COVID-19 Mandatory self-quarantine wearable device for authority monitoring with edge AI reporting & flagging system.

A mandatory self-quarantine is necessary for those who return from overseas or any red zone areas. It is important that the self-quarantine is conducted without the non-adherence issue occurring and causes the self-quarantine individual to be the carrier of the COVID-19 in the community. To navigate and resolve this issue, most countries have implemented a series of COVID-19 monitoring and tracing systems. However, there are some restrictions and limitation which can lead to intentional non-adherence. The quarantined individuals can still travel within the community by removing the wristband or simply providing an incorrect contact status in the tracing application. In this paper, a novel configuration for mandatory self-quarantine system is proposed. It will enable interaction between the wearable and contact tracing technologies to ensure that the authorities have total control of the system. The hardware of the proposed system in the wearable device is low in cost, lightweight and safe to use for the next user after the quarantine is completed. The software (software and database) that linked between the quarantine user and normal user utilizes edge artificial intelligence (AI) for reporting and flagging mechanisms.

Nonlinear Dynamics Measures for Automated EEG-Based Sleep Stage Detection.

BACKGROUND: The brain's continuous neural activity during sleep can be monitored by electroencephalogram (EEG) signals. The EEG wave pattern and frequency vary during five stages of sleep. These subtle variations in sleep EEG signals cannot be easily detected through visual inspection. SUMMARY: A range of time, frequency, time-frequency and nonlinear analysis methods can be applied to understand the complex physiological signals and their chaotic behavior. This paper presents a comprehensive comparative review and analysis of 29 nonlinear dynamics measures for EEG-based sleep stage detection. KEY MESSAGES: The characteristic ranges of these features are reported for the five different sleep stages. All nonlinear measures produce clinically significant results, that is, they can discriminate the individual sleep stages. Feature ranking based on the statistical F-value, however, shows that the third order cumulant of higher order spectra yields the most discriminative result. The distinct value ranges for each sleep stage and the discriminative power of the features can be used for sleep disorder diagnosis, treatment monitoring, and drug efficacy assessment.

Non-invasive positive pressure ventilation for treatment of respiratory failure due to severe acute exacerbations of asthma.

BACKGROUND: Asthma is a chronic respiratory condition causing inflammation and changes to the airways. Care of people with asthma includes routine and urgent management across primary and tertiary care; however, due to sub-optimal long-term care and delays in obtaining help during acute exacerbations, the mortality and morbidity related to asthma is still a major health concern. There is reason to believe that non-invasive positive pressure ventilation (NPPV) could be beneficial to patients with severe acute asthma; however, the evidence surrounding the efficacy of NPPV is unclear, despite its common use in clinical practice. OBJECTIVES: To determine the efficacy of NPPV in adults with severe acute asthma in comparison to usual medical care with respect to mortality, tracheal intubation, changes in blood gases and hospital length of stay. SEARCH METHODS: We carried out a search in the Cochrane Airways Group Specialised Register of trials (July 2012). Following this, the bibliographies of included studies and review articles were searched for additional studies (July 2012). SELECTION CRITERIA: We included randomised controlled trials of adults with severe acute asthma as the primary reason for presentation to the emergency department or for admission to hospital. Asthma diagnosis was defined by internationally accepted criteria. Studies were included if the intervention was usual medical care for the management of severe acute asthma plus NPPV applied through a nasal or facemask compared to usual medical care alone. Studies including patients with features of chronic obstructive pulmonary disease (COPD) were excluded unless data were provided separately for patients with asthma in studies recruiting both COPD and asthmatic patients. DATA COLLECTION AND ANALYSIS: A combination of two review authors independently assessed trial quality and extracted data. Study authors were contacted for additional information where required. All data were analysed using RevMan 5.1. For continuous variables, a mean difference and 95% confidence interval were used and for dichotomous variables, risk ratio with 95% confidence interval were calculated. MAIN RESULTS: We identified six trials for inclusion. Five studies on 206 participants contributed data, while one study was available in abstract form only and was not fully incorporated into this review. For the primary outcome of endotracheal intubation there were two studies that contributed data: two intubations were needed in 45 participants on NPPV and no intubations in 41 control patients (risk ratio 4.48; 95% CI 0.23 to 89.13). There were no deaths in either of these studies. Length of hospital stay was reported in two studies, though meta-analysis was not possible. Hospitalisation was reported in one small study, in which there were three admissions out of 17 on NPPV and 10 admissions out of 16 in control patients (RR 0.28, 95% CI 0.09, 0.84). AUTHORS' CONCLUSIONS: This review of studies has highlighted the paucity of data that exist to support the use of NPPV in patients in status asthmaticus. As such this course of treatment remains controversial despite its continued use in current clinical practice. Larger, prospective randomised controlled trials of rigorous methodological design are needed to determine the role of NPPV in patients with asthma.