**2. UWB medical application**

Many papers have been published by many researchers and organizations that have proposed ultra-wideband for medical applications, with different frequencies and hypothesis like:


Some of these researches are mentioned below:

In 2002, Staderini [14] presented biomedical applications of UWB radar as a mix of ordinary radar (ranging and detection) with spread spectrum radio which combines the two technologies. The paper talked the problem and interaction of radar wave energy with human tissues, and also the motion of internal organs of body and noncontact probe. The flaw of this paper is the use of 1500 MHz frequency, which is out of the UWB range (3.1–10.6 GHz). So, the results were not intrinsically right.

In 2016, Ali et al. [23] designed a noninvasive UWB system for reliable glucose concentration level measurement in human blood depending on artificial intelligence, without taking blood sample, by using two UWB micro-strip antennas with signal acquisition and data processing, where the system works in an artificial neural network manner. The system sends the UWB wave in the central frequency of 4.7 GHz from one side and receives it from the other side, and then applying artificial neural network on the received signal, the drawback of this system is the

In 2016, Seguin et al. [24] evaluated a UWB transmission signal to detect heart volume changes with frequency range 1.5–4 GHz, depending on the attenuation changes between blood and other tissues, and using TOA determination for each path of UWB, the drawback of this research is its use of only semi-dynamic heart model in the thorax area, also the propagation, and reflection of other layer. In 2016, Mackenberg et al. [25] attempted to establish a UWB system that detects the vascular pressure based on the detection of vascular dilation inside an inhomogeneous tissue. The researchers found a correlation relationship between the major peaks of signal in time domain and the amplitude of supposed values. These peaks represent the reflection from the boundary layers of proposed phantom depending on the relative and propagation times. The drawback of this study is that all experiments were applied for homogenous tissue and with one layer (silicon), while the real study must be with multilayer. These layers increased the number of

inaccurate readings and the system needs a long training time.

*Medical Application of Ultra-Wideband Technology DOI: http://dx.doi.org/10.5772/intechopen.93577*

reflected signals due to increasing the complexity of measurements.

ous tissue has different dielectric properties from one case to another.

when the tissue under test is a heterogeneous material.

heavy instruments in developmental prototype.

(SNR) case.

**77**

In 2017, Wang et al. [26] used impulse-radio (IR) UWB sensor for accurately measuring the chest compression depth. This study uses many trails, which are then compared between them. This study did not respect the human body permittivity which has an effect on the calculation of time of arrival (TOA), and it requires

In 2018, Alhawari [27] presented lung tumor detection using UWB (microwave imaging approach) that uses microstrip antenna with frequency range 3–4 GHz with best distance of 10 mm far from the thorax. This introduces a radar with the ability of tumor detection of 4 mm diameter in size, which is very accurate comparing with another chest imaging device like ultrasound and X-ray, and with low cost. The used technique is based on the comparison of the dielectric properties of normal tissue and cancerous tissue, where the cancerous tissue has higher dielectric properties than the normal tissue. The drawback of this research is that the blood and muscle tissues have high dielectric properties compared to lung tissue. Also, the experiment needs accurate adjustment for successive examination and the cancer-

In 2018, Der et al. [28] produced a UWB radar based on microwave technique with oblique projection and Rao detectors combination to detect breast tumor. This technique is used for reducing the cumbersome clutter and detecting the existence of a tumor, where the tumor region denotes the maximum power; the drawback of this manner is that it is not quite distinguishable in the low signal-to-noise ratio

In 2018, Selvaraj et al. [29] proposed an UWB antenna and microwave scattering for early breast tissue tumor detection and localization and finding the depth of tumor with frequency range 2.4–4.7 GHz. The study is based on the reflected signal which is received at a microstrip antenna. The signal passed through tumor is attenuated more than the surround normal tissue. This proposed antenna is inactive

In 2018, Aziz et al. [30] introduced a graphene-based conductor UWB patch antenna to detect brain tumor. This antenna is operated at a frequency range of 3.15–9.15 GHz depending on the changes between high-reflection coefficient of

In 2005, Paulson et al. [15] introduced an overview about the ability of UWB sensor to monitor the internal organs, sense the respiratory, and detect the cardiac function. The noncontacting image with a micro-power impulse remote sensing and low complexity has been introduced, with examples for applying UWB in medical applications. The drawback of this paper is the use of 2 GHz frequency, which is also out of the UWB range (3.1–10.6 GHz). So, the results were not intrinsically right.

In 2007, Staderini et al. [16] proposed an optimal pulsed UWB medical radar for heart beat detection, by detecting the tracking of heart wall movement depending on the obtained pulse echo average and power, which can be obtained by determining the sampling frequency and required acquisition time. The neglecting of the attenuation coefficient of medium of active path in the calculation of this paper represents a drawback.

In 2009, Leib et al. [17] proposed a pulse-based compact UWB radar used for medical diagnostic, focusing on system architecture, correlation receiver, and time delay adjustment; it is also used for detecting heart beat and respiratory movement. This study supposed that the heart beat and respiratory rates have been fixed, while these ranges have discontinuity. This discontinuity caused a high attenuation in the transmitted signal, causing inaccurate readings.

In 2010, Lazaro et al. [18] estimated vital signs monitor that uses an impulse radio UWB radar; the analytical design has been developed for performing the spectral analysis according to the harmonic and intermodulation addressing for respiration and heart signal, with its simulation and proposed harmonic filter. Finally, the results have been introduced to illustrate the accuracy of the technique for heart rate and respiration detection. The flaw of this study is that the detection is difficult if the frequencies of first breath harmonics and heart signal are being closely.

In 2010, Thiel et al. [19] introduced a UWB sensor to improve the magnetic resonance imaging (MRI) especially for cardiovascular and cancer diagnostic. Their study attempted to prove the benefit of motion tracking for high-resolution brain imaging and navigation used with cardiac MRI, and also served to support electrocardiograph (ECG) analyzing. The proposed device worked only with high or ultrahigh MRI field and did not benefit with the low-field MRI.

In 2010, Elmissaoui et al. [20] introduced an imaging radar for human tissue by analyzing the return echoes from the body layers. Their research aimed to find the time of arrival (TOA) and electromagnetic propagation direction (Ө) that basically depends on the characteristic properties of human tissue (layers). The study depended on the reflection echoes to form an image, where the echoes from the deep layers are very weak and difficult to detect because of the attenuation (drawback).

In 2011, Jalilvand et al. [21] examined a UWB system to detect a hemorrhagic stroke in a 3D simulated head model, that estimated four layers model and proving that UWB technique is suited for stroke detection, comparing with other medical imaging devices like MRI, CT scan and mammography. This manner introduced an inaccurate stroke image with low resolution which is considered as main drawback.

In 2012, Urdaneta and Wahid [22] studied a UWB imaging to detect the bone cancer. The main feature of this study is the use of monopole antenna in the frequency range 1–10 GHz based on image reconstruction technique. This measures the change between the dielectric properties of bone tissues and tumor by determining the reflection coefficient, and with a certain algorithm, but still with inaccurate size detection and with long calculation time.

## *Medical Application of Ultra-Wideband Technology DOI: http://dx.doi.org/10.5772/intechopen.93577*

noncontact probe. The flaw of this paper is the use of 1500 MHz frequency, which is out of the UWB range (3.1–10.6 GHz). So, the results were not intrinsically right. In 2005, Paulson et al. [15] introduced an overview about the ability of UWB sensor to monitor the internal organs, sense the respiratory, and detect the cardiac function. The noncontacting image with a micro-power impulse remote sensing and low complexity has been introduced, with examples for applying UWB in medical applications. The drawback of this paper is the use of 2 GHz frequency, which is also out of the UWB range (3.1–10.6 GHz). So, the results were not intrinsically

In 2007, Staderini et al. [16] proposed an optimal pulsed UWB medical radar for heart beat detection, by detecting the tracking of heart wall movement depending on the obtained pulse echo average and power, which can be obtained by determining the sampling frequency and required acquisition time. The neglecting of the attenuation coefficient of medium of active path in the calculation of this paper

In 2009, Leib et al. [17] proposed a pulse-based compact UWB radar used for medical diagnostic, focusing on system architecture, correlation receiver, and time delay adjustment; it is also used for detecting heart beat and respiratory movement. This study supposed that the heart beat and respiratory rates have been fixed, while these ranges have discontinuity. This discontinuity caused a high attenuation in the

In 2010, Lazaro et al. [18] estimated vital signs monitor that uses an impulse radio UWB radar; the analytical design has been developed for performing the spectral analysis according to the harmonic and intermodulation addressing for respiration and heart signal, with its simulation and proposed harmonic filter. Finally, the results have been introduced to illustrate the accuracy of the technique for heart rate and respiration detection. The flaw of this study is that the detection is difficult if the frequencies of first breath harmonics and heart signal are being

In 2010, Thiel et al. [19] introduced a UWB sensor to improve the magnetic resonance imaging (MRI) especially for cardiovascular and cancer diagnostic. Their study attempted to prove the benefit of motion tracking for high-resolution brain imaging and navigation used with cardiac MRI, and also served to support electrocardiograph (ECG) analyzing. The proposed device worked only with high or ultra-

In 2010, Elmissaoui et al. [20] introduced an imaging radar for human tissue by analyzing the return echoes from the body layers. Their research aimed to find the time of arrival (TOA) and electromagnetic propagation direction (Ө) that basically depends on the characteristic properties of human tissue (layers). The study depended on the reflection echoes to form an image, where the echoes from the deep layers are very weak and difficult to detect because of the attenuation (draw-

In 2011, Jalilvand et al. [21] examined a UWB system to detect a hemorrhagic stroke in a 3D simulated head model, that estimated four layers model and proving that UWB technique is suited for stroke detection, comparing with other medical imaging devices like MRI, CT scan and mammography. This manner introduced an inaccurate stroke image with low resolution which is considered as main drawback. In 2012, Urdaneta and Wahid [22] studied a UWB imaging to detect the bone

cancer. The main feature of this study is the use of monopole antenna in the frequency range 1–10 GHz based on image reconstruction technique. This measures the change between the dielectric properties of bone tissues and tumor by determining the reflection coefficient, and with a certain algorithm, but still with

right.

closely.

back).

**76**

represents a drawback.

transmitted signal, causing inaccurate readings.

*Innovations in Ultra-WideBand Technologies*

high MRI field and did not benefit with the low-field MRI.

inaccurate size detection and with long calculation time.

In 2016, Ali et al. [23] designed a noninvasive UWB system for reliable glucose concentration level measurement in human blood depending on artificial intelligence, without taking blood sample, by using two UWB micro-strip antennas with signal acquisition and data processing, where the system works in an artificial neural network manner. The system sends the UWB wave in the central frequency of 4.7 GHz from one side and receives it from the other side, and then applying artificial neural network on the received signal, the drawback of this system is the inaccurate readings and the system needs a long training time.

In 2016, Seguin et al. [24] evaluated a UWB transmission signal to detect heart volume changes with frequency range 1.5–4 GHz, depending on the attenuation changes between blood and other tissues, and using TOA determination for each path of UWB, the drawback of this research is its use of only semi-dynamic heart model in the thorax area, also the propagation, and reflection of other layer.

In 2016, Mackenberg et al. [25] attempted to establish a UWB system that detects the vascular pressure based on the detection of vascular dilation inside an inhomogeneous tissue. The researchers found a correlation relationship between the major peaks of signal in time domain and the amplitude of supposed values. These peaks represent the reflection from the boundary layers of proposed phantom depending on the relative and propagation times. The drawback of this study is that all experiments were applied for homogenous tissue and with one layer (silicon), while the real study must be with multilayer. These layers increased the number of reflected signals due to increasing the complexity of measurements.

In 2017, Wang et al. [26] used impulse-radio (IR) UWB sensor for accurately measuring the chest compression depth. This study uses many trails, which are then compared between them. This study did not respect the human body permittivity which has an effect on the calculation of time of arrival (TOA), and it requires heavy instruments in developmental prototype.

In 2018, Alhawari [27] presented lung tumor detection using UWB (microwave imaging approach) that uses microstrip antenna with frequency range 3–4 GHz with best distance of 10 mm far from the thorax. This introduces a radar with the ability of tumor detection of 4 mm diameter in size, which is very accurate comparing with another chest imaging device like ultrasound and X-ray, and with low cost. The used technique is based on the comparison of the dielectric properties of normal tissue and cancerous tissue, where the cancerous tissue has higher dielectric properties than the normal tissue. The drawback of this research is that the blood and muscle tissues have high dielectric properties compared to lung tissue. Also, the experiment needs accurate adjustment for successive examination and the cancerous tissue has different dielectric properties from one case to another.

In 2018, Der et al. [28] produced a UWB radar based on microwave technique with oblique projection and Rao detectors combination to detect breast tumor. This technique is used for reducing the cumbersome clutter and detecting the existence of a tumor, where the tumor region denotes the maximum power; the drawback of this manner is that it is not quite distinguishable in the low signal-to-noise ratio (SNR) case.

In 2018, Selvaraj et al. [29] proposed an UWB antenna and microwave scattering for early breast tissue tumor detection and localization and finding the depth of tumor with frequency range 2.4–4.7 GHz. The study is based on the reflected signal which is received at a microstrip antenna. The signal passed through tumor is attenuated more than the surround normal tissue. This proposed antenna is inactive when the tissue under test is a heterogeneous material.

In 2018, Aziz et al. [30] introduced a graphene-based conductor UWB patch antenna to detect brain tumor. This antenna is operated at a frequency range of 3.15–9.15 GHz depending on the changes between high-reflection coefficient of

normal tissue and low-reflection coefficient of cancerous tissue, as well as based on varying the ground patch width with respect to the value of SAR caused radiation. It is also noted that the antenna length will have an effect on the bandwidth produced, where the length be 7 mm and the antenna is operated as narrowband.

high cost, high complexity, long time requirement, limited resolution, or other medical preventions. These limitations motivate us to begin this research and attempt to find a new technique that avoids the ionizing radiation as well as minimize the cost and complexity. The ultra-wideband technology with its distinctive

The medical cardiovascular imaging UWB radar is a new approach for medical multi-static radar which depends on the use of two different transceivers. The first transceiver is a horn type that has been built around the body of angiography (encloses the human body), while the other is a micro-strip which has been inserted into the human blood vessel with the angiography guidewire. The wave pulses of medical radar traveled through the human tissues and then arrived at the receiver. According to the high dielectric properties, differences among the human tissues, and the blood, the radar can recognize the blood in the vessels, where the high percentage of water tissues (like blood) has high dielectric properties in comparison with other tissues. Also, the reflection coefficients' amplitude and time of peaks have been affected by the depth of blood vessels, thus making the ultra-wideband radar so favorable for cardiovascular imaging. The formation of the medical image is required for the finding of the distance between the two antennas, the propagation direction (Ө), and the time of arrival (TOA), which will be different from one tissue to another, depending on the dielectric properties (permittivity) of the tissue. The wave pulses passing through tissues with high dielectric properties (like blood) will be faster than when it passes through tissues with low dielectric properties. Also, the layers (tissues) have been recognized, depending on the finding of reflec-

**Figure 4** illustrates the possible scenarios for wave propagation (transmission) through the body layers; these scenarios are explained in the conclusion. The new medical radar has been worked instead of the X-ray angiography. To minimize the biological side effects of X-ray RF, which provides accurate real-time imaging which is necessary at catheterization angiography operation for clear imaging, the new medical radar is designed according to the standard model IEEE 802.15.3a channel parameters that consider a fifth derivative Gaussian pulse ultra-wideband with a frequency center of 5 GHz. These pulses have been passed through a hypothetical medium (which represent the human tissues); this medium has been represented by the additive white Gaussian noise (AWGN) and medium gain with a certain delay, where the delay and propagation direction in real cases will depend on the tissues that are passed through. Finally, the received signal will be compared with the transmitted signal by using a cross-correlator. **Figure 5** illustrates this simulation, which represents the MATLAB simulation for the new medical radar

UWB waves transmit through the body tissue layers (mediums) under electromagnetic wave propagation laws, where the velocity of waves are different from one to another layer according to the dielectric properties (permittivity) of this

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specifications is the suitable technique.

*Medical Application of Ultra-Wideband Technology DOI: http://dx.doi.org/10.5772/intechopen.93577*

**3.1 Medical UWB radar methodology**

tion pulses at the time of arrival and propagation direction.

with all proposed components.

**3.2 Medical radar equations**

medium [34, 37]:

**79**

In 2018, Wang [31] proposed an electromagnetic imaging for brain stroke detection based on the changes in the electrical impedance of human tissue in frequency 1–4 GHz with the use of scattered signal to produce a microwave image (MI). The main drawback is that when the stroke is near the skull, it causes an increase in the skull-induced distortion and the system is complicated multi-input multi-output (MIMO).

In 2018, Lee et al. [32] used an IR-UWB radar for monitoring heart rate and rhythms (noncontact). Also, their result's reliability and validity with ordinary ECG are compared. The percentage of mean error is 2.3% vs. 0.2% of normal ECG, which means the UWB radar is inaccurate comparing with the normal ECG. The researchers used MATLAB program to synchronize and store radar readings with normal ECG readings.

In 2018, Shen [33] used a IR-UWB radar to measure the respiration and heart beat rate. The study is based on the autocorrelation, that is, applying fast Fourier transform (FFT) to obtain the respiration rate easily, while reapplying the autocorrelation method after dividing the received signal to the sets of bins and removing one block is the resulting the heartbeat rate signal detection, where the pleural periodical movement caused by the periodicity is displayed as a drawback.

In 2019, Shyu et al. [34] proposed a UWB radar sensor to detect breathing and heart rate. They used First valley peak of the energy function of intrinsic mode functions (FVPIEF) based two-layer ensemble empirical mode decomposition (EEMD). This technique serves the feature time index to detect the frequency of heart beat rate equal to about 1 Hz, which is affected by separating the heart rate from the large breath rate (respiratory). The drawback of this technique is that the breathing movement always masks off the heart beat rate and it is still hidden in the large harmonics and noise.

In 2019, Alghanimi et al. [35] proposed noninvasive blood glucose measurement depending on the relatively changing in the blood dielectric properties by using one ultra-wideband transceiver with a frequency range of 5GHZ and calculating the reflection coefficient through the comparison between the transmitted and reflected signals; the drawback of this study is that there are many factors that can have an effect on the readings of that device like body temperature, gender, blood group, and others.

In 2020, Alghanimi et al. [36] proposed an ultra-wideband radar for angiography by using two different types of antennas. The first antenna is placed around the human body and the other is inserted into the blood vessel in front of the guidewire of catheterizing angiography. The distance between antennas will be measured by calculating the time of arrival and propagation direction, which will be depending on the ultra-wideband frequency, shape, and other specifications. This distance between the antennas includes the human tissue with its different layers, where each layer has certain dielectric properties enabling us to recognize the tissue type. The drawback of this study is the difficulty of manufacturing a small UWB antenna that can be inserted into the human vessels.

## **3. UWB medical radar for angiography**

Many commonly used medical imaging devices for cardiovascular imaging has been found such as X-ray angiography, cardiac MRI, cardiac CT, and cardiac ultrasound (echo). These devices have some limitations such as radiographic exposure,

high cost, high complexity, long time requirement, limited resolution, or other medical preventions. These limitations motivate us to begin this research and attempt to find a new technique that avoids the ionizing radiation as well as minimize the cost and complexity. The ultra-wideband technology with its distinctive specifications is the suitable technique.
