Body Fat Measuring Apparatus Using KNN User Pairing
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Solution Overview
Problem
Existing body fat measuring devices require users to repeatedly input their characteristic information, such as height, gender, and age, and often make mistakes in user pairing due to the use of single recorded weight and impedance values.
Innovation Solution
A body fat measuring apparatus that uses a KNN algorithm process to calculate distances between current and recorded data sets, sorts these distances, groups them, and pairs the user with the user name corresponding to the maximum result, eliminating the need for repeated input of user information and improving accuracy by using a wireless connection with a portable electronic device.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If single recorded weight and impedance values are used for user pairing, then device complexity is reduced, but user pairing accuracy deteriorates
Solution Approach 1:
The patent segments the user pairing process into multiple stages: first calculating distances between current measurements and all recorded profiles, then sorting these distances, selecting top K candidates, grouping by user name, and finally determining the best match. This segmentation transforms a simple single-value comparison into a multi-step sophisticated matching process that maintains accuracy while managing complexity through structured procedure.
Solution Approach 2:
The patent transitions from single-dimensional comparison (one recorded weight and impedance) to multi-dimensional analysis by storing multiple recorded analysis data sets per user, each containing weight, impedance, and timestamp. This dimensional expansion enables more accurate user identification by considering historical data patterns rather than relying on a single measurement point.
2Measurement precision
If users repeatedly input characteristic information, then measurement precision is maintained, but ease of operation deteriorates
Solution Approach 1:
The system implements self-service by automatically retrieving and using stored user characteristic information (height, gender, age) from the database during subsequent measurements. The apparatus autonomously pairs the current user with their profile based on biometric matching, eliminating the need for manual re-entry of personal data while maintaining calculation accuracy through consistent use of stored parameters.
Solution Approach 2:
User characteristic information is collected and stored in advance during the initial setup or first measurement session. This preliminary action creates a reusable database of user parameters that can be automatically applied to future measurements, eliminating repeated manual input while preserving the precision needed for accurate body fat calculations.
3Measurement precision
If multiple recorded analysis data sets are stored, then user pairing accuracy is improved, but device complexity increases
Solution Approach 1:
The patent applies dynamic filtering by selecting only the top K closest matches from the sorted distance calculations, rather than processing all recorded data sets equally. This dynamic selection adapts the computational load to the actual data distribution, maintaining high pairing accuracy by focusing on the most relevant matches while reducing unnecessary computational complexity through intelligent data pruning.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
The solution reduces user inconvenience and improves user pairing accuracy by automatically calculating body fat information using current and recorded data sets, enhancing the reliability of user identification and eliminating identification mistakes.
Implementation Method 1
detecting impedance changing of user body with a sensor that senses current passing through the user body
Data Source
AI summary
A body fat measuring apparatus, system and pairing method thereof are provided. The body fat measuring apparatus and system include: a measuring unit provided for determining a current body weight and a current impedance of a user, and the current body weight and the current impedance used as a current analysis data set; a storage unit provided for cumulatively storing a user name, a user characteristic information related to the user name, and a plurality of recorded analysis data sets corresponding to the user names; and a processor provided for pairing the user name, reading the user characteristic information related to the user name, and obtaining a body fat information by calculating with the current body weight and the current impedance of the user.