{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,20]],"date-time":"2026-03-20T18:08:39Z","timestamp":1774030119721,"version":"3.50.1"},"reference-count":34,"publisher":"MDPI AG","issue":"9","license":[{"start":{"date-parts":[[2022,4,19]],"date-time":"2022-04-19T00:00:00Z","timestamp":1650326400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Singtel Cognitive and Artificial Intelligence Lab for Enterprises","award":["NTU PA Ref: 2019-1075"],"award-info":[{"award-number":["NTU PA Ref: 2019-1075"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>A non-contact, non-invasive monitoring system to measure and estimate the heart and breathing rate of humans using a frequency-modulated continuous wave (FMCW) mm-wave radar at 77 GHz is presented. A novel diagnostic system is proposed which extracts heartbeat phase signals from the FMCW radar (reconstructed using Fourier series analysis) to test a three-layer artificial neural network model to predict the presence of arrhythmia in individuals. The effect of person orientation, distance of measurement and movement was analyzed with respect to a reference device based on statistical measures that include number of outliers, mean, mean squared error (MSE), mean absolute error (MAE), median absolute error (medAE), skewness, standard deviation (SD) and R-squared values. The individual oriented in front of the radar outperformed almost all other orientations for most distances with an expected d = 90 cm and d = 120 cm. Furthermore, it was found that the heart rate that was measured while walking and the breathing rate which was measured for a motionless individual generated results with the lowest SD and MSE. An artificial neural network (ANN) was trained using the MIT-BIH database with a training accuracy of 93.9 % and an R2 value = 0.876. The diagnostic tool was tested on 15 subjects and achieved a mean test accuracy of 75%.<\/jats:p>","DOI":"10.3390\/s22093106","type":"journal-article","created":{"date-parts":[[2022,4,20]],"date-time":"2022-04-20T00:22:43Z","timestamp":1650414163000},"page":"3106","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":68,"title":["mm-Wave Radar-Based Vital Signs Monitoring and Arrhythmia Detection Using Machine Learning"],"prefix":"10.3390","volume":"22","author":[{"given":"Srikrishna","family":"Iyer","sequence":"first","affiliation":[{"name":"School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore 639798, Singapore"}]},{"given":"Leo","family":"Zhao","sequence":"additional","affiliation":[{"name":"SCALE @ NTU Corp Lab, Nanyang Technological University, Singapore 639798, Singapore"},{"name":"NCS Group, Singapore 469272, Singapore"}]},{"given":"Manoj Prabhakar","family":"Mohan","sequence":"additional","affiliation":[{"name":"School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore 639798, Singapore"}]},{"given":"Joe","family":"Jimeno","sequence":"additional","affiliation":[{"name":"SCALE @ NTU Corp Lab, Nanyang Technological University, Singapore 639798, Singapore"},{"name":"NCS Group, Singapore 469272, Singapore"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0500-0977","authenticated-orcid":false,"given":"Mohammed Yakoob","family":"Siyal","sequence":"additional","affiliation":[{"name":"School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore 639798, Singapore"},{"name":"SCALE @ NTU Corp Lab, Nanyang Technological University, Singapore 639798, Singapore"}]},{"given":"Arokiaswami","family":"Alphones","sequence":"additional","affiliation":[{"name":"School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore 639798, Singapore"},{"name":"SCALE @ NTU Corp Lab, Nanyang Technological University, Singapore 639798, Singapore"}]},{"given":"Muhammad Faeyz","family":"Karim","sequence":"additional","affiliation":[{"name":"School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore 639798, Singapore"},{"name":"SCALE @ NTU Corp Lab, Nanyang Technological University, Singapore 639798, Singapore"}]}],"member":"1968","published-online":{"date-parts":[[2022,4,19]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"515","DOI":"10.1093\/intqhc\/mzw062","article-title":"Vital signs monitoring on general wards: Clinical staff perceptions of current practices and the planned introduction of continuous monitoring technology","volume":"28","author":"Prgomet","year":"2016","journal-title":"Int. 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