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.

Lower extremity amputation in people with diabetes: Trends and determinants

Introduction: The prevalence of diabetes is rising rapidly. Assessing quality of diabetes care is difficult. Lower Extremity Amputation (LEA) is recognised as a marker of the quality of diabetes care. The focus of this thesis was first to describe the trends in LEA rates in people with and without diabetes in the Republic of Ireland (RoI) in recent years and then, to explore the determinants of LEA in people with diabetes. While clinical and socio-demographic determinants have been well-established, the role of service-related factors has been less well-explored. Methods: Using hospital discharge data, trends in LEA rates in people with and without diabetes were described and compared to other countries. Background work included concordance studies exploring the reliability of hospital discharge data for recording LEA and diabetes and estimation of diabetes prevalence rates in the RoI from a nationally representative study (SLAN 2007). To explore determinants, a systematic review and meta-analysis assessed the effect of contact with a podiatrist on the outcome of LEA in people with diabetes. Finally, a case-control study using hospital discharge data explored determinants of LEA in people with diabetes with a particular focus on the timing of access to secondary healthcare services as a risk factor. Results: There are high levels of agreement between hospital discharge data and medical records for LEA and diabetes. Thus, hospital discharge data was deemed sufficiently reliable for use in this PhD thesis. A decrease in major diabetes-related LEA rates in people with diabetes was observed in the RoI from 2005-2012. In 2012, the relative risk of a person with diabetes undergoing a major LEA was 6.2 times (95% CI 4.8-8.1) that of a person without diabetes. Based on the systematic review and meta-analysis, contact with a podiatrist did not significantly affect the relative risk (RR) of LEA in people with diabetes. Results from the case-control study identified being single, documented CKD and documented hypertension as significant risk factors for LEA in people with diabetes whilst documented retinopathy was protective. Within the seven year time window included in the study, no association was detected between LEA in patients with diabetes and timing of patient access to secondary healthcare for diabetes management. Discussion: Many countries have reported reduced major LEA rates in people with diabetes coinciding with improved organisation of healthcare systems. Reassuringly, these first national estimates in people with diabetes in the RoI from 2005 to 2012 demonstrated reducing trends in major LEA rates. This may be attributable to changes in diabetes care and also, secular trends in smoking, dyslipidaemia and hypertension. Consistent with international practice, LEA trends data in Ireland can be used to monitor quality of care. Quantifying this improvement precisely, though, is problematic without robust denominator data on the prevalence of diabetes. However, a reduction in major diabetes-related LEA rates suggests improved quality of diabetes care. Much controversy exists around the reliability of hospital discharge data in the RoI. This thesis includes the first multi-site study to explore this issue and found hospital discharge data reliable for the reporting of the procedure of LEA and diagnosis of diabetes. This project did not detect protective effects of access to services including podiatry and secondary healthcare for LEA in people with diabetes. A major limitation of the systematic review and meta-analysis was the design and quality of the included studies. The data available in the area of effect of contact with a podiatrist on LEA risk are too sparse to say anything definitive about the efficacy of podiatry on LEA. Limitations of the case-control study include lack of a diabetes register in Ireland, restricted information from secondary healthcare and lack of data available from primary healthcare. Due to these issues, duration of disease could not be accounted for in the study which limits the conclusions that can be drawn from the results. The model of diabetes care in the RoI is currently undergoing a re-configuration with plans to introduce integrated care. In the future, trends in LEA rates should be continuously monitored to evaluate the effectiveness of changes to the healthcare system. Efforts are already underway to improve the availability of routine data from primary healthcare with the recent development of the iPCRN (Irish Primary Care Research Network). Linkage of primary and secondary healthcare records with a unique patient identifier should be the goal for the future.

Integration of micro- and macroscopic models for pedestrian evacuation simulation

Simulation of pedestrian evacuations of smart buildings in emergency is a powerful tool for building analysis, dynamic evacuation planning and real-time response to the evolving state of evacuations. Macroscopic pedestrian models are low-complexity models that are and well suited to algorithmic analysis and planning, but are quite abstract. Microscopic simulation models allow for a high level of simulation detail but can be computationally intensive. By combining micro- and macro- models we can use each to overcome the shortcomings of the other and enable new capability and applications for pedestrian evacuation simulation that would not be possible with either alone. We develop the EvacSim multi-agent pedestrian simulator and procedurally generate macroscopic flow graph models of building space, integrating micro- and macroscopic approaches to simulation of the same emergency space. By “coupling” flow graph parameters to microscopic simulation results, the graph model captures some of the higher detail and fidelity of the complex microscopic simulation model. The coupled flow graph is used for analysis and prediction of the movement of pedestrians in the microscopic simulation, and investigate the performance of dynamic evacuation planning in simulated emergencies using a variety of strategies for allocation of macroscopic evacuation routes to microscopic pedestrian agents. The predictive capability of the coupled flow graph is exploited for the decomposition of microscopic simulation space into multiple future states in a scalable manner. By simulating multiple future states of the emergency in short time frames, this enables sensing strategy based on simulation scenario pattern matching which we show to achieve fast scenario matching, enabling rich, real-time feedback in emergencies in buildings with meagre sensing capabilities.