ECG Signal Processing for Power-Efficient Ambulatory Monitoring
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Solution Overview
Problem
Conventional systems for monitoring physiological signals, such as ECG, face challenges in accuracy, reliability, and power efficiency, particularly in ambulatory settings, due to the need for significant power and processing resources to communicate waveforms and ensure data integrity.
Innovation Solution
A system comprising ECG sensing electrodes, digitizing and computing circuits, and a fastener for mechanical and electrical coupling, which processes ECG signals to remove noise, detect intervals, and compute signal-to-noise ratios, allowing for efficient data compression and transmission, while reducing power consumption and device size.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If waveform communication is implemented to ensure data accuracy and reliability, then measurement precision is improved, but use of energy increases significantly
Solution Approach 1:
The patent extracts only the essential features and parameters from the complete waveform signal for transmission and storage. Instead of communicating the entire waveform, the system identifies and transmits key characteristic points and derived parameters, significantly reducing data volume and power consumption while maintaining measurement precision for clinical decision-making.
Solution Approach 2:
The system performs preliminary processing of the waveform signal locally to pre-identify important features and parameters before transmission. By conducting feature extraction and parameter calculation in advance at the monitoring device, the system reduces the burden on communication channels and storage systems while ensuring accurate data representation.
2Reliability
If complete waveform data is transmitted and archived, then reliability is improved, but device complexity increases
Solution Approach 1:
The system extracts only the critical features and parameters from the complete waveform for archiving and transmission. This selective extraction approach maintains data reliability by preserving essential diagnostic information while significantly reducing the complexity of data management, storage requirements, and processing resources needed.
3Measurement precision
If signal processing is performed to remove noise and detect features, then measurement precision is improved, but use of energy increases
Solution Approach 1:
The system applies targeted signal processing techniques that extract only the essential features needed for accurate measurement. By focusing processing efforts on identifying key characteristic points and relevant parameters rather than processing the entire signal, the system achieves high measurement precision with reduced energy consumption.
Data Source
AI summary
Physiological signals such as ECG signals are obtained from a patient. In accordance with one or more embodiments, an apparatus, system and/or method is directed to process the digitized ECG signals (e.g., by removing noise).