Gait Characteristic Control via Wavelet Sensor Fusion
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Solution Overview
Problem
Current mobile and wearable devices face inaccuracies in monitoring gait characteristics due to variations in movement attributes, limiting their ability to accurately recognize activities and leverage user data effectively.
Innovation Solution
The integration of advanced sensor processing and data analysis methods, such as wavelet transforms, combined with sensor fusion techniques, to accurately determine gait characteristics and enable control of applications based on user movement, allowing for enhanced activity recognition and virtual environment interaction.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If current sensor processing methods are used, then device complexity is reduced, but measurement precision of gait characteristics deteriorates
Solution Approach 1:
The patent introduces wavelet transforms as an intermediary mathematical tool to process sensor data. This intermediary method enables accurate extraction of gait characteristics from raw accelerometer signals without requiring complex hardware modifications, thus improving measurement precision while managing device complexity through software-based signal processing
Solution Approach 2:
The patent replaces complex mechanical sensor systems with advanced signal processing algorithms. By substituting hardware complexity with computational methods (wavelet transforms and sensor fusion), the system achieves high measurement precision for gait characteristics without proportionally increasing device complexity
2Measurement precision
If advanced sensor processing and wavelet transforms are implemented, then measurement precision of gait characteristics improves, but device complexity increases
Solution Approach 1:
The patent makes the mobile device's existing sensors multi-functional by applying universal signal processing techniques. The same accelerometer can be used for various activities (walking, running, jogging) and the wavelet transform methodology serves multiple purposes including noise filtering, feature extraction, and activity recognition, thereby improving measurement precision without proportionally increasing complexity
Solution Approach 2:
The patent changes the processing parameters of existing sensors through wavelet transforms and fusion algorithms. By modifying how sensor data is processed rather than changing the sensors themselves, the system achieves improved gait characteristic accuracy while avoiding the complexity of additional hardware components
Data Source
AI summary
Methods and apparatus for controlling any aspect of a virtual environment in a mobile or wearable device are described, where the user is performing a gait activity such as walking, jogging or running, and the controlling is performed leveraging the gait characteristics of the user. For example, the gait characteristics may include velocity and stride length, and the sensors utilized to obtain any contextual information may be accelerometers.