Multi-rate ECG Processing for Low-power R-R Interval Measurement
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Solution Overview
Problem
Wireless sensor devices face challenges in measuring R-R intervals due to motion artifact noise and baseline wander, which require extensive mathematical calculations, leading to higher power consumption and reduced battery life.
Innovation Solution
A method and system for R-R interval measurement using multi-rate ECG processing, where a wireless sensor device detects an ECG signal, performs QRS peak detection, and calculates R-R intervals based on high resolution peaks obtained by sampling at varying rates, reducing power consumption through efficient processing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If extensive mathematical calculations are performed to create robust heart function measurement algorithms, then measurement reliability is improved, but power consumption increases
Solution Approach 1:
The ECG signal processing is segmented into two distinct stages: a low-resolution detection phase that identifies approximate QRS peak locations using minimal computation, and a high-resolution refinement phase that precisely determines peak positions only in the vicinity of detected candidates. This segmentation allows the system to achieve reliable measurements while minimizing overall power consumption by applying intensive calculations only where necessary.
Solution Approach 2:
The system applies partial action by performing extensive mathematical calculations only locally around detected low-resolution peaks rather than across the entire ECG signal. The high-resolution search is confined to a limited time window surrounding each candidate peak, reducing the total computational burden while maintaining measurement reliability in critical regions.
2Measurement precision
If high resolution peak detection is performed across the entire ECG signal, then measurement precision is improved, but processing time and power consumption increase
Solution Approach 1:
The signal processing is divided into two segments: a first pass at low resolution to identify candidate peak regions, and a second pass at high resolution focused only on those candidate regions. This segmentation eliminates the need to apply computationally intensive high-resolution algorithms to the entire ECG signal, thereby reducing processing time while maintaining precision where it matters most.
Solution Approach 2:
The low-resolution peak detection serves as a preliminary action that pre-identifies regions of interest before the high-resolution search is performed. By first locating approximate peak positions using minimal processing, the system prepares the groundwork for subsequent precise measurement only in relevant time windows, avoiding unnecessary computations in non-critical regions.
3Reliability
If robust heart function measurement algorithms are implemented, then measurement reliability is improved, but device complexity increases
Solution Approach 1:
The algorithm is segmented into two distinct processing stages with different complexity levels. The first stage uses simple low-resolution detection to identify candidate peaks, while the second stage applies more complex high-resolution refinement only to those candidates. This segmentation reduces overall device complexity by avoiding the need to implement full high-resolution processing across the entire signal continuously.
Solution Approach 2:
The system dynamically adjusts processing intensity based on signal characteristics. Rather than maintaining constant high computational effort, the algorithm transitions between low and high resolution modes depending on whether a peak candidate is detected, optimizing the balance between reliability and complexity in real-time operation.
Data Source
AI summary
A method and system for R-R interval measurement of a user are disclosed. In a first aspect, the method comprises detecting an electrocardiogram (ECG) signal of the user. The method includes performing QRS peak detection on the ECG signal to obtain a low resolution peak and searching near the low resolution peak for a high resolution peak. The method includes calculating the R-R interval measurement based upon the high resolution peak. In a second aspect, a wireless sensor device comprises a processor and a memory device coupled to the processor, wherein the memory device includes an application that, when executed by the processor, causes the processor to carry out the steps of the method.