Early diagnosis of disorders based on behavioural shifts and biomedical signals

There are many disorders that directly affect people’s behaviour. The people that are suffering from such a disorder are not aware of their situation, and too often the disorders are identified by relatives or co-workers because they notice behavioural shifts. However, when these changes become noticeable, it is often too late and irreversible damages have already been produced. Early detection is the key to prevent severe health-related damages and healthcare costs, as well as to improve people’s quality of life. Nowadays, in full swing of ubiquitous computing paradigm, users’ behaviour patterns can be unobtrusively monitored by means of interactions with many electronic devices. The application of this technology for the problem at hand would lead to the development of systems that are able to monitor disorders’ onset and progress in an ubiquitous and unobtrusive way, thus enabling their early detection. Some attempts for the detection of specific disorders based on these technologies have been proposed, but a global methodology that could be useful for the early detection of a wide range of disorders is still missing. This thesis aims to fill that gap by presenting as main contribution a global screening methodology for the early detection of disorders based on unobtrusive monitoring of physiological and behavioural data. The proposed methodology is the result of a cross-case analysis between two individual validation scenarios: stress in the workplace and Alzheimer’s Disease (AD) at home, from which conclusions that contribute to each of the two research fields have been drawn. The analysis of similarities and differences between the two case studies has led to a complete and generalized definition of the steps to be taken for the detection of a new disorder based on ubiquitous computing.Jendearen portaeran eragin zuzena duten gaixotasun ugari daude. Hala ere, askotan, gaixotasuna pairatzen duten pertsonak ez dira euren egoerataz ohartzen, eta familiarteko edo lankideek identifikatu ohi dute berau jokabide aldaketetaz ohartzean. Portaera aldaketa hauek nabarmentzean, ordea, beranduegi izan ohi da eta atzerazeinak diren kalteak eraginda egon ohi dira. Osasun kalte larriak eta gehiegizko kostuak ekiditeko eta gaixoen bizi kalitatea hobetzeko gakoa, gaixotasuna garaiz detektatzea da. Gaur egun, etengabe zabaltzen ari den Nonahiko Konputazioaren paradigmari esker, erabiltzaileen portaera ereduak era diskretu batean monitorizatu daitezke, gailu teknologikoekin izandako interakzioari esker. Eskuartean dugun arazoari konponbidea emateko teknologi hau erabiltzeak gaixotasunen sorrera eta aurrerapena nonahi eta era diskretu batean monitorizatzeko gai diren sistemak garatzea ekarriko luke, hauek garaiz hautematea ahalbidetuz. Gaixotasun konkretu batzuentzat soluzioak proposatu izan dira teknologi honetan oinarrituz, baina metodologia orokor bat, gaixotasun sorta zabal baten detekzio goiztiarrerako erabilgarria izango dena, oraindik ez da aurkeztu. Tesi honek hutsune hori betetzea du helburu, mota honetako gaixotasunak garaiz hautemateko, era diskretu batean atzitutako datu fisiologiko eta konportamentalen erabileran oinarritzen den behaketa sistema orokor bat proposatuz. Proposatutako metodologia bi balidazio egoera desberdinen arteko analisi gurutzatu baten emaitza da: estresa lantokian eta Alzheimerra etxean, balidazio egoera bakoitzari dagozkion ekarpenak ere ondorioztatu ahal izan direlarik. Bi kasuen arteko antzekotasun eta desberdintasunen analisiak, gaixotasun berri bat nonahiko konputazioan oinarrituta detektatzeko jarraitu beharreko pausoak bere osotasunean eta era orokor batean definitzea ahalbidetu du

Remote Assessment of the Cardiovascular Function Using Camera-Based Photoplethysmography

Camera-based photoplethysmography (cbPPG) is a novel measurement technique that allows the continuous monitoring of vital signs by using common video cameras. In the last decade, the technology has attracted a lot of attention as it is easy to set up, operates remotely, and offers new diagnostic opportunities. Despite the growing interest, cbPPG is not completely established yet and is still primarily the object of research. There are a variety of reasons for this lack of development including that reliable and autonomous hardware setups are missing, that robust processing algorithms are needed, that application fields are still limited, and that it is not completely understood which physiological factors impact the captured signal. In this thesis, these issues will be addressed. A new and innovative measuring system for cbPPG was developed. In the course of three large studies conducted in clinical and non-clinical environments, the system’s great flexibility, autonomy, user-friendliness, and integrability could be successfully proven. Furthermore, it was investigated what value optical polarization filtration adds to cbPPG. The results show that a perpendicular filter setting can significantly enhance the signal quality. In addition, the performed analyses were used to draw conclusions about the origin of cbPPG signals: Blood volume changes are most likely the defining element for the signal's modulation. Besides the hardware-related topics, the software topic was addressed. A new method for the selection of regions of interest (ROIs) in cbPPG videos was developed. Choosing valid ROIs is one of the most important steps in the processing chain of cbPPG software. The new method has the advantage of being fully automated, more independent, and universally applicable. Moreover, it suppresses ballistocardiographic artifacts by utilizing a level-set-based approach. The suitability of the ROI selection method was demonstrated on a large and challenging data set. In the last part of the work, a potentially new application field for cbPPG was explored. It was investigated how cbPPG can be used to assess autonomic reactions of the nervous system at the cutaneous vasculature. The results show that changes in the vasomotor tone, i.e. vasodilation and vasoconstriction, reflect in the pulsation strength of cbPPG signals. These characteristics also shed more light on the origin problem. Similar to the polarization analyses, they support the classic blood volume theory. In conclusion, this thesis tackles relevant issues regarding the application of cbPPG. The proposed solutions pave the way for cbPPG to become an established and widely accepted technology

Biomedical Engineering

Biomedical engineering is currently relatively wide scientific area which has been constantly bringing innovations with an objective to support and improve all areas of medicine such as therapy, diagnostics and rehabilitation. It holds a strong position also in natural and biological sciences. In the terms of application, biomedical engineering is present at almost all technical universities where some of them are targeted for the research and development in this area. The presented book brings chosen outputs and results of research and development tasks, often supported by important world or European framework programs or grant agencies. The knowledge and findings from the area of biomaterials, bioelectronics, bioinformatics, biomedical devices and tools or computer support in the processes of diagnostics and therapy are defined in a way that they bring both basic information to a reader and also specific outputs with a possible further use in research and development

Advanced Signal Processing in Wearable Sensors for Health Monitoring

Smart, wearables devices on a miniature scale are becoming increasingly widely available, typically in the form of smart watches and other connected devices. Consequently, devices to assist in measurements such as electroencephalography (EEG), electrocardiogram (ECG), electromyography (EMG), blood pressure (BP), photoplethysmography (PPG), heart rhythm, respiration rate, apnoea, and motion detection are becoming more available, and play a significant role in healthcare monitoring. The industry is placing great emphasis on making these devices and technologies available on smart devices such as phones and watches. Such measurements are clinically and scientifically useful for real-time monitoring, long-term care, and diagnosis and therapeutic techniques. However, a pertaining issue is that recorded data are usually noisy, contain many artefacts, and are affected by external factors such as movements and physical conditions. In order to obtain accurate and meaningful indicators, the signal has to be processed and conditioned such that the measurements are accurate and free from noise and disturbances. In this context, many researchers have utilized recent technological advances in wearable sensors and signal processing to develop smart and accurate wearable devices for clinical applications. The processing and analysis of physiological signals is a key issue for these smart wearable devices. Consequently, ongoing work in this field of study includes research on filtration, quality checking, signal transformation and decomposition, feature extraction and, most recently, machine learning-based methods

Annual Report of the University, 1992-1993, Volumes 1-4

SIGNIFICANT DEVELOPMENTS Preparation, approval by President Peck, delivery to NMCHE of UNM\u27s response to House Memorials 38 and 25 (on minorities and women). Development and packaging of a presentation on minorities at UNM to Hispanic community people and organizations. Renewal of faculty instructional workload report and other information for use by President Peck and others in the President\u27s Council in testimony to the legislature on accountability by faculty. Significant workload and contributions to WICHE\u27s Diversity Project: - responses to long questionnaire - projected demographics - substitution for O. Forbes on planning for diversity Reprogramming of obsolete computer program of the University of Southern California\u27s Faculty Planning Model. Work remains incomplete. Support and staff work for University Planning Council, Faculty Senate Long Range Planning Committee, Senate President, Senate Budget Committee, Student Learning Outcomes Assessment Committee, Admissions and Registration Committee, Staff Council; Graduate Petition and grade Review Subcommittee Service to NMCHE\u27s Outcomes Assessment Advisory Group; NMCHE\u27s review group on diversity plans Service on Albuquerque Business/Education Compact Conducted several special data analyses to provide user outcome information for the Center for Academic Program Support (CAPS). Wrote reports to summarize analyses. Served in an advisory capacity to VP Zuniga Forbes for the two surveys (Campus Climate for Diversity, ACT Student Opinion Survey) and helped to draw the sample for the ACT survey. Conducted secondary analyses and prepared report of all analyses of the Freshman Survey (CIRP) for VP Zuniga Forbes. Gave presentation of CIRP findings to the Regents Subcommittee on Student Affairs. Conducted secondary analyses and prepared report of all analyses of the Campus Climate for Diversity Survey for VP Zuniga Forbes