Heartbeat detector from ECG and PPG signals based on wavelet transform and upper envelopes

Area of Science:

• Biomedical Engineering
• Signal Processing
• Cardiology

Background:

• Cardiac activity analysis is crucial for health monitoring and performance evaluation.
• Electrocardiogram (ECG) and photoplethysmogram (PPG) are common methods for recording cardiac activity, despite differing waveforms.
• The first derivative of PPG signals exhibits structural similarity to ECG, suggesting shared analysis techniques.

Purpose of the Study:

• To develop a robust technique for detecting heartbeats in both ECG and PPG signals.
• To leverage signal processing methods for enhanced cardiac activity analysis.
• To compare the proposed technique against existing methods for accuracy and adaptability.

Main Methods:

• A novel technique utilizing wavelet transform and envelopes for heartbeat detection.
• Wavelet transform is employed to enhance QRS complexes in cardiac signals.
• Envelopes serve as an adaptive threshold for precise temporal localization of heartbeats.

Main Results:

• The proposed method achieved >99.94% accuracy, 99.96% true positive rate, and 99.76% positive prediction value for ECG signals.
• For PPG signals, the method yielded >99.27% accuracy, 99.98% true positive rate, and 99.50% positive prediction value.
• The technique demonstrated superior performance compared to three other methods on both ECG and PPG datasets.

Conclusions:

• The developed wavelet and envelope-based technique effectively detects heartbeats in both ECG and PPG signals.
• The method shows high accuracy and adaptability across different cardiac signal recording technologies.
• This approach offers a promising advancement for non-invasive cardiac monitoring and analysis.