Smartwatch ECG Monitoring for Idiopathic Arrhythmia Detection
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Solution Overview
Problem
Current methods for monitoring and diagnosing idiopathic arrhythmias are inadequate due to their idiopathic nature, which makes them difficult to detect with short monitoring windows and non-real-time data analysis, leading to delayed diagnosis and increased healthcare costs, and existing wearable devices are not adapted for long-term, real-time monitoring.
Innovation Solution
A system utilizing machine learning approaches, including neural networks, to detect and predict idiopathic arrhythmias through electrocardiogram sensors, which can alert emergency services and update electronic medical records, allowing for real-time monitoring and long-term data collection with a non-invasive, cost-effective smart device.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If common ECG or ambulatory ECG procedures are used for monitoring, then the monitoring can be performed with standard equipment, but the monitoring window is too short to detect idiopathic arrhythmias and data analysis is not done in real time
Solution Approach 1:
The system performs preliminary data collection and processing by continuously acquiring ECG signals and pre-processing them through filtering and feature extraction. This preliminary action enables the system to have ready-to-analyze data when arrhythmia episodes occur, improving detection reliability without requiring excessively long monitoring periods.
Solution Approach 2:
The monitoring system operates continuously in the background, constantly acquiring and pre-processing ECG data without interruption. This continuous operation ensures that no arrhythmia episode is missed while maintaining real-time analysis capability, resolving the contradiction between monitoring duration and detection reliability.
2Duration of action of moving object
If a subcutaneous Holter monitor is used, then monitoring periods of over 2 years are possible with 87% smaller size, but it is invasive, single use and expensive
Solution Approach 1:
The system employs a disposable, non-invasive smartwatch that can be worn and then discarded or replaced. This approach eliminates the invasiveness of subcutaneous monitors while maintaining long monitoring capability through multiple uses of the same device type. The device is designed for ease of replacement rather than permanent implantation.
Solution Approach 2:
The patent replaces the mechanical/invasive subcutaneous electrode system with a non-invasive optical or surface electrode system integrated into a smartwatch. This substitution eliminates skin penetration and associated harms while maintaining monitoring functionality through alternative sensing mechanisms.
3Reliability
If Holter monitor is worn at patient's waist, then ECG can be recorded over 24-48 hours, but it causes nuisance to patients for sleeping and day-to-day activities
Solution Approach 1:
The monitoring device is integrated into a thin, flexible smartwatch that conforms to the wrist anatomy. This form factor is significantly less obtrusive than waist-worn Holter monitors, allowing patients to sleep and perform daily activities without nuisance while maintaining continuous ECG recording capability.
4Measurement precision
If data is uploaded to post-processing system after monitoring period, then comprehensive analysis can be performed, but diagnosis is delayed and healthcare costs increase
Solution Approach 1:
The system implements real-time feedback by continuously analyzing ECG data as it is acquired and immediately notifying patients and healthcare providers when arrhythmia is detected. This eliminates the delay inherent in post-processing approaches while maintaining analysis accuracy through the same sophisticated algorithms, thereby reducing diagnosis time without sacrificing measurement precision.
Solution Approach 2:
The system performs preliminary real-time analysis of ECG data during the monitoring period itself, rather than waiting for post-processing. This preliminary action enables immediate detection and notification of arrhythmias, dramatically reducing diagnosis time while the same data can subsequently undergo comprehensive post-processing analysis for confirmation and detailed characterization.
Data Source
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AI summary
According to an aspect of the invention, it is provided a method for detecting idiopathic arrythmias of a user, comprising: • Receiving a first signal (13) acquired by an electrocardiogram sensor (11); • Determining an occurrence of idiopathic arrythmia in the first signal (13) based on a comparison between said first signal (13) and at least one reference signals; and • When the occurrence of the idiopathic arrythmia is determined: ∘ Requesting the user to provide information about his/her health state; and ∘ Sending a message based on the first signal (13) and the information about the health state of the user