Ventilator Camera-Based Component Recognition

Resolve Bottlenecks,
Find Innovative SolutionsGenerate Solutions

Solution Overview

Problem

Mechanical ventilators face challenges in accurately measuring and compensating for pneumatic properties due to exposure to patient contaminants, leading to unreliable measurements and the need for manual calibration, which can be error-prone and fail to account for varying ventilation circuit and patient interface components.

Innovation Solution

A ventilator system with a camera, database, and controller that uses image recognition to identify and track ventilation circuit components, automatically adjusting gas composition and output to ensure accurate therapy delivery without manual calibration, by recognizing and compensating for changes in component orientation and connection within the ventilation circuit.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Reliability

If measurements are taken distal from the patient in the ventilator, then reliability of measurements is improved by avoiding patient contaminants, but measurement precision deteriorates due to losses in the ventilation circuit

Engineering Contradiction:

Improvemeasurement reliabilityVSAvoidventilation measurement precision

Core Design Contradiction:

ReliabilityVSMeasurement precision

Solution Approach 1:

The system uses a camera to capture images of ventilation circuit components, identifies them through image recognition, and feeds this information back to automatically adjust compensation parameters. This closed-loop feedback mechanism ensures that the ventilator continuously adapts to the actual circuit configuration, maintaining measurement precision while relying on distal measurements for reliability.

Inventive Principle:

Principle #23Feedback

Solution Approach 2:

The ventilator system performs self-calibration by automatically identifying its own ventilation circuit components through image recognition and adjusting compensation parameters without external intervention. The system serves itself by detecting component orientations and connections, then autonomously programming the correct compensation values into the controller.

Inventive Principle:

Principle #25Self-service

2Measurement precision

If manual calibration is performed to compensate for ventilation circuit properties, then measurement precision can be improved, but ease of operation deteriorates due to programming requirements and potential errors

Engineering Contradiction:

Improveventilation measurement precisionVSAvoidcalibration operation ease

Core Design Contradiction:

Measurement precisionVSEase of operation

Solution Approach 1:

Inventive Principle:

Principle #25Self-service

Solution Approach 2:

The system replaces manual mechanical calibration procedures with an automated optical recognition system. Instead of requiring caregivers to physically measure and program circuit parameters, the camera-based image recognition system automatically detects component orientations and connections, substituting manual operations with automated visual identification and electronic parameter adjustment.

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

3Device complexity

If the ventilator uses fixed compensation assumptions, then device complexity is reduced, but adaptability deteriorates when component configurations vary from assumptions

Engineering Contradiction:

Improvecompensation algorithm complexityVSAvoidcircuit configuration adaptability

Core Design Contradiction:

Device complexityVSAdaptability or versatility

Solution Approach 1:

The system transitions from static, fixed compensation assumptions to dynamic, adaptive compensation. The camera continuously captures images of the ventilation circuit, and the image recognition system dynamically identifies component orientations and connections in real-time. The controller automatically adjusts compensation parameters based on the detected configuration, allowing the system to adapt to varying circuit arrangements without increasing inherent algorithmic complexity.

Inventive Principle:

Principle #15Dynamics

Solution Approach 2:

The image recognition system provides universal adaptability by being able to identify multiple types of ventilation circuit components and their various orientations and connections through a single unified approach. The system can handle different component configurations, tube orientations, and circuit arrangements using the same camera-based identification method, making the ventilator versatile across diverse clinical setups.

Inventive Principle:

Principle #6Universality (Multi-functionality)

Data Source

PatentUS11247010B2Imaging system and method for control and diagnostics within mechanical ventilation

Publication Date: 2022.02.15 KONINKLIJKE PHILIPS NV

AI summary

A ventilator system (10) includes a ventilator source (12), camera (14), database (16) and controller (16). A first plurality of ventilation components in a ventilation circuit (34) are coupled between the ventilator source and a patient. The camera captures images of the ventilation circuit. The database includes multi-view images of a second plurality of ventilation components pre-approved for use with the ventilator source. The controller (16) includes (i) a control module (22), (ii) a component recognition and identification module (24), (iii) a component tracking module (26) configured to track targets and to detect at least one change in tracked targets, and (iv) a ventilation compensation module (28). An operation of the ventilator source (12) is controlled with operating parameters determined as a function of at least (i) a gas composition algorithm, (ii) an output of the component recognition and identification module (24), and (iii) an output of the ventilation compensation module (28) determined as a function of an output of the component tracking module (26).