@inproceedings{5c2007497abe4320b1b087fabe7da643,
title = "Noncontact Detection of Heartbeat and Respiratory Rate via 77GHz Radar Based on Adaptive Double Sliding-Time Window Algorithm",
abstract = "In radar-based vital sign monitoring, it's a challenge to keep the trade-off between high accuracy and real-time processing capability. To offer an effective approach towards this challenge and achieve noncontact detection of human heartbeat and respiratory rate, this paper proposes a joint time-frequency detection algorithm. This algorithm bases on adaptive double sliding-time window (ADSW) technology using both fast Fourier transform (FFT) and time domain searching-peak (TSP) methods to perform preliminary detection. Then adaptive weighting is utilized to adjust the lengths of next data sliding windows dynamically and obtain the final output from previous detection results. In the meanwhile, the chosen weighting factors are determined by signal characteristics such as the short average energy (SAE) and zero-crossing rate (SAZC), which can improve the real-time capability as well as maintain good accuracy. Finally an experiment was carried out and the proposed algorithm achieved good results.",
keywords = "adaptive double sliding-time window (ADSW), millimeter-wave Doppler radar, noncontact, vital sign",
author = "Zichen Li and Xiongkui Zhang and Yihao Ma and Hui Shang and Cheng Jin",
note = "Publisher Copyright: {\textcopyright} 2019 IEEE.; 2019 IEEE International Conference on Signal, Information and Data Processing, ICSIDP 2019 ; Conference date: 11-12-2019 Through 13-12-2019",
year = "2019",
month = dec,
doi = "10.1109/ICSIDP47821.2019.9172982",
language = "English",
series = "ICSIDP 2019 - IEEE International Conference on Signal, Information and Data Processing 2019",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
booktitle = "ICSIDP 2019 - IEEE International Conference on Signal, Information and Data Processing 2019",
address = "United States",
}