1,721,023 research outputs found
Remote Monitoring of COVID-19 Patients Following Discharge from a Tertiary Care Center
No full textThe COVID-19 pandemic has affected people, healthcare systems and caregivers on a global scale causing bottlenecks in hospital resources and overload of healthcare systems. The presence of disease sequelae in
patients hospitalized due to COVID-19 warrants additional care and monitoring of these patients. Remote monitoring techniques have been implemented in several domains of healthcare such as cardiology, cardiac rehabilitation and nephrology. Monitoring of vital signs using these technologies has allowed the tracking of patients with more granularity, resulting in better clinical outcomes such as reduction in hospitalizations. Therefore, we hypothesize that remote monitoring is beneficial in managing COVID-19 patients post-hospitalization, enabling home-based patient follow-up. In this study, we investigated the use of remote
monitoring on a COVID-19 patient cohort discharged from a tertiary care center. A post-hoc division of patients into two groups (alert-generating patients and non-alert generating patients) was performed. The longitudinal progression of sensor and questionnaire data was studied using linear mixed-effect models. The measured heart rate values were statistically significant in terms of the intercept (p<0.001), indicating a difference between the two patient groups at baseline immediately post-discharge.The authors would like to acknowledge Dr. David Ruttens for his help in data collection for this project. The authors would like to thank the assistants and nurses at the Department of Pneumology, Ziekenhuis Oost-Limburg as well as the scientific researchers of Future Health for their help in the data collection procedure
Identifying Changes in Functional Capacity of Cardiorespiratory Patients Undergoing Exercise Rehabilitation
No full textHeart failure (HF) and chronic obstructive pulmonary disease (COPD) are two common complex multimorbid cardiorespiratory diseases. Due to their complex nature, it is challenging to identify changes in health status of affected patients. In this study, we analyse the progression of functional capacity as a first step in identifying changes in disease status of HF and COPD patients. 60 patients (NHF=35, NCOPD=25) undergoing cardiopulmonary rehabilitation were included in this study. A six-minute walk test (6MWT) assessing the sixminute walking distance (6MWD) was used to monitor the functional capacity of these patients. Patients performed five 6MWTs in total (1 baseline, 4 follow-up) with spotcheck HR and SpO2 values also being measured before and after each 6MWT. The progression of the 6MWDs was analysed using a two-way mixed ANOVA. To predict changes in functional capacity, patients were divided into two groups (“improved” vs “not improved”) based on a minimal clinically significant distance change. A decision tree classifier was trained on 6MWD, HR and SpO2 data features and evaluated using balanced accuracy. The mixed ANOVA showed a significant interaction effect as well as significant between-subjects and withinsubject effects. The classifier showed good performance in predicting improvement of functional capacity.The authors would like to thank Daimy Roebroek, Frauke Somers and Julie Deckers for their help in collecting data from patients for this study
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
Full text link“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Full text linkWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
Dispelling the Myths Behind First-author Citation Counts
Full text linkWe conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
Akoestische Eventdetectie: Kenmerk-, Evaluatie- en Datasetontwerp
No full textIt takes more time to think of a silent scene, action or event than finding one that emanates sound. Not only speaking or playing music but almost everything that happens is accompanied with or results in one or more sounds mixed together. This makes acoustic event detection (AED) one of the most researched topics in audio signal processing nowadays and it will probably not see a decline anywhere in the near future. This is due to the thirst for understanding and digitally abstracting more and more events in life via the enormous amount of recorded audio through thousands of applications in our daily routine. But it is also a result of two intrinsic properties of audio: it doesn't need a direct sight to be perceived and is less intrusive to record when compared to image or video.
Many applications such as context-based indexing, health monitoring and smart environments, profit from the techniques developed for AED and results are still far from perfect. For instance, automatic music transcription (AMT) usually needs some corrections by expert musicians, and voice-controlled applications often require you to repeat a voice command or a word to your mobile phone before being understood. This is due to the challenging nature of the AED task. It is more than classifying one event into one of a predefined set of classes as it is pointing out a target event from anything else.
In this thesis we focus on two AED applications which, at first sight, seem to be coming from two different worlds. The first is note onset detection (NOD), an atomic component for many music applications like fingerprinting for search engines and recommender systems, digital effects or simply AMT. From its name, the target events of NOD are the starting of musical notes. For the second application, howling detection (HD), the target is more of an artifact than a desired enjoyable event as howling is that sort of beep that shows up when a closed feedback loop is created between a microphone and a loudspeaker which occurs frequently in public address (PA) systems and hearing aids (HA). A HD algorithm is expected to produce some sort of activation function signaling the resonant frequency as soon as the howling starts in order to automatically filter it out. Surprisingly, both events share a specific time-frequency pattern, hence the key idea behind the spectral sparsity feature suggested in this work.
After introducing AED in Part I, inspired from the work done for NOD, a general 3-step processing scheme is sketched out for detection of pattern-specific events in audio signals. This is followed by a summary of the state-of-the-art methods used for each of the steps. Part I ends by comparing the different metrics and techniques traditionally used for NOD and HD performance evaluation pointing out how unsuitable they are to handle the imbalanced nature of the datasets used in both problems. Moreover, it suggests a framework for a more fair evaluation and more generalized results using precision-recall (PR) curves and k-fold cross-validation scores.
The two main parts of the thesis reside in Parts II and III, discussing the challenges and suggesting possible solutions for the two applications of interest, NOD and HD, respectively. The contributions for each can be divided into three groups following from the problems' solution steps: feature design, annotated dataset generation and evaluation enhancement.
A feature based on spectral sparsity with two flavors, normalised identification of note onset based on spectral sparsity (NINOS2) and NINOS2-Transposed (NINOS2-T), is suggested for respectively detecting note onsets and howling frequencies. When tested on a dataset of synthetically mixed musical note onsets, NINOS2 outperformed the state-of-the-art NOD feature, Logarithmic Spectral Flux (LSF), for the sustained-strings instruments, pushing the F1-score to cross the 50 % border. This group of pitched non-percussive instruments is quite challenging as they have softer onsets, i.e., slowly building-up transients. A novel pre-processing step preceding the application of the NINOS detection function, is found to contribute to the performance increase. The pre-processing consists in retaining a subset of frequencies traditionally neglected but found here to be tightly related to onsets. For HD, NINOS2-T marked a higher average area under the PR curve (PR-AUC) than all the standalone HD features found in literature, for both music and speech examples. The performance of NINOS2-T remained the highest when restricting the evaluation to early howling detection.
Existing datasets for both problems are relatively limited in terms of quantity and quality. For NOD, the available datasets are mainly manually annotated by two or more experts, limiting their availability due to the expensive annotation process. Moreover the annotation is subjective and note-context dependent. A similar situation exists for HD where datasets are made of recorded and manually annotated howling or sometimes poorly simulated by sinusoidal superposition. Part II starts by introducing a MATLAB tool "Mix-Notes" which is developed for generating automatically annotated NOD datasets. In Part III, a large HD dataset is created by simulating a closed-loop system, using several acoustic
impulse responses (AIRs) to cover a wide range of howling frequencies, and applying the simulated system to different music and speech input files. On top of using those datasets for testing the suggested NOD and HD features, a different NOD experiment is carried out in which a real NOD dataset is augmented using a semi-synthetic dataset, created using the "Mix-Notes" tool, for training a state-of-the-art data-driven Convolutional Neural Network (CNN) model. This is done to overcome the limited availability of annotated real datasets. When running the experiment on piano excerpts, using two different augmentation strategies, preliminary results show better and more stable performance.
To ensure a fair NOD evaluation, a novel parameter, the overall time shift in annotations, is proposed in Part II. While consistently lacking in literature when reporting F1-scores, this parameter is found crucial for making results comparable for different datasets and algorithms. The best-case F1-score can vary drastically when including this overall time shift in annotations parameter and it is found beneficial to use this parameter as a tunable hyperparameter when training a deep data-driven model on datasets that are annotated differently. The performance of HD features is traditionally compared for a subset of howling candidates using the receiver operating characteristic (ROC) metric. The use of howling candidates is intended to differentiate between howling and signal components and results in a fairly well balanced dataset, yet it excludes the detection of early howling and ringing. To overcome this limitation, in Part III, we suggest a novel HD approach considering all frequency bins as howling candidates. Since this yields a highly imbalanced dataset, for which ROC evaluation has been proven unsuitable, we propose to use the PR and PR-AUC evaluation metrics instead. Moreover, the PR assessment used a grid of equidistant thresholds in order to evaluate the HD feature robustness to threshold variations.
While searching for answers to the different NOD and HD problems, questions never stopped popping up. Part IV revisits some learned lessons, discusses various open questions and suggests some future steps for further research in the presented topics.status: Publishe
koamabayili/VECTRON-author-checklist: VECTRON author checklist
No full textWe have done our best to complete the author checklist relating to the use of animals in the hut study. Note that the objective for the hut study was to evaluate the IRS treatment applications for residual efficacy against Anopheles mosquitoes, including the local An. coluzzii mosquito population. Cows were only used to attract mosquitoes into the huts and no tests were carried out directly on the cows. The author checklist is intended for use with studies where experiments are carried out on animals, which is why we have had such difficulty in completing this for the hut study, as many of the questions do not relate to how the cows were used
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