REAL TIME DATA ACQUISITION AND MONITORING OF PATIENTS WITH CORONARY HEART DISEASE IN A HOME ENVIRONMENT

The high mortality rate associated with cardiovascular related diseases requires the implementation of a personalised, ubiquitous health monitoring system. With the recent advancements of wireless sensor network technologies, these study proposes a real time data acquisition and monitoring system for patients with a track history of coronary heart diseases based on the implementation of a microcontroller, GSM Module and temperature sensors. This pervasive healthcare system will provide a round the clock monitoring and has an in built alerting mechanism for detecting anomalies in cardiac activities. The aim of the study is to minimize the need for caretakers and help the gravely ill senior citizens to survive an independent life. Apart from that, this study will help reduce the mortality rate of victim by shortening the response time of medical team to the victims. In these study, the proposed design mechanism will consider the following key criteria namely safety, data security, energy efficiency, durability and cost incurred

ECG denoising based on adaptive signal processing technique

An Electrocardiogram (ECG) monitoring system deals with several challenges related with noise sources. The main goal of this text was the study of Adaptive Signal Processing Algorithms for ECG noise reduction when applied to real signals. This document presents an adaptive ltering technique based on Least Mean Square (LMS) algorithm to remove the artefacts caused by electromyography (EMG) and power line noise into ECG signal. For this experiments it was used real noise signals, mainly to observe the di erence between real noise and simulated noise sources. It was obtained very good results due to the ability of noise removing that can be reached with this technique. A recolha de sinais electrocardiogr a cos (ECG) sofre de diversos problemas relacionados com ru dos. O objectivo deste trabalho foi o estudo de algoritmos adaptativos para processamento digital de sinal, para redu c~ao de ru do em sinais ECG reais. Este texto apresenta uma t ecnica de redu c~ao de ru do baseada no algoritmo Least Mean Square (LMS) para remo c~ao de ru dos causados quer pela actividade muscular (EMG) quer por ru dos causados pela rede de energia el ectrica. Para as experiencias foram utilizados ru dos reais, principalmente para aferir a diferen ca de performance do algoritmo entre os sinais reais e os simulados. Foram conseguidos bons resultados, essencialmente devido as excelentes caracter sticas que esta t ecnica tem para remover ru dos

REAL TIME DATA ACQUISITION AND MONITORING OF PATIENTS WITH CORONARY HEART DISEASE IN A HOME ENVIRONMENT

The high mortality rate associated with cardiovascular related diseases requires the implementation of a personalised, ubiquitous health monitoring system. With the recent advancements of wireless sensor network technologies, these study proposes a real time data acquisition and monitoring system for patients with a track history of coronary heart diseases based on the implementation of a microcontroller, GSM Module and temperature sensors. This pervasive healthcare system will provide a round the clock monitoring and has an in built alerting mechanism for detecting anomalies in cardiac activities. The aim of the study is to minimize the need for caretakers and help the gravely ill senior citizens to survive an independent life. Apart from that, this study will help reduce the mortality rate of victim by shortening the response time of medical team to the victims. In these study, the proposed design mechanism will consider the following key criteria namely safety, data security, energy efficiency, durability and cost incurred

Advanced sensors technology survey

This project assesses the state-of-the-art in advanced or 'smart' sensors technology for NASA Life Sciences research applications with an emphasis on those sensors with potential applications on the space station freedom (SSF). The objectives are: (1) to conduct literature reviews on relevant advanced sensor technology; (2) to interview various scientists and engineers in industry, academia, and government who are knowledgeable on this topic; (3) to provide viewpoints and opinions regarding the potential applications of this technology on the SSF; and (4) to provide summary charts of relevant technologies and centers where these technologies are being developed

Seamless Multimodal Biometrics for Continuous Personalised Wellbeing Monitoring

Artificially intelligent perception is increasingly present in the lives of every one of us. Vehicles are no exception, (...) In the near future, pattern recognition will have an even stronger role in vehicles, as self-driving cars will require automated ways to understand what is happening around (and within) them and act accordingly. (...) This doctoral work focused on advancing in-vehicle sensing through the research of novel computer vision and pattern recognition methodologies for both biometrics and wellbeing monitoring. The main focus has been on electrocardiogram (ECG) biometrics, a trait well-known for its potential for seamless driver monitoring. Major efforts were devoted to achieving improved performance in identification and identity verification in off-the-person scenarios, well-known for increased noise and variability. Here, end-to-end deep learning ECG biometric solutions were proposed and important topics were addressed such as cross-database and long-term performance, waveform relevance through explainability, and interlead conversion. Face biometrics, a natural complement to the ECG in seamless unconstrained scenarios, was also studied in this work. The open challenges of masked face recognition and interpretability in biometrics were tackled in an effort to evolve towards algorithms that are more transparent, trustworthy, and robust to significant occlusions. Within the topic of wellbeing monitoring, improved solutions to multimodal emotion recognition in groups of people and activity/violence recognition in in-vehicle scenarios were proposed. At last, we also proposed a novel way to learn template security within end-to-end models, dismissing additional separate encryption processes, and a self-supervised learning approach tailored to sequential data, in order to ensure data security and optimal performance. (...)Comment: Doctoral thesis presented and approved on the 21st of December 2022 to the University of Port

A selective list of acronyms and abbreviations

A glossary of acronyms, abbreviations, initials, code words, and phrases used at the John F. Kennedy Space Center is presented. The revision contains more than 12,100 entries

Affective Computing

This book provides an overview of state of the art research in Affective Computing. It presents new ideas, original results and practical experiences in this increasingly important research field. The book consists of 23 chapters categorized into four sections. Since one of the most important means of human communication is facial expression, the first section of this book (Chapters 1 to 7) presents a research on synthesis and recognition of facial expressions. Given that we not only use the face but also body movements to express ourselves, in the second section (Chapters 8 to 11) we present a research on perception and generation of emotional expressions by using full-body motions. The third section of the book (Chapters 12 to 16) presents computational models on emotion, as well as findings from neuroscience research. In the last section of the book (Chapters 17 to 22) we present applications related to affective computing