Sensor Algorithm Configuration for Physiological Monitoring
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Solution Overview
Problem
Physiological monitoring systems face challenges in updating algorithms for sensors, leading to suboptimal calculations of patient parameters due to outdated configurations and differing sensor capabilities, which affect the accuracy and quality of measurements.
Innovation Solution
The system allows for algorithm configuration data to be stored on sensors, enabling them to transmit updated configurations to monitors, allowing for real-time execution and deletion of configurations when sensors disconnect, ensuring the use of specific and improved algorithms based on sensor capabilities.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If algorithm configuration data is stored centrally in monitors, then field updates can be managed centrally, but all monitors must be updated to use latest algorithms, causing loss of time and reduced productivity
Solution Approach 1:
The patent segments the algorithm configuration system by storing algorithm configuration data locally in each sensor device rather than centrally in monitors. This allows each sensor to independently provide updated algorithms to connected monitors without requiring system-wide updates, resolving the contradiction between consistency and update time.
Solution Approach 2:
The patent introduces the sensor as an intermediary carrier that stores and transmits algorithm configuration data to monitors. This intermediary role allows algorithms to be distributed from sensors to monitors on-demand, eliminating the need for centralized field updates while maintaining algorithm consistency through the sensor's local storage.
2Device complexity
If generic algorithms are used in monitors, then device complexity is reduced, but measurement precision deteriorates due to inability to account for specific sensor capabilities
Solution Approach 1:
The patent applies local quality by storing sensor-specific algorithm configuration data directly in each sensor device. This allows each sensor to provide tailored algorithms that account for its specific capabilities and characteristics, improving measurement precision without requiring complex centralized configuration management in monitors.
Solution Approach 2:
The patent enables parameter changes by allowing algorithm configuration data to be dynamically transmitted from sensors to monitors. This permits the monitor to adapt its processing parameters based on the specific sensor connected, improving measurement precision while keeping the monitor's base structure simple.
3Reliability
If algorithm updates are performed through field updates of all monitors, then centralized control is maintained, but productivity decreases due to the need to update every installed monitor
Solution Approach 1:
The patent implements self-service by enabling sensors to autonomously store and transmit their own algorithm configuration data to connected monitors. This eliminates the need for manual field updates of monitors, as each sensor automatically provides the appropriate algorithms when connected, dramatically improving deployment efficiency while maintaining control through the sensor's pre-configured data.
4Measurement precision
If sensor-specific algorithm configurations are stored in each sensor, then measurement precision is improved, but device complexity increases due to memory requirements in sensors
Solution Approach 1:
The patent applies preliminary action by pre-storing algorithm configuration data in the sensor's memory during manufacturing or initial setup. This preliminary preparation allows the sensor to immediately provide optimized algorithms when connected to a monitor, improving measurement precision without requiring complex real-time configuration processing or large memory capacities during operation.
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
This approach enhances the quality and accuracy of physiological parameter calculations by ensuring the latest algorithm configurations are used, improving measurement precision and adaptability to different sensor types without the need for widespread field updates.
Implementation Method 1
a sensor configured to store algorithm configuration data and generate a photoplethysmography (PPG) signal
Implementation Method 2
at least one light detector configured to receive the light signal after the light signal has been attenuated by body tissue of a subject
Data Source
AI summary
Systems and methods are provided for operating a physiological monitoring system that comprises a distributed algorithm. The physiological monitoring system may comprise a sensor and a physiological monitor that may be communicatively coupled with the sensor. The sensor may store algorithm configuration data; and the physiological monitor may store an executable code segment configured to execute a first algorithm. The physiological monitor may be configured to receive the algorithm configuration data and to configure or modify at least part of the first algorithm based upon the algorithm configuration data to determine at least one physiological parameter of a subject based on physiological signal provided by the sensor.