330 research outputs found

    Wearable Sensors as a Preoperative Assessment Tool: A Review

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    Surgery is a common first-line treatment for many types of disease, including cancer. Mortality rates after general elective surgery have seen significant decreases whilst postoperative complications remain a frequent occurrence. Preoperative assessment tools are used to support patient risk stratification but do not always provide a precise and accessible assessment. Wearable sensors (WS) provide an accessible alternative that offers continuous monitoring in a non-clinical setting. They have shown consistent uptake across the perioperative period but there has been no review of WS as a preoperative assessment tool. This paper reviews the developments in WS research that have application to the preoperative period. Accelerometers were consistently employed as sensors in research and were frequently combined with photoplethysmography or electrocardiography sensors. Pre-processing methods were discussed and missing data was a common theme; this was dealt with in several ways, commonly by employing an extraction threshold or using imputation techniques. Research rarely processed raw data; commercial devices that employ internal proprietary algorithms with pre-calculated heart rate and step count were most commonly employed limiting further feature extraction. A range of machine learning models were used to predict outcomes including support vector machines, random forests and regression models. No individual model clearly outperformed others. Deep learning proved successful for predicting exercise testing outcomes but only within large sample-size studies. This review outlines the challenges of WS and provides recommendations for future research to develop WS as a viable preoperative assessment tool

    Desarrollo de nuevos dispositivos y algoritmos para la monitorización ambulatoria de personas con epilepsia

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    La epilepsia es una enfermedad crónica con un enorme impacto sociosanitario. Aunque en la actualidad se dispone de una gran cantidad de fármacos antiepilépticos y de otros tratamientos más selectivos como la cirugía o la estimulación cerebral, un porcentaje considerable de pacientes no están controlados y continúan teniendo crisis epilépticas. Estas personas suelen vivir condicionadas por la posibilidad de un ataque epiléptico y sus posibles consecuencias, como accidentes, lesiones o incluso la muerte súbita inexplicable. En este contexto, un dispositivo capaz de monitorizar el estado de salud y avisar de un posible ataque epiléptico contribuiría a mejorar la calidad de vida de estas personas. La presente Tesis Doctoral se centra en el desarrollo de un novedoso sistema de monitorización ambulatoria que permita identificar y predecir los ataques epilépticos. Dicho sistema está compuesto por diferentes sensores capaces de registrar de forma sincronizada diferentes señales biomédicas. Mediante técnicas de aprendizaje automático supervisado, se han desarrollado diferentes modelos predictivos capaces de clasificar el estado de la persona epiléptica en normal, preictal (antes de la crisis) e ictal (crisis)

    The 2023 wearable photoplethysmography roadmap

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    Photoplethysmography is a key sensing technology which is used in wearable devices such as smartwatches and fitness trackers. Currently, photoplethysmography sensors are used to monitor physiological parameters including heart rate and heart rhythm, and to track activities like sleep and exercise. Yet, wearable photoplethysmography has potential to provide much more information on health and wellbeing, which could inform clinical decision making. This Roadmap outlines directions for research and development to realise the full potential of wearable photoplethysmography. Experts discuss key topics within the areas of sensor design, signal processing, clinical applications, and research directions. Their perspectives provide valuable guidance to researchers developing wearable photoplethysmography technology

    30th European Congress on Obesity (ECO 2023)

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    This is the abstract book of 30th European Congress on Obesity (ECO 2023

    The Omics basis of human health: investigating plasma proteins and their genetic effects on complex traits

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    Over the past decade, the advancements in technology and the growing amount of identified genetic variants have led to a high number of important discoveries in the field of precision medicine concerning human biology and pathophysiology. However, it became evident that genomics alone could not properly explain the onset and regulation of the specific molecular mechanisms of certain phenotypes. Studying omics helped complement this gap in genetic research, providing detailed information on the quantification of molecules that are involved in structural and functional processes in the organism. Specifically, protein production, levels, and regulation are dynamic and change during the course of one’s lifetime. This information has proven fundamental to understanding how certain proteins affect complex phenotypes such as neurological and psychiatric disorders. In this thesis, I describe the three groups of analyses I conducted over the course of my doctoral programme on different sets of blood plasma proteins and over a broad range of neurological, psychiatric, cardiovascular, and electrophysiology phenotypes. The underlying mechanisms that trigger the onset of psychiatric and neurological conditions are often not limited to the nervous system, but rather stem from multi-system molecular triggers. The first part of the work I carried out aims at investigating the frequent co-occurrence and comorbidity of neurological and cardiovascular phenotypes by conducting a genome-wide association (GWA) meta-analysis of 183 neurology-related blood proteins on data from over 12000 individuals. The second part concerns the bivariate and multivariate analyses conducted on 276 cardiology and inflammatory proteins, while the third illustrates the contribution to consortia focussed on heart rate and electrophysiology. Results from the second and third parts of the work provided information that played an important role in understanding a part of the genetic mechanisms of the complex traits of interest. Overall, the results presented in this thesis strongly support the notion that proteomics is an important tool to be used to study complex traits and drug discovery and development should focus on targeting protein synthesis and regulation. Furthermore, the results also support the notion that complex diseases involve more than one biological system, and in order to gain a better understanding of human pathology, it is fundamental to study the causes and effects across the entire organism

    Investigating different approaches and analyses of psychological variables to enhance sport and exercise

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    This thesis addresses the acquisition of knowledge through a logical step by step process during the PhD course, highlighting five research activities with a main focus on sport and exercise psychology. The ultimate goal for research looked at exploring wearable devices and associated digital technology to deliver interventions aimed to increase exercise while measuring psychological variables such as stress. A foundation was initially set with a systematic review and meta-analysis on correlations between physical activity and key variables such as self-efficacy, self-regulation, and anxiety measured using validated questionnaires. A continued interest in exploring psychometric tools and their validation in sport drove the analysis of a motivation scales and related parameters in a cohort of Italian rugby players. With the beginning of the COVID-19 pandemic, however, community-based sports activities stopped, and the way in which exercise was performed and measured rapidly changed, as I highlighted in the report “Physical activity: Benefits and challenges during the COVID-19 pandemic”. In this unexpected scenario, government agencies as well as private entities and academic institutions applied digital technology to deliver health and wellbeing messages. The use of novel tools was beneficial while facing increased sedentarism occurring during restrictions and lock-down periods. The study performed, involving office workers and electronically delivering exercise interventions in the form of active breaks, showed improvement in wellbeing and stress reduction. Finally, the last study presented can be viewed as a marker in time, as people return to normality, exercising and performing their normal routine but with a new emphasis in keeping track of their own health and wellbeing through wearable technology, following the change in measuring physical and psychological variables consolidated during the pandemic. The results met the intended goal to successfully provide a message-based, digitally delivered intervention aimed at increasing exercise and reducing stress among university students, using wearables to measure the outcome. Moreover, the comparison of wearable-associated stress (based on physiological stimuli) with self-reported stress using a validated questionnaire (e.g., Perceived Stress Scale-10) showed a promising connection. I intend to continue in this direction to further explore benefits and limitations of digital technology in sport and exercise psychology

    Algorithms for automated diagnosis of cardiovascular diseases based on ECG data: A comprehensive systematic review

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    The prevalence of cardiovascular diseases is increasing around the world. However, the technology is evolving and can be monitored with low-cost sensors anywhere at any time. This subject is being researched, and different methods can automatically identify these diseases, helping patients and healthcare professionals with the treatments. This paper presents a systematic review of disease identification, classification, and recognition with ECG sensors. The review was focused on studies published between 2017 and 2022 in different scientific databases, including PubMed Central, Springer, Elsevier, Multidisciplinary Digital Publishing Institute (MDPI), IEEE Xplore, and Frontiers. It results in the quantitative and qualitative analysis of 103 scientific papers. The study demonstrated that different datasets are available online with data related to various diseases. Several ML/DP-based models were identified in the research, where Convolutional Neural Network and Support Vector Machine were the most applied algorithms. This review can allow us to identify the techniques that can be used in a system that promotes the patient’s autonomy.N/

    Measuring blood flow and pulsatility with MRI: optimisation, validation and application in cerebral small vessel disease

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    Cerebral small vessel disease (SVD) is the breakdown of the small blood vessels of the brain, leading to many cases of stroke and dementia. The pathophysiology of SVD is largely unknown, although several mechanisms have been suggested. One such mechanism is the role of increased blood flow pulsatility into the brain, caused by vessel stiffening, leading to damage of the microvasculature. Magnetic resonance imaging (MRI) allows us to non-invasively measure blood flow and velocity using a technique called phase contrast-MRI – traditionally used with 2D slices across the vessel(s) of interest. An advanced form of phase-contrast MRI, known as 4D flow, has emerged in recent years that allows for a volume of data to be acquired, containing velocity information in all directions. However, to keep scan times practical when collecting this amount of data, spatiotemporal resolution has to be sacrificed. The main aim of this thesis was to assess 4D flow’s capabilities, including comparing it to the more well-established 2D method in healthy volunteers, patients, and phantom experiments, so as to better understand its role in investigating SVD. Another aim was to learn more about the role of flow and pulsatility in SVD development in patients using data acquired in the longitudinal Mild Stroke Study 3 (MSS3). Firstly, I systematically reviewed studies that have assessed the human brain using 4D flow. Across 61 relevant studies, I found a general consensus for the current use of the technique in this context. I then optimised the Siemens prototype 4D flow sequence (N = 11 healthy volunteers), testing different parameters to find the combination that best balanced scan quality and duration. I then assessed the test-retest repeatability and intra-rater reliability of both 2D and 4D methods (N = 11 healthy volunteers), as well as differences between them. Following this, I performed the same 4D-2D comparison on SVD patients (N = 10). Absolute flow measurements using 4D flow were shown to have moderate repeatability and reliability, while flow pulsatility measurements showed acceptable repeatability and reliability. Furthermore, 2D arterial pulsatility was measured higher than with 4D, while 4D often measured higher flow rates than 2D. 4D flow was shown to be feasible when used on SVD patients, with no noticeable issues caused by potential patient movement. Flow data analysis from the longitudinal SVD study MSS3 showed that intracranial pulsatility is associated with cross-sectional SVD lesion volume but not longitudinal lesion growth, with stronger associations seen in the arteries of the neck compared to the venous sinuses

    Improving passive driver fatigue, sitting health risk factors and user experience in automobiles. Conception, development and evaluation of a novel interactive seating system

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    Lange Fahrten in Automobilen werden oftmals von monotoniebedingter Ermüdung durch mangelnde Stimulation sowie körperlichen Gesundheitsrisiken durch langanhaltendes Sitzen begleitet. In der Literatur werden kognitive Zusatzaufgaben als Maßnahme gegen monotoniebedingte Ermüdung vorgeschlagen. Der Stand der Technik um gesundheitliche Risiken durch langanhaltendes Sitzen im Fahrzeug zu reduzieren, beschränkt sich hauptsächlich auf Sitzsysteme, welche die Passagiere passiv mobilisieren. Mit dem Ziel die Fahrsicherheit zu erhöhen und gleichzeitig Gesundheitsrisiken zu reduzieren, wurde ein neuartiges interaktives Sitzsystem (IASS) konzipiert, entwickelt und evaluiert. Das IASS soll den Fahrer/die Fahrerin oder die Passagiere dazu motivieren mit dem Sitz zu interagieren und dabei aktive Bewegungen gegen die Sitzfläche auszuführen. Im Gegensatz zu aktuellen interaktiven Sitzsystemen erfolgt die grundlegende Interaktion nicht über ein Display. Stattdessen werden auditive Einsprachen, Luftblasen in der Lehne, Vibrationsmotoren sowie die Ambientebeleuchtung genutzt. Ein Display kommt lediglich bei der Einführung in die Nutzung des Systems oder ergänzend für die Passagiere zum Einsatz. Das ermöglicht, dass der Fahrer/die Fahrerin den Blick und damit auch die Aufmerksamkeit auf der Straße behalten kann. Dadurch soll das System, im Gegensatz zum Stand der Technik, nicht nur für die Passagiere, sondern auch für den Fahrer/die Fahrerin geeignet sein. Das wiederum eröffnet die Möglichkeit das IASS als Zusatzaufgabe neben dem Fahren zu nutzen, um einer momotoniebedingten Reduktion der Aufmerksamkeit entgegenzuwirken. Dabei ist anzumerken, dass die erhöhte Fahrsicherheit durch eine verbesserte Aufmerksamkeit nicht nur den Insassen, sondern auch den anderen Verkehrsteilnehmern dient. Gleichzeitig haben alle Passagiere die Möglichkeit, durch die physiologisch sinnvollen Bewegungen gegen den Sitz, die Gesundheitsrisiken durch langanhaltendes Sitzen zu reduzieren. Insgesamt wurden drei Probandenstudien durchgeführt, um das IASS zu entwickeln und zu evaluieren. Die erste Probandenstudie diente der Entwicklung des IASS. Um die Bewegungen des Passagiers/der Passagierin bei der Interaktion zu detektieren, wurden Drucksensoren in der Sitzlehne integriert. Zur Gewährleistung einer zuverlässigen Bewegungserkennung von Passagieren mit unterschiedlichen anthropometrischen Merkmalen, war es entscheidend, die Sensoren an optimalen Positionen in der Lehne zu platzieren. Daher war der erste Schritt im Entwicklungsprozess des IASS die Durchführung einer Probandenstudie, um diese optimalen Positionen festzulegen. Im Rahmen der Studie wurden Sitzdruckverteilungsbilder erfasst und anschließend mit einer Methode, dem Statistical Parametric Mapping ausgewertet, die für gewöhnlich bei der funktionellen Magnetresonanztomographie eingesetzt wird. In der vorliegenden Arbeit wurde diese Methode erstmalig zur Auswertung von Sitzdruckverteilungen herangezogen. Der Vorteil gegenüber herkömmlichen Methoden ist die hohe örtliche Auflösung. Damit war es möglich, die Sensoranbringungspunkte sehr präzise zu definieren. Anschließend wurde das IASS auf Basis der in der ersten Studie gewonnenen Information aufgebaut und anschließend in zwei weiteren Probandenstudien mit einem aktuellen Sitzmassagesystem (MS) hinsichtlich Wirksamkeit verglichen. In der zweiten Probandestudie sollte das Potential des IASS für die Fahrsicherheit bewertet werden. Die im Fahrsimulator durchgeführte Studie zeigte, dass das IASS die monotoniebedingte Ermüdung reduzierte, während dieser Effekt bei Nutzung des MS nicht auftrat. Das IASS wurde ebenfalls bezüglich des Nutzererlebnisses sowie der emotionalen Wahrnehmung gegenüber dem MS bevorzugt. Außerdem bewerteten die Probanden und Probandinnen, dass das IASS im Vergleich zum MS, sowohl Komfort wesentlich stärker erhöhte als auch Diskomfort stärker reduzierte. In der dritten und abschließenden Probandenstudie wurde untersucht, ob das IASS den körperlichen Gesundheitsrisiken durch langanhaltendes Sitzen besser entgegen wirkt als das MS. Hierfür wurden beide Sitzsysteme in einem Serienfahrzeug verbaut. Um die Effekte beider Sitzsysteme zu vergleichen, wurden gesundheitsrelevante Parameter erfasst. Damit fahrtbedingte Signalstörungen ausgeschlossen werden konnten, wurde die Studie im stehenden Fahrzeug durchgeführt. Das Elektrokardiogramm zeigte, dass ausschließlich das IASS die Herzfrequenz erhöhte. Elektromyographische Messungen zeigten außerdem, dass das IASS die Aktivität in den sechs erfassten Muskeln erhöhte, während beim MS lediglich ein Muskel eine Tendenz zur Aktivitätserhöhung zeigte. Entsprechend sind die gesundheitsfördernden Effekte des IASS im Vergleich zum MS als wesentlich stärker einzustufen. Nach dem Kenntnisstand des Autors, ist dies die erste wissenschaftliche Publikation welche eine motorische Zusatzaufgabe als Maßnahme gegen monotoniebedingte Ermüdung im Fahrzeug untersucht. Darüber hinaus wurde erstmalig direkt verglichen, ob ein automobiles Sitzsystem welches zu aktiven Bewegungen animiert, einem System das die Passagiere passiv bewegt, hinsichtlich der Reduktion der negativen körperlichen Effekte des Sitzens überlegen ist
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