This paper presents the first microwave-sensor-node integrated into a short-range wireless sensor network based on ZigBee technology. The node includes an analog front-end circuit, a Frequency Modulated Continuous Wave generator, an Analog-to-Digital-Converter module, a transceiver, a power unit, a processing unit and a new one-port dielectric permittivity sensor which is able to measuring the separation of structural cracks by the reflection coefficient measured in microwave frequencies. The analog front-end is composed of a pair of power dividers, an isolator and a mixer. The dielectric permittivity sensor is based on a patch antenna of variable length. The processing unit and transceiver are implemented with an Arduino UNO and an XBee module respectively. Additionally, the methodology for data processing is presented and the results of the measurement of a synthetic crack are presented. The results show that the system was successfully implemented with a sensitivity of 0.07 GHz/mm, for an opening range of between 0 and 5 mm and for a frequency range ranging from 2.782 GHz to 3.131 GHz. It is important to mention that the measurement was done remotely, placing the sensor 3 m from the client PC.

In this work, a methodology is presented for the determination of the respiration rate of a person under test (PUT), the detection of movements, as well as the elimination of the spurious effects produced by the movements of the PUT. The methodology is based on Empirical Modal Decomposition (EMD) applied to the phase signal obtained by means of a quadrature Doppler radar operating in S band. The EMD allows to automatically eliminate the continuos component (CC) which is present in the phase signal since one of the main characteristics of the modes generated by the EMD is that its mean is equal to zero. On the other hand, the first mode of the EMD is used for the detection of movements while the sum of the second and third modes are used for the elimination of the CC drift caused by the DC drift and the high frequency components produced by the movements of the PUT. The proposed methodology was successfully tested in a PUT at rest and performing movements of the head, arm and combination of head, arm, and torso. The average respiration rate measured was 20.78 breaths / min with a standard deviation of 2.53 breaths/min.