ABSTRACT
In heart rate variability (HRV) measurement, a Holter monitor is typically used to observe ECG data. However, since this device lacks mobility, any alternative wearable devices with a similar capability of recording cardiac data are preferred. On the other hand, the application provided alongside wearable devices are mostly installed in smartphone environments, which cause significant concern in user’s privacy. It is better to develop our application to calculate sensitive data. This study proposed an application that utilizes a commercialized wearable wireless device to collect electrocardiography data and performs an HRV measurement using time domain, frequency domain, and nonlinear domain. Furthermore, it also examines RR interval and ECG data produced by Polar H10. This study is done by prototyping and experimenting involving participants in a laboratory environment. As a result, the proposed application successfully extracts several pieces of information based on HRV measurement. Using T-test shows data RR interval data and ECG data produced by Polar H10 are equal. Thus, RR interval data is suggested for HRV measurement instead of ECG data from the device. Because in ECG data produced by Polar H10 consist of noise especially in early recording. The benefit of using this application is the ability to conducting real-time and continuous measurement cardiac data based on HVR methods.
- Van Gent. 2018. Heart Rate Analysis for Human Factors: Development and Validation of an Open Source Toolkit for Noisy Naturalistic Heart Rate Data. Humanist-Vce.Eu (2018), 13–14.Google Scholar
- Rahel Gilgen-Ammann, Theresa Schweizer, and Thomas Wyss. 2019. RR interval signal quality of a heart rate monitor and an ECG Holter at rest and during exercise. European Journal of Applied Physiology 119, 7 (2019), 1525–1532. https://doi.org/10.1007/s00421-019-04142-5Google ScholarCross Ref
- Pedro Miguel Caridade Gomes, Petra Margaritoff, and Hugo Silva. 2019. pyHRV: Development and evaluation of an open-source python toolbox for heart rate variability (HRV). Proc. Int’l Conf. on Electrical, Electronic and Computing Engineering (IcETRAN) (2019), 822–828.Google Scholar
- Katrina Hinde, Graham White, and Nicola Armstrong. 2021. Wearable devices suitable for monitoring twenty four hour heart rate variability in military populations. Sensors (Switzerland) 21, 4 (2021), 1–20. https://doi.org/10.3390/s21041061Google ScholarCross Ref
- Eko Sakti Pramukantoro and Akio Gofuku. 2021. A study of bluetooth low energy (BLE) frameworks on the IoT based heart monitoring system. LifeTech 2021 - 2021 IEEE 3rd Global Conference on Life Sciences and Technologies (2021), 108–110. https://doi.org/10.1109/LifeTech52111.2021.9391777Google Scholar
- Andrea Sgoifo, Luca Carnevali, Maria De Los Angeles Pico Alfonso, and Mario Amore. 2015. Autonomic dysfunction and heart rate variability in depression. Stress 18, 3 (2015), 343–352. https://doi.org/10.3109/10253890.2015.1045868Google ScholarCross Ref
- Fred Shaffer and J. P. Ginsberg. 2017. An Overview of Heart Rate Variability Metrics and Norms. Frontiers in Public Health 5 (2017). https://doi.org/10.3389/fpubh.2017.00258Google Scholar
- Task Force of the European Society of Cardiology the North American Society of Pacing Electrophysiology. 2014. Heart Rate Variability : Standards of Measurement, Physiological Interpretation, and Clinical Use. 93, 5 (2014), 1043–1065.Google Scholar
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