Optical Perfusion Sensor Control for Syncope Diagnosis
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Solution Overview
Problem
Implantable cardiac monitors struggle to accurately diagnose syncope events, as they often occur infrequently and have sudden onset, making it challenging to determine if they are related to cardiac arrhythmias or other factors like low blood pressure.
Innovation Solution
An implantable medical device equipped with an optical perfusion sensor that monitors blood oxygen saturation levels, allowing for the detection of changes in blood oxygen saturation and perfusion values, which can indicate cardiac arrhythmias or other conditions contributing to syncope, thereby modifying the operation of the cardiac signal sensing module based on these readings.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If implantable cardiac monitors continuously monitor cardiac signals to capture syncope events, then the reliability of diagnosis is improved, but the loss of time and energy consumption increase due to the infrequent and sudden nature of syncope events
Solution Approach 1:
The system performs preliminary monitoring of cardiac signals and pre-conditions (such as blood pressure indicators) to identify patients at risk before syncope occurs. By detecting early warning signs and preparing diagnostic resources in advance, the system can quickly capture relevant data when syncope happens, improving diagnostic reliability without requiring continuous full-scale monitoring.
Solution Approach 2:
Instead of continuous monitoring, the system uses periodic sampling of cardiac signals and physiological parameters at strategically selected intervals. The monitoring frequency is dynamically adjusted based on detected patterns and risk levels, allowing the system to capture syncope events while reducing overall power consumption and data processing requirements.
2Measurement precision
If implantable cardiac monitors store all cardiac signal data for later analysis, then the measurement precision of syncope diagnosis is improved, but the device complexity and data management burden increase
Solution Approach 1:
The system extracts and stores only the most diagnostically relevant features and parameters from cardiac signals, such as interval measurements, waveform characteristics, and physiological indicators. By filtering out redundant data and focusing on key diagnostic elements, the system maintains high diagnostic precision while significantly reducing storage requirements and simplifying data management.
Solution Approach 2:
Instead of storing complete high-resolution cardiac signal waveforms, the system creates simplified representations or copies of the essential diagnostic information. This includes storing processed features, event markers, and summarized physiological parameters that capture the critical diagnostic elements without requiring full signal storage, thereby reducing device complexity.
3Reliability
If the optical perfusion sensor continuously monitors blood oxygen saturation levels, then the reliability of detecting perfusion changes is improved, but the energy consumption increases
Solution Approach 1:
The monitoring frequency and intensity of the optical perfusion sensor are dynamically adjusted based on detected physiological conditions and risk levels. During periods of stability, monitoring is reduced to conserve energy, while during periods of detected abnormality or high risk, monitoring intensity increases to capture critical perfusion changes, thus maintaining reliability while optimizing energy consumption.
Solution Approach 2:
The system applies partial monitoring by focusing optical sensing on specific time windows or physiological states where perfusion changes are most likely to occur. Rather than continuous full-intensity monitoring, the system activates enhanced monitoring only when triggered by cardiac events or physiological thresholds, achieving sufficient detection reliability with reduced overall energy expenditure.
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 the IMD to effectively monitor and store cardiac signals corresponding to changes in blood oxygen saturation, providing clinicians with valuable insights into the physiological condition at the time of a syncopic event, helping to differentiate between arrhythmia-related and non-arrhythmia-related causes.
Implementation Method 1
a detector that senses light that was emitted by the light source and transmitted through the blood-perfused tissue or reflected by a blood mass
Implementation Method 2
senses light that was emitted by the light source and transmitted through the blood-perfused tissue or reflected by a blood mass
Implementation Method 3
The detector may generate an electrical signal that indicates an amount (or intensity) of light absorbed and/or reflected by a blood mass
Data Source
AI summary
An optical perfusion sensor may monitor blood oxygen saturation of blood-perfused tissue, which may be referred to as tissue perfusion, until a tissue perfusion value is within a threshold range of a reference value, and, in some examples, for at least a minimum period of time. The tissue perfusion value may indicate an absolute blood oxygen saturation level or a relative change in blood oxygen saturation level. The reference value may be, for example, determined by an oxygen (O2) variation index that indicates a change in blood oxygen saturation of tissue. In some examples, the optical perfusion sensor may be activated upon detecting a cardiac event, such as a cardiac arrhythmia. In addition, in some examples, cardiac signal monitoring may be activated upon detecting a threshold change in tissue perfusion.