Workout Data Segmentation and Comparison for Fitness Insights
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current electronic devices lack the capability to effectively analyze and provide descriptive insights into user workout records, failing to offer meaningful data analysis and reward systems that motivate users to maintain a consistent workout routine.
Innovation Solution
An electronic device equipped with a sensor circuit, processor, and memory that classifies workout data into sections, compares them, and provides descriptive information, along with a reward system based on user performance, to enhance user engagement and understanding of their workout progress.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If workout data is collected and stored without analysis, then data quantity increases, but data usefulness and user insight remain insufficient
Solution Approach 1:
The patent divides workout data into multiple sections based on different criteria (time intervals, intensity levels, activity types). This segmentation transforms raw data into structured, analyzable units that can be processed more effectively, resolving the contradiction between data quantity and data usefulness by making the data systematically organized rather than merely accumulated.
Solution Approach 2:
The system provides feedback by comparing workout sections with each other and generating descriptive information about performance. This feedback mechanism converts raw data into actionable insights, addressing the information loss problem by ensuring that collected data actually contributes to user understanding and improvement.
2Loss of information
If detailed workout analysis is provided, then user insight improves, but processing time and computational resources increase
Solution Approach 1:
By segmenting workout data into manageable sections, the system can process and analyze smaller units independently and more efficiently. This reduces the computational burden compared to analyzing entire workout sessions at once, thereby decreasing processing time while still providing comprehensive insights through the aggregation of section-level analyses.
Solution Approach 2:
The patent selects specific sections for detailed comparison and analysis rather than processing every single data point uniformly. This partial action approach focuses computational resources on the most meaningful segments, providing sufficient user insight without the excessive processing time that would result from exhaustive analysis of all data.
3Measurement precision
If workout data is divided into multiple sections for analysis, then analysis precision improves, but system complexity increases
Solution Approach 1:
The segmentation principle is applied to divide workout data into distinct sections based on meaningful criteria. This creates a structured framework that improves analysis precision by allowing focused comparison of specific segments, while the segmentation rules themselves provide a manageable complexity level through clear classification criteria.
Solution Approach 2:
The patent employs universal classification criteria that can be applied across different types of workout data and users. This multi-functional approach allows the same segmentation and comparison logic to work for various workout scenarios, reducing system complexity by avoiding the need for specialized processing rules for each situation while maintaining high analysis precision.
Data Source
AI summary
An electronic device is provided. The electronic device includes a sensor circuit configured to obtain workout associated data using at least one or more sensors, a processor electrically connected with the at least one or more sensors, and a memory electrically connected with the processor. The processor is configured to classify the obtained data for each kind, divide the data, which is classified for each kind, into a plurality of sections, compare the sections with each other and select at least one or more sections, and provide description information about the selected section.