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An Algorithm for Initial Localization of Feature Waveforms Based on Differential Analysis Parameter Setting and Its Application in Clinical Electrocardiograms.
- Source :
- Electronics (2079-9292); Aug2024, Vol. 13 Issue 15, p2996, 16p
- Publication Year :
- 2024
-
Abstract
- In a biological signal analysis system, signals of the same type may exhibit significant variations in their feature waveforms. Biological signals are typically weak, which increases the complexity of their analysis. Furthermore, clinical biomedical signals are susceptible to various interferences from the human body itself, including muscle movements, respiration, and heartbeat. These interference factors further escalate the complexity and difficulty of signal analysis. Therefore, precise and targeted preprocessing is often required before analyzing these clinical biomedical signals to enhance the accuracy and reliability of subsequent feature extraction and classification. Here, we have established an effective and practical algorithm model that integrates preprocessing with the initial localization of target feature waveforms, achieving the following four objectives: 1. Determining the periodic positions of target feature waveforms. 2. Preserving the original amplitude and shape of target feature waveforms while eliminating negative interference. 3. Reducing or eliminating interference from other feature waveforms in the input signal. 4. Decreasing noise in the input signal, such as baseline drift, powerline interference, and muscle artifacts commonly found in biological signals. We have validated the algorithm on clinical electrocardiogram (ECG) data and the authoritative MIT-BIH open-source ECG database demonstrating its effectiveness and reliability. [ABSTRACT FROM AUTHOR]
- Subjects :
- MEDICAL protocols
DATABASES
HUMAN body
CLINICAL medicine
SIGNALS & signaling
Subjects
Details
- Language :
- English
- ISSN :
- 20799292
- Volume :
- 13
- Issue :
- 15
- Database :
- Complementary Index
- Journal :
- Electronics (2079-9292)
- Publication Type :
- Academic Journal
- Accession number :
- 178947658
- Full Text :
- https://doi.org/10.3390/electronics13152996