A Novel Vital-Sign Sensing Algorithm for Multiple Subjects Based on 24-GHz FMCW Doppler Radar
A novel non-contact vital-sign sensing algorithm for use in cases of multiple subjects is proposed. The approach uses a 24 GHz frequency-modulated continuous-wave Doppler radar with the parametric spectral estimation method. Doppler processing and spectral estimation are concurrently implemented to...
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Published in | Remote sensing (Basel, Switzerland) Vol. 11; no. 10; p. 1237 |
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Format | Journal Article |
Language | English |
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Abstract | A novel non-contact vital-sign sensing algorithm for use in cases of multiple subjects is proposed. The approach uses a 24 GHz frequency-modulated continuous-wave Doppler radar with the parametric spectral estimation method. Doppler processing and spectral estimation are concurrently implemented to detect vital signs from more than one subject, revealing excellent results. The parametric spectral estimation method is utilized to clearly identify multiple targets, making it possible to distinguish multiple targets located less than 40 cm apart, which is beyond the limit of the theoretical range resolution. Fourier transformation is used to extract phase information, and the result is combined with the spectral estimation result. To eliminate mutual interference, the range integration is performed when combining the range and phase information. By considering breathing and heartbeat periodicity, the proposed algorithm can accurately extract vital signs in real time by applying an auto-regressive algorithm. The capability of a contactless and unobtrusive vital sign measurement with a millimeter wave radar system has innumerable applications, such as remote patient monitoring, emergency surveillance, and personal health care. |
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AbstractList | A novel non-contact vital-sign sensing algorithm for use in cases of multiple subjects is proposed. The approach uses a 24 GHz frequency-modulated continuous-wave Doppler radar with the parametric spectral estimation method. Doppler processing and spectral estimation are concurrently implemented to detect vital signs from more than one subject, revealing excellent results. The parametric spectral estimation method is utilized to clearly identify multiple targets, making it possible to distinguish multiple targets located less than 40 cm apart, which is beyond the limit of the theoretical range resolution. Fourier transformation is used to extract phase information, and the result is combined with the spectral estimation result. To eliminate mutual interference, the range integration is performed when combining the range and phase information. By considering breathing and heartbeat periodicity, the proposed algorithm can accurately extract vital signs in real time by applying an auto-regressive algorithm. The capability of a contactless and unobtrusive vital sign measurement with a millimeter wave radar system has innumerable applications, such as remote patient monitoring, emergency surveillance, and personal health care. |
Author | Yook, Jong-Gwan Park, Jin-Kwan Kim, Byung-Hyun Lee, Hyunjae |
Author_xml | – sequence: 1 givenname: Hyunjae surname: Lee fullname: Lee, Hyunjae – sequence: 2 givenname: Byung-Hyun surname: Kim fullname: Kim, Byung-Hyun – sequence: 3 givenname: Jin-Kwan orcidid: 0000-0002-4160-2900 surname: Park fullname: Park, Jin-Kwan – sequence: 4 givenname: Jong-Gwan orcidid: 0000-0001-6711-289X surname: Yook fullname: Yook, Jong-Gwan |
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SubjectTerms | Algorithms breathing Continuous radiation Doppler radar Fourier transforms Frequency dependence health services Heart rate Identification Information processing Interferometry Methods Millimeter waves monitoring Monitoring systems multiple subjects mutual interference Parameter estimation parametric spectral estimation patients Periodicity Physiology Radar Radar equipment Radar systems Remote monitoring remote sensing Researchers Respiration Sensors Signal processing Sleep apnea Spectra Surveillance radar Target recognition vital sign monitoring |
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Title | A Novel Vital-Sign Sensing Algorithm for Multiple Subjects Based on 24-GHz FMCW Doppler Radar |
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