Graphene-based terahertz reconfigurable printed ridge gap waveguide structure.

Graphene-based microwave devices have enabled reconfigurability, thus paving the way to the realization of flexible wireless terahertz systems with featured performances. Despite great progress in the development of graphene-based terahertz devices in the literature, high insertion loss and wide tunable range are still significant challenges at such high frequencies. In this work, we introduce the use of graphene to implement a reconfigurable printed ridge gap waveguide (RPRGW) structure over the terahertz frequency range for the first time. This guiding structure is suitable for both millimeter and terahertz wave applications due to its supporting quasi-TEM mode, which exhibits low dispersion compared to other traditional guiding structures. The presented solution is featured with low loss as the signal propagates in a lossless air gap, which is separated from the lossy graphene elements responsible for the reconfigurable behavior. In addition, this guiding structure is deployed to implement a tunable RPPGW power divider as an application example for the proposed structure.

A Novel Sensor-Array System for Contactless Electrocardiogram Acquisition.

The cardiac ECG is one of the most important human biometrics. An electrocardiogram (ECG) or EKG, captures the electrical activity of the heart and allows a healthcare professional to evaluate, diagnose, and monitor patient cardiac condition. The standard method to capture electrocardiogram signals (ECG) involves skin preparation and attachment of wet electrodes to the skin, which is not comfortable for the patient and requires a trained technician. In this work, a novel contactless-based ECG system is proposed, where 128 sensors are deployed on a mattress to capture the ECG information from the back of the patient. The proposed system can capture the ECG through clothing and is more comfortable to the patients. The measurements captured by the proposed system provides a 100% accuracy of QRS complex detection and heartbeat rate estimation and a maximum of 4% error in other major ECG features compared to a hospital-grade standard system. This paper shows that ECG features can be accurately extracted from contactless electrodes, through clothing and from the back of the patient.