3D Camera Infant Respiratory Monitoring via Depth Mapping
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Solution Overview
Problem
Conventional infant respiratory monitoring systems are inadequate for real-time detection and often struggle with background noise, lacking sophisticated image analysis capabilities, which is critical for early detection of respiratory issues associated with sudden infant death syndrome (SIDS).
Innovation Solution
A 3D camera-based system that monitors infant respiratory movements by tracking abdominal cavity distance using depth maps and respiratory metrics, integrated with facial recognition and object detection algorithms to provide real-time alerts for potential respiratory issues, such as rolling or shallow breathing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional approaches are used for infant respiratory monitoring, then physical attachment of devices is required, but this causes discomfort and potential harm to the infant
Solution Approach 1:
The patent replaces mechanical/physical attachment devices with an optical system using depth cameras to monitor respiratory movements. The system captures depth information from the infant's chest and abdomen regions, tracking movements without any physical contact, thereby eliminating infant discomfort while maintaining monitoring reliability
Solution Approach 2:
The patent introduces depth camera technology as an intermediary between the monitoring system and the infant. Instead of directly attaching sensors to the infant's body, the system uses optical depth mapping to indirectly measure respiratory movements through chest and abdomen surface movements, reducing harmful physical contact
2Reliability
If conventional monitoring systems are used, then they struggle with background noise, but this reduces detection accuracy
Solution Approach 1:
The patent applies local quality by focusing the depth camera's monitoring on specific regions of interest (chest and abdomen areas) rather than the entire scene. By concentrating computational resources and analysis on these localized regions where respiratory movements occur, the system filters out background noise from other areas while maintaining high detection accuracy
Solution Approach 2:
The patent transitions from 2D video analysis to 3D depth-based monitoring. By utilizing the depth dimension, the system can distinguish between actual respiratory movements (which create depth changes) and background noise (which remains at constant depth), significantly improving signal-to-noise ratio and detection accuracy
3Ease of operation
If simple video monitoring is used, then the system is easy to operate, but it lacks sophisticated image analysis capability
Solution Approach 1:
The patent implements self-service by incorporating automated depth map generation, movement detection, and respiratory pattern analysis algorithms within the camera system. The system automatically processes depth information, identifies chest and abdomen movements, calculates respiratory rates, and generates alerts without requiring manual intervention, thereby providing sophisticated analysis while maintaining ease of operation
Solution Approach 2:
The patent creates a multi-functional system where the depth camera serves multiple purposes: it captures depth maps for respiratory monitoring, detects infant position and movement, identifies chest and abdomen regions, and provides real-time alerts. This universal approach consolidates multiple monitoring functions into a single system, maintaining simplicity while enhancing analytical capabilities
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
The system effectively monitors infant respiratory health by providing timely alerts for abnormal breathing patterns, enhancing the ability to detect potential SIDS risks and improving caregiver response.
Implementation Method 1
a 3D camera, positioned above the infant subject, configured to output image data including depth information
Data Source
AI summary
Systems and methods employing a depth-sensing camera to detect abdomen rise and fall during an infant sleep period, or lack thereof due to respiratory arrest. Visual processing of image data collected by one or more 3D digital camera is performed to detect the infant and to measure a distance between an infant's abdominal cavity and a camera baseline over time. An alarm may be triggered at by the system, locally and/or at remote devices, such as a mobile phone, tablet, laptop, etc. The monitoring system may also detect situations when an infant rolls from a back-sleeping to a belly-sleeping position.