![]() ![]() Some authors have published manuscripts that gather the bio-radar hardware implementation state-of-the-art and they are presented in. Thenceforth, these systems were implemented using incorporated analog and digital signal processing and thereafter the RF front-end components were integrated in a single chip using CMOS processes. Then, the followed prototypes were implemented with transceivers composed by single Radio Frequency (RF) hardware components interconnected with each other. The pioneers in measured both the respiration and heartbeat separately during apnea interspersed periods. The concept of non-contact extraction of human physiological parameters, has been demonstrated by pioneers during the 1970s and its state-of-the-art have been following a time line of hardware implementation. Due to the Doppler effect, there is a phase change as the subject’s chest-wall moves towards or away from the radar and hence a phase modulation in the received signal is created. This example is composed by a Continuous Wave (CW) Doppler radar which continuously transmits a sinusoidal carrier, generated digitally, and receives the echo from the reflecting target. In order to better understand its operation principal, an example of a bio-radar’s system is represented by the block diagram in Figure 1. ![]() From the Doppler effect it is possible to relate the received signal properties with the distance change between the radar antennas and the subject chest-wall, which moves according to the cardiopulmonary function. For this purpose, it uses electromagnetic waves, which are transmitted towards to the chest-wall of the subject under monitoring, and the reflected echo is received. Thus, it is possible to define the Bio-Radar system as a technology capable to acquire vital signals, such as the respiratory signal and the cardiac signal, without interfering directly with the patient. Applications in psychology are also possible, as for example the measurement of stress response. ![]() In terms of commercial applications, it can be highlighted the vehicular area, where the driver’s vital signals are monitored to avoid any possible accident in case of cardiac failure or these systems usage in ambulances to minimize the direct contact with critical patients. Also for sleeping monitoring, namely to support cases of Obstructive Sleep Apnea (OSA) syndrome without interfering with the normal life style of the patients, or in the prevention of Sudden Infant Death Syndrome (SIDS). In the medical field, among many other applications, it can be highlighted the continuous monitoring of vital signals in bedridden patients, as in the burn units in hospitals, where physical contact with the patient is totally discouraged. The contactless measurement of bio-signals has the potential to improve many areas. Several sources of random motion are considered, along with different approaches to compensate the distortions caused by them. In this paper, an extended review on the already implemented methods is done, considering continuous wave radars. Therefore, the signal processing algorithms developed for these applications have been facing several challenges regarding the random motion detection and mitigation. Once the main applications of these systems intend to monitor subjects during long periods of time and under noisy environments, it is impossible to guarantee the patient immobilization, hence its random motion, as well as other clutter sources, will interfere in the acquired signals. These systems have countless applications, from short range detection to assist in rescue missions, to long-term applications as for the continuous sleeping monitoring. See for a more extensive discussion.The bio-radar system can measure vital signals accurately, by using the Doppler effect principle, which relates the received signal properties to the distance change between the radar antennas and the subject chest-wall. Weather radars can also pick up returns from nearby objects on the ground (ground clutter) and flying insects. So, rain will occur in some places (such as the western side of the Olympic Mountains) without it showing up on our loop. ![]() The beam can be blocked by mountains, and some areas are simply too far away from any radar. The coverage of the Pacific Northwest by weather radar is by no means uniform. Our loop shows the signals recorded by several radars in the northwest over the last several hours. High values of dbz (color scale to the right of the image) indicate large drops and heavy precipitation. Raindrops and snow produce reflections that become stronger as the size of the drop or flake increases. Weather radars send out pulses of microwave energy and listen between the transmitted pulses for part of that the energy to be reflected back to the radar. ![]()
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