Biometric Scale Integrating ECG and Weight Signals
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Solution Overview
Problem
Current biometric monitoring devices are cumbersome and inefficient as they require separate devices for weight and biometric data capture, lacking a comprehensive and secure method for user identification and health status tracking.
Innovation Solution
A monitoring system that combines electrocardiograph (ECG) signals and weight signals using electrodes and a scale component, processing these signals to generate a current biometric signal, which is then matched against historical data to determine user identity and health status using disease and fitness models.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If separate devices are used for weight data and biometric data capture, then each device can be specialized and simple, but the overall system becomes cumbersome and requires multiple devices, connections, and wires
Solution Approach 1:
The patent combines weight measurement functionality and biometric data capture functionality into a single integrated monitoring device. The scale component with weight sensor is merged with the ECG component containing electrodes, allowing both weight and cardiac electrical activity to be measured simultaneously by the same device, eliminating the need for separate devices, connections, and wires
Solution Approach 2:
The monitoring device is designed to perform multiple functions: it measures weight through the scale component and weight sensor, captures biometric data through the ECG component and electrodes, processes both types of data, and provides comprehensive health monitoring. This multi-functional design replaces multiple specialized devices with a single universal monitoring system
2Reliability
If conventional biometric identification methods (fingerprints, DNA, retinal maps, facial recognition) are used, then identification security is high, but cost and complexity increase
Solution Approach 1:
The system uses the user's own physiological data (ECG signals and weight measurements) that are naturally produced during normal use of the device. The ECG component captures the heart's electrical activity and the scale component measures weight, both of which are inherent to the user's body and automatically recorded during device operation, eliminating the need for separate identification actions
Solution Approach 2:
The patent changes the biometric identification approach from using static physical characteristics (fingerprints, DNA, retinal maps, facial features) to using dynamic physiological parameters (ECG signal patterns and weight measurements). These parameters change over time and provide continuous verification, offering security while being simpler to implement with the integrated sensors
3Reliability
If multiple separate devices are used for biometric monitoring, then each device can be optimized for its specific function, but the overall system requires more components, connections, and wires
Solution Approach 1:
The patent merges the scale component with the ECG component into a single integrated monitoring device. The weight sensor and electrodes share the same device housing and processing unit, reducing the total number of components while maintaining the specialized measurement capabilities for both weight and biometric data
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
Enables efficient and secure user identification and health status tracking by integrating ECG and weight data capture, providing a comprehensive biometric profile for fitness and disease monitoring.
Implementation Method 1
receiving an electrocardiograph (ECG) signal from an ECG component
Implementation Method 2
receive a weight signal from a scale component in contact with the user
Data Source
AI summary
A method for configuring a monitoring component for a user includes receiving an electrocardiograph (ECG) signal from an ECG component, receiving a weight signal from a scale component, and combining features extracted from the ECG signal and the weight signal to generate a current biometric signal. Responsive to the current biometric signal matching a historical biometric signal, the method includes obtaining a user profile and determining a health status for association with the user profile by classifying the current biometric signal using disease models and fitness models.