Heartbeat Detection via Derivative-Product Signal Processing
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Solution Overview
Problem
Conventional heartbeat detection methods struggle to accurately detect heartbeats in ECG waveforms contaminated with noise from body motion, leading to incorrect threshold settings and misidentification of noise as heartbeats.
Innovation Solution
A method that calculates the amount or degree of change in sampling data, multiplies it by previous sampling data, and detects peaks in the product to determine heartbeat times, effectively emphasizing peak components and reducing noise interference.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If a threshold-based method is used to detect R waves in ECG waveforms, then heartbeat detection is simplified, but noise components are misidentified as heartbeats and detection accuracy deteriorates
Solution Approach 1:
The patent segments the ECG waveform analysis into multiple processing stages: first derivative calculation to emphasize abrupt changes, multiplication with original waveform to enhance peak components, and threshold-based peak detection. This segmentation allows each stage to address specific aspects of the detection problem, improving overall accuracy while maintaining operational simplicity.
Solution Approach 2:
The patent introduces an intermediary processing step by multiplying the first derivative values with the original ECG waveform values. This intermediary operation serves as a mediator that enhances the peak components derived from heartbeats while suppressing noise, bridging the gap between simple threshold detection and accurate heartbeat identification.
2Difficulty of detecting and measuring
If the first derivative of ECG waveform is used to detect heartbeats, then abrupt changes from R wave to S wave are made conspicuous, but noise components that abruptly change are misidentified as heartbeats
Solution Approach 1:
The patent merges two signal processing operations: calculating the first derivative of the ECG waveform and multiplying it with the original waveform values. This combination preserves the advantage of making abrupt changes conspicuous while simultaneously enhancing peak components and suppressing noise, thereby solving the misidentification problem.
Solution Approach 2:
The patent creates a composite signal processing approach by combining the first derivative signal with the original ECG waveform through multiplication. This composite processing method integrates the strengths of both signals: the derivative's ability to highlight abrupt changes and the original waveform's ability to maintain peak structure, resulting in improved detection accuracy.
3Adaptability or versatility
If threshold is periodically updated based on peak values, then adaptation to waveform variations is improved, but threshold increases in noisy portions causing false negatives
Solution Approach 1:
The patent performs preliminary processing of the ECG waveform by calculating the first derivative and multiplying with original values before threshold-based detection. This preliminary action prepares the signal by enhancing peak components and suppressing noise, ensuring that subsequent threshold updates are based on reliable peak values rather than noise, thus maintaining both adaptability and reliability.
Data Source
AI summary
A heartbeat detection device includes a difference value calculation unit (3) for calculating, from a sampling data sequence of an electrocardiographic waveform of a living body, one of an amount of change and a degree of change of sampling data for each sampling time, a multiplication unit (4) for calculating, for each sampling time, a product by multiplying one of an amount of change and a degree of change of the sampling data at a time K by one of the sampling data at the time K and sampling data at a time before the time K by a predetermined time t, a peak detection unit (5) for detecting a peak of the product, and a heartbeat time determination unit (6) for setting time of the peak of the product as a heartbeat time.