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Heart Rate Variability (HRV), which measures the fluctuation of heartbeat intervals, has been considered as an important indicator for general health evaluation. This paper proposes a new algorithm for HRV monitoring in which frequency-modulated continuous-wave (FMCW) radar is used to separate echo signals from different distances, and the beamforming technique is adopted to improve signal quality. After the phase reflecting the chest wall motion is demodulated, the acceleration is calculated to enhance the heartbeat and suppress the impact of respiration. The time interval of each heartbeat is estimated based on the smoothed acceleration waveform. Finally, a joint optimization algorithm was developed and is used to precisely segment the acceleration signal for analyzing HRV. Experimental results from 10 participants show the potential of the proposed algorithm for obtaining a noncontact HRV estimation with high accuracy. The proposed algorithm can measure the interbeat interval (IBI) with a root mean square error (RMSE) of 14.9 ms and accurately estimate HRV parameters with an RMSE of 3.24 ms for MEAN (the average value of the IBI), 4.91 ms for the standard deviation of normal to normal (SDNN), and 9.10 ms for the root mean square of successive differences (RMSSD). These results demonstrate the effectiveness and feasibility of the proposed method in emotion recognition, sleep monitoring, and heart disease diagnosis.<\/jats:p>","DOI":"10.3390\/s23156681","type":"journal-article","created":{"date-parts":[[2023,7,27]],"date-time":"2023-07-27T02:14:48Z","timestamp":1690424088000},"page":"6681","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":16,"title":["A Real-Time Evaluation Algorithm for Noncontact Heart Rate Variability Monitoring"],"prefix":"10.3390","volume":"23","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-0412-9859","authenticated-orcid":false,"given":"Xiangyu","family":"Han","sequence":"first","affiliation":[{"name":"State Key Laboratory of Fluid Power and Mechatronic Systems, School of Mechanical Engineering, Zhejiang University, Hangzhou 310027, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8426-1205","authenticated-orcid":false,"given":"Qian","family":"Zhai","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Fluid Power and Mechatronic Systems, School of Mechanical Engineering, Zhejiang University, Hangzhou 310027, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ning","family":"Zhang","sequence":"additional","affiliation":[{"name":"National Research Center for Rehabilitation Technical Aids, Beijing 100176, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xiufeng","family":"Zhang","sequence":"additional","affiliation":[{"name":"National Research Center for Rehabilitation Technical Aids, Beijing 100176, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Long","family":"He","sequence":"additional","affiliation":[{"name":"Zhiyuan Research Institute, Hangzhou 310024, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2901-3388","authenticated-orcid":false,"given":"Min","family":"Pan","sequence":"additional","affiliation":[{"name":"Department of Mechanical Engineering, University of Bath, Bath BA2 7AY, UK"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4879-0211","authenticated-orcid":false,"given":"Bin","family":"Zhang","sequence":"additional","affiliation":[{"name":"Department of Electrical Engineering, University of South Carolina, Columbia, SC 29208, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2797-0264","authenticated-orcid":false,"given":"Tao","family":"Liu","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Fluid Power and Mechatronic Systems, School of Mechanical Engineering, Zhejiang University, Hangzhou 310027, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2023,7,26]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"e13898","DOI":"10.1111\/psyp.13898","article-title":"Cross-instrument feasibility, validity, and reproducibility of wireless heart rate monitors: Novel opportunities for extended daily life monitoring","volume":"58","author":"Kunkels","year":"2021","journal-title":"Psychophysiology"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"9767","DOI":"10.1109\/ACCESS.2018.2794346","article-title":"ECG signal preprocessing and SVM classifier-based abnormality detection in remote healthcare applications","volume":"6","author":"Venkatesan","year":"2018","journal-title":"IEEE Access"},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"109","DOI":"10.1007\/s10484-020-09466-z","article-title":"Heart rate variability biofeedback improves emotional and physical health and performance: A systematic review and meta analysis","volume":"45","author":"Lehrer","year":"2020","journal-title":"Appl. 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