Wearable Swimming Style Detection via Axis-Specific Acceleration Analysis
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing methods for determining swimming style during swimming training do not accurately differentiate between styles, leading to inappropriate processing and output of evaluation index information such as calorie consumption, pulse wave, and stroke information, and fail to adapt music reproduction to match the swimming style.
Innovation Solution
A wearable apparatus and information processing method that acquires user data, determines swimming style through principal component analysis, and outputs evaluation index information correlated with each style, allowing for accurate processing and adaptive music reproduction based on detected body motion and biological signals.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If swimming style determination is performed without considering sensitivity axis direction, then the determination process is simpler, but the accuracy of swimming style determination deteriorates
Solution Approach 1:
The patent changes the parameter used for swimming style determination from simple acceleration magnitude to acceleration components along specific sensitivity axes. By selecting appropriate sensitivity axes based on the determined swimming style, the system achieves more accurate determination while maintaining reasonable process complexity through systematic axis selection rules.
2Measurement precision
If all correlation coefficients in three axes are obtained and added together, then swimming style determination can be performed, but the processing load becomes considerable
Solution Approach 1:
The patent extracts only the necessary correlation coefficients from the three axes rather than processing all of them. By selecting correlation coefficients corresponding to specific sensitivity axes that have been determined through preliminary analysis, the system reduces the processing load while maintaining sufficient accuracy for swimming style determination.
Solution Approach 2:
The patent segments the three-axis acceleration data into specific sensitivity axis components. Instead of treating all three axes equally, the system identifies and processes only the relevant axis components for each swimming style, dividing the complex processing task into manageable segments based on swimming style characteristics.
3Device complexity
If evaluation index information is output without correlation to swimming style, then the output process is simpler, but the usefulness and accuracy of the information deteriorates
Solution Approach 1:
The patent merges swimming style determination results with evaluation index information output. By combining the swimming style label with the evaluation indices (calorie consumption, pulse wave, stroke information), the system provides enriched information that maintains context while avoiding excessive complexity in the output process through structured combination rules.
4Device complexity
If music reproduction is not adapted to swimming style, then the music player is simpler, but the training efficiency and motivation are reduced
Solution Approach 1:
The patent introduces dynamic adaptation of music reproduction based on detected swimming style. Instead of using a fixed or random music selection, the system dynamically selects and reproduces music that matches the current swimming style, making the music player adaptive and responsive to user activity while maintaining reasonable system complexity through style-based selection rules.
Data Source
AI summary
An information processing method includes causing an information acquisition section to perform a process of acquiring user information including body motion information of a user, causing a processing section to perform a process of determining a swimming style of the user on the basis of the user information, and obtaining evaluation index information which is at least one of calorie consumption information, pulse wave information, and stroke information when the user swims in each swimming style, and causing an output section to output information in which the evaluation index information in each swimming style is correlated with each swimming style.