Multidimensional embedded MEMS motion detectors for wearable mechanocardiography and 4D medical imaging

Background: Cardiovascular diseases are the number one cause of death. Of these deaths, almost 80% are due to coronary artery disease (CAD) and cerebrovascular disease. Multidimensional microelectromechanical systems (MEMS) sensors allow measuring the mechanical movement of the heart muscle offering an entirely new and innovative solution to evaluate cardiac rhythm and function. Recent advances in miniaturized motion sensors present an exciting opportunity to study novel device-driven and functional motion detection systems in the areas of both cardiac monitoring and biomedical imaging, for example, in computed tomography (CT) and positron emission tomography (PET). Methods: This Ph.D. work describes a new cardiac motion detection paradigm and measurement technology based on multimodal measuring tools — by tracking the heart’s kinetic activity using micro-sized MEMS sensors — and novel computational approaches — by deploying signal processing and machine learning techniques—for detecting cardiac pathological disorders. In particular, this study focuses on the capability of joint gyrocardiography (GCG) and seismocardiography (SCG) techniques that constitute the mechanocardiography (MCG) concept representing the mechanical characteristics of the cardiac precordial surface vibrations. Results: Experimental analyses showed that integrating multisource sensory data resulted in precise estimation of heart rate with an accuracy of 99% (healthy, n=29), detection of heart arrhythmia (n=435) with an accuracy of 95-97%, ischemic disease indication with approximately 75% accuracy (n=22), as well as significantly improved quality of four-dimensional (4D) cardiac PET images by eliminating motion related inaccuracies using MEMS dual gating approach. Tissue Doppler imaging (TDI) analysis of GCG (healthy, n=9) showed promising results for measuring the cardiac timing intervals and myocardial deformation changes. Conclusion: The findings of this study demonstrate clinical potential of MEMS motion sensors in cardiology that may facilitate in time diagnosis of cardiac abnormalities. Multidimensional MCG can effectively contribute to detecting atrial fibrillation (AFib), myocardial infarction (MI), and CAD. Additionally, MEMS motion sensing improves the reliability and quality of cardiac PET imaging.Moniulotteisten sulautettujen MEMS-liiketunnistimien käyttö sydänkardiografiassa sekä lääketieteellisessä 4D-kuvantamisessa Tausta: Sydän- ja verisuonitaudit ovat yleisin kuolinsyy. Näistä kuolemantapauksista lähes 80% johtuu sepelvaltimotaudista (CAD) ja aivoverenkierron häiriöistä. Moniulotteiset mikroelektromekaaniset järjestelmät (MEMS) mahdollistavat sydänlihaksen mekaanisen liikkeen mittaamisen, mikä puolestaan tarjoaa täysin uudenlaisen ja innovatiivisen ratkaisun sydämen rytmin ja toiminnan arvioimiseksi. Viimeaikaiset teknologiset edistysaskeleet mahdollistavat uusien pienikokoisten liiketunnistusjärjestelmien käyttämisen sydämen toiminnan tutkimuksessa sekä lääketieteellisen kuvantamisen, kuten esimerkiksi tietokonetomografian (CT) ja positroniemissiotomografian (PET), tarkkuuden parantamisessa. Menetelmät: Tämä väitöskirjatyö esittelee uuden sydämen kineettisen toiminnan mittaustekniikan, joka pohjautuu MEMS-anturien käyttöön. Uudet laskennalliset lähestymistavat, jotka perustuvat signaalinkäsittelyyn ja koneoppimiseen, mahdollistavat sydämen patologisten häiriöiden havaitsemisen MEMS-antureista saatavista signaaleista. Tässä tutkimuksessa keskitytään erityisesti mekanokardiografiaan (MCG), joihin kuuluvat gyrokardiografia (GCG) ja seismokardiografia (SCG). Näiden tekniikoiden avulla voidaan mitata kardiorespiratorisen järjestelmän mekaanisia ominaisuuksia. Tulokset: Kokeelliset analyysit osoittivat, että integroimalla usean sensorin dataa voidaan mitata syketiheyttä 99% (terveillä n=29) tarkkuudella, havaita sydämen rytmihäiriöt (n=435) 95-97%, tarkkuudella, sekä havaita iskeeminen sairaus noin 75% tarkkuudella (n=22). Lisäksi MEMS-kaksoistahdistuksen avulla voidaan parantaa sydämen 4D PET-kuvan laatua, kun liikeepätarkkuudet voidaan eliminoida paremmin. Doppler-kuvantamisessa (TDI, Tissue Doppler Imaging) GCG-analyysi (terveillä, n=9) osoitti lupaavia tuloksia sydänsykkeen ajoituksen ja intervallien sekä sydänlihasmuutosten mittaamisessa. Päätelmä: Tämän tutkimuksen tulokset osoittavat, että kardiologisilla MEMS-liikeantureilla on kliinistä potentiaalia sydämen toiminnallisten poikkeavuuksien diagnostisoinnissa. Moniuloitteinen MCG voi edistää eteisvärinän (AFib), sydäninfarktin (MI) ja CAD:n havaitsemista. Lisäksi MEMS-liiketunnistus parantaa sydämen PET-kuvantamisen luotettavuutta ja laatua

Reducing the Risk: Psychological and Technological Approaches for Improving Handwashing Practices in the Foodservice Industry

As Americans are spending greater portions of their dollar on food consumed outside the home, the foodservice industry plays more of an integral part of daily existence compared to previous generations. Given the numerous annual foodborne illness outbreaks that threaten human lives while undermining confidence in the food supply, food safety is a pertinent issue for industry stakeholders, government regulators, and consumers. Food worker handwashing reduces the risk of foodborne illness transmission, yet compliance with this simple behavior is a complex problem. This dissertation addresses, predominantly, the issue of sub-optimal handwashing practices through applying psychology and technology, including wearable computers and a video game. Chapter one discusses prior efforts to improve handwashing compliance, while providing a theoretical framework to guide industry professionals through strategies that consider the potentially negative psychological effects of interventions on employees. Chapter two highlights handwashing practices of early childhood center food handlers. While average compliance was 22%, strict adherence to the guidelines would have required 12 minutes/hour devoted to handwashing. Chapter three explores handwashing in relation to organizational climate factors; managerial commitment was the only significant predictor of handwashing. Chapter four shows wearable technology-based training is preferred by food handlers. Chapter five indicates how participants who viewed strictly video-based training were four times as likely to wash hands compared to participants trained with smart glasses. Chapter six highlights the efficiency of handwashing training with smart glasses. Chapter seven includes the design and development of a video game played while washing hands. Perceptions of the device were only slightly positive, showing the need for either improved reward mechanisms or alternative strategies to motivate handwashing. Chapter eight evaluates the relationship between risk classification of foodservice establishments and food safety violation rates. High priority facilities had significantly higher food safety violation rates compared to medium and low priority facilities. In looking to the future of foodservice, many jobs are highly susceptible to automation; emotional intelligence may translate to greater job security in the coming years. Chapter nine evaluated perceptions of job insecurity rendered by automation in relation to emotional intelligence. There was no correlation between the two variables

School performance and undetected and untreated visual problems in schoolchildren in Ireland; a population-based cross-sectional study

This study explored the association between children’s vision and their school academic progress as reported by parents/guardians. Participants were 1,612 schoolchildren (722 6-7-year-olds, 890 12-13-year-olds) in randomly selected schools in Ireland. In advance of data collection, parents/guardians reported school performance as (a) much better than classmates (high-performance) (b) about the same as classmates (average-performance) (c) not as well as classmates (low-performance). Measurements included logMAR monocular visual acuities (with spectacles if worn, and pinhole) in the distance (3 m) and near (40 cm); the amplitude of accommodation; stereoacuity, colour vision assessment, and cyclopleged autorefraction. Controlling for confounders, children presenting with visual impairment (vision poorer than 0.3logMAR (6/12) in the ‘better eye’), amblyopia (‘lazy eye’), uncorrected refractive error (hyperopia ≥+3.50D and astigmatism ≥1.50DC), reduced for age ability to adjust focus from distance to near tasks (accommodation), impaired three-dimensional vision (stereoacuity), and defective colour vision were more likely to report low-performance in school. The majority of low-performing participants (68%) did not have an eye examination within the 12 months before data collection. Children with academic performance challenges ought to have a comprehensive eye examination, to detect potential vision problems for early intervention minimising any negative impact they may have on educational outcomes

To Make the World Smarter and Safer

To Make the World Smarter and Safer: Матеріали XIII всеукраїнської науково-практичної конференції студентів, аспірантів та викладачів Лінгвістичного навчально-методичного центру кафедри іноземних мов СумДУ 28 березня 2019 р

Proceedings of the 1st joint workshop on Smart Connected and Wearable Things 2016

These are the Proceedings of the 1st joint workshop on Smart Connected and Wearable Things (SCWT'2016, Co-located with IUI 2016). The SCWT workshop integrates the SmartObjects and IoWT workshops. It focusses on the advanced interactions with smart objects in the context of the Internet-of-Things (IoT), and on the increasing popularity of wearables as advanced means to facilitate such interactions