ArticleSensors (Basel, Switzerland)2022
Remotely Monitoring COVID-19 Patient Health Condition Using Metaheuristics Convolute Networks from IoT-Based Wearable Device Health Data.
Article in Sensors (Basel, Switzerland), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers, 1 of them a synthesis that pooled it.
What it found
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The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
15 citing papers in PubMed, 1 synthesis or guideline pooled it.
- A systematic review and knowledge mapping on ICT-based remote and automatic COVID-19 patient monitoring and care.BMC health services research · 2023Pooled it
- A novel IoT-aware wearable sensor device for healthcare data management framework using hybrid optimization algorithm.Physical and engineering sciences in medicine · 2026Article
- PhysioDimClassifier-imbalance data classifier model for IoMT-based remote patient monitoring systems.MethodsX · 2025Article
- Applications of Machine Learning (ML) and Mathematical Modeling (MM) in Healthcare with Special Focus on Cancer Prognosis and Anticancer Therapy: Current Status and Challenges.Pharmaceutics · 2024Review
- Wearable Devices and Explainable Unsupervised Learning for COVID-19 Detection and Monitoring.Diagnostics (Basel, Switzerland) · 2023Article
- Remote Patient Activity Monitoring System by Integrating IoT Sensors and Artificial Intelligence Techniques.Sensors (Basel, Switzerland) · 2023Article
- The Use of a Technology Acceptance Model (TAM) to Predict Patients' Usage of a Personal Health Record System: The Role of Security, Privacy, and Usability.International journal of environmental research and public health · 2023Article
- Decision trees for early prediction of inadequate immune response to coronavirus infections: a pilot study on COVID-19.Frontiers in medicine · 2023Article
- Article
- A Review of Recent Advances in Vital Signals Monitoring of Sports and Health via Flexible Wearable Sensors.Sensors (Basel, Switzerland) · 2022Review
- The Role of Personality and Top Management Support in Continuance Intention to Use Electronic Health Record Systems among Nurses.International journal of environmental research and public health · 2022Article
- Accuracy and Precision of Wearable Devices for Real-Time Monitoring of Swimming Athletes.Sensors (Basel, Switzerland) · 2022Article
- Exposure Detection Applications Acceptance: The Case of COVID-19.International journal of environmental research and public health · 2022Article
- Machine learning applications for COVID-19 outbreak management.Neural computing & applications · 2022Review
- Article
Corrections and comments
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Authors and funding
11 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Today, COVID-19-patient health monitoring and management are major public health challenges for technologies. This research monitored COVID-19 patients by using the Internet of Things. IoT-based collected real-time GPS helps alert the patient automatically to reduce risk factors. Wearable IoT devices are attached to the human body, interconnected with edge nodes, to investigate data for making health-condition decisions. This system uses the wearable IoT sensor, cloud, and web layers to explore the patient's health condition remotely. Every layer has specific functionality in the COVID-19 symptoms' monitoring process. The first layer collects the patient health information, which is transferred to the second layer that stores that data in the cloud. The network examines health data and alerts the patients, thus helping users take immediate actions. Finally, the web layer notifies family members to take appropriate steps. This optimized deep-learning model allows for the management and monitoring for further analysis.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.