Smartphone Fingernail Imaging for Objective Capillary Refill
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Solution Overview
Problem
Current capillary refill time (CRT) tests are subjective and lack high temporal resolution, limiting their ability to provide quantitative data for assessing peripheral perfusion, which is crucial for chronic disease management and monitoring.
Innovation Solution
An image processing system using a smartphone application with high temporal resolution to measure capillary refill time (Q-CRT) by analyzing pixel color intensity data from fingernail videos, leveraging machine learning for automatic detection and computation of refill times.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If digitized techniques and computer processing are used to create objective CRT measurement, then measurement precision is improved, but device complexity increases making it impractical for bedside care
Solution Approach 1:
The patent uses a smartphone camera to capture video images of the fingernail bed, creating a digital copy of the visual assessment. This allows objective analysis through image processing while using readily available technology instead of complex specialized equipment. The video frames serve as copies that can be analyzed computationally to determine CRT objectively.
Solution Approach 2:
The patent replaces manual visual assessment by healthcare providers with automated image processing algorithms. The system uses computer vision to detect color changes in the fingernail bed across video frames, substituting the mechanical/subjective human eye assessment with an automated digital system that provides objective measurements without requiring complex instrumentation.
2Measurement precision
If current quantitative approaches are used to measure CRT, then measurement precision is improved, but the full potential of Q-CRT data is not leveraged
Solution Approach 1:
The patent segments the Q-CRT measurement into multiple analytical components: color intensity values across different video frames, temporal patterns of color change, and comparative analysis between baseline and post-compression states. This segmentation allows extraction of multiple predictive indicators from the same data set, including refill time, color change rate, and waveform characteristics, thereby leveraging the full potential of the quantitative data.
Solution Approach 2:
The system provides feedback by analyzing the complete Q-CRT waveform and comparing it against established patterns or thresholds. The image processing system generates objective feedback about peripheral perfusion status based on the quantitative analysis of color intensity changes over time, enabling clinicians to interpret the full range of information contained in the Q-CRT measurement rather than just a single time value.
3Measurement precision
If high temporal resolution image processing is used to measure Q-CRT, then measurement precision and predictive information are improved, but ease of operation should be maintained for general use
Solution Approach 1:
The system performs automated fingernail detection and video frame analysis without requiring user intervention or manual tracking. The machine learning model automatically identifies the fingernail bed in each video frame and extracts color intensity data, eliminating the need for operators to manually mark regions of interest or process images. This self-service capability maintains ease of operation while achieving high temporal resolution measurements.
Solution Approach 2:
The patent transforms the complex video data into simplified quantitative parameters that are easy to interpret. By converting color intensity information across multiple frames into a single Q-CRT value with associated predictive indicators, the system maintains operational simplicity while capturing high temporal resolution information. The processed parameters provide clinically actionable insights without requiring complex data analysis by the operator.
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
Provides objective, high-resolution Q-CRT data for monitoring peripheral perfusion, enabling predictive analysis and tracking of perfusion changes over time without additional equipment or training, accessible for various healthcare settings.
Implementation Method 1
analyzing pixel color intensity data from fingernail videos
Data Source
AI summary
The present disclosure relates to a process that comprises, in at least one embodiment: accessing a camera via an application; prompting a user to induce blanching for a time period of 10 seconds; processing information from the camera to automatically detect one or more fingernails for each of the one or more fingers; accessing video data from the camera; computing a capillary refill time; causing a display screen to display the capillary refill time; and transmitting the capillary refill time to a computing device.