ORCID Profile
0000-0002-1428-8071
Current Organisations
Mayo Clinic
,
South Dakota School of Mines and Technology
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Publisher: MDPI AG
Date: 20-06-2023
DOI: 10.3390/S23125744
Abstract: The measurement of physiologic pressure helps diagnose and prevent associated health complications. From typical conventional methods to more complicated modalities, such as the estimation of intracranial pressures, numerous invasive and noninvasive tools that provide us with insight into daily physiology and aid in understanding pathology are within our grasp. Currently, our standards for estimating vital pressures, including continuous BP measurements, pulmonary capillary wedge pressures, and hepatic portal gradients, involve the use of invasive modalities. As an emerging field in medical technology, artificial intelligence (AI) has been incorporated into analyzing and predicting patterns of physiologic pressures. AI has been used to construct models that have clinical applicability both in hospital settings and at-home settings for ease of use for patients. Studies applying AI to each of these compartmental pressures were searched and shortlisted for thorough assessment and review. There are several AI-based innovations in noninvasive blood pressure estimation based on imaging, auscultation, oscillometry and wearable technology employing biosignals. The purpose of this review is to provide an in-depth assessment of the involved physiologies, prevailing methodologies and emerging technologies incorporating AI in clinical practice for each type of compartmental pressure measurement. We also bring to the forefront AI-based noninvasive estimation techniques for physiologic pressure based on microwave systems that have promising potential for clinical practice.
Publisher: MDPI AG
Date: 23-02-2023
DOI: 10.3390/ELECTRONICS12051101
Abstract: Microwaves are non-ionizing electromagnetic radiation with waves of electrical and magnetic energy transmitted at different frequencies. They are widely used in various industries, including the food industry, telecommunications, weather forecasting, and in the field of medicine. Microwave applications in medicine are relatively a new field of growing interest, with a significant trend in healthcare research and development. The first application of microwaves in medicine dates to the 1980s in the treatment of cancer via ablation therapy since then, their applications have been expanded. Significant advances have been made in reconstructing microwave data for imaging and sensing applications in the field of healthcare. Artificial intelligence (AI)-enabled microwave systems can be developed to augment healthcare, including clinical decision making, guiding treatment, and increasing resource-efficient facilities. An overview of recent developments in several areas of microwave applications in medicine, namely microwave imaging, dielectric spectroscopy for tissue classification, molecular diagnostics, telemetry, biohazard waste management, diagnostic pathology, biomedical sensor design, drug delivery, ablation treatment, and radiometry, are summarized. In this contribution, we outline the current literature regarding microwave applications and trends across the medical industry and how it sets a platform for creating AI-based microwave solutions for future advancements from both clinical and technical aspects to enhance patient care.
Publisher: MDPI AG
Date: 30-07-2023
DOI: 10.3390/ELECTRONICS12153276
Abstract: Electrophysiology is the study of the electrical properties of biological tissues, which involves the movement of ions across cell membranes. The analysis of the movement of electrical charges through the body has a wide range of biomedical applications, such as diagnosing and planning treatment in cardiovascular, nervous systems, muscular, and gastrointestinal disorders. The dielectric properties of biological tissues change according to the water content in the tissue and are measured as permittivity and conductivity relative to the frequency of the electrical field. This principle has been applied in diagnostics and therapeutics using microwave energysuch as imaging and ablation, etc. This review article summarizes the potential use of measuring dielectric properties using microwave imaging and how it can augment electrophysiological studies in medicine.
Publisher: MDPI AG
Date: 17-10-2022
DOI: 10.3390/ELECTRONICS11203341
Abstract: Evolution of mobile broadband is ensured by adopting a unified and more capable radio interface (RI). For ubiquitous connectivity among a wide variety of wireless applications, the RI enables the adoption of an adaptive bandwidth with high spectrum flexibility. To this end, the modern-day communication system needs to cater to extremely high bandwidth, starting from below 1 GHz to 100 GHz, based on different deployments. This instigates the creation of a platform called the Internet of Everything (IoE), which is based on the concept of all-round connectivity involving humans to different objects or things via sensors. In simple words, IoE is the intelligent connection of people, processes, data, and things. To enable seamless connectivity, IoE resorts to low-cost, compact, and flexible broadband antennas, RFID-based sensors, wearable electromagnetic (EM) structures, circuits, wireless body area networks (WBAN), and the integration of these complex elements and systems. IoE needs to ensure broader information dissemination via simultaneous transmission of data to multiple users through separate beams and to that end, it takes advantage of metamaterials. The precise geometry and arrangement of metamaterials enable smart properties capable of manipulating EM waves and essentially enable the metamaterial devices to be controlled independently to achieve desirable EM characteristics, such as the direction of propagation and reflection. This review paper presents a comprehensive study on next-generation EM devices and techniques, such as antennas and circuits for wearable and sub 6 GHz 5G applications, WBAN, wireless power transfer (WPT), the direction of arrival (DoA) of propagating waves, RFID based sensors for biomedical and healthcare applications, new techniques of metamaterials as well as transformation optics (TO) and its applications in designing complex media and arbitrary geometry conformal antennas and optical devices that will enable future IoE applications.
Publisher: MDPI AG
Date: 16-12-2022
DOI: 10.3390/S22249919
Abstract: The search for non-invasive, fast, and low-cost diagnostic tools has gained significant traction among many researchers worldwide. Dielectric properties calculated from microwave signals offer unique insights into biological tissue. Material properties, such as relative permittivity (εr) and conductivity (σ), can vary significantly between healthy and unhealthy tissue types at a given frequency. Understanding this difference in properties is key for identifying the disease state. The frequency-dependent nature of the dielectric measurements results in large datasets, which can be postprocessed using artificial intelligence (AI) methods. In this work, the dielectric properties of liver tissues in three mouse models of liver disease are characterized using dielectric spectroscopy. The measurements are grouped into four categories based on the diets or disease state of the mice, i.e., healthy mice, mice with non-alcoholic steatohepatitis (NASH) induced by choline-deficient high-fat diet, mice with NASH induced by western diet, and mice with liver fibrosis. Multi-class classification machine learning (ML) models are then explored to differentiate the liver tissue groups based on dielectric measurements. The results show that the support vector machine (SVM) model was able to differentiate the tissue groups with an accuracy up to 90%. This technology pipeline, thus, shows great potential for developing the next generation non-invasive diagnostic tools.
Location: United States of America
No related grants have been discovered for Sayan Roy.