Biometric Data Aggregation System with Local Preprocessing
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Solution Overview
Problem
Current systems for biometric data aggregation and visualization are limited in their ability to efficiently collect, process, and display data from multiple sources, leading to difficulties in practical utilization for physical performance tracking and medical monitoring, particularly in terms of data structure, format, storage, retrieval, and rendering.
Innovation Solution
A system comprising non-transitory computer storage medium and hardware processors that receive and process data from various sensors, upload it to a remote server, and generate graphical and tabular representations for presentation within a graphical user interface, enabling secure, reliable, and efficient data communication and visualization.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If data from multiple sensors is collected and processed in detail, then the comprehensiveness of health tracking is improved, but the network bandwidth and processing resources required increase
Solution Approach 1:
The system performs preliminary data processing and feature extraction at the sensor source before transmission to the cloud. Local preprocessing filters and selects only the most relevant biometric features, reducing the amount of data that needs to be transmitted over the network while preserving essential health information.
Solution Approach 2:
The patent extracts and transmits only the most critical biometric data points and processed features rather than all raw sensor data. This selective extraction maintains the completeness of health tracking for key parameters while significantly reducing network bandwidth requirements.
2Ease of operation
If detailed biometric data is stored and processed locally, then data accessibility is improved, but device storage capacity and processing power requirements increase
Solution Approach 1:
The system segments data processing into multiple levels: local device processing for immediate accessibility, cloud processing for comprehensive analysis, and hierarchical storage architecture. This segmentation allows detailed data to be stored and processed without requiring all data to reside on the device simultaneously, reducing local storage and processing burden.
Solution Approach 2:
The patent introduces a cloud-based processing layer as an intermediary between local sensors and comprehensive data analysis. This intermediary handles the computationally intensive tasks of processing and storing detailed biometric data, allowing devices to maintain data accessibility while offloading storage and processing requirements to the cloud.
3Speed
If real-time data processing is implemented, then responsiveness of health monitoring is improved, but computational resources and processing time increase
Solution Approach 1:
The system performs preliminary data processing and feature extraction at the sensor source before transmission to the cloud. Local preprocessing filters and selects only the most relevant biometric features, reducing the amount of data that needs to be transmitted over the network while preserving essential health information.
Solution Approach 2:
The patent implements partial real-time processing at the device level for immediate responsiveness, while comprehensive processing occurs asynchronously in the cloud. This partial action approach provides timely responses for critical health parameters without requiring continuous high-power computational resources for all data processing.
Data Source
AI summary
Systems and methods described herein facilitate biometric, health, and activity data aggregation and visualization in order to provide improved physical performance tracking and medical monitoring. In some examples, the system can providing real time access to healthcare providers during telehealth sessions. In some examples, the system can include infectious disease monitoring, enabling a healthcare provider to monitor and provide healthcare to a group of patients outside of a clinical setting.