Patient Terminal Medical Device Digitization via AI Screen Capture
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Solution Overview
Problem
Existing systems for sharing medical device data with healthcare providers are inefficient and prone to fragility due to manual data transfer by patients, which can lead to delays and loss of data integrity.
Innovation Solution
A system utilizing deep learning models for device identification, verification, data determination, and interpretation to automate the digitization and transfer of medical data from patient terminals to healthcare providers, employing modules for device identification, verification, and data interpretation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual data collection on paper is used, then patients can obtain medical data, but data transfer is delayed and data is subject to fragility
Solution Approach 1:
The patent replaces the mechanical paper-based data collection system with an automated digital system using cameras, deep learning models, and image processing to capture and transfer medical device data electronically, eliminating manual handling and physical transport of paper records
Solution Approach 2:
The system enables automatic data capture and transfer where the medical device data is self-digitized through camera scanning and automated processing, without requiring patient intervention to manually transcribe or transport data to healthcare providers
2Ease of operation
If Bluetooth or USB connection is used to download medical data, then data can be transferred digitally, but the patient still owns the data and must send it manually to the healthcare provider
Solution Approach 1:
The patent introduces an intermediary automated processing system that acts as a bridge between the medical device and healthcare provider, using camera scanning, deep learning models, and image processing to automatically transfer data without requiring the patient to manually send it, while ensuring data integrity through automated verification
3Productivity
If automated digitization system is implemented, then data transfer efficiency is improved, but system complexity increases
Solution Approach 1:
The patent employs a multi-functional integrated system where a single processing pipeline handles device identification, data capture, image processing, and data transfer across multiple medical device types, reducing overall system complexity through universal processing rather than separate specialized systems for each device
Solution Approach 2:
The system uses camera-based optical copying to capture data from medical device displays, creating digital replicas of the displayed information that can be processed and transferred, simplifying the digitization process compared to direct electronic connections
Data Source
AI summary
A system for digitizing medical devices at a patient terminal is disclosed. The system includes a processing subsystem which includes a device identification module which trains a first deep learning model, generates type-casted scanner clickables, enables scanning of the medical devices, receives multimedia of the medical devices, and identifies type of the medical devices. The processing subsystem also includes a verification module which receives a medical data transfer request and verifies an identity of a patient. The processing subsystem also includes a data determination module which trains a second deep learning model and determines data displayed on screen. The processing subsystem also includes a data interpretation module which trains a third deep learning model and interprets the data being medical data. The processing subsystem also includes a data transfer module which transfers the medical data to at least one of the healthcare providers and preferred recipients, thereby digitizing the medical devices.