Wearable Arrhythmia Detection Using Rest-State Heartbeat Screening
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Solution Overview
Problem
Existing methods for detecting cardiac arrhythmia are inconvenient and inefficient, often requiring noticeable symptoms and are not feasible for continuous monitoring, and lack effective threshold-based prediction systems.
Innovation Solution
A system using a wearable device with an accelerometer to detect periods of rest, measure heartbeat intervals, and analyze them for arrhythmia probability, alerting the user to take an electrocardiogram when thresholds are exceeded, followed by electrocardiogram analysis for confirmation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional ECG procedure is used for detecting cardiac arrhythmia, then detection accuracy is improved, but convenience and feasibility for continuous monitoring deteriorates
Solution Approach 1:
The patent replaces the mechanical ECG measurement system with an optical measurement system using a photoplethysmogram (PPG) sensor. The PPG sensor uses light to detect blood volume changes in the microvascular bed, substituting the electrical field-based ECG method with an optical field-based method that can be continuously monitored through a wearable device.
Solution Approach 2:
The system automatically detects periods of rest using an accelerometer and autonomously triggers heartbeat interval measurements without requiring user initiation. The wearable device self-monitors the user's activity state and performs arrhythmia detection measurements automatically during rest periods, eliminating the need for manual operation.
2Productivity
If heartbeat interval measurement is performed continuously, then arrhythmia detection capability is improved, but measurement quality and reliability deteriorates due to movement interference
Solution Approach 1:
The system dynamically adjusts its measurement strategy based on the user's activity state. The accelerometer continuously monitors movement, and when a period of rest is detected (acceleration below threshold), the system automatically triggers a heartbeat interval measurement. This dynamic adaptation ensures high-quality measurements during rest while avoiding unreliable measurements during movement.
Solution Approach 2:
The system performs preliminary detection of rest periods using the accelerometer before initiating the actual heartbeat interval measurement. By first identifying when the user is at rest through acceleration threshold comparison, the system prepares and triggers the measurement at the optimal time, ensuring measurement quality from the outset.
3Loss of time
If threshold-based probability prediction is implemented, then early warning capability is improved, but false alarm rate increases
Solution Approach 1:
The system uses feedback from multiple measurement cycles to refine arrhythmia probability assessment. Heartbeat intervals are measured over multiple periods during rest, and the probability of arrhythmia is calculated based on the variability and patterns observed across these repeated measurements. This feedback mechanism allows the system to distinguish between normal variations and true arrhythmia signs, reducing false alarms while maintaining early warning capability.
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
Enables reliable and efficient detection of arrhythmia by improving measurement quality during rest periods, reducing interference, and providing timely alerts for confirmed arrhythmia conditions.
Implementation Method 1
a wearable device with an accelerometer to detect periods of rest
Implementation Method 2
measuring a photoplethysmogram of the person for a period of time
Data Source
Figure 1~2
Figure 3~4B
Figure 5A~6
AI summary
Disclosed are a system and a method for determining a probability for a person to have arrhythmia. The system (100) comprises means for measuring heartbeat interval of the person (102) for a period of time; an accelerometer; means for measuring an electrocardiogram (116) of the person (102); a user interface (114) for providing information and alerts, and a processor (112). The processor (112) is configured to detect a period of rest of the person (102), based on measurement data from the accelerometer; analyse the measured heartbeat interval to determine a probability of having arrhythmia for the person; generate an alert to the user interface (114), if the probability exceeds a predetermined threshold value, to alert the person to measure the electrocardiogram with the means for measuring an electrocardiogram (116); analyse the measured electrocardiogram to determine if the probable arrhythmia is confirmed; and indicate the confirmed arrhythmia to the person (102) via the user interface (114).