Blended Electrolyte Sensor Fusion for Speed and Precision
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Solution Overview
Problem
Existing electrolyte sensors face limitations such as slow response times, offset errors, and lack of specificity, which can lead to inaccurate assessments of electrolyte concentrations in patients, necessitating a method to combine data from different sensors to mitigate these issues.
Innovation Solution
A medical system that combines data from a fast response time sensor, like an ECG sensor, and a high-accuracy sensor, like a chemical sensor, using a controller to create a blended analyte value that reduces sensor offset errors, gain errors, and latency, thereby improving the accuracy and speed of electrolyte concentration measurements.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If a fast response time sensor (e.g., ECG sensor) is used, then the response speed of electrolyte concentration measurement is improved, but measurement precision deteriorates due to offset errors and lack of specificity
Solution Approach 1:
The patent combines data from multiple sensor types (ECG sensor and chemical sensor) to create a blended analyte value. The ECG sensor provides fast response time while the chemical sensor provides high accuracy, and their fusion resolves the contradiction between speed and precision
2Measurement precision
If a high-accuracy sensor (e.g., chemical sensor) is used, then measurement precision is improved, but response time deteriorates due to slow reaction speed
Solution Approach 1:
The patent merges data from the chemical sensor (high accuracy, slow response) with the ECG sensor (fast response, lower accuracy). The controller fuses these complementary data streams to achieve both high accuracy and fast response time simultaneously
3Measurement precision
If multiple sensors are combined to reduce errors, then measurement precision is improved, but device complexity increases
Solution Approach 1:
The controller uses feedback from the fast sensor to adjust and normalize readings from the slow sensor in real-time. This feedback mechanism allows the system to maintain high accuracy without requiring complex post-processing of multiple independent sensor streams
Data Source
AI summary
Embodiments herein relate to systems and methods for combining data from different types of sensors. In an embodiment, a medical system is included. The medical system can include a first sensor configured to produce a first value for an analyte and a second sensor different than the first sensor, the second sensor configured to produce a second value for the analyte. The medical system can also include a controller configured to receive the first and second values. The controller can create a blended analyte value from the first value and second value. Other embodiments are included herein.