Acceptability of and symptom findings from an online symptom check-in tool for COVID-19 outpatient follow-up among a predominantly healthcare worker population.

Introduction: Health systems worldwide have had to prepare for a surge in volume in both the outpatient and inpatient settings since the emergence of COVID-19. Early international healthcare experiences showed approximately 80% of patients with COVID-19 had mild disease and therfore could be managed as outpatients. However, SARS-CoV-2 can cause a biphasic illness with those affected experiencing a clinical deterioration usually seen after day 4 of illness.

Multimodal detection of head-movement artefacts in EEG.

Artefacts arising from head movements have been a considerable obstacle in the deployment of automatic event detection systems in ambulatory EEG. Recently, gyroscopes have been identified as a useful modality for providing complementary information to the head movement artefact detection task. In this work, a comprehensive data fusion analysis is conducted to investigate how EEG and gyroscope signals can be most effectively combined to provide a more accurate detection of head-movement artefacts in the EEG.

Automatic detection of EEG artefacts arising from head movements using EEG and gyroscope signals.

Contamination of EEG signals by artefacts arising from head movements has been a serious obstacle in the deployment of automatic neurological event detection systems in ambulatory EEG. In this paper, we present work on categorizing these head-movement artefacts as one distinct class and on using support vector machines to automatically detect their presence. The use of additional physical signals in detecting head-movement artefacts is also investigated by means of support vector machines classifiers implemented with gyroscope waveforms.

Automatic detection of EEG artefacts arising from head movements.

The need for reliable detection of artefacts in raw and processed EEG is widely acknowledged. In this paper, we present the results of an investigation into appropriate features for artefact detection in the REACT ambulatory EEG system. The study focuses on EEG artefacts arising from head movement.