Real-Time Heart Rate Monitoring for Wearable Electrocardiography Using Filter-Based and Peak Threshold Algorithms: A Comparative Study

Desima Klaudia Hasibuan; Indra Hardian Mulyadi

doi:10.30871/ji.v10i2.983

Desima Klaudia Hasibuan Departement of Electrical Engineering, Politeknik Negeri Batam
Indra Hardian Mulyadi Departement of Electrical Engineering, Politeknik Negeri Batam

DOI: https://doi.org/10.30871/ji.v10i2.983

Keywords: Wearable electrocardiograph, Bluetooth, heart rate, real-time monitoring, AD8232

Abstract

Wearable and wireless Electrocardiograph (ECG) enables real-time and long-term monitoring of heart rate (i.e. 24 hours). Several algorithms have been introduced to increase the accuracy of the heart rate calculation for this type of ECG. This study aims to compare the accuracy of two heart rate calculation algorithms: Filter-Based and Peak Threshold. Both algorithms were implemented into a wearable ECG prototype comprising AD8232, 8-bit microcontroller (ATMega328), and Bluetooth. ECG signals and heart rate (in Beat per Minute (BPM)) were sent via Bluetooth and displayed in real-time on a Windows-based application created using Visual C #. Experiments were conducted on 10 healthy subjects aged 20.4 ± 2.0 years and body weight of 60.8 ± 10.2 kg. The measurement results calculated by using Filter-Based and Peak Threshold were compared to a commercial wearable ECG (Kinetic^TM) as a ‘ground truth’. The test results showed that the Filter-Based algorithm resulted in a more accurate calculation with the Root Mean Square Error (RMSE) of 1.53, compared to the Peak Threshold algorithm with RMSE of 2.69.

Downloads

Download data is not yet available.

References

[1] Emelia J. Benjamin et al., "Heart Disease and
Stroke Statistics-2017 Update: A Report From the
American Heart Association," American Heart
Association, 2017.
[2] Pusdatin, "Info Data: Situasi Kesehatan
Jantung," Kementrerian Kesehatan Republik
Indonesia, Jakarta, 2014.
[3] Jakko Malviuo and Robert Plonsey,
Bioelectromagnetism-Principles and
Applications of Bioelectric and Biomagnetic
Fields. New York: Oxford University Press,
1995.
[4] H.C. Chen and S.W. Chen, "A Moving Average
based Filtering with its Application to Reak-time
QRS Detection," in Computers in Cardiology,
Thessaloniki Chalkidiki, 2003, pp. 585-588.
[5] J. Pan and W. J. Tompkins, "A Real-Time QRS
Detection Algorithm," IEEE Transactions on
Biomedical Engineering, vol. BME-32, no. 3,
pp. 230-236, March 1985.
[6] Trio Pambudi Utomo, Nuryani Nuryani, and
Darmanto, "QRS Peak Detection for Heart Rate
Monitoring on Android Smartphone," Journal of
Physics: Conference Series, vol. 909, no. 1, pp.
1-7, 2017.