Evaluation of Heart Rate Variability by Smartphone App Using Pulse Photoplethysmography in Acute Myocardial Infarction

Tien Anh  Hoang; Nhat Long  Tran

doi:10.18502/jthc.v20i1.19220

Tien Anh Hoang Department of Cardiology, Hue University of Medicine and Pharmacy Hospital, Hue City, Vietnam.
Nhat Long Tran Hue University of Medicine and Pharmacy, Hue University, Hue City, Vietnam.

DOI: https://doi.org/10.18502/jthc.v20i1.19220

Keywords: Heart Rate Variability, Photoplethysmography, Smartphone, Acute Myocardial Infarction

Abstract

Background: Heart rate variability (HRV) correlates with localized myocardial ischemia and predicts adverse cardiovascular outcomes after acute myocardial infarction (AMI), including sudden cardiac death, non-sudden cardiac death, and noncardiac death. Photoplethysmography (PPG) measurements demonstrate good agreement with ECG for time-domain HRV indices. In this study, HRV was measured via smartphone PPG, focusing on standard deviation of all normal RR (NN) intervals (SDNN) and root mean square of successive differences (rMSSD)—parameters recognized for their low error and recommended for clinical use.

Methods: This cross-sectional case-control study was conducted at a tertiary hospital in Vietnam. HRV indices (SDNN and rMSSD) were measured for 2 minutes using a camera-based PPG smartphone application. Clinical data were collected at admission. Linear and logistic regression analyses assessed associations between HRV, AMI status, and clinical severity. Receiver operating characteristic (ROC) curve analysis evaluated diagnostic performance.

Results: A total of 101 patients with AMI and 121 age- and sex-matched healthy controls were included. The AMI group exhibited significantly lower HRV indices, with a mean SDNN of 20.63 ±10.16 ms and rMSSD of 23.67±12.38 ms, compared with 33.99±11.72 ms (SDNN) and 35.9 ±16.21 ms (rMSSD) in the control group (P <0.001 for both). An SDNN cutoff of ≤21.35 ms yielded an area under the curve of 0.832, with a sensitivity of 87.6% and specificity of 62.4% for identifying AMI. Lower HRV was also significantly associated with higher clinical severity indicators, including reduced left ventricular ejection fraction, Killip class II-IV, regional wall motion abnormalities, and multivessel coronary artery disease.

Conclusions: The use of camera-based HRV smartphone applications to measure short-term SDNN and rMSSD may serve as a novel digital health tool to improve the detection of coronary artery disease, particularly AMI, given its simplicity and noninvasive nature.