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 inRemote sensing (Basel, Switzerland) Vol. 11; no. 10; p. 1237
Main Authors Lee, Hyunjae, Kim, Byung-Hyun, Park, Jin-Kwan, Yook, Jong-Gwan
Format Journal Article
LanguageEnglish
Published Basel MDPI AG 24.05.2019
Subjects
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
United States > US
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Summary: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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ISSN:2072-4292
2072-4292
DOI:10.3390/rs11101237