IEEE Circuits and Systems Magazine - Q1 2021 - 59
challenging to extract the heart rate in the same way
with high accuracy. This is mainly due to the harmonics of the respiration and the intermodulation between
respiration and heartbeat signal that may become dominant and cause errors. To overcome this, the state space
method (SSM) was applied for RR and HR detection using SFCW radar in [2]. It successfully suppressed the
unwanted harmonics and intermodulation interferences
in the spectrum. Experimental results for different scenarios including subject holding breath, subject breathing normally, and subject facing the radar at different
angles, were reported. In all cases, the SSM successfully
extracts respiration and heart rate of the subject. This
method showed clear advantages over conventional
FFT in avoiding unwanted harmonics and products resulting from intermodulation. This method also showed
a relatively small error of 1.2% in the heart rate estimation. The reported SNR was 50 dB when combining the
SSM with either CSD or AD, 46.6 dB when suing SSM
alone compared to 8.6 dB when using FFT alone.
The reported algorithm in [64] uses targets removing random body motion that affect the detection of vital signs. It uses continuous wavelet transform (CWT)
to identify the locations of the artifacts and then applies the moving average to smooth these identified
artifacts. It also uses the discrete wavelet transform
(DWT) to separate the heartbeat signal from the respiration signal which results in accurate detection.
Preprocessing
′ [k, l ]
Sm,n
3D Raw Data
Sm,n[k, l ]
System
Calibration
Background
Removal
BP Imaging
MIMO
Image Sequence
I (i, j, l )
Change
Detection
IFFT Along
Fast Time
Domain
Bandpass Filtering
Along Slow Time
Domain
(.)λ
Ehchanced Image
~
I (i, j )
Ehchanced
Imaging
Averaging
Prescreening
Based on Global
Threshold
Ic (i, j )
I (i, j )
Y
Morphological
Filtering
CFAR
Clustering
IMF (i, j )
Number
and Location
Indication
N
Automatic Detection
and Localization
No Life
Figure 17. Automatic Detection Method [55]. Licensed under Creative Commons attribution license https://creativecommons.org/
licenses/by/4.0/
Test Pixel
Guard Window
Clutter Window
Cross-Range
Range
Cy
Gy
Gx
Vital-Sign-Enchanced
Image
Cx
Estimate
Parameters of
Clutter Distribution
Compute
the
Threshold
Compare
With the
Threshold
CFAR
Image
Constant False Alarm Rate
Sliding Window
Figure 18. Illustration of the CFAR method [55]. Licensed under Creative Commons attribution license https://creativecommons
.org/licenses/by/4.0/
FIRST QUARTER 2021
IEEE CIRCUITS AND SYSTEMS MAGAZINE
59
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IEEE Circuits and Systems Magazine - Q1 2021
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