Using Capacitance Sensor to Extract Characteristic Signals of Dozing from Skin Surface

Skin is the largest organ of the human body and a physiological structure that is directly exposed to the environment. From a theoretical perspective, numerous physiological and psychological signals use the skin as a medium for input and output with the outside world. Therefore, the skin is considered an optimal signal interception point when developing noninvasive, direct, and rapid signal exploration devices. To date, skin signal interceptions are predominantly performed by measuring skin impedance. However, this method is prone to interference such as sweat secretion, salt accumulation on the skin, and muscle contractions, which may result in a substantial amount of interference and erroneous results. The present study proposes novel and effective methods for skin signal interception, such as using a nested probe as a sensor to measure capacitance to be further processed as physiological and psychological signals. The experimental results indicate that the capacitance curve for the transition between wakefulness and dozing exhibits significant changes. This change in the curve can be analyzed by computer programs to clearly and rapidly determine whether the subject has entered the initial phases of sleep

SSR verilerinin YSA ile işlenerek psikolojik test skorlarının sınıflandırılması

06.03.2018 tarihli ve 30352 sayılı Resmi Gazetede yayımlanan “Yükseköğretim Kanunu İle Bazı Kanun Ve Kanun Hükmünde Kararnamelerde Değişiklik Yapılması Hakkında Kanun” ile 18.06.2018 tarihli “Lisansüstü Tezlerin Elektronik Ortamda Toplanması, Düzenlenmesi ve Erişime Açılmasına İlişkin Yönerge” gereğince tam metin erişime açılmıştır.Günümüzde biyolojik işaretlerin hastalık teşhisinde kullanılması yaygınlaşmaktadır. Vücuttan ölçülerek alınan sempatik deri yanıtı da günümüzde kullanılmaya başlanan biyolojik işaretlerden biridir. Biyolojik işaretlerin incelenmesi için günümüzde kullanılan birçok yöntem vardır. Bunlar içinde yapay sinir ağları (YSA) çok yaygın olarak kullanılmaktadır. Bu çalışmada da elde edilen veriler YSA ile analiz edilmiştir.Fibromiyalji sendromu teşhisi zor bir kronik ağrı hastalığıdır. Psikolojik testler yardımıyla %100 doğruluk oranı olmadan teşhis yapılmaya çalışılır. Hastalığın teşhisinde kullanılan psikolojik test skorları tam güvenirlilik sağlamamaktadır. Fibromiyalji sendromu otonom sinir sistemine bağlı bir hastalıktır. Sempatik deri yanıtı da otonom sinir sistemindeki değişikliklerden etkilenmektedir. Bu ilişkiden yola çıkarak psikolojik test skorlarının yerini alabilecek sempatik deri yanıtının doğruluk yüzdesinin hesaplanması amaçlanmıştır. Bu amaçla psikolojik test skorları YSA ile analiz edilmiş ve teşhis parametreleriyle aralarındaki ilişki doğruluk yüzdeleri hesaplanmıştır.Bu çalışmada psikolojik test skorlarından Verbal ağrı skalası (VERBAL) ve Beck depresyon envanteri (BDI) kullanılmıştır. İki farklı eğitim algoritmasında YSA ile analiz yapılmıştır. Verbal ve BDI ile aralarındaki ilişkilerin tespiti için fizyolojik test verileri ve laboratuvar test verileri hem ayrı ayrı hem de birlikte analiz edilerek doğruluk yüzdeleri çıkartılmıştır. Daha sonra SSR parametreleri eklenerek SSR'nin etkisi incelenmiştir.Yapılan çalışmalar sonucunda Levenberg-Marquardt (LM) eğitim algoritması için SSR'nin arttırıcı etkisi olduğu tespit edilmiştir. Psikolojik test skorlarının yerine kullanılabilecek veriler göz önünde bulundurulurken SSR'nin de dikkate alınması gerektiği sonucuna varılmıştır.Nowadays, the use of biological signals for the diagnosis of the disease is spreading. Sympathetic skin response received from the body by measuring is one of the biological markers started to be used in the present. There are many methods used today for the examination of biological signals. Among these artificial neural networks (ANN) are very widely used. The data obtained from this study were analyzed by artificial neural network.Fibromyalgia syndrome is a chronic pain disorder which is difficult to diagnose. With the help of psychological tests, it is tried to diagnose without being 100% accuracy rate. Psychological test scores used in the diagnosis of the disease does not provide full reliability. Fibromyalgia syndrome is a disorder that depends on autonomic nervous system. Sympathetic skin response is also affected by the changes in the autonomic nervous system. Based on this relationship it is aimed at calculating of the percentage of accuracy of sympathetic skin response which can be replaced by psychological test scores. For this purpose, psychological test scores were analyzed by ANN and the percentage of accuracy of relationship with diagnostic parameters was calculated.In this study, from psychological testing scores, verbal pain scale scores (verbal) and the Beck depression inventory (BDI) were used. It was analyzed by ANN in two different training algorithms. For the determination of relationship between verbal and BDI, the percentages of accuracy of physiological test data and laboratory test data were revealed by analyzing both separately and together. Then, by adding the SSR parameters, the effect of SSR was investigated.As a result of the studies, it has been found that SSR has an additive effect on Levenberg-Marquardt (LM) training algorithm. It is concluded that SSR has to be taken into consideration while the data used instead of psychological test scores are being considered

Genetics and Etiology of Down Syndrome

This book provides a concise yet comprehensive source of current information on Down syndrome. Research workers, scientists, medical graduates and paediatricians will find it an excellent source for reference and review. This book has been divided into four sections, beginning with the Genetics and Etiology and ending with Prenatal Diagnosis and Screening. Inside, you will find state-of-the-art information on: 1. Genetics and Etiology 2. Down syndrome Model 3. Neurologic, Urologic, Dental & Allergic disorders 4. Prenatal Diagnosis and Screening Whilst aimed primarily at research workers on Down syndrome, we hope that the appeal of this book will extend beyond the narrow confines of academic interest and be of interest to a wider audience, especially parents and relatives of Down syndrome patients

Advanced Sensing and Image Processing Techniques for Healthcare Applications

This Special Issue aims to attract the latest research and findings in the design, development and experimentation of healthcare-related technologies. This includes, but is not limited to, using novel sensing, imaging, data processing, machine learning, and artificially intelligent devices and algorithms to assist/monitor the elderly, patients, and the disabled population

Social media narratives in non-communicable disease: their dynamics and value for patients, communities and health researchers

Background: Usage of social media is now widespread and growing, as is the number of people living with Non-Communicable Diseases (NCDs) such as diabetes and cancer. This thesis examines how social media are being used to share or discuss NCDs and the benefits, challenges and implications of these trends as a manifestation of digital public health. Aim and research questions: The aim of this research is to address the gap in empirical, evidence-based research into the secondary use of data from social media to understand patient health issues and inform public health research into NCDs. To this end, seven research questions, each linked to a sub-project, were defined and tested during the course of the six-year programme: 1.What is the status of the existing multi-disciplinary research literature based on analysis of data posted on social media for public health research, and where are the gaps in this research? 2.Can existing systematic review methods be re-purposed and applied to analyse data posted on social media? 3.How are research sponsors and researchers addressing the ethical challenges of analysing data posted on social media? 4.To what extent are diabetes-related posts on Twitter relevant to the clinical condition and what topics and intentions are represented in these posts? 5.In what ways do people affected by Type 1 diabetes use different social media (e.g. for social interaction, support-seeking, information-sharing) and what are the implications for researchers wishing to use these data sources in their studies? 6.Are these differences in platform usage and associated data types also seen in people affected by lung cancer? 7.Can characteristic illness trajectories be seen in a cancer patient’s digital narrative and what insights can be gained to inform palliative care services? Methods: A range of different qualitative and quantitative methods and frameworks were used to address each of the research questions listed. Arksey and O’Malley’s five-stage scoping review framework and the PRISMA guidelines are applied to the systematic scoping review of existing literature. The PRISMA guidelines and checklist are re-purposed and applied to the manual extraction and analysis of social media posts. Bjerglund-Andersen and Söderqvist’s typology of social media uses in research and Conway’s taxonomy of ethical considerations are used to classify the ethics guidelines available to researchers. The findings of these were used to inform the research design of the four empirical studies. The methods applied in the conduct of the empirical studies include a content and narrative analysis of cross-sectional and longitudinal data sourced from Twitter, Facebook, the Type 1 diabetes discussion forum on Diabetes.co.uk and the lung cancer discussion forum on Macmillan.org.uk, as well as the application of Bales’ Interaction Process Analysis and Emanuel and Emanuel’s framework for a good death. Results : Of the 49 systematic, quasi-systematic and scoping reviews identified, 24 relate to the secondary use of data from social media, with eight of these focused on infectious disease surveillance and only two on NCDs. Existing reviews tend to be fragmented, narrow in scope and siloed in different academic communities, with limited consideration of the different types of data, analytical methods and ethical issues involved, therefore creating a need for further reviews to synthesise the emerging evidence-base. The rapid increase in the volume of published research is evident, from the results of RQ1, with 87% of the eligible studies published between 2013-2017. Of the 105 eligible empirical studies that focused on NCDs, cancer (54%) and diabetes (20%) dominate the literature. Data is sourced from Twitter (26%), Facebook (14%) and blogs (10%), conducted, published and funded by the medical community. Since 2012, automated methods have increasingly been applied to extract and analyse large volumes of data. Those that use manual methods for extraction did not apply a consistent approach to doing so; the PRISMA guidelines and checklist were therefore re-purposed and applied to analyse data extracted from social media in response to RQ2. The deficit of ethical guidance available to inform research that involves social media data was also identified as a result of RQ3 and the guidelines provided by the ESRC, BPS, AoIR and NIHR were prioritised for the purposes of this research project. Results from the four empirical studies (RQ4-7) reveal that different forms of social interaction and support are represented in the variety of social media platforms available and that this is influenced by the type and nature of the condition with which people are affected, as well as the affordances offered by such platforms. In the pilot study associated with RQ4, Twitter was identified as a ‘noisy’ source of data about diabetes, with only 66% of the sample being relevant to the clinical condition. Twelve per cent of the eligible sample was associated with Type 2 diabetes, compared to 6% for Type 1, and most were information-giving in nature (49%) and correlated with the diagnosis, treatment and management of the condition (44%). A comparison of Twitter to the Type 1 Diabetes community on Facebook and the discussion forum on Diabetes.co.uk for RQ5 indicated that all three social media platforms were used to disseminate information about the condition. However, the Type 1 Diabetes Group on Facebook and the Type 1 discussion forum on Diabetes.co.uk were also used for social interaction and peer support, hence defying the generalisations made in public health studies, where social media platforms were often considered equal or synonymous. The results from the third empirical study into lung cancer (RQ6) support this, indicating that, by virtue of their digital architecture, user base and self-moderating communities, the Lung Cancer Support Group on Facebook and the lung cancer discussion forum on Macmillan.org.uk are more successful in their utility for social interaction and emotional and informational support. Meanwhile, the sample derived from Twitter hashtags showed greater companionship support. The final empirical study in this PhD research project is associated with RQ7 and used longitudinal data posted by a terminally ill patient on Twitter. This revealed that patient activity on social media mirrors the different phases of the end-of-life illness trajectory described in the literature and that it is comparable to or compliments insights garnered using more traditional qualitative research techniques. It also shows the value of such innovative methods for understanding how terminal disease is experienced by and affects individuals, how they cope, how support is sought and obtained and how patients feel about the ability of palliative care services to meet their needs at different stages. Conclusions: The analysis of health data posted on social media continues to be an expanding and evolving field of multi-disciplinary research. The results of the studies included in this thesis reveal the emergence of new methods and ethical considerations to inform research design as well as ethics policy. The re-purposed PRISMA guidelines and checklist were presented at the 2014 Medicine 2.0 Summit and World Congress whilst the review of ethical guidelines was published in the Research Ethics journal. The four empirical studies that extracted and analysed data from social media provide novel insight into the social narratives of those impacted by diabetes and cancer and can be used to inform future research and practice. The results of these studies have, to date, been presented at four international conferences and published in npj Digital Medicine and BMC Palliative Care. Although this thesis and associated publications contribute to an emerging body of knowledge, further research is warranted into the manual versus automated techniques that can be applied and the differences in social interaction and support needed by people affected by different NCDs

Vincristine-Induced Peripheral Neuropathy: Assessing Preventable Strategies in Paediatric Acute Lymphoblastic Leukaemia

Background: Acute Lymphoblastic Leukaemia is the most common cancer experienced by children with overall survival rates now exceeding 90%. However, most children will experience vincristine-induced peripheral neuropathy (VIPN) during treatment resulting in sensory-motor abnormalities. To date, there are no approved preventative therapeutics or mitigation strategies for VIPN. This body of work set out to: (1) establish a high-throughput and high-content assay with the capacity to identify neuroprotective compounds, (2) test the feasibility of repurposing olesoxime as a neuroprotectant, and (3) compare traditional statistical methods with machine learning models to identify patients at risk of VIPN. Methods: (1) In vitro neuronal cultures were exposed to vincristine to recapitulate the VIPN phenotype and olesoxime assessed as a positive control. The neurotoxicity assay was miniaturised in 384-well microplates with automation steps to reduce manual handling. (2) Olesoxime and vincristine were applied to proliferating malignant cell lines to ensure the efficacy of vincristine was maintained. (3) Machine learning algorithms were developed using data from a local retrospective cohort to predict VIPN. Results: (1) Neurite length was reduced in a dose-responsive manner with vincristine. Assay miniaturisation and automation steps helped facilitate a high-throughput workflow. An optimised multiplexed dye solution enabled image acquisition and neurite quantification. Further, olesoxime was found to protect neurites and deemed suitable as a positive control (2) Cell viability assays confirmed olesoxime did not interfere with vincristine efficacy in leukemia cells. (3) Machine learning algorithms showed equivalency to traditional univariate analysis. The observation of severe class imbalance meant that patients who were least susceptible to VIPN could be identified. Conclusions: This body of work demonstrates the successful development of a neurotoxicity assay suitable for neuroprotectant drug discovery. Olesoxime was found suitable as a positive control in the assay. Further, viability studies indicated that vincristine retains it efficacy with olesoxime, opening the possibility of its use as an adjunctive therapy. Finally, this work developed machine learning models with the capacity to identify patients with VIPN-free survival. The utility of this model may mean that it can be used to stratify patients prospectively in the clinic based on favourable clinical features

Case series of breast fillers and how things may go wrong: radiology point of view

INTRODUCTION: Breast augmentation is a procedure opted by women to overcome sagging breast due to breastfeeding or aging as well as small breast size. Recent years have shown the emergence of a variety of injectable materials on market as breast fillers. These injectable breast fillers have swiftly gained popularity among women, considering the minimal invasiveness of the procedure, nullifying the need for terrifying surgery. Little do they know that the procedure may pose detrimental complications, while visualization of breast parenchyma infiltrated by these fillers is also deemed substandard; posing diagnostic challenges. We present a case series of three patients with prior history of hyaluronic acid and collagen breast injections. REPORT: The first patient is a 37-year-old lady who presented to casualty with worsening shortness of breath, non-productive cough, central chest pain; associated with fever and chills for 2-weeks duration. The second patient is a 34-year-old lady who complained of cough, fever and haemoptysis; associated with shortness of breath for 1-week duration. CT in these cases revealed non thrombotic wedge-shaped peripheral air-space densities. The third patient is a 37‐year‐old female with right breast pain, swelling and redness for 2- weeks duration. Previous collagen breast injection performed 1 year ago had impeded sonographic visualization of the breast parenchyma. MRI breasts showed multiple non- enhancing round and oval shaped lesions exhibiting fat intensity. CONCLUSION: Radiologists should be familiar with the potential risks and hazards as well as limitations of imaging posed by breast fillers such that MRI is required as problem-solving tool

Primary Health Care

This book presents examples from various countries about the provision of health services at the primary care level. Chapters examine the role of professionals in primary healthcare services and how they can work to improve the health of individuals and communities. Written by authors from Africa, Asia, America, Europe, and Australia, this book provides up-to-date information on primary health care, including telehealth services in the era of COVID-19