This book offers the readers an opportunity to acquire the concepts of artificial intelligence (AI) enabled sub-THz systems for novel applications in the biomedical field. The readers will also be inspired to contextualize these applications for solving real life problems such as non-invasive glucose monitoring systems, cancer detection and dental imaging. The introductory section of this book focuses on existing technologies for radio frequency and infrared sensing in biomedical applications, and their limited use in sensing applications, as well as the advantages of using THz technology in this context. This is followed by a detailed comparative analysis of THz electronics technology and other conventional electro optic THz setups highlighting the superior efficiency, affordability and portability of electronics-based THz systems. The book also discusses electronic sub-THz measurement systems for different biomedical applications. The chapters elucidate two major applications where sub-THz provides an edge over existing state of the art techniques used for non-invasive measurement of blood glucose levels and intraoperative assessment of tumor margins. There is a detailed articulation of an application of leveraging machine learning for measurement systems for non-invasive glucose concentration measurement. This helps the reader relate to the output in a more user-friendly format and understand the possible use cases in a more lucid manner. The book is intended to help the reader learn how to build tissue phantoms and characterize them at sub-THz frequencies in order to test the measurement systems. Towards the end of the book, a brief introduction to system automation for biomedical imaging is provided as well for quick analysis of the data. The book will empower the reader to understand and appreciate the immense possibilities of using electronic THz systems in the biomedical field, creating gateways for fueling further research in this area.

Highlights the concepts of AI-enabled sub-THz systems for novel applications in the biomedical field Includes applications for solving real-life Discusses superior efficiency, affordability, and portability of electronics-based THz systems over conventional one

Autorentext

• Shiban K. Koul received the B.E. degree in electrical engineering from Regional Engineering College, Srinagar, India, in 1977, and the M.Tech. and Ph.D. degrees in microwave engineering from the Indian Institute of Technology Delhi, New Delhi, India, in 1979 and 1983, respectively. He is an Emeritus Professor with the Indian Institute of Technology, Delhi since 2019 and Mentor Deputy Director (Strategy & Planning, International affairs) with IIT Jammu, J&K, India since 2018. He served as Deputy Director (Strategy and Planning) with IIT Delhi from 2012-2016 He also served as the Chairman of Astra Microwave Products Limited, Hyderabad from 2009-2019 and Dr R.P. Shenoy Astra Microwave Chair Professor at IIT Delhi from 2014-2019. His research interests include RF MEMS, high frequency wireless communication, microwave engineering, microwave passive and active circuits, device modelling, millimetre and sub-millimetre wave IC design, body area networks, flexible and wearable electronics, medical applications of sub-terahertz waves and reconfigurable microwave circuits including miniaturized antennas.
  Priyansha Kaurav completed her Ph.D. from Indian Institute of Technology, Delhi at the Centre of Applied Research in Electronics (CARE) with a focus on RF and Microwaves. She worked as Teaching Assistant at CARE, IIT Delhi for the past 2 years. Her primary research is centered around Electronics Terahertz Sensors and Artificial Intelligence in RF and Microwave. .

  Inhalt
  Chapter 1. Terahertz Spectrum in Biomedical Engineering.- Chapter 2. Electronic Sub-Terahertz VNA Measurement Techniques.- Chapter 3. Biological Tissue Interaction with Sub-Terahertz Spectrum.- Chapter 4. Non-invasive Sub-Terahertz Blood Glucose Measurement.- Chapter 5. Breast Tumor Margin Assessment using Sub-THz.- Chapter 6. Sub-THz and THz waves for Skin Diagnosis and Therapy.- Chapter 7. Machine Learning and Biomedical Sub-THz/THz Technology.- Chapter 8. Automation in Sub-THz/THz Imaging Systems.- Index.