@inproceedings{cc0a8debad1445f3b71775dca22b9df3,
title = "Estimating Heart Rate during Steady-State Activities and Transitions Based on Signal of PPG and ACC",
abstract = "Photoplethysmography (PPG) signal has often been used to non-invasively monitor heart rate (HR). However, it's difficult to obtain accurate HR during exercise because of motion artifacts (MA). Accelerometer (ACC) is a common wearable sensor, which can effectively reflect the users' body movement. In this paper, we present a method based on synchronized PPG and ACC to estimate HR during steady-state activities and related transitions. Firstly, we locate the steady state and transitional state by ACC signal. In steady-state activities, HR is obtained by spectrum peak screening. In the transitional-state activities, the spectrum search range is narrowed and then screen the peaks to estimate HR. The method was validated with the IEEE Signal Processing Cup 2015 challenge database. Pearson's correlation coefficient between PPG-estimated and true HR was 0.9933, and the mean absolute error (MAE) between them was 1.3262 beats per minute (BPM).",
keywords = "ACC, Heart Rate, Monitor, PPG",
author = "Qiang Zhang and Chuanbin Ge and Yi Xin",
note = "Publisher Copyright: {\textcopyright} 2020 IEEE.; 17th IEEE International Conference on Mechatronics and Automation, ICMA 2020 ; Conference date: 13-10-2020 Through 16-10-2020",
year = "2020",
month = oct,
day = "13",
doi = "10.1109/ICMA49215.2020.9233764",
language = "English",
series = "2020 IEEE International Conference on Mechatronics and Automation, ICMA 2020",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "279--283",
booktitle = "2020 IEEE International Conference on Mechatronics and Automation, ICMA 2020",
address = "United States",
}