Drug Delivery Device Recognition via Visual Feature Matching
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Solution Overview
Problem
Patients with diabetes face challenges in recognizing and managing multiple drug delivery devices, including distinguishing between authentic and counterfeit devices, monitoring device status, and ensuring correct usage.
Innovation Solution
A user device equipped with a camera and software that recognizes drug delivery devices based on distinctive features such as shape, color, and codes, providing assistance in device identification, status monitoring, and authenticity verification.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If patients use multiple drug delivery devices, then treatment effectiveness is improved, but device recognition and management becomes more difficult
Solution Approach 1:
The patent applies color coding to different drug delivery devices, where each device type or brand is assigned a distinctive color scheme. This allows patients to quickly distinguish between multiple devices without needing to read labels or remember complex specifications, directly addressing the recognition difficulty while maintaining treatment effectiveness.
Solution Approach 2:
The patent uses visual copying of distinctive device features through augmented reality overlays. The mobile device captures an image of the physical drug delivery device and superimposes digital annotations that copy and highlight key identification features, making it easier for patients to recognize and manage multiple devices by providing enhanced visual information.
2Loss of information
If patients manually track device usage, then monitoring capability is maintained, but user burden and error risk increase
Solution Approach 1:
The patent implements self-service monitoring where the mobile device automatically captures images of the drug delivery device and uses image recognition algorithms to extract usage information without requiring manual patient input. The system autonomously tracks device status, usage patterns, and maintenance needs, eliminating the burden of manual tracking while ensuring accurate information recording.
Solution Approach 2:
The patent provides real-time feedback to patients through the mobile application, displaying device status, usage history, and reminders for maintenance or refilling. This automated feedback loop keeps patients informed about their device status without requiring them to actively monitor or record information, reducing user burden while preventing information loss.
3Measurement precision
If visual attributes are added to drug delivery devices for identification, then device distinguishability is improved, but device complexity increases
Solution Approach 1:
The patent employs color coding as a primary identification method, assigning distinctive colors to different device types, brands, or formulations. This approach provides high identification accuracy through immediate visual recognition while adding minimal complexity to the device design, as color application is a straightforward manufacturing process.
Solution Approach 2:
The patent uses digital copying of identification information through augmented reality. Instead of adding physical complexity to the device, the system captures images of the device and superimposes digital annotations that copy and enhance visual identification features, providing high identification accuracy without increasing physical device complexity.
Data Source
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AI summary
- 33 - PAT20182-WO-PCT Abstract Drug Delivery Device Recognition 5 A system comprising a user device and a drug delivery device is provided, the user device comprising a processor, a memory, a display and a camera; the drug delivery device comprising a body, an injection mechanism and a cap; wherein the memory of the user device stores instructions which, when executed by the processor, cause the 10 user device to: capture, using the camera of the device, at least one image and/or video of a drug delivery device; identify, in the at least one captured image and/or video of the drug delivery device, at least one distinctive feature; compare the at least one distinctive feature identified based on the at least one image and/or video to at least one predefined set of distinctive features, the predefined set of distinctive features 15 being stored in the memory of the user device; identify the drug delivery device based on a match of the at least one distinctive feature identified based on the at least one image and/or video with at least one distinctive features of the predefined set of distinctive features; and output the result of identification of the drug delivery device on the display. 20