ReviewSN computer science2020
Wearable Technology to Assist the Patients Infected with Novel Coronavirus (COVID-19).
Review in SN computer science, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 40 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
40 citing papers in PubMed.
- Artificial Intelligence-Based Wearable Sensing Technologies for the Management of Cancer, Diabetes, and COVID-19.Biosensors · 2025Review
- Temperature-Responsive Hybrid Composite with Zero Temperature Coefficient of Resistance for Wearable Thermotherapy Pads.Micromachines · 2025Article
- Article
- Wearable Devices and Explainable Unsupervised Learning for COVID-19 Detection and Monitoring.Diagnostics (Basel, Switzerland) · 2023Article
- Predictive algorithm for the regional spread of coronavirus infection across the Russian Federation.BMC medical informatics and decision making · 2023Article
- Conv-CapsNet: capsule based network for COVID-19 detection through X-Ray scans.Multimedia tools and applications · 2023Article
- Engineering organ-on-a-chip systems to model viral infections.Biofabrication · 2023Review
- Randomized Controlled Trial Evaluating the Benefit of a Novel Clinical Decision Support System for the Management of COVID-19 Patients in Home Quarantine: A Study Protocol.International journal of environmental research and public health · 2023Article
- Survival study on deep learning techniques for IoT enabled smart healthcare system.Health and technology · 2023Article
- Multi-region machine learning-based novel ensemble approaches for predicting COVID-19 pandemic in Africa.Environmental science and pollution research international · 2023Article
- Wearable technology for early detection of COVID-19: A systematic scoping review.Preventive medicine · 2022Article
- Detecting COVID-19 patients via MLES-Net deep learning models from X-Ray images.BMC medical imaging · 2022Article
- Advanced materials used in wearable health care devices and medical textiles in the battle against coronavirus (COVID-19): A review.Journal of industrial textiles · 2022Review
- Predictive modeling for COVID-19 readmission risk using machine learning algorithms.BMC medical informatics and decision making · 2022Article
- Prognosis patients with COVID-19 using deep learning.BMC medical informatics and decision making · 2022Article
- A deep learning-driven low-power, accurate, and portable platform for rapid detection of COVID-19 using reverse-transcription loop-mediated isothermal amplification.Scientific reports · 2022Article
- A proficient approach to forecast COVID-19 spread via optimized dynamic machine learning models.Scientific reports · 2022Article
- Review on people's trust on home use medical devices during Covid-19 pandemic in India.Health and technology · 2022Review
- Home pulse oximetry after discharge from a quaternary-care children's hospital: Prescriber patterns and perspectives.Pediatric pulmonology · 2022Article
- When Patients Recover From COVID-19: Data-Driven Insights From Wearable Technologies.Frontiers in big data · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Wearable technology plays a significant role in our daily life as well as in the healthcare industry. The recent coronavirus pandemic has taken the world's healthcare systems by surprise. Although trials of possible vaccines are underway, it would take a long time before the vaccines are permitted for public use. Most of the government efforts are currently geared towards preventing the spread of the coronavirus and predicting probable hot zones. The essential and healthcare workers are the most vulnerable towards coronavirus infections due to their required proximity to potential coronavirus patients. Wearable technology can potentially assist in these regards by providing real-time remote monitoring, symptoms prediction, contact tracing, etc. The goal of this paper is to discuss the different existing wearable monitoring devices (respiration rate, heart rate, temperature, and oxygen saturation) and respiratory support systems (ventilators, CPAP devices, and oxygen therapy) which are frequently used to assist the coronavirus affected people. The devices are described based on the services they provide, their working procedures as well as comparative analysis of their merits and demerits with cost. A comparative discussion with probable future trends is also drawn to select the best technology for COVID-19 infected patients. It is envisaged that wearable technology is only capable of providing initial treatment that can reduce the spread of this pandemic.
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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.