Role of artificial intelligence and internet of things based medical diagnostics smart health care system for a post-COVID-19 world

The present chapter is focused on the latest available technique and technology helpful in monitoring a large number of people having after corona disease effect. The most favorable way of monitoring a large number of people together can be possible only through the online wireless monitoring system. Artificial intelligence (AI) and machine learning (ML) technique-based systems can only handle this kind of post COVID scenario, as it is quick, accurate and many a time automatic. Thus present book chapter is focused on the review of the present latest AI/ML-based health monitoring systems. Separate sub-topics on cardiac, nephrology, and diabetics have been taken elaborately. The health monitoring system shall be capable of monitoring diseases such as cardiac, nephrology, and diabetes. Internet of things (IoT) wearable devices (medical sensors) are useful for recording various body parameters of the patient like comprehensive pressure, fever, physics activity, heart rate, etc. A real-time IoT-based system is capable to deliver the data to caregiving medical centers, doctors, or family members for proper treatment. IoT-based patient monitoring has a few drawbacks related to the error in analysis and acceptability among the medical fraternity. Other issues include security and privacy. Devices capture private health-related information and these data are highly vulnerable as being in the public domain through the internet. Thus it may attract unethical people for misuse. © 2023 Elsevier Inc. All rights reserved.

Virtual Cardiac Rehabilitation in a Pandemic Scenario: A Review of HCI Design Features, User Acceptance and Barriers

We report on the literature review of best practices in virtual cardiac rehabilitation (VCR), with a focus on technology usability, acceptance, and adoption barriers. We reviewed recent papers published in scientific conferences and journals on the topics of virtual cardiac rehabilitation and remote cardiac monitoring, with a publication dates from 2019 to 2021. Cardiovascular disease is a leading cause of mortality in elderly populations worldwide, and older adults are at an increased risk of COVID-19. Before the pandemic, the uptake of VCR technologies was slow due to concerns about technology effectiveness and cost. Since early 2020, better acceptance and adoption of VCR into routine care have been observed in many countries, including Canada. Some VCR components, like patient education or consultations are digitized relatively easy with online education sessions and resource repositories available for patients. Other elements such as supervised exercise and safe physical activity are more difficult to implement and require use of home cardiac monitoring technology. A proper HCI design of VCR services can contribute to better technology adoption by both service provider s and patients, and lead to improved patient outcomes. Design recommendations to increase adoption and improve user engagement with VCR by older adults include using multimodal interfaces, providing structured training and support, tailoring content and mode of delivery to the user, enabling automatic data transfer and easy integration across various systems and devices, improving accuracy of home cardiac monitoring devices, and conducting systematic technology validation studies, including remote usability evaluations for VCR technologies as part of the technology adoption life cycle. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.

Arrhythmia patterns during and after hospitalization for COVID-19 infection detected via patch-based mobile cardiac telemetry.

BACKGROUND: Coronavirus infection is the cause of the current world-wide pandemic. Cardiovascular complications occur in 20-30% of patients with COVID-19 infection including myocardial injury and arrhythmias. Current understanding of specific arrhythmia type and frequency is limited. OBJECTIVE: We aimed to analyze arrhythmia type and frequency in patients with COVID infection, identifying arrhythmia patterns over time during hospitalization and post discharge utilizing a patch based mobile cardiac telemetry system. METHODS: A prospective cohort study during the COVID-19 pandemic was performed. We included in our study patients hospitalized with COVID-19 infection who had a patch-based mobile telemetry device placed for cardiac monitoring. RESULTS: Quantitative reports for 59 patients were available for analysis. Arrhythmias were detected in 72.9% of patients and at a consistent frequency throughout the monitoring period in 52.9%-89.5% of patients daily. The majority of arrhythmias were SVT (59.3% of patients) and AF (22.0%). New onset AF was noted in 15.0% of all patients and was significantly associated with older age (OR 1.4 for 5 yrs. difference; 95% CI 1.03-2.13). Of 9 patients who were discharged with continued patch monitoring, 7 (78%) had arrhythmic events during their outpatient monitoring period. CONCLUSION: In COVID-19 patients arrhythmias were observed throughout hospitalization with a consistent daily frequency. Patients continued to exhibit cardiac arrhythmias after hospital discharge of a type and frequency similar to that seen during hospitalization. These findings suggest that the risk of arrhythmia associated with COVID infection remains elevated throughout the hospital course as well as following hospital discharge.

Predicting QT interval prolongation in patients diagnosed with the 2019 novel coronavirus infection.

INTRODUCTION: 2019 novel coronavirus (COVID-19) patients frequently develop QT interval prolongation that predisposes them to Torsades de Pointes and sudden cardiac death. Continuous cardiac monitoring has been recommended for any COVID-19 patient with a Tisdale Score of seven or more. This recommendation, however, has not been validated. METHODS: We included 178 COVID-19 patients admitted to a non-intensive care unit setting of a tertiary academic medical center. A receiver operating characteristics curve was plotted to determine the accuracy of the Tisdale Score to predict QT interval prolongation. Multivariable analysis was performed to identify additional predictors. RESULTS: The area under the curve of the Tisdale Score was 0.60 (CI 95%, 0.46-0.75). Using the cutoff of seven to stratify COVID-19, patients had a sensitivity of 85.7% and a specificity of 7.6%. Risk factors independently associated with QT interval prolongation included a history of end-stage renal disease (ESRD) (OR, 6.42; CI 95%, 1.28-32.13), QTc ≥450 ms on admission (OR, 5.90; CI 95%, 1.62-21.50), and serum potassium ≤3.5 mmol/L during hospitalization (OR, 4.97; CI 95%, 1.51-16.36). CONCLUSION: The Tisdale Score is not a useful tool to stratify hospitalized non-critical COVID-19 patients based on their risks of developing QT interval prolongation. Clinicians should initiate continuous cardiac monitoring for patients who present with a history of ESRD, QTc ≥450 ms on admission or serum potassium ≤3.5 mmol/L.

Kinocardiography Derived from Ballistocardiography and Seismocardiography Shows High Repeatability in Healthy Subjects.

Recent years have witnessed an upsurge in the usage of ballistocardiography (BCG) and seismocardiography (SCG) to record myocardial function both in normal and pathological populations. Kinocardiography (KCG) combines these techniques by measuring 12 degrees-of-freedom of body motion produced by myocardial contraction and blood flow through the cardiac chambers and major vessels. The integral of kinetic energy (iK) obtained from the linear and rotational SCG/BCG signals, and automatically computed over the cardiac cycle, is used as a marker of cardiac mechanical function. The present work systematically evaluated the test-retest (TRT) reliability of KCG iK derived from BCG/SCG signals in the short term (<15 min) and long term (3-6 h) on 60 healthy volunteers. Additionally, we investigated the difference of repeatability with different body positions. First, we found high short-term TRT reliability for KCG metrics derived from SCG and BCG recordings. Exceptions to this finding were limited to metrics computed in left lateral decubitus position where the TRT reliability was moderate-to-high. Second, we found low-to-moderate long-term TRT reliability for KCG metrics as expected and confirmed by blood pressure measurements. In summary, KCG parameters derived from BCG/SCG signals show high repeatability and should be further investigated to confirm their use for cardiac condition longitudinal monitoring.

Inpatient cardiac monitoring using a patch-based mobile cardiac telemetry system during the COVID-19 pandemic.

INTRODUCTION: Coronavirus disease 2019 (COVID-19) is a worldwide pandemic, and cardiovascular complications and arrhythmias in these patients are common. Cardiac monitoring is recommended for at risk patients; however, the availability of telemetry capable hospital beds is limited. We sought to evaluate a patch-based mobile telemetry system for inpatient cardiac monitoring during the pandemic. METHODS: A prospective cohort study was performed of inpatients hospitalized during the pandemic who had mobile telemetry devices placed; patients were studied up until the time of discharge or death. The primary outcome was a composite of management changes based on data obtained from the system and detection of new arrhythmias. Other clinical outcomes and performance characteristics of the mobile telemetry system were studied. RESULTS: Eighty-two patients underwent mobile telemetry device placement, of which 31 (37.8%) met the primary outcome, which consisted of 24 (29.3%) with new arrhythmias detected and 18 (22.2%) with management changes. Twenty-one patients (25.6%) died during the study, but none from primary arrhythmias. In analyses, age and heart failure were associated with the primary outcome. Monitoring occurred for an average of 5.3 ± 3.4 days, with 432 total patient-days of monitoring performed; of these, QT-interval measurements were feasible in 400 (92.6%). CONCLUSION: A mobile telemetry system was successfully implemented for inpatient use during the COVID-19 pandemic and was shown to be useful to inform patient management, detect occult arrhythmias, and monitor the QT-interval. Patients with advanced age and structural heart disease may be more likely to benefit from this system.