Seizure Classification of EEG based on Wavelet Signal Denoising Using a Novel Channel Selection Algorithm

Epilepsy is a disorder of the nervous system that can affect people of any age group. With roughly 50 million people worldwide diagnosed with the disorder, it is one of the most common neurological disorders. The EEG is an indispensable tool for diagnosis of epileptic seizures in an ideal case, as brain waves from an epileptic person will present distinct abnormalities. However, in real world situations there will often be biological and electrical noise interference, as well as the issue of a multichannel signal, which introduce a great challenge for seizure detection. For this study, the Temple University Hospital (TUH) EEG Seizure Corpus dataset was used. This paper proposes a novel channel selection method which isolates different frequency ranges within five channels. This is based upon the frequencies at which normal brain waveforms exhibit. A one second window was selected, with a 0.5 second overlap. Wavelet signal denoising was performed using Daubechies 4 wavelet decomposition, thresholding was applied using minimax soft thresholding criteria. Filter banking was used to localise frequency ranges from five specific channels. Statistical features were then derived from the outputs. After performing bagged tree classification using 500 learners, a test accuracy of 0.82 was achieved.Comment: 8 pages, 6 figures, accepted for publication at the 13th Asia Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA ASC

Epileptic multi-seizure type classification using electroencephalogram signals from the Temple University Hospital Seizure Corpus:A review

Epilepsy is one of the most paramount neurological diseases, affecting about 1% of the world's population. Seizure detection and classification are difficult tasks and are ongoing challenges in biomedical signal processing to enhance medical diagnosis. This paper presents and highlights the unique frequency and amplitude information found within multiple seizure types, including their morphologies, to aid the development of future seizure classification algorithms. Whilst many published works in the literature have reported on seizure detection using electroencephalogram (EEG), there has yet to be an exhaustive review detailing multi-seizure type classification using EEG. Therefore, this paper also includes a detailed review of multi-seizure type classification performance based on the Temple University Hospital Seizure Corpus (TUSZ) dataset for focal and generalised classification, and multi-seizure type classification. Deep learning techniques have a higher overall average performance for focal and generalised classification compared to machine learning techniques, whereas hybrid deep learning approaches have the highest overall average performance for multi-seizure type classification. Finally, this paper also highlights the limitations of the TUSZ dataset and suggests some future work, including the curation of a standardised training and testing dataset from the TUSZ that would allow a proper comparison of classification methods and spur advancement in the field.</p

A New Experimental Infection Model in Ferrets Based on Aerosolised Mycobacterium bovis

There is significant interest in developing vaccines to control bovine tuberculosis, especially in wildlife species where this disease continues to persist in reservoir species such as the European Badger (Meles meles). However, gaining access to populations of badgers (protected under UK law) is problematic and not always possible. In this study, a new infection model has been developed in ferrets (Mustela furo), a species which is closely related to the badger. Groups of ferrets were infected using a Madison infection chamber and were examined postmortem for the presence of tuberculous lesions and to provide tissue samples for confirmation of Mycobacterium bovis by culture. An infectious dose was defined, that establishes infection within the lungs and associated lymph nodes with subsequent spread to the mesentery lymph nodes. This model, which emphasises respiratory tract infection, will be used to evaluate vaccines for the control of bovine tuberculosis in wildlife species

Multilaboratory Evaluation of a Novel Lateral Flow Immunochromatographic Assay for Confirming Isolation of Mycobacterium bovis from Veterinary Diagnostic Specimens

ABSTRACT A novel lateral flow immunochromatographic device (LFD) was evaluated in several veterinary diagnostic laboratories. It was confirmed to be specific for Mycobacterium bovis and M. caprae cells. The performance of the novel LFD was assessed relative to the confirmatory tests routinely applied after culture (spoligotyping or quantitative PCR [qPCR]) in each laboratory; liquid (MGIT or BacT/Alert) and/or solid (Stonebrink, Coletsos, or Lowenstein-Jensen) cultures were tested. In comparison to spoligotyping of acid-fast-positive MGIT cultures, percent agreement between positive LFD and spoligotyping results was excellent in two United Kingdom laboratories (97.7 to 100%) but lower in the Spanish context (76%), where spoligotyping was applied to MGIT cultures previously confirmed to be positive for M. tuberculosis complex (MTBC) by qPCR. Certain spoligotypes of M. bovis and M. caprae were not detected by the LFD in Spanish MGIT cultures. Compared to qPCR confirmation, the agreement between positive LFD and qPCR results was 42.3% and 50% for BacT/Alert and MGIT liquid cultures, respectively, and for solid cultures, it ranged from 11.1 to 89.2%, depending on the solid medium employed (Coletsos, 11.1%; Lowenstein-Jensen, 55.6%; Stonebrinks, 89.2%). Correlation between the novel LFD and BD MGIT TBc Identification test results was excellent when 190 MGIT cultures were tested ( r = 0.9791; P &lt; 0.0001), with the added benefit that M. bovis was differentiated from another MTBC species in one MGIT culture by the novel LFD. This multilaboratory evaluation demonstrated the novel LFD's potential utility as a rapid test to confirm isolation of M. bovis and M. caprae from veterinary specimens following culture. </jats:p

Relationship between ambient temperature at sampling and the interferon gamma test result for bovine tuberculosis in cattle

Publication history: Accepted - 17 May 2023; Published online - 19 May 2023.Bovine tuberculosis (bTB) is a disease of significant economic and zoonotic importance, therefore, optimising tests for the identification of Mycobacterium bovis infected cattle is essential. The Interferon Gamma (IFN-γ) Release Assay (IGRA) can diagnose M. bovis infected cattle at an early stage, is easy to perform and can be used alongside skin tests for confirmatory purposes or to increase diagnostic sensitivity. It is known that IGRA performance is sensitive to environmental conditions under which samples are taken and transported. In this study, the association between the ambient temperature on the day of bleeding and the subsequent IGRA result for bTB was quantified using field samples from Northern Ireland (NI). Results of 106,434 IGRA results (2013–2018) were associated with temperature data extracted from weather stations near tested cattle herds. Model dependent variables were the levels of IFN-γ triggered by avian purified protein derivative (PPDa), M. bovis PPD (PPDb), their difference (PPD(b-a)) as well as the final binary outcome (positive or negative for M. bovis infection). IFN-γ levels after both PPDa and PPDb stimulation were lowest at the extremes of the temperature distribution for NI. The highest IGRA positive probability (above 6%) was found on days with moderate maximum temperatures (6–16 °C) or moderate minimum temperatures (4–7 °C). Adjustment for covariates did not lead to major changes in the model estimates. These data suggest that IGRA performance can be affected when samples are taken at high or low temperatures. Whilst it is difficult to exclude physiological factors, the data nonetheless supports the temperature control of samples from bleeding through to laboratory to help mitigate post-collection confounders

Access to Research Veterinary Medicine International Volume

There is significant interest in developing vaccines to control bovine tuberculosis, especially in wildlife species where this disease continues to persist in reservoir species such as the European Badger (Meles meles). However, gaining access to populations of badgers (protected under UK law) is problematic and not always possible. In this study, a new infection model has been developed in ferrets (Mustela furo), a species which is closely related to the badger. Groups of ferrets were infected using a Madison infection chamber and were examined postmortem for the presence of tuberculous lesions and to provide tissue samples for confirmation of Mycobacterium bovis by culture. An infectious dose was defined, that establishes infection within the lungs and associated lymph nodes with subsequent spread to the mesentery lymph nodes. This model, which emphasises respiratory tract infection, will be used to evaluate vaccines for the control of bovine tuberculosis in wildlife species

An Artificial Light Source Influences Mating and Oviposition of Black Soldier Flies, Hermetia illucens

Current methods for mass-rearing black soldier flies, Hermetia illucens (L.) (Diptera: Stratiomyidae), in the laboratory are dependent on sunlight. Quartz-iodine lamps and rare earth lamps were examined as artificial light sources for stimulating H. illucens to mate and lay eggs. Sunlight was used as the control. Adults in the quartz-iodine lamp treatment had a mating rate of 61% of those in the sunlight control. No mating occurred when the rare earth lamp was used as a substitute. Egg hatch for the quartz-iodine lamp and sunlight treatments occurred in approximately 4 days, and the hatch rate was similar between these two treatments. Larval and pupal development under these treatments required approximately 18 and 15 days at 28°° C, respectively. Development of methods for mass rearing of H. illucens using artificial light will enable production of this fly throughout the year without investing in greenhouse space or requiring sunlight

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