Arduino-based noise robust online heart-rate detection

Area of Science:

• Biomedical Engineering
• Signal Processing
• Wearable Technology

Background:

• Electrocardiogram (ECG) signals are crucial for monitoring heart rate.
• Real-time and noise-robust heart rate detection remains a challenge in ambulatory settings.
• Existing methods may require complex hardware or are susceptible to artifacts.

Purpose of the Study:

• To develop and validate a noise-robust, real-time heart rate detection system using ECG data.
• To implement an automated, low-cost system for heart rate monitoring.
• To assess the system's accuracy and performance against established techniques.

Main Methods:

• An online data acquisition system was developed for collecting human ECG signals.
• Heart rate detection was performed using a window-based autocorrelation peak localization technique.
• A low-cost Arduino UNO board was utilized for the complete automated implementation.

Main Results:

• The system demonstrated high accuracy, with a mean percentage error of 0.72% in detected heart rate.
• Performance was validated using simulated noisy ECG data across various signal-to-noise ratio (SNR) levels.
• The automated system's performance was comparable to PC-based heart rate detection techniques.

Conclusions:

• The developed system offers a noise-robust and accurate solution for real-time heart rate detection from ECG.
• The low-cost, automated implementation using Arduino UNO makes it suitable for accessible health monitoring.
• The system's reliability in the presence of noise is a significant advancement for practical ECG-based heart rate monitoring.