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Compressive Sensing In Healthcare

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Compressive Sensing in Healthcare

Compressive Sensing in Healthcare Book
Author : Mahdi Khosravy,Nilanjan Dey,Carlos A. Duque
Publisher : Academic Press
Release : 2020-06-03
ISBN : 0128212470
Language : En, Es, Fr & De

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Book Description :

Compressive Sensing in Healthcare, part of the Advances in Ubiquitous Sensing Applications for Healthcare series gives a review on compressive sensing techniques in a practical way, also presenting deterministic compressive sensing techniques that can be used in the field. The focus of the book is on healthcare applications for this technology. It is intended for both the creators of this technology and the end users of these products. The content includes the use of EEG and ECG, plus hardware and software requirements for building projects. Body area networks and body sensor networks are explored. Provides a toolbox for compressive sensing in health, presenting both mathematical and coding information Presents an intuitive introduction to compressive sensing, including MATLAB tutorials Covers applications of compressive sensing in health care

Compressive Sensing in Healthcare

Compressive Sensing in Healthcare Book
Author : Mahdi Khosravy,Nilanjan Dey,Carlos A. Duque
Publisher : Academic Press
Release : 2020-05-18
ISBN : 0128212489
Language : En, Es, Fr & De

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Book Description :

Compressive Sensing in Healthcare, part of the Advances in Ubiquitous Sensing Applications for Healthcare series gives a review on compressive sensing techniques in a practical way, also presenting deterministic compressive sensing techniques that can be used in the field. The focus of the book is on healthcare applications for this technology. It is intended for both the creators of this technology and the end users of these products. The content includes the use of EEG and ECG, plus hardware and software requirements for building projects. Body area networks and body sensor networks are explored. Provides a toolbox for compressive sensing in health, presenting both mathematical and coding information Presents an intuitive introduction to compressive sensing, including MATLAB tutorials Covers applications of compressive sensing in health care

Compressed Sensing Magnetic Resonance Image Reconstruction Algorithms

Compressed Sensing Magnetic Resonance Image Reconstruction Algorithms Book
Author : Bhabesh Deka,Sumit Datta
Publisher : Springer
Release : 2018-12-29
ISBN : 9811335974
Language : En, Es, Fr & De

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Book Description :

This book presents a comprehensive review of the recent developments in fast L1-norm regularization-based compressed sensing (CS) magnetic resonance image reconstruction algorithms. Compressed sensing magnetic resonance imaging (CS-MRI) is able to reduce the scan time of MRI considerably as it is possible to reconstruct MR images from only a few measurements in the k-space; far below the requirements of the Nyquist sampling rate. L1-norm-based regularization problems can be solved efficiently using the state-of-the-art convex optimization techniques, which in general outperform the greedy techniques in terms of quality of reconstructions. Recently, fast convex optimization based reconstruction algorithms have been developed which are also able to achieve the benchmarks for the use of CS-MRI in clinical practice. This book enables graduate students, researchers, and medical practitioners working in the field of medical image processing, particularly in MRI to understand the need for the CS in MRI, and thereby how it could revolutionize the soft tissue imaging to benefit healthcare technology without making major changes in the existing scanner hardware. It would be particularly useful for researchers who have just entered into the exciting field of CS-MRI and would like to quickly go through the developments to date without diving into the detailed mathematical analysis. Finally, it also discusses recent trends and future research directions for implementation of CS-MRI in clinical practice, particularly in Bio- and Neuro-informatics applications.

Compressed Sensing Supplement

Compressed Sensing Supplement Book
Author : Anonim
Publisher : Unknown
Release : 2016
ISBN : 0987650XXX
Language : En, Es, Fr & De

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Book Description :

Download Compressed Sensing Supplement book written by , available in PDF, EPUB, and Kindle, or read full book online anywhere and anytime. Compatible with any devices.

Understanding the Practical Limitations of Applying Analog Compressed Sensing Systems to ECG Signals

Understanding the Practical Limitations of Applying Analog Compressed Sensing Systems to ECG Signals Book
Author : Anna Marie Rogers Dixon
Publisher : Unknown
Release : 2012
ISBN : 0987650XXX
Language : En, Es, Fr & De

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Book Description :

Body area networks (BAN), networks of wearable and wireless physiological sensors, are expected to have a profound positive impact in healthcare. The bio-signal sensors are equipped with ultra-low power radios communicating to a BAN personal base station, and ultimately the healthcare provider. Most of the power dissipated in a state-of-the-art bio-signal sensor occurs when the RF power amplifier transmits data to the personal base station. Thus, a method is desired that decreases the amount of data to be transmitted which reduces the duty cycle of the power amplifier and increases the overall energy efficiency. Compressed sensing (CS) is a compression scheme capable of significantly reducing a signal acquisition's data rate. CS requires only a few incoherent measurements to compress signals that are sparse in some domain. Since compressed sensing is still an emerging topic, only a handful of CS systems have been realized in hardware. These systems have shown promising and yet limited abilities. The objective of this research is to provide designers with a roadmap that enables them to more easily make correct decisions in designing analog CS encoders and decoders for bio-signals. By showing the impact of the considerations of this CS system on ECG signals, it will set up a framework for how to approach and/or analyze the design of these systems for all bio-signals. The CS roadmap accomplishes this goal this by demonstrating the importance of signal sparsity, guides the design of sensing matrix generation, addressing the impact of several analog CS imperfections on CS compression and guides the selection of proper CS reconstruction algorithms.

Big Data

Big Data Book
Author : Charl Janse Van Rensburg
Publisher : Unknown
Release : 2017
ISBN : 0987650XXX
Language : En, Es, Fr & De

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Book Description :

In recent times Big Data has been talked about in many areas, ranging from information technology, to government and healthcare, and to business. Big Data is changing the world we live in in many respects, especially as data of the individual becomes available in forms which it has not been previously, for example, data about the behaviour of indiviuals tracked via mobile phones. We discuss Big Data and whether it is having the said affect, or if it is only an unsubstantiated hype about something old coated under a new name. Convinced that Big Data is indeed a phenomenon of our day worthy of spending time and money on, we investigate whether Compressed Sensing (CS), a new and exciting tool in the signal processing field, can provide sensible solutions to Big Data problems. CS proposes a framework in which we simultaneously acquire and compress a signal of interest. However, for this to work, the way in which we acquire the signal needs to adhere to some uncertainty principles and the signal of interest need to be sparse in some basis representation. We argue that because Big Data many times exhibit sparsity and generally poses challenges to the storage capacity of different devices and systems, CS can be a useful tool in addressing challenges in the Big Data era and should be considered as a potential research area. This mini-dissertation provides an overview of CS and is by no means a full in-depth mathematical treatment of CS. It is written to provide the statistician with the necessary background and building blocks of CS, for use in the Big Data environment, and herein, CS is presented in a simple and clear manner for a statistician not familiar with the field. The literature review, however, provides all the texts required should the reader want the specific mathematical details. The document aims to thus link CS in the statistical and engineering fields.

Biomedical Signal Analysis for Connected Healthcare

Biomedical Signal Analysis for Connected Healthcare Book
Author : Sridhar Krishnan
Publisher : Academic Press
Release : 2019-06-15
ISBN : 9780128130865
Language : En, Es, Fr & De

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Book Description :

Biomedical Signal Analysis for Connected Healthcare provides rigorous coverage on several generations of techniques, including time domain approaches for event detection, spectral analysis for interpretation of clinical events of interest, time-varying signal processing for understanding dynamical aspects of complex biomedical systems, the application of machine learning principles in enhanced clinical decision-making, the application of sparse techniques and compressive sensing in providing low-power applications that are essential for wearable designs, the emerging paradigms of the Internet of Things, and connected healthcare. Provides comprehensive coverage of biomedical engineering, technologies, and healthcare applications of various physiological signals Covers vital signals, including ECG, EEG, EMG and body sounds Includes case studies and MATLAB code for selected applications

Smart Textiles for Medicine and Healthcare

Smart Textiles for Medicine and Healthcare Book
Author : Textile Institute (Manchester, England)
Publisher : CRC Press
Release : 2007-03-09
ISBN : 0987650XXX
Language : En, Es, Fr & De

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Book Description :

This text combines medical & smart textiles by looking at how smart or intelligent textiles are being used in healthcare. It assesses trends in smart medical textiles & their diverse uses in areas such as woundcare & drug release systems. It also reviews their role in monitoring the health of particular groups such as the elderly.

Wireless ECG System with Bluetooth Low Energy and Compressed Sensing

Wireless ECG System with Bluetooth Low Energy and Compressed Sensing Book
Author : Wanbo Li
Publisher : Unknown
Release : 2016
ISBN : 0987650XXX
Language : En, Es, Fr & De

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Book Description :

Electrocardiogram (ECG) is a noninvasive technology widely used in health care systems for diagnosis of heart diseases, and a wearable ECG sensor with long-term monitoring is necessary for real-time heart disease detection. However, the conventional ECG is restricted considering the physical size and power consumption of the system. In this thesis, we propose a Wireless ECG System with Bluetooth Low Energy (BLE) and Compressed Sensing (CS).The proposed Wireless ECG System includes an ECG sensor board based on a BLE chip, an Android application and a web service with a database. The ECG signal is first collected by the ECG Sensor Board and then transmitted to the Android application through BLE protocol. At last, the ECG signal is uploaded to the cloud database from the Android app. We also introduce Compressed Sensing into our system with a novel sparse sensing matrix, data compression and a modified Compressive Sampling Matching Pursuit (CoSaMP) reconstruction algorithm. Experiment results show that the amount of data transmitted is reduced by about 57% compared to not using Compressed Sensing, and reconstruction time is 64% less than using Orthogonal Matching Pursuit (OMP) or Iterative Re-weighted Least Squares (IRLS) algorithm.

Sensors Applications Sensors in Medicine and Health Care

Sensors Applications  Sensors in Medicine and Health Care Book
Author : J. Hesse,J. W. Gardner
Publisher : Wiley-VCH
Release : 2004-08-20
ISBN : 0987650XXX
Language : En, Es, Fr & De

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Book Description :

Taken as a whole, this series covers all major fields of application for commercial sensors, as well as their manufacturing techniques and major types. As such the series does not treat bulk sensors, but rather places strong emphasis on microsensors, microsystems and integrated electronic sensor packages. Each of the individual volumes is tailored to the needs and queries of readers from the relevant branch of industry. A review of applications for point-of-care diagnostics, their integration into portable systems and the comfortable, easy-to-use sensors that allow patients to monitor themselves at home. The book covers such advanced topics as minimal invasive surgery, implantable sensors and prostheses, as well as biocompatible sensing.

Proceedings of 4th Global Summit and Expo on Multimedia Artificial Intelligence 2018

Proceedings of 4th Global Summit and Expo on Multimedia   Artificial Intelligence 2018 Book
Author : ConferenceSeries
Publisher : ConferenceSeries
Release : 2021-06-16
ISBN : 0987650XXX
Language : En, Es, Fr & De

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Book Description :

July 19-21, 2018 Rome, Italy Key Topics : Imaging and Image Processing, Multimedia Cloud and Big Data, Multimedia IoT, Multimedia Systems & Services, Computer Games Design & Development, Multimedia Applications, Computer Graphics & Animation, Compter Vision and Pattern Recognition, Virtual Reality & Augmented Reality, Artificial Intelligence & Machine Learning, Natural language processing & Tensorflow, Artificial Intelligence for Bussines, Neural Networks, Human Computer Interaction and Visualization, Artificial Intelligence & Multimedia Technologies in Healthcare,

Sparse Reconstruction of Compressive Sensing Magnetic Resonance Imagery Using a Cross Domain Stochastic Fully Connected Conditional Random Field Framework

Sparse Reconstruction of Compressive Sensing Magnetic Resonance Imagery Using a Cross Domain Stochastic Fully Connected Conditional Random Field Framework Book
Author : Yaguang Li
Publisher : Unknown
Release : 2016
ISBN : 0987650XXX
Language : En, Es, Fr & De

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Book Description :

Prostate cancer is a major health care concern in our society. Early detection of prostate cancer is crucial in the successful treatment of the disease. Many current methods used in detecting prostate cancer can either be inconsistent or invasive and discomforting to the patient. Magnetic resonance imaging (MRI) has demonstrated its ability as a non-invasive and non-ionizing medical imaging modality with a lengthy acquisition time that can be used for the early diagnosis of cancer. Speeding up the MRI acquisition process can greatly increase the number of early detections for prostate cancer diagnosis. Compressive sensing has exhibited the ability to reduce the imaging time for MRI by sampling a sparse yet sufficient set of measurements. Compressive sensing strategies are usually accompanied by strong reconstruction algorithms. This work presents a comprehensive framework for a cross-domain stochastically fully connected conditional random field (CD-SFCRF) reconstruction approach to facilitate compressive sensing MRI. This approach takes into account original k-space measurements made by the MRI machine with neighborhood and spatial consistencies of the image in the spatial domain. This approach facilitates the difference in domain between MRI measurements made in the k-space, and the reconstruction results in spatial domain. An adaptive extension of the CD-SFCRF approach that takes into account regions of interest in the image and changes the CD-SFCRF neighborhood connectivity based on importance is presented and tested as well. Finally, a compensated CD-SFCRF approach that takes into account MRI machine imaging apparatus properties to correct for degradations and aberrations from the image acquisition process is presented and tested. Clinical MRI data were collected from twenty patients with ground truth data examined and con firmed by an expert radiologist with multiple years of prostate cancer diagnosis experience. Compressive sensing simulations were performed and the reconstruction results show the CD-SFCRF and extension frameworks having noticeable improvements over state of the art methods. Tissue structure and image details are well preserved while sparse sampling artifacts were reduced and eliminated. Future work on this framework include extending the current work in multiple ways. Extensions including integration into computer aided diagnosis applications as well as improving on the compressive sensing strategy.

The Emergence of internetable Health Care

The Emergence of  internetable  Health Care Book
Author : Daniel R. Masys
Publisher : Unknown
Release : 1997
ISBN : 0987650XXX
Language : En, Es, Fr & De

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Book Description :

Download The Emergence of internetable Health Care book written by Daniel R. Masys, available in PDF, EPUB, and Kindle, or read full book online anywhere and anytime. Compatible with any devices.

Energy Efficient Acquisition and Inferencing for Low Power Physiological Sensing

Energy Efficient Acquisition and Inferencing for Low Power Physiological Sensing Book
Author : Zainul Mohammed Charbiwala
Publisher : Unknown
Release : 2012
ISBN : 0987650XXX
Language : En, Es, Fr & De

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Book Description :

Affordable, wearable, embedded, wireless medical sensor systems that enable continuous long term monitoring of physiological signals could revolutionize health care. Realizing this vision demands devices that are small, unobtrusive and low power. Effectively inferring health conditions begins by acquiring physiological signals of interest and decisions made about what signals are acquired, when, where and at what rate affect not only the energy efficiency of the sampling process but also that of other downstream components in the signal processing chain. While the Nyquist sampling theorem provides for exact reconstruction from discrete-time samples, the prescribed rate is often wasteful for physiological sensing applications since it neither exploits the structure of signals fully nor does it take into account that many applications don't require full reconstruction at all. This dissertation illustrates how energy efficiency of the entire system can be improved by targeting just the signal acquisition process while being cognizant of the entire sensing information stack, from sampling, processing and communication to the top-level application inferences. A key ingredient that makes optimizing the sensing stack worthwhile is that the sampling stage, which is usually abstracted away from the system, can now utilize sophisticated methods that have emerged in the past few years. Recent advances in sampling and recovery techniques have demonstrated considerable rate reductions by employing stronger models of the phenomenon coupled with application-specific objectives (detection or control vs. reconstruction), which potentially translates to higher energy, processing and communications efficiency at the system level. This research describes four major thrusts that span the processing chain from hardware to algorithms to inferences. First, recognizing that signal conditioning front-end circuits could account for a large portion of the energy expenditure in low power sensing, we demonstrate how prudently duty cycling them could increase device lifetime by threefold and reduce data rate by almost fourfold for an electrocardiography monitor. Then, we go on to show how one could further slash data rates using the new theory of compressed sensing. For a neural spike recorder, we exploit the fact that action potentials have both a structure and short term stability in their morphology. This meant that we could utilize historical signal information to optimize and adapt compressed sensing recovery, with only receiver-side modifications, doubling the compression ratio. Third, since body area networks are prone to congestion and interference, we propose a rate control algorithm for the wireless channel so that the most important data from the most informative sensors gets delivered for maximum inference quality. Finally, we prove that compressedsensing could be utilized not only to compress signals but could also improve the robustness of sensor transmissions at low computational cost by viewing it as joint source-channel coding for wireless erasure channels.

Digital Health Approach for Predictive Preventive Personalised and Participatory Medicine

Digital Health Approach for Predictive  Preventive  Personalised and Participatory Medicine Book
Author : Lotfi Chaari
Publisher : Springer
Release : 2019-07-10
ISBN : 3030118002
Language : En, Es, Fr & De

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Book Description :

This collection, entitled Digital Health for Predictive, Preventive, Personalized and Participatory Medicine contains the proceedings of the first International conference on digital healthtechnologies (ICDHT 2018). Ten recent contributions in the fields of Artificial Intelligence (AI) and machine learning, Internet of Things (IoT) and data analysis, all applied to digital health. This collection enables researchers to learn about recent advances in the above mentioned fields. It brings a technological viewpoint of P4 medicine. Readers will discover how advanced Information Technology (IT) tools can be used for healthcare. For instance, the use of connected objects to monitor physiological parameters is discussed. Moreover, even if compressed sensing is nowadays a common acquisition technique, its use for IoT is presented in this collection through one of the pioneer works in the field. In addition, the use of AI for epileptic seizure detection is also discussed as being one of the major concerns of predictive medicine both in industrialized and low-income countries. This work is edited by Prof. Lotfi Chaari, professor at the University of Sfax, and previously at the University of Toulouse. This work comes after more than ten years of expertise in the biomedical signal and image processing field.

Sensing Techniques for Next Generation Cognitive Radio Networks

Sensing Techniques for Next Generation Cognitive Radio Networks Book
Author : Bagwari, Ashish,Bagwari, Jyotshana,Tomar, Geetam Singh
Publisher : IGI Global
Release : 2018-08-30
ISBN : 152255355X
Language : En, Es, Fr & De

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Book Description :

The inadequate use of wireless spectrum resources has recently motivated researchers and practitioners to look for new ways to improve resource efficiency. As a result, new cognitive radio technologies have been proposed as an effective solution. Sensing Techniques for Next Generation Cognitive Radio Networks is a pivotal reference source that provides vital research on the application of spectrum sensing techniques. While highlighting topics such as radio identification, compressive sensing, and wavelet transform, this publication explores the standards and the methods of cognitive radio network architecture. This book is ideally designed for IT and network engineers, practitioners, and researchers seeking current research on radio scene analysis for cognitive radios and networks.

ECG Signal Compression Using Compressive Sensing and Wavelet Transform

ECG Signal Compression Using Compressive Sensing and Wavelet Transform Book
Author : Akanksha Mishra,Falgun Thakkar,Rahul Kher,Chintan Modi
Publisher : Unknown
Release : 2015-01-08
ISBN : 9781632780454
Language : En, Es, Fr & De

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Book Description :

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.

Dun s Healthcare Reference Book

Dun s Healthcare Reference Book Book
Author : Anonim
Publisher : Unknown
Release : 1996
ISBN : 0987650XXX
Language : En, Es, Fr & De

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Book Description :

Download Dun s Healthcare Reference Book book written by , available in PDF, EPUB, and Kindle, or read full book online anywhere and anytime. Compatible with any devices.