Edited by the people who were forerunners in creating the field, together with contributions from 34 leading international experts, this handbook provides the definitive reference on Blind Source Separation, giving a broad and comprehensive description of all the core principles and methods, numerical algorithms and major applications in the fields of telecommunications, biomedical engineering and audio, acoustic and speech processing. Going beyond a machine learning perspective, the book reflects recent results in signal processing and numerical analysis, and includes topics such as optimization criteria, mathematical tools, the design of numerical algorithms, convolutive mixtures, and time frequency approaches. This Handbook is an ideal reference for university researchers, RD algebraic identification of under-determined mixtures, time-frequency methods, Bayesian approaches, blind identification under non negativity approaches, semi-blind methods for communicationsShows the applications of the methods to key application areas such as telecommunications, biomedical engineering, speech, acoustic, audio and music processing, while also giving a general method for developing applications

https://ie.technion.ac.il/~mcib/Gribonval_Zibulevsky_SCA_chapter.pdf

Handbook of Blind Source Separation: Independent Component Analysis and Applications

Some patients, especially patients with chronic diseases such as heart disease, require continuous monitoring of their condition. Wearable devices for patient monitoring were introduced many years ago – for instance, wearable ambulatory ECG (electrocardiogram) recorders commonly known as Holter monitors (Figure 1) are used for monitoring cardiac patients. However, these monitors are quite bulky and can only record the signal for a limited time. Patients are often asked to wear a Holter monitor for a few days and then return to the clinic for diagnosis. This often overlooks transient but life-threatening events. In addition, we don’t know under what condition the signals are acquired, and this often leads to false alarms. For example, a sudden rise in heart rate may be caused by emotion, such as watching a horror movie, or by exercise, rather than by a heart condition. Body sensing To address these issues, the concept of Body Sensor Networks (BSN) was first proposed in 2002 by Prof. Guang-Zhong Yang from Imperial College London. The aim of the BSN is to provide a truly personalised monitoring platform that is pervasive, intelligent, and Figure 1 A patient wearing a Holter monitor

Body sensor networks

https://www.cs.ubc.ca/~murphyk/Teaching/CS540-Spring10/projects/Yu-hsmm09.pdf

Hidden semi-Markov models

Multisensor fusion and integration is a rapidly evolving research area and requires interdisciplinary knowledge in control theory, signal processing, artificial intelligence, probability and statistics, etc. The advantages gained through the use of redundant, complementary, or more timely information in a system can provide more reliable and accurate information. This paper provides an overview of current sensor technologies and describes the paradigm of multisensor fusion and integration as well as fusion techniques at different fusion levels. Applications of multisensor fusion in robotics, biomedical system, equipment monitoring, remote sensing, and transportation system are also discussed. Finally, future research directions of multisensor fusion technology including microsensors, smart sensors, and adaptive fusion techniques are presented.

Multisensor fusion and integration: approaches, applications, and future research directions

Much previous work in artificial intelligence has neglected representing time in all its complexity. In particular, it has neglected continuous change and the indeterminacy of the future. To rectify this, I have developed a first-order temporal logic, in which it is possible to name and prove things about facts, events, plans, and world histories. In particular, the logic provides analyses of causality, continuous change in quantities, the persistence of facts (the frame problem), and the relationship between tasks and actions. It may be possible to implement a temporal-inference machine based on this logic, which keeps track of several “maps” of a time line, one per possible history.

A Temporal Logic for Reasoning about Processes and Plans.

Telemedicine is having a great impact on the monitoring of patients located in remote non-clinical environments, such as homes, elderly communities, gymnasiums, schools, remote military bases, ships, and the like. A number of applications, ranging from data collection to chronic patient surveillance, and even to the control of therapeutic procedures, are being implemented in many parts of the world. As part of this growing trend, this paper discusses the problems in electrocardiogram (ECG) real-time data acquisition, transmission and visualization over the Internet. ECG signals are transmitted in real time from a patient in a remote non-clinical environment to a specialist in a hospital or clinic using the current capabilities and availability of the Internet. A prototype system is described that is composed of (1) a portable data acquisition and pre-processing module connected to the computer at the remote site via its RS-232 port, (2) a Java-based client-server platform, and (3) software modules to handle communication protocols between the data acquisition module and the patient's personal computer, and to handle client-server communication. The purpose of the system is the provision of extended monitoring for patients under drug therapy after infarction, data collection in some particular cases, remote consultation and low-cost ECG monitoring for the elderly.

Real-time ECG transmission via Internet for nonclinical applications

Current research offers a complex perspective on the main characteristics of Millennials (or Gen-Ys, as they are also called) as a generation in which knowledge is acquired, shared, and created as an extension of the primacy of relationships and networks and embedded in the connections that information technology provides. Aspects of the servant-leadership model provide a context from which to examine the construction of workplace practice (action) and purpose (meaning) among members of the Millennial generation. However, theories developed in previous generations are not automatically applicable and require critical examination and adaptation if they are to offer an understanding of means for motivating and influencing Millennials toward more broadly defined goals and aspirations in multigenerational workplaces. After a review of recent literature, we conclude that future organizational paradigms will have to develop a multigenerational collaborative culture. With this in mind, we discuss how service leadership contributes to these new networked and collaborative organizations to help Millennials flourish and prepare them for leadership positions as well.

Adapting leadership theory and practice for the networked, millennial generation

The diversity of factors that take part in the design of intelligent patient monitoring and management systems is presented. Particular attention is given to intelligent monitoring and management interfaces, and to the use of knowledge-based systems in patient monitoring and management. >

Intelligent patient monitoring and management systems: a review

Describes a novel technique for the cancellation of the ventricular activity for applications such as P-wave or atrial fibrillation detection. The procedure was thoroughly tested and compared with a previously published method, using quantitative measures of performance. The novel approach estimates, by means of a dynamic time delay neural network (TDNN), a time-varying, nonlinear transfer function between two ECG leads. Best results were obtained using an Elman TDNN with 9 input samples and 20 neurons, employing a sigmoidal tangencial activation in the hidden layer and one linear neuron in the output stage. The method does not require a previous stage of QRS detection. The technique was quantitatively evaluated using the MIT-BIH arrhythmia database and compared with an adaptive cancellation scheme proposed in the literature. Results show the advantages of the proposed approach, and its robustness during noisy episodes and QRS morphology variations.

Atrial activity enhancement by Wiener filtering using an artificial neural network

Information management for critical care monitoring is still a very difficult task. Medical staff are often overwhelmed by the amount of data provided by the increased number of specific monitoring devices and instrumentation, and the lack of an effective automated system. Specifically, a basic task such as arrhythmia detection still produce an important amount of undesirable alarms, due in part to the mechanistic approach of current monitoring systems. In this work, multisensor and multisource data fusion schemes to improve atrial and ventricular activity detection in critical care environments are presented. Applications of these schemes are quantitatively evaluated and compared with current methods, showing the potential advantages of data fusion techniques for event detection in noise corrupted signals.

https://www.hal.inserm.fr/inserm-00134401/document

Fernando Mora

Papers

Real-time ECG transmission via Internet for nonclinical applications

Adapting leadership theory and practice for the networked, millennial generation

Intelligent patient monitoring and management systems: a review

Atrial activity enhancement by Wiener filtering using an artificial neural network

Multisensor fusion for atrial and ventricular activity detection in coronary care monitoring