Wireless Sensor Association Verification via Signal Confidence
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Solution Overview
Problem
Wireless patient monitoring systems face challenges in ensuring accurate association of sensors with the correct patient due to the lack of visual cues provided by cables, leading to potential misconnection and incorrect data reception.
Innovation Solution
A wireless system with a hub and peripheral devices that use wireless communication to transmit physiological data to a processor, which registers and evaluates the association status of each sensor with the patient by deriving confidence values based on signal characteristics and attributes, providing a graphical user interface for confirmation and alarm notifications.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If wireless communication is used to eliminate cables, then ease of operation and device management are improved, but the ability to visually confirm proper connection between sensor and patient is lost
Solution Approach 1:
The system provides automatic feedback by monitoring wireless signal characteristics (signal strength, consistency, physiological plausibility) and comparing them against expected values for proper sensor-patient association. The processor generates confidence scores and visual indicators that continuously feedback to clinicians about the reliability of the sensor-patient association, eliminating the need for manual cable verification while maintaining connection confirmation reliability.
Solution Approach 2:
The patent replaces the mechanical cable connection system with a wireless communication system. Instead of relying on physical cable presence as the verification mechanism for proper connection, the system uses wireless signal characteristics (RF signal strength, signal consistency, physiological data plausibility) to verify sensor-patient association, substituting mechanical verification with electronic and computational verification methods.
2Adaptability or versatility
If multiple wireless sensors are deployed, then monitoring coverage is improved, but the risk of inadvertent connection to wrong patient increases
Solution Approach 1:
The system segments the monitoring environment by creating unique identification and verification mechanisms for each sensor-patient pair. Each wireless sensor is assigned specific identification data and associated with particular patient characteristics (demographics, medical record number, room location). The processor evaluates multiple independent attributes (signal strength, physiological consistency, demographic matching) for each sensor individually, allowing simultaneous monitoring of multiple patients while preventing cross-contamination of data.
Solution Approach 2:
The processor acts as an intermediary between wireless sensors and the central monitoring system, performing verification and validation functions. It receives raw wireless signals from multiple sensors, evaluates their association attributes against patient-specific criteria, and only transmits confirmed valid data to the monitoring system. This intermediary layer prevents inadvertent connection errors by filtering and verifying sensor-patient associations before data is used for patient care.
3Productivity
If automated association evaluation is implemented, then productivity is improved by reducing manual verification time, but device complexity increases
Solution Approach 1:
The system implements self-service by enabling automatic self-verification of sensor-patient associations. The wireless sensors automatically transmit their identification and signal characteristics, and the processor automatically evaluates association attributes (signal strength, physiological plausibility, demographic matching) without requiring manual intervention. The system self-corrects and self-validates connections, reducing clinician workload while managing complexity through automated algorithms rather than manual procedures.
Data Source
AI summary
Systems and methods of evaluating an association between a wireless sensor and a monitored patient include a plurality of peripheral electronic devices each having a wireless communication system and a sensor. A processor receives measured physiological parameter data from the peripheral electronic devices and establishes an association status between each of the peripheral electronic devices and the monitored patient based upon identified characteristics in the physiological parameter data.