Esther Rodriguez-Villegas

Bio: Esther Rodriguez-Villegas is an academic researcher from Imperial College London. The author has contributed to research in topics: Low voltage & Low-power electronics. The author has an hindex of 30, co-authored 153 publications receiving 3334 citations. Previous affiliations of Esther Rodriguez-Villegas include Spanish National Research Council & University of Seville.

Wearable electroencephalography. What is it, why is it needed, and what does it entail?

Abstract: The electroencephalogram (EEG) is a classic noninvasive method for measuring a person's brain waves and is used in a large number of fields: from epilepsy and sleep disorder diagnosis to brain-computer interfaces (BCIs). Electrodes are placed on the scalp to detect the microvolt-sized signals that result from synchronized neuronal activity within the brain. Current long-term EEG monitoring is generally either carried out as an inpatient in combination with video recording and long cables to an amplifier and recording unit or is ambulatory. In the latter, the EEG recorder is portable but bulky, and in principle, the subject can go about their normal daily life during the recording. In practice, however, this is rarely the case. It is quite common for people undergoing ambulatory EEG monitoring to take time off work and stay at home rather than be seen in public with such a device. Wearable EEG is envisioned as the evolution of ambulatory EEG units from the bulky, limited lifetime devices available today to small devices present only on the head that can record EEG for days, weeks, or months at a time. Such miniaturized units could enable prolonged monitoring of chronic conditions such as epilepsy and greatly improve the end-user acceptance of BCI systems. In this article, we aim to provide a review and overview of wearable EEG technology, answering the questions: What is it, why is it needed, and what does it entail? We first investigate the requirements of portable EEG systems and then link these to the core applications of wearable EEG technology: epilepsy diagnosis, sleep disorder diagnosis, and BCIs. As a part of our review, we asked 21 neurologists (as a key user group) for their views on wearable EEG. This group highlighted that wearable EEG will be an essential future tool. Our descriptions here will focus mainly on epilepsy and the medical applications of wearable EEG, as this is the historical background of the EEG, our area of expertise, and a core motivating area in itself, but we will also discuss the other application areas. We continue by considering the forthcoming research challenges, principally new electrode technology and lower power electronics, and we outline our approach for dealing with the electronic power issues. We believe that the optimal approach to realizing wearable EEG technology is not to optimize any one part but to find the best set of tradeoffs at both the system and implementation level. In this article, we discuss two of these tradeoffs in detail: investigating the online compression of EEG data to reduce the system power consumption and the optimal method for providing this data compression.

Wearable Electroencephalography

Abstract: The electroencephalogram (EEG) is a classic noninvasive method for measuring a person's brainwaves and is used in a large number of fields: from epilepsy and sleep disorder diagnosis to brain-computer interfaces (BCIs). Electrodes are placed on the scalp to detect the microvolt-sized signals that result from synchronized neuronal activity within the brain. Current long-term EEG monitoring is generally either carried out as an inpatient in combination with video recording and long cables to an amplifier and recording unit or is ambulatory. In the latter, the EEG recorder is portable but bulky, and in principle, the subject can go about their normal daily life during the recording. In practice, however, this is rarely the case. It is quite common for people undergoing ambulatory EEG monitoring to take time off work and stay at home rather than be seen in public with such a device. Wearable EEG is envisioned as the evolution of ambulatory EEG units from the bulky, limited lifetime devices available today to small devices present only on the head that can record EEG for days, weeks, or months at a time [see Figure 1(a) and (b)]. Such miniaturized units could enable prolonged monitoring of chronic conditions such as epilepsy and greatly improve the end-user acceptance of BCI systems. In this article, we aim to provide a review and overview of wearable EEG technology, answering the questions: What is it, why is it needed, and what does it entail? We first investigate the requirements of portable EEG systems and then link these to the core applications of wearable EEG technology: epilepsy diagnosis, sleep disorder diagnosis, and BCIs. As a part of our review, we asked 21 neurologists (as a key user group) for their views on wearable EEG. This group highlighted that wearable EEG will be an essential future tool. Our descriptions here will focus mainly on epilepsyand the medical applications of wearable EEG, as this is the historical background of the EEG, our area of expertise, and a core motivating area in itself, but we will also discuss the other application areas. We continue by considering the forthcoming research challenges, principally new electrode technology and lower power electronics, and we outline our approach for dealing with the electronic power issues. We believe that the optimal approach to realizing wearable EEG technology is not to optimize any one part but to find the best set of tradeoffs at both the system and implementation level. In this article, we discuss two of these tradeoffs in detail: investigating the online compression of EEG data to reduce the system power consumption and the optimal method for providing this data compression.

Breathing Detection: Towards a Miniaturized, Wearable, Battery-Operated Monitoring System

Abstract: This paper analyzes the main challenges associated with noninvasive, continuous, wearable, and long-term breathing monitoring The characteristics of an acoustic breathing signal from a miniature sensor are studied in the presence of sources of noise and interference artifacts that affect the signal Based on these results, an algorithm has been devised to detect breathing It is possible to implement the algorithm on a single integrated circuit, making it suitable for a miniature sensor device The algorithm is tested in the presence of noise sources on five subjects and shows an average success rate of 913% (combined true positives and true negatives)

Solution to trapped charge in FGMOS transistors

Abstract: A solution to the problem of charge being trapped on the gate of a floating gate MOS transistor during fabrication is presented. The solution does not alter the floating nature of the gate of the device since it does not use any kind of active or passive device to get rid of the accumulated charge. In addition, it does not require any post-processing techniques such as exposure to UV light and does not require any extra masks.

Automatic adventitious respiratory sound analysis: A systematic review.

Abstract: Background Automatic detection or classification of adventitious sounds is useful to assist physicians in diagnosing or monitoring diseases such as asthma, Chronic Obstructive Pulmonary Disease (COPD), and pneumonia While computerised respiratory sound analysis, specifically for the detection or classification of adventitious sounds, has recently been the focus of an increasing number of studies, a standardised approach and comparison has not been well established Objective To provide a review of existing algorithms for the detection or classification of adventitious respiratory sounds This systematic review provides a complete summary of methods used in the literature to give a baseline for future works Data sources A systematic review of English articles published between 1938 and 2016, searched using the Scopus (1938-2016) and IEEExplore (1984-2016) databases Additional articles were further obtained by references listed in the articles found Search terms included adventitious sound detection, adventitious sound classification, abnormal respiratory sound detection, abnormal respiratory sound classification, wheeze detection, wheeze classification, crackle detection, crackle classification, rhonchi detection, rhonchi classification, stridor detection, stridor classification, pleural rub detection, pleural rub classification, squawk detection, and squawk classification Study selection Only articles were included that focused on adventitious sound detection or classification, based on respiratory sounds, with performance reported and sufficient information provided to be approximately repeated Data extraction Investigators extracted data about the adventitious sound type analysed, approach and level of analysis, instrumentation or data source, location of sensor, amount of data obtained, data management, features, methods, and performance achieved Data synthesis A total of 77 reports from the literature were included in this review 55 (7143%) of the studies focused on wheeze, 40 (5195%) on crackle, 9 (1169%) on stridor, 9 (1169%) on rhonchi, and 18 (2338%) on other sounds such as pleural rub, squawk, as well as the pathology Instrumentation used to collect data included microphones, stethoscopes, and accelerometers Several references obtained data from online repositories or book audio CD companions Detection or classification methods used varied from empirically determined thresholds to more complex machine learning techniques Performance reported in the surveyed works were converted to accuracy measures for data synthesis Limitations Direct comparison of the performance of surveyed works cannot be performed as the input data used by each was different A standard validation method has not been established, resulting in different works using different methods and performance measure definitions Conclusion A review of the literature was performed to summarise different analysis approaches, features, and methods used for the analysis The performance of recent studies showed a high agreement with conventional non-automatic identification This suggests that automated adventitious sound detection or classification is a promising solution to overcome the limitations of conventional auscultation and to assist in the monitoring of relevant diseases

A review of wearable sensors and systems with application in rehabilitation.

Abstract: The aim of this review paper is to summarize recent developments in the field of wearable sensors and systems that are relevant to the field of rehabilitation. The growing body of work focused on the application of wearable technology to monitor older adults and subjects with chronic conditions in the home and community settings justifies the emphasis of this review paper on summarizing clinical applications of wearable technology currently undergoing assessment rather than describing the development of new wearable sensors and systems. A short description of key enabling technologies (i.e. sensor technology, communication technology, and data analysis techniques) that have allowed researchers to implement wearable systems is followed by a detailed description of major areas of application of wearable technology. Applications described in this review paper include those that focus on health and wellness, safety, home rehabilitation, assessment of treatment efficacy, and early detection of disorders. The integration of wearable and ambient sensors is discussed in the context of achieving home monitoring of older adults and subjects with chronic conditions. Future work required to advance the field toward clinical deployment of wearable sensors and systems is discussed.

How to… home page

Abstract: Home PURPOSE OF THE CENTER: To develop the center to address state-of-the-art research, create innovating educational programs, and support technology transfers using commercially viable results to assist the Army Research Laboratory to develop the next generation Future Combat System in the telecommunications sector that assures prevention of perceived threats, and Non Line of Sight/Beyond Line of Sight lethal support.

An Introduction to Medical Statistics

Abstract: QUITE apart from the academic consideration that vital and medical statistics now form an obligatory part of the education of students seeking the University of London's diploma in public health, the demand for information about the methods of vital and medical statistics is increasing. The most casual reader of the newspapers is now aware that population problems are of serious practical importance and that the publications of the General Register Office cannot be ignored. It is scarcely an exaggeration to say that the recently issued preliminary report on the census of 1931 is one of the most sensational documents which has appeared for years, and that he who reads it intelligently will understand what is meant by saying that civilisation is in the melting pot. An Introduction to Medical Statistics. By Hilda M. Woods William T. Russell. Pp. x + 125. (London: P. S. King and Son, Ltd., 1931.) 7s. 6d.