Capillary Refill Measurement Using Optical Compression Feedback
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Solution Overview
Problem
Existing physiological signal measurement devices face inaccuracies in capillary refilling time measurements due to insufficient compression or misalignment of sensor elements, leading to incorrect blood circulation assessments.
Innovation Solution
The device includes an information processor to calculate capillary refilling time based on detected light intensity changes, using band-pass filtering and multiple regression analysis to determine appropriate compression and alignment, and provides feedback for correction.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If compression is applied to measure capillary refilling time, then blood is removed from capillary and transmitted light intensity increases, but insufficient compression may occur leading to inaccurate measurement
Solution Approach 1:
The system analyzes the waveform characteristics of transmitted light intensity changes during compression and provides feedback to determine whether the compression was sufficient. By examining features such as the magnitude of light intensity increase and waveform shape, the system can identify inadequate compression and prompt the user to apply appropriate compression force, thereby ensuring reliable measurements.
Solution Approach 2:
The system performs preliminary analysis of the light intensity waveform during the compression period to assess whether sufficient compression has been applied before calculating the capillary refilling time. This preliminary check allows the system to validate the measurement conditions and avoid inaccurate results from insufficient compression.
2Measurement precision
If sensor elements are misaligned with compression direction, then blood removal from capillary is insufficient, but detecting and correcting this misalignment adds complexity to the device
Solution Approach 1:
The system uses feedback from the transmitted light intensity waveform characteristics to indirectly detect sensor misalignment. By analyzing whether the light intensity increases appropriately during compression, the system can infer alignment issues and guide the user to correct the sensor position, avoiding the need for complex alignment verification mechanisms.
Solution Approach 2:
The system replaces complex mechanical alignment verification mechanisms with optical-based detection and signal analysis. By using the light intensity waveform itself as an indicator of proper alignment and compression, the system eliminates the need for separate alignment verification hardware while maintaining measurement precision.
3Reliability
If user must determine measurement appropriateness manually, then measurement reliability can be ensured, but user burden increases and productivity decreases
Solution Approach 1:
The system performs self-verification of measurement appropriateness by automatically analyzing the transmitted light intensity waveform characteristics. The device independently determines whether compression was sufficient and whether the measurement conditions are appropriate, eliminating the need for manual user assessment and improving measurement efficiency while maintaining reliability.
Solution Approach 2:
The system provides automated feedback to the user regarding measurement quality, indicating whether the measurement is appropriate or if re-measurement is needed. This feedback mechanism maintains measurement reliability by ensuring proper conditions are met while improving productivity by eliminating manual determination steps.
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
Ensures accurate capillary refilling time measurements by identifying and correcting for insufficient compression and sensor misalignment, thereby improving blood circulation assessment reliability.
Implementation Method 1
The light from the light emitter in the above-described physiological signal measurement device is transmitted through a physiological tissue having blood in the capillary and enters the light detector
Data Source
AI summary
A physiological signal measurement device includes: an information processor of one or more processors configured to calculate, based on change in a detected light intensity that is detected by a light detector configured to detect light emitted from a light emitter and transmitted through a physiological tissue, a capillary refilling time after a compression period in which the physiological tissue is compressed. The information processor uses the detected light intensity to determine whether the change in the detected light intensity is appropriate for calculating the capillary refilling time.