Robust Heart Rate Estimation During Physical Exercise Using Photoplethysmographic Signals

Area of Science:

• Biomedical Engineering
• Physiological Monitoring
• Signal Processing

Background:

• Estimating heart rate (HR) from photoplethysmographic (PPG) signals during physical exercise is challenging due to motion artifacts.
• Intense physical activity can corrupt PPG signals, leading to inaccurate HR readings by shifting spectral peaks.

Purpose of the Study:

• To develop and validate a robust method for accurate HR estimation from PPG signals contaminated by motion artifacts during exercise.
• To address the limitations of existing methods in handling high-intensity motion during physiological monitoring.

Main Methods:

• The proposed method utilizes spectral estimation combined with median filtering to process PPG signals.
• This approach is designed to identify and correct for distortions caused by motion artifacts in the PPG waveform.

Main Results:

• Experimental results from 12 subjects running at high speeds demonstrated the effectiveness of the method.
• The average absolute error in HR estimation was found to be as low as 1.31 beats/minute.

Conclusions:

• The developed technique provides a simple yet effective solution for reliable HR monitoring during strenuous physical activities.
• This method shows significant potential for improving the accuracy of wearable fitness trackers and medical monitoring devices.