OCR Supplemental Device for Insulin Pen Dose Reading

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Solution Overview

Problem

In medical devices, such as insulin injection pens, manual reading of dosing scales can be time-consuming and error-prone, especially for patients with poor eyesight, and requires manual data entry for electronic transmission, which is inefficient and prone to errors.

Innovation Solution

A supplemental device with optical and acoustical sensors that attaches to the injection device, using OCR technology to capture and recognize the dose displayed on the dosage window, allowing for accurate electronic recording and transmission of medication information.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Productivity

If manual reading and recording of dosing scales is used, then device complexity is low, but productivity is reduced and errors increase

Engineering Contradiction:
Improvedosing speedVSAvoiddevice complexity
Core Design Contradiction:
ProductivityVSDevice complexity

Solution Approach 1:

The patent replaces the manual mechanical reading and recording process with an automated optical recognition system. An optical sensor captures images of the dosing scale, and image processing algorithms automatically recognize and record the dose value, eliminating the need for manual intervention while significantly improving dosing speed and accuracy.

Inventive Principle:
Principle #28Mechanics substitution (Replace mechanical system)

Solution Approach 2:

The system enables self-service by allowing the dosing device to automatically capture, process, and record its own dosing information. The optical sensor and image processing work together to autonomously extract dose values from the scale without requiring user intervention, making the system self-sufficient in data acquisition and recording.

Inventive Principle:
Principle #25Self-service

2Reliability

If manual data entry is used for electronic transmission, then device complexity is low, but reliability is reduced due to potential errors

Engineering Contradiction:
Improvedosing accuracyVSAvoiddevice complexity
Core Design Contradiction:
ReliabilityVSDevice complexity

Solution Approach 1:

The patent eliminates manual data entry by implementing an automated optical recognition system that captures images of the dosing scale and uses image processing algorithms to automatically extract and transmit dose information electronically. This substitution of manual mechanical entry with automated optical-electronic processing significantly improves reliability and eliminates human error.

Inventive Principle:
Principle #28Mechanics substitution (Replace mechanical system)

3Ease of operation

If mechanical readouts with small text are used, then device complexity is low, but ease of operation is reduced for patients with poor eyesight

Engineering Contradiction:
ImprovereadabilityVSAvoiddevice complexity
Core Design Contradiction:
Ease of operationVSDevice complexity

Solution Approach 1:

The patent replaces the mechanical readout system with small text with an automated optical recognition system. The optical sensor captures the dosing scale, and image processing algorithms automatically recognize the dose value, converting it into a large, clear digital display that is easily readable by patients with poor eyesight, thereby improving ease of operation.

Inventive Principle:
Principle #28Mechanics substitution (Replace mechanical system)

Solution Approach 2:

The system creates a digital copy of the dosing scale information through optical imaging and processing. Instead of requiring patients to directly read small mechanical text, the system captures an image of the scale, processes it to extract the dose value, and displays it in an enlarged, clear format, making the information accessible to visually impaired users.

Inventive Principle:
Principle #26Copying

4Productivity

If automated OCR system is implemented, then productivity is improved, but device complexity increases

Engineering Contradiction:
Improvedosing speedVSAvoiddevice complexity
Core Design Contradiction:
ProductivityVSDevice complexity

Solution Approach 1:

The patent implements automated OCR technology to replace manual reading and recording processes. The optical sensor captures images of the dosing scale, and integrated image processing algorithms automatically recognize dose values and enable electronic transmission, significantly improving dosing speed while managing device complexity through integration.

Inventive Principle:
Principle #28Mechanics substitution (Replace mechanical system)

Applied Scientific Principles

This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.

Function Achieved in This Case

Enables rapid, accurate, and error-free recording of medication doses, improving user experience and reducing the burden on patients with visual impairments by automating the data entry process.

Implementation Method 1

an optical sensor, which may for instance be a charge coupled device (CCD) sensor or a complementary metal oxide semiconductor (CMOS) sensor, to obtain image data

Methodology Applied
Scientific EffectLight reflection: Reflection

Data Source

PatentEP3167408B1A device and method for performing optical character recognition
Publication Date: 2023.12.13 SANOFI AVENTIS DEUT GMBH
  • EP3167408B1 patent drawingFigure 1a
  • EP3167408B1 patent drawingFigure 1b~2a
  • EP3167408B1 patent drawingFigure 2b~2c

AI summary

A method of performing character isolation in an optical character recognition process, the method comprising receiving image data representing one or more character columns, determining a number of black pixels in each column of the image data, defining a vertical separation threshold which is a maximum number of black pixels in a column, dividing the columns into different pixel groups and groups of excluded columns by excluding any columns with a number of black pixels below the vertical separation threshold, identifying the pixel group representing the left most character column in the image data, determining whether there are one or two pixel groups representing character columns in the image data and, if it is determined that there are two pixel groups representing character columns, using a predetermined width value for a right most character column in order to identify a right hand boundary of the right most character column.