IEEE Circuits and Systems Magazine - Q1 2021 - 42

hardware used, lowering implementation costs, and the combinations of them. Besides that, this review also focuses on literature aimed at increasing the detection accuracy and reducing
the processing time using FPGAs, prior to benchmarking them
against other processing platforms. Finally, a perspective on the
future of human vital signs detection using radar sensors concludes this review.

I. Introduction
uman health status can be mainly determined
from the available vital signals that can be acquired directly from the body, whether invasively
or non-invasively. Signals such as blood pressure, heart
rate, respiration rate, blood oxygen, motion parameters
etc., can provide a precursor to indicate the quality of life
for an individual. Among them, signals acquired to indicate the heart rate (HR) and respiration rate (RR) are vital physiological signals indicating the health condition
of the person.
Heart rate detection and monitoring can indicate the
health status of a person's cardiovascular system. The
heart rate changes based on how a person reacts to different situations such as fear, illness, depression etc.
Likewise, the instability of respiration rate is an early
indicator of physiological variability, whether short- or
long term. Thus, HR and RR can be used in various applications, such as sleep monitoring, elderly health homemonitoring, infants or preterm condition monitoring,
post-surgery monitoring and trapped victim detection
in search and rescue operations [1].
The topic of human vital sign detection has been attracting the interest of many researchers in recent years
and has been enabled using different methods and technologies. While some researchers use contact-type
methods to detect human vital signs, such as wearable
devices and sensors to perform measurements when
attached to the human body, other researchers tend
to use contactless technologies such as radar systems,
cameras and laser technologies. Non-invasive radarbased detection method is preferred by many researchers over other available detection methods. This is
because such radar systems reduce the inconvenience
caused by wearable devices and electrocardiogram
(ECG) equipment. Direct contact methods applied on
the human body potentially causes discomfort/harm to
the target, and this is especially evident in the case of
skin burn injuries, preterm and sleep monitoring. More-

over, the use of direct contact methods may also cause
the targets to change their behavior due to awareness
and obtrusion caused by the device, thus affecting the
measurement accuracy. On the contrary, the application of radar systems eliminates these possibilities and
their potential errors.
Besides that, radar-based detection has also been
favored in many cases over other non-contact methods
due to its applicability for non-line-of-sight monitoring,
sensing in foggy environments, and its ability in throughwall detection. Moreover, privacy concern does not arise
when using such methods, as no videos or pictures are
involved in the detection [1]-[3]. In radar-based human
vital sign detection, the received signal upon reflection
is processed to acquire useful information. Several of the
processing steps involved include demodulation, amplification, digitization, transfer, storage, denoising, filtration,
and information extraction. These steps are generally
categorized as signal acquisition and processing. Radar
signals can be processed using different platforms such
as Central processing unit (CPU), digital signal processors (DSP), Graphic processing units (GPU), application
specific integrated circuits (ASIC)-based processors, field
programmable gate arrays (FPGAs), or the combinations
of these platforms. Table 1 compares the features of radarbased sensors, ECGs, wearable devices, camera-based
sensors, and laser-based sensors for vital sign detection.
Table 1.
Comparison between different technologies for vital
sign detection.
Feature

Wearable
Radar ECG Devices Camera Laser

Convenience

Yes

Through wall
detection

Yes

N/A

Privacy
concerns

Yes

Safety
concerns

Yes

N/A

Dark, foggy
environment

Yes

Non-line-ofYes
sight detection

N/A

Interference

Yes

Ameen is with Advanced Communication Engineering (ACE) CoE, Faculty of Electronic Engineering Technology, Universiti Malaysia Perlis, 02600 Arau,
Perlis, Malaysia. He is also with Research Product Development Company (RPDC), Riyadh, Saudi Arabia. 2Dr. Jack is with Advanced Communication
Engineering (ACE) CoE, Faculty of Electronic Engineering Technology, Universiti Malaysia Perlis, 02600 Arau, Perlis, Malaysia. He is also with ESATTELEMIC Research Division, KU Leuven, 3001 Leuven, (corresponding author: pjsoh@unimap.edu.my). 3Dr. Omar is with King Saud University, Department of Electrical Engineering, Riyadh, Saudi Arabia. He is also with Prince Sultan Advanced Technology Research Institute (PSATRI), KSU, Riyadh,
Saudi Arabia, in addition to KACST-TIC in RF and Photonics for the e-Society (RFTONICS), KSU, Riyadh, Saudi Arabia. 4Dr. Muataz is with Flex, No
2736, Mukim 1, Lorong Perusahaan Baru 2, Kawasan Perusahaan Perai, 13600 Perai, Penang, Malaysia. 5Dr. Marco is with imec - Netherlands, 5656AE
Eindhoven, The Netherlands. 6Prof. Dominique is with ESAT-TELEMIC Research Division, KU Leuven, Leuven, Belgium.

IEEE CIRCUITS AND SYSTEMS MAGAZINE

FIRST QUARTER 2021

IEEE Circuits and Systems Magazine - Q1 2021

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