Adaptive ECG Noise Detection for Unsupervised Wearable Monitoring
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Solution Overview
Problem
Wearable ECG devices often record ECGs with inherent noise due to lack of supervision, leading to challenges in proper device handling and signal quality issues.
Innovation Solution
An apparatus and method for adaptive noise detection in wearable devices, utilizing a physiological signal input channel, adaptive noise detector, and signal characteristic model to generate a profile based on training data, determining signal quality and transmitting only signals within a predefined tolerance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If wearable ECG devices record continuously without supervision, then productivity is improved, but signal quality deteriorates due to inherent noise
Solution Approach 1:
The patent implements a feedback mechanism where the signal characteristic model continuously analyzes recorded ECG signals and provides real-time quality assessment. The system compares signal characteristics against the trained model to determine if signals meet quality thresholds, enabling automatic quality control during continuous monitoring without requiring expert supervision.
Solution Approach 2:
The system performs self-service through automated noise detection and quality assessment. The signal characteristic model, trained on profile training data, enables the device to autonomously evaluate signal quality, filter noisy recordings, and transmit only high-quality signals without external intervention, resolving the contradiction between continuous monitoring and signal quality maintenance.
2Measurement precision
If real-time noise detection is implemented, then signal quality is improved, but device complexity increases
Solution Approach 1:
The patent applies preliminary action by training the signal characteristic model offline using profile training data collected from reference devices. This pre-training phase prepares the model to perform rapid noise detection during actual use, reducing the computational burden during real-time operation while maintaining high signal quality assessment capabilities.
3Measurement precision
If signal filtering is applied to remove noise, then purity is improved, but loss of information may occur
Solution Approach 1:
The system dynamically adjusts the noise detection threshold parameter based on the trained signal characteristic model. By optimizing this parameter, the system achieves the right balance between removing noise (improving purity) and preserving genuine signal features (minimizing information loss), ensuring that only signals exceeding the quality threshold are transmitted.
Data Source
AI summary
An apparatus and method for adaptive noise detection in wearable devices. The apparatus includes at least a physiological signal input channel configured to receive a physiological signal from a subject. The apparatus for adaptive noise detection in wearable devices further includes an adaptive noise detector communicatively connected to the at least a physiological signal input channel, wherein the adaptive noise detector further includes a signal characteristic model configured to generate a signal characteristic profile based on the physiological signal using profile training data, a signal output datapath, and a decision block.