This book provides a comprehensive overview of the state of the art in signal quality assessment techniques for physiological signals, and chiefly focuses on ECG (electrocardiography) and PPG (photoplethysmography) signals obtained from wearable sensors in ambulatory clinical settings. It presents the techniques currently proposed by leading researchers, as well as examples using data from clinical trials on wearable sensors for inpatient and outpatient settings. In addition, the book assesses current approaches through a practical lens by discussing the implications of deploying the various proposed systems for clinical practices and health outcomes. As such, it will be of considerable interest to both graduate students and researchers working to develop personalized healthcare applications, as well as physiological sensor software and hardware developers.
This third, and final, volume is devoted to a discussion of monitoring systems. While the applications of physiological monitoring are many and varied, the primary concern here is with viability monitoring, the use of a measurement system to obtain factual, quantitative information about the physiological responses of a subject in a stressful environment, in order to plan protective measures which will ensure the safety and functional capability of that subject in such environments. Included are a description of instrumentation required for the measurement of individual physiological parameters, a discussion of related problems in system design, including simultaneous measurement of several parameters, data transmission or telemetry, and the use of magnetic tape recording as a system adjunct. Basic guidelines of system troubleshooting and interference reduction are also included. Section IV contains a brief survey of additional measurement techniques and data handling considerations which, while not state of the art or standard practice, will undoubtedly affect the field of physiological monitoring in the near future.
Vital signs, such as heart rate and respiration rate, are useful to health monitoring because they can provide important physiological insights for medical diagnosis and well-being management. Most traditional methods for measuring vital signs require a person to wear biomedical devices, such as a capnometer, a pulse oximeter, or an electrocardiogram sensor. These contact-based technologies are inconvenient, cumbersome, and uncomfortable to use. There is a compelling need for technologies that enable contact-free, easily deployable, and long-term monitoring of vital signs for healthcare. Contactless Vital Signs Monitoring presents a systematic and in-depth review on the principles, methodologies, and opportunities of using different wavelengths of an electromagnetic spectrum to measure vital signs from the human face and body contactlessly. The volume brings together pioneering researchers active in the field to report the latest progress made, in an intensive and structured way. It also presents various healthcare applications using camera and radio frequency-based monitoring, from clinical care to home care, to sport training and automotive, such as patient/neonatal monitoring in intensive care units, general wards, emergency department triage, MR/CT cardiac and respiratory gating, sleep centers, baby/elderly care, fitness cardio training, driver monitoring in automotive settings, and more. This book will be an important educational source for biomedical researchers, AI healthcare researchers, computer vision researchers, wireless-sensing researchers, doctors/clinicians, physicians/psychologists, and medical equipment manufacturers. - Includes various contactless vital signs monitoring techniques, such as optical-based, radar-based, WiFi-based, RFID-based, and acoustic-based methods. - Presents a thorough introduction to the measurement principles, methodologies, healthcare applications, hardware set-ups, and systems for contactless measurement of vital signs using camera or RF sensors. - Presents the opportunities for the fusion of camera and RF sensors for contactless vital signs monitoring and healthcare.
v.1: This volume is the first of a three-volume handbook covering the applications of electronics in monitoring bioelectric physiological responses. The fundamental concepts and methods presented in this volume form a foundation for the detailed technical discussions in the succeeding volumes and, it is hoped, provide a common language and basis of understanding between the physiologist and electronic engineer engaged in this field. The data obtained by monitoring physiological responses in varied environments can be used to improve the efficiency and increase the safety of a human subject in aircraft and spacecraft. -- DTIC website.
The desire to improve muscle function and prevent overuse injuries from exercise and throughout training has led to the development of various methods to aid recovery and track readiness to perform. Ergogenic aids such as cold-water immersion, massage, and dynamic recovery procedures may have positive effects but the results of the related research remain equivocal. Furthermore, novel interventions in this scenario, like compression garments, ice vests, and photobiomodulation therapy are promising but need more evidence-based data to support their effectiveness. Similarly, to properly monitor individual physical conditioning, there is a growing interest toward unobtrusive measures to accurately represent physiological status during and/or after exercise. There are several techniques being used, such as subjective ratings of well-being, heart rate monitoring, hormonal and hematological profile assessments. However, more sensitive indexes like heart rate variability and muscle activation (voluntary and/or involuntary) are arising as attractive alternatives that may delineate physical conditioning status and readiness to perform more precisely than the aforementioned measures. The purpose of this Research Topic is to critically evaluate and summarize recent data from observational and intervention studies related to non-invasive methods designed to promote recovery and objectively monitor training status. Their association to physical performance and physiological recovery in athletes during training and competition is a major focus of this Topic.
Photoplethysmography: Technology, Signal Analysis, and Applications is the first comprehensive volume on the theory, principles, and technology (sensors and electronics) of photoplethysmography (PPG). It provides a detailed description of the current state-of-the-art technologies/optical components enabling the extreme miniaturization of such sensors, as well as comprehensive coverage of PPG signal analysis techniques including machine learning and artificial intelligence. The book also outlines the huge range of PPG applications in healthcare, with a strong focus on the contribution of PPG in wearable sensors and PPG for cardiovascular assessment. - Presents the underlying principles and technology surrounding PPG - Includes applications for healthcare and wellbeing - Focuses on PPG in wearable sensors and devices - Presents advanced signal analysis techniques - Includes cutting-edge research, applications and future directions
Classification Techniques for Medical Image Analysis and Computer Aided Diagnosis covers the most current advances on how to apply classification techniques to a wide variety of clinical applications that are appropriate for researchers and biomedical engineers in the areas of machine learning, deep learning, data analysis, data management and computer-aided diagnosis (CAD) systems design. The book covers several complex image classification problems using pattern recognition methods, including Artificial Neural Networks (ANN), Support Vector Machines (SVM), Bayesian Networks (BN) and deep learning. Further, numerous data mining techniques are discussed, as they have proven to be good classifiers for medical images. - Examines the methodology of classification of medical images that covers the taxonomy of both supervised and unsupervised models, algorithms, applications and challenges - Discusses recent advances in Artificial Neural Networks, machine learning, and deep learning in clinical applications - Introduces several techniques for medical image processing and analysis for CAD systems design
Designed to serve as a primary reference source for researchers and students interested in expanding their research to consider a biopsychosocial approach, this book provides a thorough, state-of-the-art, and user-friendly coverage of basic techniques for measurement of physiological variables in health psychology research.
