Valentina E. Balas

G. R. Sinha

Basant Agarwal

Tarun Kumar Sharma

Mehul Mahrishi

Pankaj Dadheech

This book constitutes the refereed proceedings of the 5th International Conference on Emerging Technologies in Computer Engineering, ICETCE 2021, held in Jaipur, India, in February 2022. The 40 revised full papers along with 20 short papers presented were carefully reviewed and selected from 235 submissions. The papers are organized according to the following topical headings: ​cognitive computing; Internet of Things (IoT); machine learning and applications; soft computing; data science and big data analytics; blockchain and cyber security.

5th International Conference, ICETCE 2022, Jaipur, India, February 4–5, 2022, Revised Selected Papers

Emerging Technologies in Computer Engineering: Cognitive Computing and Intelligent IoT

Sensors are integral to modern living and are found in a huge number of applications in science, engineering and technology thus it is critical for scientists and technologists to understand the physical principles behind sensor types as well as their characteristics, applications, and how they can be suitably employed in sensor technologies. Whilst there exists a vast literature on the physics and characteristics of traditional sensors, this book provides a broad overview of the range of sensor technologies and attendant topics needed to optimise and utilise these devices in the modern world. Not only reviewing sensors by classification, the book encompasses the physics, design characteristics, simulation and interface electronics, and it includes case studies, future challenges and several other aspects of wider sensor technology to provide an overview of modern sensors and their applications. The broad scope will appeal to industrial and academic researchers and application engineers, especially those developing and implementing real-time hardware implementations employing smart sensors for emerging applications. Key Features Features a broad review of sensor types, including MEMS, wearable and smart sensors Presents application of modern sensors and emerging research directions Incorporates case studies Reviews wider associated technologies such as simulation, materials and interface electronics Interdisciplinary appeal making the text suitable for industrial and academic researchers as well as application engineers

Advances in Modern Sensors: Physics, Design, Simulation and Applications

Chinmay Chakraborty

Varun Bajaj

This book examines the use of biomedical signal processing—EEG, EMG, and ECG—in analyzing and diagnosing various medical conditions, particularly diseases related to the heart and brain. In combination with machine learning tools and other optimization methods, the analysis of biomedical signals greatly benefits the healthcare sector by improving patient outcomes through early, reliable detection. The discussion of these modalities promotes better understanding, analysis, and application of biomedical signal processing for specific diseases. The major highlights of Biomedical Signal Processing for Healthcare Applications include biomedical signals, acquisition of signals, pre-processing and analysis, post-processing and classification of the signals, and application of analysis and classification for the diagnosis of brain- and heart-related diseases. Emphasis is given to brain and heart signals because incomplete interpretations are made by physicians of these aspects in several situations, and these partial interpretations lead to major complications. FEATURES Examines modeling and acquisition of biomedical signals of different disorders Discusses CAD-based analysis of diagnosis useful for healthcare Includes all important modalities of biomedical signals, such as EEG, EMG, MEG, ECG, and PCG Includes case studies and research directions, including novel approaches used in advanced healthcare systems This book can be used by a wide range of users, including students, research scholars, faculty, and practitioners in the field of biomedical engineering and medical image analysis and diagnosis.

Biomedical Signal Processing for Healthcare Applications

G. R. Sinha

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