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Biomedical Signal and Image Processing with Artificial Intelligence
This book focuses on advanced techniques used for feature extraction, analysis, recognition, and classification in the area of biomedical signal and image processing. Contributions cover all aspects of artificial intelligence, machine learning, and deep learning in the field of biomedical signal and image processing using novel and unexplored techniques and methodologies. The book covers recent developments in both medical images and signals analyzed by artificial intelligence techniques. The authors also cover topics related to development based artificial intelligence, which includes machine learning, neural networks, and deep learning. This book will provide a platform for researchers who are working in the area of artificial intelligence for biomedical applications. Provides insights into medical signal and image analysis using artificial intelligence; Includes novel and recent trends of decision support system for medical research; Outlines employment of evolutionary algorithms for biomedical data, big data analysis for medical databases, and reliability, opportunities, and challenges in clinical data.
IoT Applications for Healthcare Systems
This book discusses communications technologies used in the field of healthcare, including IoT, soft computing, machine learning, big data, augmented reality, and wearable sensors. The book presents various applications that are helpful for research scholars and scientists who are working toward identifying and pinpointing the potential of this technology. The book also helps researchers and practitioners to understand and analyze the e-healthcare architecture through IoT and the state-of-the-art in IoT countermeasures with real-time challenges. Topics of interest include healthcare systems based on advanced development boards, mobile health parameters recording and monitoring systems, remote health / patient monitoring, hospital operations management, abnormality / disease detection by IoT devices, and efficient drug management. The book is relevant to a range of researchers, academics, and practitioners working on the intersection of IoT and healthcare.
Proceedings of the 2009 International Conference on Signals, Systems and Automation (ICSSA 2009)
This book is a collection of papers from the 2009 International Conference on Signals, Systems and Automation (ICSSA 2009). The conference at a glance: - Pre-conference Workshops/Tutorials on 27th Dec, 2009 - Five Plenary talks - Paper/Poster Presentation: 28-29 Dec, 2009 - Demonstrations by SKYVIEWInc, SLS Inc., BSNL, Baroda Electric Meters, SIS - On line paper submission facility on website - 200+ papers are received from India and abroad - Delegates from different countries including Poland, Iran, USA - Delegates from 16 states of India - Conference website is seen by more than 3000 persons across the world (27 countries and 120 cities)
Scientific Basis for Ayurvedic Therapies
Arguably the oldest form of health care, Ayurveda is often referred to as the "Mother of All Healing." Although there has been considerable scientific research done in this area during the last 50 years, the results of that research have not been adequately disseminated. Meeting the need for an authoritative, evidence-based reference, Scientific Basis for Ayurvedic Therapies is the first book to analyze and synthesize current research supporting Ayurvedic medicine. This book reviews the latest scientific information, evaluates the research data, and presents it in an easy to use format. The editor has carefully selected topics based on the availability of scientific studies and the prevalenc...
ECG Signal Compression Using Compressive Sensing and Wavelet Transform
In this work, analysis of various Wavelet Transform basis functions for signal compression have been studied and implemented. Compressed Sensing (CS) is a novel approach of reconstructing a sparse signal much below the significant Nyquist rate of sampling. Due to the fact that ECG signals can be well approximated by the few linear combinations of wavelet basis, this work introduces a comparison of the reconstructed 10 ECG signals based on different wavelet families, by evaluating the performance measures as MSE (Mean Square Error), PSNR (Peak Signal To Noise Ratio), PRD (Percentage Root Mean Square Difference) and CoC (Correlation Coefficient). Various wavelets namely Coiflets, Daubechies, Symlets, Biorthogonal, Reverse biorthogonal etc. have been studied and used to reconstruct the cardiac signals.
India Today
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Encyclopedia Indica
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Screen World
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