Feature Engineering and Computational Intelligence in ECG Monitoring - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Feature Engineering and Computational Intelligence in ECG Monitoring write by Chengyu Liu. This book was released on 2020-06-24. Feature Engineering and Computational Intelligence in ECG Monitoring available in PDF, EPUB and Kindle. This book discusses feature engineering and computational intelligence solutions for ECG monitoring, with a particular focus on how these methods can be efficiently used to address the emerging challenges of dynamic, continuous & long-term individual ECG monitoring and real-time feedback. By doing so, it provides a “snapshot” of the current research at the interface between physiological signal analysis and machine learning. It also helps clarify a number of dilemmas and encourages further investigations in this field, to explore rational applications of feature engineering and computational intelligence in ECG monitoring. The book is intended for researchers and graduate students in the field of biomedical engineering, ECG signal processing, and intelligent healthcare.
ECG Signal Processing, Classification and Interpretation
ECG Signal Processing, Classification and Interpretation - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook ECG Signal Processing, Classification and Interpretation write by Adam Gacek. This book was released on 2011-09-18. ECG Signal Processing, Classification and Interpretation available in PDF, EPUB and Kindle. The book shows how the various paradigms of computational intelligence, employed either singly or in combination, can produce an effective structure for obtaining often vital information from ECG signals. The text is self-contained, addressing concepts, methodology, algorithms, and case studies and applications, providing the reader with the necessary background augmented with step-by-step explanation of the more advanced concepts. It is structured in three parts: Part I covers the fundamental ideas of computational intelligence together with the relevant principles of data acquisition, morphology and use in diagnosis; Part II deals with techniques and models of computational intelligence that are suitable for signal processing; and Part III details ECG system-diagnostic interpretation and knowledge acquisition architectures. Illustrative material includes: brief numerical experiments; detailed schemes, exercises and more advanced problems.
Computational Intelligence in Biomedical Engineering
Computational Intelligence in Biomedical Engineering - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Computational Intelligence in Biomedical Engineering write by Rezaul Begg. This book was released on 2007-12-04. Computational Intelligence in Biomedical Engineering available in PDF, EPUB and Kindle. As in many other fields, biomedical engineers benefit from the use of computational intelligence (CI) tools to solve complex and non-linear problems. The benefits could be even greater if there were scientific literature that specifically focused on the biomedical applications of computational intelligence techniques. The first comprehensive field-
Deep Learning Concepts in Operations Research
Deep Learning Concepts in Operations Research - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Deep Learning Concepts in Operations Research write by Biswadip Basu Mallik. This book was released on 2024-08-30. Deep Learning Concepts in Operations Research available in PDF, EPUB and Kindle. The model-based approach for carrying out classification and identification of tasks has led to the pervading progress of the machine learning paradigm in diversified fields of technology. Deep Learning Concepts in Operations Research looks at the concepts that are the foundation of this model-based approach. Apart from the classification process, the machine learning (ML) model has become effective enough to predict future trends of any sort of phenomena. Such fields as object classification, speech recognition, and face detection have sought extensive application of artificial intelligence (AI) and ML as well. Among a variety of topics, the book examines: An overview of applications and computing devices Deep learning impacts in the field of AI Deep learning as state-of-the-art approach to AI Exploring deep learning architecture for cutting-edge AI solutions Operations research is the branch of mathematics for performing many operational tasks in other allied domains, and the book explains how the implementation of automated strategies in optimization and parameter selection can be carried out by AI and ML. Operations research has many beneficial aspects for decision making. Discussing how a proper decision depends on several factors, the book examines how AI and ML can be used to model equations and define constraints to solve problems and discover proper and valid solutions more easily. It also looks at how automation plays a significant role in minimizing human labor and thereby minimizes overall time and cost.
Smart Wearable Devices in Healthcare—Methodologies, Applications, and Algorithms
Smart Wearable Devices in Healthcare—Methodologies, Applications, and Algorithms - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Smart Wearable Devices in Healthcare—Methodologies, Applications, and Algorithms write by Chang Yan. This book was released on 2023-12-14. Smart Wearable Devices in Healthcare—Methodologies, Applications, and Algorithms available in PDF, EPUB and Kindle. Wearable health devices have been an emerging technology that enables an ambulatory acquisition of physiological signals to monitor health status over a long time (hours/days/weeks/years) inside and outside clinical environments. Big data and deep learning, in particular, are receiving a lot of attention in this rapidly growing digital health community. A key benefit of deep learning is to analyze and learn massive amounts of data, which makes it especially valuable in healthcare since raw data is largely gathered from personalized wearable health devices. A wide range of users may benefit from unobstructed and even remote monitoring of pertinent or vital signs, which makes it easier to detect life-threatening diseases early, track the progression of pathologies and stress levels, evaluate the efficacy of therapies, provide low-cost and reliable diagnoses, etc. Today’s personal health devices have provided an amazing insight into people’s health and wellness, which allow clinicians to use these smart wearables to collect and analyze measuring data like electroencephalogram (EEG), electrocardiogram (ECG or EKG), respiration, heart rate, temperature level, blood oxygen, and blood pressure for health monitoring or clinical trials. This Research Topic mainly focuses on the technical revolution in wearable health systems, which aims to design more smart and useful wearables, contributing to a substantial change in the methodologies, applications, and algorithms of machine learning for wearable health devices. With the help of deep learning and sensor fusion capabilities from wearable health platforms, this data will be used more effectively, which can help to construct smart, novel, specific solutions to improve the quality of healthcare and capabilities of utilizing new deep learning technologies.
