VAMP - a vision based sensor network for health care hygiene

Adequate hand-washing has been shown to be a critical activity in preventing the transmission of infections such as MRSA in health-care environments. Hand-washing guidelines published by various health-care related institutions recommend a technique incorporating six hand-washing poses that ensure all areas of the hands are thoroughly cleaned. In this paper, an embedded wireless vision system (VAMP) capable of accurately monitoring hand-washing quality is presented. The VAMP system hardware consists of a low resolution CMOS image sensor and FPGA processor which are integrated with a microcontroller and ZigBee standard wireless transceiver to create a wireless sensor network (WSN) based vision system that can be retargeted at a variety of health care applications. The device captures and processes images locally in real-time, determines if hand-washing procedures have been correctly undertaken and then passes the resulting high-level data over a low-bandwidth wireless link. The paper outlines the hardware and software mechanisms of the VAMP system and illustrates that it offers an easy to integrate sensor solution to adequately monitor and improve hand hygiene quality. Future work to develop a miniaturized, low cost system capable of being integrated into everyday products is also discussed.

A study of silicon and germanium junctionless transistors

Technology boosters, such as strain, HKMG and FinFET, have been introduced into semiconductor industry to extend Moore’s law beyond 130 nm technology nodes. New device structures and channel materials are highly demanded to keep performance enhancement when the device scales beyond 22 nm. In this work, the properties and feasibility of the proposed Junctionless transistor (JNT) have been evaluated for both Silicon and Germanium channels. The performance of Silicon JNTs with 22 nm gate length have been characterized at elevated temperature and stressed conditions. Furthermore, steep Subthreshold Slopes (SS) in JNT and IM devices are compared. It is observed that the floating body in JNT is relatively dynamic comparing with that in IM devices and proper design of the device structure may further reduce the VD for a sub- 60 mV/dec subthreshold slope. Diode configuration of the JNT has also been evaluated, which demonstrates the first diode without junctions. In order to extend JNT structure into the high mobility material Germanium (Ge), a full process has been develop for Ge JNT. Germanium-on-Insulator (GeOI) wafers were fabricated using Smart-Cut with low temperature direct wafer bonding method. Regarding the lithography and pattern transfer, a top-down process of sub-50-nm width Ge nanowires is developed in this chapter and Ge nanowires with 35 nm width and 50 nm depth are obtained. The oxidation behaviour of Ge by RTO has been investigated and high-k passivation scheme using thermally grown GeO2 has been developed. With all developed modules, JNT with Ge channels have been fabricated by the CMOScompatible top-down process. The transistors exhibit the lowest subthreshold slope to date for Ge JNT. The devices with a gate length of 3 μm exhibit a SS of 216 mV/dec with an ION/IOFF current ratio of 1.2×103 at VD = -1 V and DIBL of 87 mV/V.

Artefact detection and removal algorithms for EEG diagnostic systems

The electroencephalogram (EEG) is a medical technology that is used in the monitoring of the brain and in the diagnosis of many neurological illnesses. Although coarse in its precision, the EEG is a non-invasive tool that requires minimal set-up times, and is suitably unobtrusive and mobile to allow continuous monitoring of the patient, either in clinical or domestic environments. Consequently, the EEG is the current tool-of-choice with which to continuously monitor the brain where temporal resolution, ease-of- use and mobility are important. Traditionally, EEG data are examined by a trained clinician who identifies neurological events of interest. However, recent advances in signal processing and machine learning techniques have allowed the automated detection of neurological events for many medical applications. In doing so, the burden of work on the clinician has been significantly reduced, improving the response time to illness, and allowing the relevant medical treatment to be administered within minutes rather than hours. However, as typical EEG signals are of the order of microvolts (μV ), contamination by signals arising from sources other than the brain is frequent. These extra-cerebral sources, known as artefacts, can significantly distort the EEG signal, making its interpretation difficult, and can dramatically disimprove automatic neurological event detection classification performance. This thesis therefore, contributes to the further improvement of auto- mated neurological event detection systems, by identifying some of the major obstacles in deploying these EEG systems in ambulatory and clinical environments so that the EEG technologies can emerge from the laboratory towards real-world settings, where they can have a real-impact on the lives of patients. In this context, the thesis tackles three major problems in EEG monitoring, namely: (i) the problem of head-movement artefacts in ambulatory EEG, (ii) the high numbers of false detections in state-of-the-art, automated, epileptiform activity detection systems and (iii) false detections in state-of-the-art, automated neonatal seizure detection systems. To accomplish this, the thesis employs a wide range of statistical, signal processing and machine learning techniques drawn from mathematics, engineering and computer science. The first body of work outlined in this thesis proposes a system to automatically detect head-movement artefacts in ambulatory EEG and utilises supervised machine learning classifiers to do so. The resulting head-movement artefact detection system is the first of its kind and offers accurate detection of head-movement artefacts in ambulatory EEG. Subsequently, addtional physiological signals, in the form of gyroscopes, are used to detect head-movements and in doing so, bring additional information to the head- movement artefact detection task. A framework for combining EEG and gyroscope signals is then developed, offering improved head-movement arte- fact detection. The artefact detection methods developed for ambulatory EEG are subsequently adapted for use in an automated epileptiform activity detection system. Information from support vector machines classifiers used to detect epileptiform activity is fused with information from artefact-specific detection classifiers in order to significantly reduce the number of false detections in the epileptiform activity detection system. By this means, epileptiform activity detection which compares favourably with other state-of-the-art systems is achieved. Finally, the problem of false detections in automated neonatal seizure detection is approached in an alternative manner; blind source separation techniques, complimented with information from additional physiological signals are used to remove respiration artefact from the EEG. In utilising these methods, some encouraging advances have been made in detecting and removing respiration artefacts from the neonatal EEG, and in doing so, the performance of the underlying diagnostic technology is improved, bringing its deployment in the real-world, clinical domain one step closer.

Developing executive capability — banking and beyond

The transition to becoming a leader is perhaps the least understood and most difficult in business. This Portfolio of Exploration examines the development of conscious awareness and meaning complexity as key transformational requirements to operate competently at leadership level and to succeed in a work environment characterised by change and complexity. It recognises that developing executive leadership capability is not just an issue of personality increasing what we know or expertise. It requires development of complexity in terms of how we know ourselves, relate to others, construe leadership and organisation, problem solve in business and understand the world as a whole. The exploration is grounded in the theory of adult mental development as outlined by Robert Kegan (1982, 1994) and in his collaborations with Lisa Laskow Lahey (2001, 2009). The theory points to levels of consciousness which impact on how we make meaning of and experience the world around us and respond to it. Critically it also points to transformational processes which enable us to evolve how we make meaning of our world as a means to close the mismatch between the demands of this world and our ability to cope. The exploration is laid out in three stages. Using Kegan’s (1982, 1994) theory as a framework it begins with a reflection of my career to surface how I made meaning of banking, management and subsequently leadership. In stage two I engage with a range of source thinkers in the areas of leadership, decision making, business, organisation, growth and complexity in a transformational process of developing greater conscious and complex understanding of organisational leadership (also recognising ever increasing complexity in the world). Finally, in stage three, I explore how qualitative changes as a result of this transformational effort have benefitted my professional, leadership and organisational capabilities.

ENVIRON 2011: 21st Irish Environmental Researchers Colloquium

The theme of this year’s colloquium is “Towards 2020: Environmental challenges and opportunities for the next decade” which reflects the many environmental targets that have been set for the year 2020 in areas of climate change, renewable energy, water protection and biodiversity. In relation to the latter, we are delighted to have Professor Michael Depledge (Former Chairman of UK Science Advisory Committee on the Environment & Climate Change) at ENVIRON 2011 to deliver the colloquium keynote address on “Health and the Value of Nature”. The colloquium plenary session has a number of high profile speakers who will address the colloquium theme of environmental challenges and opportunities for the next decade including Professor John Sweeney (NUI Maynooth), Ms Laura Burke (Director of EPA’s Office of Climate, Licensing Research and Resource Use) and Mr John Mullins (CEO of Bord Gais). The research programme has 95 oral presentations and 60 poster presentations in the themes of water quality, energy and climate change, marine and coastal research, environmental management, environmental technologies, environment and health, and biodiversity and ecosystems. In addition, for the first year, poster presenters have the opportunity to make a 1 minute oral presentation on their poster during the oral sessions in the relevant theme. The 2011 colloquium also sees an increase the number of workshops and seminars accompanying the programme with an emphasis on training and development for postgraduates in the environmental area. We are particularly pleased to have a link with the Environment Graduate Programme in the “Ocean Studies Workshop” which illustrates how the ENVIRON colloquium can support and benefit from the various graduate programmes currently being developed within Universities. Finally ENVIRON 2011 and the UCC 2011 Law and the Environment symposium have been deliberately scheduled together at the same time and location to allow delegates from both conferences to benefit from each other’s programmes.