Apparel Sensor Housings With Location-Based Algorithm Selection
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Solution Overview
Problem
Existing athletic activity systems struggle to provide personalized and engaging experiences, often using generic algorithms that are not accurate for individual users, leading to decreased motivation and interest in exercise.
Innovation Solution
The system includes electronic modules that calculate athletic activity parameters using location information to select appropriate algorithms, utilizing removable housings with identification memories and sensors to track user-specific data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If generic algorithms are used to track athletic performance, then the system can work with a wide range of individuals, but the accuracy of performance data is reduced
Solution Approach 1:
The system dynamically selects algorithms based on real-time sensor data patterns and user characteristics detected during exercise. The algorithm selection is not static but adapts during the athletic activity based on measured parameters such as motion patterns, heart rate responses, and activity intensity, thereby maintaining both broad compatibility and high accuracy for individual users.
Solution Approach 2:
The system changes algorithmic parameters based on user-specific data collected during exercise sessions. By analyzing sensor data patterns and adjusting algorithm parameters dynamically, the system tailors the calculation methods to match individual user characteristics while maintaining compatibility across diverse user populations.
2Measurement precision
If location information is used to select algorithms, then measurement accuracy is improved, but device complexity increases
Solution Approach 1:
The system pre-establishes multiple algorithm options and their selection criteria before athletic activity begins. Location information and user profiles are pre-configured with associated algorithms, so during exercise the system simply needs to match current conditions to pre-defined algorithm selections rather than making complex real-time decisions, thereby reducing operational complexity while maintaining accuracy.
3Adaptability or versatility
If personalized tracking is implemented, then user engagement and motivation are enhanced, but system complexity increases
Solution Approach 1:
The system segments the algorithm selection process into distinct modules: location-based selection, activity-type selection, and user-profile-based selection. Each module handles a specific aspect of personalization independently, making the overall system more manageable and less complex while still providing comprehensive personalized tracking capabilities.
Data Source
AI summary
Systems and methods are provided for calculating athletic activity parameters. Multiple housings are position at different locations on a user's body. The housings are configured to be removably engaged with an electronic module that includes a sensor and a processor configured to calculate athletic activity parameters. Each housing is connected to or includes an identification memory that stores information identifying a location of the housing. The electronic module uses the location information to select an algorithm to use when calculating the athletic activity parameters.