Seven-Segment Display Reader for Remote Health Monitoring
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Solution Overview
Problem
Existing digital health care systems struggle to effectively read and manage data from sensor devices with seven-segment displays, particularly in remote settings, due to limitations in existing datasets, low accuracy in digit recognition, and the need for physical coupling of devices, which hinders telemedicine and remote health care delivery.
Innovation Solution
A computer-implemented method and system that captures digital images of seven-segment displays using a smartphone or digital camera, processes them using optical character recognition and machine learning to determine sensor readings, and sends them to a remote health management platform for analysis, enabling remote health monitoring and management.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If physical coupling of sensor devices to monitoring systems is required, then data transmission reliability is improved, but telemedicine and remote health care delivery are hindered
Solution Approach 1:
The patent captures images of seven-segment display readings using a smartphone or digital camera, creating a visual copy of the sensor data. This image copy can be transmitted remotely without requiring physical coupling of the sensor device to the monitoring system, thus enabling telemedicine while maintaining data integrity
Solution Approach 2:
The patent introduces an image processing system as an intermediary between the sensor device and the monitoring system. The system captures images of the display, processes them through OCR and machine learning algorithms, and transmits the extracted data remotely, serving as a mediator that eliminates the need for direct physical connection
2Adaptability or versatility
If high-definition displays with Internet capability are used in sensor devices, then remote communication capability is improved, but cost becomes prohibitive for many patients
Solution Approach 1:
Instead of equipping sensor devices with expensive high-definition displays and Internet capability, the patent uses a separate computing device with camera to capture images of the simple seven-segment display. This copying approach enables remote communication functionality without adding costly components to the original sensor device
Solution Approach 2:
The patent makes the sensor device universally compatible with any smartphone or digital camera, allowing the same low-cost seven-segment display device to work with multiple different computing devices. This multi-functionality approach enables remote communication without requiring expensive built-in Internet capability in the sensor device itself
3Device complexity
If existing datasets and template matching approaches are used for digit recognition, then implementation simplicity is improved, but recognition accuracy deteriorates due to tilts, orientations, and artifacts
Solution Approach 1:
The patent performs preliminary preprocessing of the captured image before recognition, including adjusting for tilts and orientations, removing artifacts from back-lights and reflections, and normalizing the display appearance. This preliminary action prepares the image in advance, enabling accurate recognition without requiring complex real-time adjustment mechanisms
Solution Approach 2:
The patent transforms the recognition approach by changing parameters from simple template matching to machine learning-based classification. The system trains models on diverse datasets that include various tilts, orientations, and lighting conditions, allowing the recognizer to adapt to different parameters and maintain high accuracy across varying conditions
4Measurement precision
If users are required to manually identify area of interest and individually identify digits, then recognition precision is improved, but ease of operation deteriorates especially for older patients
Solution Approach 1:
The patent implements self-service functionality where the system automatically identifies the area of interest containing the seven-segment display and extracts the digits without requiring user intervention. The image processing system autonomously performs cropping, orientation detection, and digit extraction, making the system easy to operate for all users including older patients who may have difficulty with manual identification tasks
Data Source
AI summary
Computer-implemented methods, systems and devices having segmented numeral character recognition. In an embodiment, users may take digital pictures of a seven-segment display on a sensor device. For example, a user at a remote location may use a digital camera to capture a digital image of a seven-segment display on a sensor device. Captured images of a seven-segment display may then be sent or uploaded over a network to a remote health management system. The health care management system includes a reader that processes the received images to determine sensor readings representative of the values output on the seven-segment displays of the remote sensor devices. Machine learning and OCR are used to identify numeric characters in images associated with seven-segment displays. In this way, a remote heath management system can obtain sensor readings from remote locations when users only have access to sensor devices with seven-segment displays.