometer, gyroscope, magnetometer) perform multiple functions including location tracking, velocity determination, and gait analysis. This universal utilization of existing sensors eliminates the need for specialized expensive wearable sensor packages, reducing hardware costs while maintaining reliable contextual monitoring capability.
4Productivity
If sensors are processed to provide contextual information in real-time, then user dynamics information is available directly to the user, but processing requirements increase power consumption
Solution Approach 1:
The patent applies selective processing of sensor data by focusing computational resources on extracting only the essential gait parameters (velocity, stride length, cadence) from accelerometer signals using wavelet transforms and signal filtering. This partial processing approach provides real-time useful information while minimizing unnecessary computational overhead and power consumption compared to comprehensive sensor fusion algorithms.
Data Source
AI summary
Some embodiments of the invention provide methods and apparatus for generating a user's contextual information using a mobile or wearable device. In some embodiments, obtaining the user's contextual information comprises obtaining sensors information, and applying a transformation to the sensors signals, wherein the transformation to the sensors signals comprises the use of wavelets, and the sensors comprise an accelerometer.