Dual-Planar Monopole Antenna-Based Remote Sensing System for Microwave Medical Applications.

Neurodegenerative diseases (NDs) can be life threatening and have chronic impacts on patients and society. Timely diagnosis and treatment are imperative to prevent deterioration. Conventional imaging modalities, such as Computed Tomography (CT), Magnetic Resonance Imaging (MRI), and Positron Emission Tomography (PET), are expensive and not readily accessible to patients. Microwave sensing and imaging (MSI) systems are promising tools for monitoring pathological changes, namely the lateral ventricle enlargement associated with ND, in a non-invasive and convenient way. This paper presents a dual-planar monopole antenna-based remote sensing system for ND monitoring. First, planar monopole antennas were designed using the simulation software CST Studio Suite. The antenna analysis was carried out regarding the reflection coefficient, gain, radiation pattern, time domain characterization, E-field distribution, and Specific Absorption Rate (SAR). The designed antennas were then integrated with a controlling circuit as a remote sensing system. The system was experimentally validated on brain phantoms using a vector network analyzer and a laptop. The collected reflection coefficient data were processed using a radar-based imaging algorithm to reconstruct images indicating brain abnormality in ND. The results suggest that the system could serve as a low-cost and efficient tool for long-term monitoring of ND, particularly in clinics and care home scenarios.

Evaluation of Unobtrusive Microwave Sensors in Healthcare 4.0-Toward the Creation of Digital-Twin Model.

The prevalence of chronic diseases and the rapid rise in the aging population are some of the major challenges in our society. The utilization of the latest and unique technologies to provide fast, accurate, and economical ways to collect and process data is inevitable. Industry 4.0 (I4.0) is a trend toward automation and data exchange. The utilization of the same concept of I4.0 in healthcare is termed Healthcare 4.0 (H4.0). Digital Twin (DT) technology is an exciting and open research field in healthcare. DT can provide better healthcare in terms of improved patient monitoring, better disease diagnosis, the detection of falls in stroke patients, and the analysis of abnormalities in breathing patterns, and it is suitable for pre- and post-surgery routines to reduce surgery complications and improve recovery. Accurate data collection is not only important in medical diagnoses and procedures but also in the creation of healthcare DT models. Health-related data acquisition by unobtrusive microwave sensing is considered a cornerstone of health informatics. This paper presents the 3D modeling and analysis of unobtrusive microwave sensors in a digital care-home model. The sensor is studied for its performance and data-collection capability with regards to patients in care-home environments.

Integrated Flexible Hybrid Silicone-Textile Dual-Resonant Sensors and Switching Circuit for Wearable Neurodegeneration Monitoring Systems.

This paper describes the design, development, and testing of flexible hybrid silicone-textile sensors and a flexible switching circuit that were integrated into a wearable system for monitoring neurodegenerative diseases. A total of 6 planar monopole antenna sensors were fabricated that propagates at two separate resonant frequencies: 800 MHz and 2.1 GHz respectively. In addition, 2 switching circuits, each having 3 switches and 4 SMA breakout boards, were assembled and placed on the wearable neurodegeneration monitoring system. Each switching circuit connects 3 sensors to a single port on a vector network analyzer (VNA) that is used to generate and receive microwave signals. Experiments were performed using the wearable device with the developed sensors and switching circuit on phantoms mimicking two common physiological changes in the brain caused by neurodegenerative diseases: 1) brain atrophy and 2) lateral ventricle enlargement. The dual nature of the sensors' resonance allows it to detect both brain atrophy and lateral ventricle enlargement separately at different operating frequency. This provides the advantage of minimizing the number of sensor elements needed to monitor neurodegenerative disease. The use of a switching circuit also allows for quick and convenient measurements by choosing which sensors are active for ports 1 and 2 on the VNA respectively. In addition to being low-cost, the flexibility of the materials used in fabrication allows the sensors and switching circuit to be conformal to the patient's head. Results from the experiments indicates that the sensors and switching circuit were working successfully when integrated into the wearable device.