Electrolyte Sensor Fusion Controller
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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 solution to combine data from different sensors for improved accuracy and reliability.
Innovation Solution
A medical system that combines data from a fast response time sensor, such as an ECG sensor, and a high-accuracy sensor, such as a chemical sensor, using a controller to create a blended analyte value that reduces sensor offset errors, gain errors, and latency, thereby enhancing the accuracy and reliability of electrolyte concentration measurements.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If a fast response time sensor is used, then response speed is improved, but measurement precision deteriorates due to offset errors and gain errors
Solution Approach 1:
The patent combines data from a fast response time sensor (first sensor) and a high accuracy sensor (second sensor) using a controller to create a blended analyte value. This merging allows the system to achieve both fast response and high measurement precision by leveraging the complementary strengths of each sensor type.
Solution Approach 2:
The controller dynamically adjusts the blending parameters based on sensor performance characteristics. By changing the weighting parameters in the blending algorithm, the system optimizes the contribution of each sensor to achieve the desired balance between response speed and measurement precision under different conditions.
2Measurement precision
If a high accuracy sensor is used, then measurement precision is improved, but response time deteriorates due to sensor latency
Solution Approach 1:
The system merges data from both sensors with the controller creating a blended analyte value that compensates for the latency of the high accuracy sensor. The fast sensor provides timely data that compensates for the delay inherent in high accuracy measurements.
Solution Approach 2:
The controller acts as an intermediary that processes and blends data from both sensors. It reconciles the timing differences between the fast response sensor and the high accuracy sensor, producing a blended value that reflects both speed and precision without the latency penalty of using the high accuracy sensor alone.
3Reliability
If multiple sensors are combined, then reliability is improved, but device complexity increases
Solution Approach 1:
The controller is designed to perform multiple functions: it receives data from both sensors, processes the raw signals, applies the blending algorithm, and outputs the blended analyte value. This multi-functionality reduces the need for separate processing units and simplifies the overall system architecture.
Solution Approach 2:
The system uses its own internal resources to process and blend sensor data. The controller leverages the existing sensor outputs and applies mathematical blending operations without requiring external complex processing systems, thereby maintaining reliability while managing complexity through self-sufficient data processing.
Data Source
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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.