Medically Relevant Criteria used in EEG Compression for Improved Post-Compression Seizure Detection

Biomedical signals aid in the diagnosis of different disorders and abnormalities. When targeting lossy compression of such signals, the medically relevant information that lies within the data should maintain its accuracy and thus its reliability. In fact, signal models that are inspired by the bio-physical properties of the signals at hand allow for a compression that preserves more naturally the clinically significant features of these signals. In this paper, we illustrate this through the example of EEG signals; more specifically, we analyze three specific lossy EEG compression schemes. These schemes are based on signal models that have different degrees of reliance on signal production and physiological characteristics of EEG. The resilience of these schemes is illustrated through the performance of seizure detection post compression.Comment: This work has been submitted to the IEEE for possible publication. Copyright may be transferred without notice, after which this version may no longer be accessibl

Detection of Sentiment Provoking Events in Social Media

Social media has become one of the main sources of news and events due to its ability to disseminate and propagate information very fast and to a large population. Social media platforms are widely accessible to the population making it difficult to extract relevant information from the huge amount of posted data. In our study, we propose an algorithm that automatically detects events using strong sentiment classification and appropriate clustering techniques. We focus our study on a specific type of events that triggers strong sentiment among the public. Results show that the suggested methodology is able to identify important events, such as a mass shooting and plane crash, using a generalized and simple approach

The evolving SARS-CoV-2 epidemic in Africa: Insights from rapidly expanding genomic surveillance

INTRODUCTION Investment in Africa over the past year with regard to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) sequencing has led to a massive increase in the number of sequences, which, to date, exceeds 100,000 sequences generated to track the pandemic on the continent. These sequences have profoundly affected how public health officials in Africa have navigated the COVID-19 pandemic. RATIONALE We demonstrate how the first 100,000 SARS-CoV-2 sequences from Africa have helped monitor the epidemic on the continent, how genomic surveillance expanded over the course of the pandemic, and how we adapted our sequencing methods to deal with an evolving virus. Finally, we also examine how viral lineages have spread across the continent in a phylogeographic framework to gain insights into the underlying temporal and spatial transmission dynamics for several variants of concern (VOCs). RESULTS Our results indicate that the number of countries in Africa that can sequence the virus within their own borders is growing and that this is coupled with a shorter turnaround time from the time of sampling to sequence submission. Ongoing evolution necessitated the continual updating of primer sets, and, as a result, eight primer sets were designed in tandem with viral evolution and used to ensure effective sequencing of the virus. The pandemic unfolded through multiple waves of infection that were each driven by distinct genetic lineages, with B.1-like ancestral strains associated with the first pandemic wave of infections in 2020. Successive waves on the continent were fueled by different VOCs, with Alpha and Beta cocirculating in distinct spatial patterns during the second wave and Delta and Omicron affecting the whole continent during the third and fourth waves, respectively. Phylogeographic reconstruction points toward distinct differences in viral importation and exportation patterns associated with the Alpha, Beta, Delta, and Omicron variants and subvariants, when considering both Africa versus the rest of the world and viral dissemination within the continent. Our epidemiological and phylogenetic inferences therefore underscore the heterogeneous nature of the pandemic on the continent and highlight key insights and challenges, for instance, recognizing the limitations of low testing proportions. We also highlight the early warning capacity that genomic surveillance in Africa has had for the rest of the world with the detection of new lineages and variants, the most recent being the characterization of various Omicron subvariants. CONCLUSION Sustained investment for diagnostics and genomic surveillance in Africa is needed as the virus continues to evolve. This is important not only to help combat SARS-CoV-2 on the continent but also because it can be used as a platform to help address the many emerging and reemerging infectious disease threats in Africa. In particular, capacity building for local sequencing within countries or within the continent should be prioritized because this is generally associated with shorter turnaround times, providing the most benefit to local public health authorities tasked with pandemic response and mitigation and allowing for the fastest reaction to localized outbreaks. These investments are crucial for pandemic preparedness and response and will serve the health of the continent well into the 21st century

Design and evaluation of multichannel electroencephalography signal compression techniques

This thesis presents different techniques for Electroencephalogram (EEG) compression for the purpose of reduction in storage and bandwidth requirements. Two types of recordings are considered: long-term recordings of scalp EEG and long-term recording of intra-cerebral EEG (iEEG) signals of patients suffering from epileptic seizures. Thus, this thesis project targets outpatient long-term monitoring of EEG signals of patients suffering from epileptic seizures. The analysis of these methods is done first using classic RD performance metric which is a commonly used metric in signal compression. However, in medical signals, it is important to preserve important diagnostic information. In order to move towards such a diagnostics-oriented performance assessment, we propose in this thesis a framework to evaluate the performance of EEG compression mechanisms in terms of post-compression seizure detection capability.Cette thèse présente différentes techniques suggérées pour la compression d'électroencéphalogrammes (EEG) dans le but de réduire l'espace de stockage et réduire la bande passante requise pour transmettre ces signaux. Deux types d'enregistrements sont considérés: enregistrements à long terme des signaux effectués à la surface du crâne et enregistrements à long terme des signaux effectués dans le crâne (iEEG) des patients souffrant de crises d'épilepsie. Ce projet de thèse vise la surveillance long terme et à distance des signaux EEG de patients souffrant de crises d'épilepsie. L'analyse de ces méthodes se fait d'abord en utilisant une métrique de performance basée sur la quantité de distortion introduite par la compression. Cette métrique est couramment utilisée dans la compression des signaux. Cependant, les EEGs contiennent des informations importantes pour le diagnostic médical. Alors, nous proposons dans cette thèse un nouveau contexte pour évaluer la performance de ces systèmes de compression. Ce contexte est basé sur la détection des épisodes de crise testée post-compression