24 research outputs found

    The motivational mechanisms driving the antidepressant effect of ketamine

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    Ketamine is a rapidly-acting antidepressant and has shown to be effective in depressed individuals who have previously failed to benefit from other available treatments. An important question is how ketamine works. Addressing this might help inform more targeted and efficient treatments in the future. The aim of this thesis was to examine the neural, cognitive, and computational mechanisms underpinning the antidepressant response to ketamine in treatment-resistant depression. The work has specifically focused on motivational processing, since ketamine is particularly effective in alleviating symptoms of anhedonia, which are thought to be related to impaired reward-related function. Following a general introduction (Chapter 1), the first experimental chapter (Chapter 2) focuses on identifying suitable reward and punishment tasks for repeated testing in a clinical trial. Test retest properties of various tasks are explored in healthy individuals, assessed by both traditional measures of task performance (e.g., accuracy) and computational parameters. Chapter 3 outlines a pilot simultaneous EEGfMRI study in healthy individuals probing the neural dynamics of the motivation to exert cognitive effort, an important but understudied process in depression. The third study (Chapter 4) uses resting-state fMRI to examine how ketamine modulates fronto-striatal circuitry, which is known to drive motivational behaviour, in depressed and healthy individuals. The final experimental chapter (Chapter 5) examines which cognitive and computational measures of motivational processing (using tasks identified in Chapter 2) change following a single dose of ketamine compared to placebo in depression, using a crossover design. Based on preliminary findings, it is tentatively proposed that ketamine might affect reward processing by enhancing fronto-striatal circuitry functional connectivity, as well as by increasing exploratory behaviours, and possibly punishment learning rates. The general discussion (Chapter 6) discusses these findings in relation to contemporary models of anhedonia and antidepressant action, considering both the limitations of the work presented and possible future directions

    Wearable and BAN Sensors for Physical Rehabilitation and eHealth Architectures

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    The demographic shift of the population towards an increase in the number of elderly citizens, together with the sedentary lifestyle we are adopting, is reflected in the increasingly debilitated physical health of the population. The resulting physical impairments require rehabilitation therapies which may be assisted by the use of wearable sensors or body area network sensors (BANs). The use of novel technology for medical therapies can also contribute to reducing the costs in healthcare systems and decrease patient overflow in medical centers. Sensors are the primary enablers of any wearable medical device, with a central role in eHealth architectures. The accuracy of the acquired data depends on the sensors; hence, when considering wearable and BAN sensing integration, they must be proven to be accurate and reliable solutions. This book is a collection of works focusing on the current state-of-the-art of BANs and wearable sensing devices for physical rehabilitation of impaired or debilitated citizens. The manuscripts that compose this book report on the advances in the research related to different sensing technologies (optical or electronic) and body area network sensors (BANs), their design and implementation, advanced signal processing techniques, and the application of these technologies in areas such as physical rehabilitation, robotics, medical diagnostics, and therapy

    Smart Sensors for Healthcare and Medical Applications

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    This book focuses on new sensing technologies, measurement techniques, and their applications in medicine and healthcare. Specifically, the book briefly describes the potential of smart sensors in the aforementioned applications, collecting 24 articles selected and published in the Special Issue “Smart Sensors for Healthcare and Medical Applications”. We proposed this topic, being aware of the pivotal role that smart sensors can play in the improvement of healthcare services in both acute and chronic conditions as well as in prevention for a healthy life and active aging. The articles selected in this book cover a variety of topics related to the design, validation, and application of smart sensors to healthcare

    The Impact of Digital Technologies on Public Health in Developed and Developing Countries

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    This open access book constitutes the refereed proceedings of the 18th International Conference on String Processing and Information Retrieval, ICOST 2020, held in Hammamet, Tunisia, in June 2020.* The 17 full papers and 23 short papers presented in this volume were carefully reviewed and selected from 49 submissions. They cover topics such as: IoT and AI solutions for e-health; biomedical and health informatics; behavior and activity monitoring; behavior and activity monitoring; and wellbeing technology. *This conference was held virtually due to the COVID-19 pandemic

    WOFEX 2021 : 19th annual workshop, Ostrava, 1th September 2021 : proceedings of papers

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    The workshop WOFEX 2021 (PhD workshop of Faculty of Electrical Engineer-ing and Computer Science) was held on September 1st September 2021 at the VSB – Technical University of Ostrava. The workshop offers an opportunity for students to meet and share their research experiences, to discover commonalities in research and studentship, and to foster a collaborative environment for joint problem solving. PhD students are encouraged to attend in order to ensure a broad, unconfined discussion. In that view, this workshop is intended for students and researchers of this faculty offering opportunities to meet new colleagues.Ostrav

    Improving Access and Mental Health for Youth Through Virtual Models of Care

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    The overall objective of this research is to evaluate the use of a mobile health smartphone application (app) to improve the mental health of youth between the ages of 14–25 years, with symptoms of anxiety/depression. This project includes 115 youth who are accessing outpatient mental health services at one of three hospitals and two community agencies. The youth and care providers are using eHealth technology to enhance care. The technology uses mobile questionnaires to help promote self-assessment and track changes to support the plan of care. The technology also allows secure virtual treatment visits that youth can participate in through mobile devices. This longitudinal study uses participatory action research with mixed methods. The majority of participants identified themselves as Caucasian (66.9%). Expectedly, the demographics revealed that Anxiety Disorders and Mood Disorders were highly prevalent within the sample (71.9% and 67.5% respectively). Findings from the qualitative summary established that both staff and youth found the software and platform beneficial

    Acoustic sensing as a novel approach for cardiovascular monitoring at the wrist

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    Cardiovascular diseases are the number one cause of deaths globally. An increased cardiovascular risk can be detected by a regular monitoring of the vital signs including the heart rate, the heart rate variability (HRV) and the blood pressure. For a user to undergo continuous vital sign monitoring, wearable systems prove to be very useful as the device can be integrated into the user's lifestyle without affecting the daily activities. However, the main challenge associated with the monitoring of these cardiovascular parameters is the requirement of different sensing mechanisms at different measurement sites. There is not a single wearable device that can provide sufficient physiological information to track the vital signs from a single site on the body. This thesis proposes a novel concept of using acoustic sensing over the radial artery to extract cardiac parameters for vital sign monitoring. A wearable system consisting of a microphone is designed to allow the detection of the heart sounds together with the pulse wave, an attribute not possible with existing wrist-based sensing methods. Methods: The acoustic signals recorded from the radial artery are a continuous reflection of the instantaneous cardiac activity. These signals are studied and characterised using different algorithms to extract cardiovascular parameters. The validity of the proposed principle is firstly demonstrated using a novel algorithm to extract the heart rate from these signals. The algorithm utilises the power spectral analysis of the acoustic pulse signal to detect the S1 sounds and additionally, the K-means method to remove motion artifacts for an accurate heartbeat detection. The HRV in the short-term acoustic recordings is found by extracting the S1 events using the relative information between the short- and long-term energies of the signal. The S1 events are localised using three different characteristic points and the best representation is found by comparing the instantaneous heart rate profiles. The possibility of measuring the blood pressure using the wearable device is shown by recording the acoustic signal under the influence of external pressure applied on the arterial branch. The temporal and spectral characteristics of the acoustic signal are utilised to extract the feature signals and obtain a relationship with the systolic blood pressure (SBP) and diastolic blood pressure (DBP) respectively. Results: This thesis proposes three different algorithms to find the heart rate, the HRV and the SBP/ DBP readings from the acoustic signals recorded at the wrist. The results obtained by each algorithm are as follows: 1. The heart rate algorithm is validated on a dataset consisting of 12 subjects with a data length of 6 hours. The results demonstrate an accuracy of 98.78%, mean absolute error of 0.28 bpm, limits of agreement between -1.68 and 1.69 bpm, and a correlation coefficient of 0.998 with reference to a state-of-the-art PPG-based commercial device. A high statistical agreement between the heart rate obtained from the acoustic signal and the photoplethysmography (PPG) signal is observed. 2. The HRV algorithm is validated on the short-term acoustic signals of 5-minutes duration recorded from each of the 12 subjects. A comparison is established with the simultaneously recorded electrocardiography (ECG) and PPG signals respectively. The instantaneous heart rate for all the subjects combined together achieves an accuracy of 98.50% and 98.96% with respect to the ECG and PPG signals respectively. The results for the time-domain and frequency-domain HRV parameters also demonstrate high statistical agreement with the ECG and PPG signals respectively. 3. The algorithm proposed for the SBP/ DBP determination is validated on 104 acoustic signals recorded from 40 adult subjects. The experimental outputs when compared with the reference arm- and wrist-based monitors produce a mean error of less than 2 mmHg and a standard deviation of error around 6 mmHg. Based on these results, this thesis shows the potential of this new sensing modality to be used as an alternative, or to complement existing methods, for the continuous monitoring of heart rate and HRV, and spot measurement of the blood pressure at the wrist.Open Acces

    Preface

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    Actas de SABI2020

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    Los temas salientes incluyen un marcapasos pulmonar que promete complementar y eventualmente sustituir la conocida ventilación mecánica por presión positiva (intubación), el análisis de la marchaespontánea sin costosos equipamientos, las imágenes infrarrojas y la predicción de la salud cardiovascular en temprana edad por medio de la biomecánica arterial

    Divide and conquer: an oscillatory division of labour in service of episodic memory

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    Both oscillatory synchronisation and oscillatory desynchronisation underpin the formation and retrieval of episodic memories. This paradox begs the question: how can two polar opposite neural phenomena produce the same outcome? Here, we investigate this conundrum by presenting a series of empirical experiments that test the hypothesis that these two phenomena reflect a division of labour in service of episodic memory. We demonstrate that neocortical desynchrony correlates with enhanced information representation, while hippocampal synchrony stiches this information together into a coherent memory trace. Critically, we demonstrate that these processes interact. Neocortical desynchrony precedes and predicts hippocampal synchrony during episodic memory formation, while hippocampal synchrony precedes and predicts neocortical desynchrony during episodic memory retrieval. This thesis suggests that the interaction between neocortical desynchrony and hippocampal synchrony sits at the heart of the formation and retrieval of episodic memories, providing empirical resolution to the so-called synchronisation/desynchronisation conundrum
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