Advances in non-invasive biomedical signal sensing and processing with machine learning / Saeed Mian Qaisar, Humaira Nisar, Abdulhamit Subasi, editors.
Qaisar, Saeed Mian, editor.; Nisar, Humaira, 1970- editor.; Subasi, Abdulhamit, editor.
2023
R857.B54
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Title Advances in non-invasive biomedical signal sensing and processing with machine learning / Saeed Mian Qaisar, Humaira Nisar, Abdulhamit Subasi, editors.
ISBN 9783031232398 (electronic bk.)
3031232399 (electronic bk.)
3031232380
9783031232381
DOI https://doi.org/10.1007/978-3-031-23239-8
Published Cham, Switzerland : Springer, 2023.
Language English
Description 1 online resource (xvii, 373 pages) : illustrations (some color)
Other Standard Identifiers 10.1007/978-3-031-23239-8 doi
Call Number R857.B54
Dewey Decimal Classification 610.28
Summary This book presents the modern technological advancements and revolutions in the biomedical sector. Progress in the contemporary sensing, Internet of Things (IoT) and machine learning algorithms and architectures have introduced new approaches in the mobile healthcare. A continuous observation of patients with critical health situation is required. It allows monitoring of their health status during daily life activities such as during sports, walking and sleeping. It is realizable by intelligently hybridizing the modern IoT framework, wireless biomedical implants and cloud computing. Such solutions are currently under development and in testing phases by healthcare and governmental institutions, research laboratories and biomedical companies. The biomedical signals such as electrocardiogram (ECG), electroencephalogram (EEG), Electromyography (EMG), phonocardiogram (PCG), Chronic Obstructive Pulmonary (COP), Electrooculography (EoG), photoplethysmography (PPG), and image modalities such as positron emission tomography (PET), magnetic resonance imaging (MRI) and computerized tomography (CT) are non-invasively acquired, measured, and processed via the biomedical sensors and gadgets. These signals and images represent the activities and conditions of human cardiovascular, neural, vision and cerebral systems. Multi-channel sensing of these signals and images with an appropriate granularity is required for an effective monitoring and diagnosis. It renders a big volume of data and its analysis is not feasible manually. Therefore, automated healthcare systems are in the process of evolution. These systems are mainly based on biomedical signal and image acquisition and sensing, preconditioning, features extraction and classification stages. The contemporary biomedical signal sensing, preconditioning, features extraction and intelligent machine and deep learning-based classification algorithms are described. Each chapter starts with the importance, problem statement and motivation. A self-sufficient description is provided. Therefore, each chapter can be read independently. To the best of the editors⁰́₉ knowledge, this book is a comprehensive compilation on advances in non-invasive biomedical signal sensing and processing with machine and deep learning. We believe that theories, algorithms, realizations, applications, approaches, and challenges, which are presented in this book will have their impact and contribution in the design and development of modern and effective healthcare systems.
Access Note Access limited to authorized users.
Source of Description Online resource; title from PDF title page (SpringerLink, viewed March 8, 2023).
Added Author Qaisar, Saeed Mian, editor.
Nisar, Humaira, 1970- editor.
Subasi, Abdulhamit, editor.
Available in Other Form Print version: 9783031232381
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