Vital-Signs Monitor Patch With Adaptive Sampling for False Alarm Reduction
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Solution Overview
Problem
Existing vital-sign monitoring systems often generate false alarms, leading to unnecessary interventions and increased workload for healthcare providers, and continuous monitoring is cumbersome and impractical due to the need for intrusive sensor connections and frequent manual measurements.
Innovation Solution
A vital-signs monitor patch with integrated electrodes and sensors that communicates wirelessly to a surveillance server, adjusting sampling rates based on alert conditions to reduce false alarms and allow continuous, minimally intrusive patient monitoring.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If continuous monitoring is implemented using traditional intrusive methods, then monitoring reliability is improved, but patient comfort and ease of operation deteriorate due to intrusive sensor connections and frequent manual measurements
Solution Approach 1:
The patent replaces traditional mechanical/intrusive sensor connections with wireless communication technology. The monitor patch communicates vital sign data wirelessly to the external receiver, eliminating the need for cumbersome wired connections and intrusive sensors, thereby maintaining monitoring reliability while significantly improving patient comfort and ease of operation
Solution Approach 2:
The monitoring system is divided into separate functional modules: a minimally intrusive monitor patch that collects vital sign data and an external receiver that processes and displays the data. This segmentation allows the patch to remain simple and comfortable for the patient while the complex processing functions are handled externally
2Measurement precision
If fixed high sampling rate is used, then measurement precision is improved, but energy consumption increases and false alarms increase
Solution Approach 1:
The patent implements dynamic sampling rate adjustment where the sampling frequency adapts based on the patient's physiological state and alert conditions. During normal conditions, a lower sampling rate conserves battery power, while during alert conditions, the sampling rate increases automatically to improve measurement precision and detect critical changes
Solution Approach 2:
The system changes the sampling rate parameter dynamically based on detected conditions. The processor adjusts the sampling frequency from a first rate during normal operation to a second rate during alert conditions, optimizing both energy consumption and measurement precision according to actual needs
3Measurement precision
If fixed high sampling rate is used, then measurement precision is improved, but false alarms increase due to excessive data processing
Solution Approach 1:
The system dynamically adjusts sampling rates based on alert conditions, using higher rates only when necessary to detect critical changes. This reduces the overall number of data points processed, thereby reducing false alarms while maintaining measurement precision during critical events
Solution Approach 2:
The processor changes the sampling rate parameter from a first rate to a second rate based on detected alert conditions. This parameter adjustment optimizes the balance between measurement precision and false alarm reduction by processing more data only when clinically necessary
4Productivity
If continuous monitoring is implemented, then productivity is improved by reducing manual measurements, but device complexity increases due to continuous data processing requirements
Solution Approach 1:
The monitoring system is segmented into a simple monitor patch for data collection and a separate external receiver for complex data processing and display. This division reduces the complexity of the wearable device while maintaining continuous monitoring capabilities that improve nurse productivity
Solution Approach 2:
The monitor patch autonomously performs vital sign measurements and wireless data transmission without requiring manual intervention. The system automatically processes data and generates alerts, reducing nurse workload and improving productivity while keeping the patch design relatively simple
Data Source
AI summary
Systems and methods of reducing false alarms associated with a vital-sign monitor are disclosed. One or more data samples of a vital sign of a patient are generated at a first sampling rate in a normal mode of operation. Whether the one or more data samples satisfy an alert condition is determined. An alert mode of operation is entered into if the alert condition is satisfied. One or more additional data samples of the vital sign are generated at a second sampling rate higher than the first sampling rate in the alert mode.