Proxy Model for Health Indicators Using Mobile Data
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Solution Overview
Problem
Conventional health assessment methods are invasive, time-consuming, and costly, relying on active participation and accurate reporting from individuals, which can be unreliable and burdensome for both the person and the entity performing the assessment.
Innovation Solution
A computer-implemented method using an artificial neural network trained with labeled data from mobile electronic devices to determine health indicators, such as life expectancy, by processing personal activity metrics from sensors like smartphones and wearable devices, reducing the need for traditional invasive assessments.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional health assessment methods are used, then health indicators can be determined, but the process is invasive, time-consuming, and costly
Solution Approach 1:
The patent creates a proxy model (artificial neural network) that copies the functionality of traditional health assessment processes. Instead of directly performing invasive medical examinations, the system uses mobile device sensor data as a copy or surrogate of actual health status, enabling health indicator determination without time-consuming physical assessments
Solution Approach 2:
The patent replaces mechanical/physical health assessment methods (physical examinations, medical testing) with an electronic/computational system. Mobile device sensors and machine learning algorithms substitute for traditional medical equipment and procedures, eliminating the need for invasive physical assessments while maintaining assessment capabilities
2Reliability
If conventional health assessment methods are used, then health indicators can be determined, but the process is invasive and requires active participation
Solution Approach 1:
The system enables self-service health assessment by using mobile devices that individuals already possess and carry daily. The sensors in these devices automatically collect health-related data without requiring active participation in assessment activities. Individuals simply use their existing devices, and the system passively gathers and processes data to determine health indicators
Solution Approach 2:
The patent introduces mobile devices as intermediaries between the individual and the health assessment process. Instead of direct interaction between the person and medical examiners, the mobile device serves as a mediator that collects, transmits, and processes health data, making the assessment process more convenient and less invasive while maintaining reliability
3Reliability
If conventional health assessment methods are used, then comprehensive health evaluation can be performed, but substantial costs are imposed on the entity
Solution Approach 1:
The patent leverages inexpensive mobile devices that individuals already own as the basis for health assessment. Instead of investing in expensive medical equipment and facilities, the system uses readily available, low-cost smartphones and wearables. This dramatically reduces the cost burden on entities performing assessments while maintaining comprehensive evaluation capabilities through multiple sensor data streams
Data Source
AI summary
A computer-implemented method for health assessment includes providing an artificial neural network trained with training data. The method also includes receiving activity data comprising personal activity metrics corresponding to a target person, and determining, by the artificial neural network, a health indicator of the target person based upon the activity data corresponding to the target person. The method further includes outputting the health indicator of the target person to an electronic device for communication of the health indicator to a user of the electronic device. Other embodiments are disclosed.