ReviewMicromachines2020
A Systematic Review of Non-Contact Sensing for Developing a Platform to Contain COVID-19.
Review in Micromachines, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers, 2 of them syntheses that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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
9 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- The Impact of SARS-CoV-2 Infection on Heart Rate Variability: A Systematic Review of Observational Studies with Control Groups.International journal of environmental research and public health · 2023Pooled it
- A Survey on Machine Learning and Internet of Medical Things-Based Approaches for Handling COVID-19: Meta-Analysis.Frontiers in public health · 2022Pooled it
- Introducing a Remote Patient Monitoring Usability Impact Model to Overcome Challenges.Sensors (Basel, Switzerland) · 2024Review
- Introducing the Pi-CON Methodology to Overcome Usability Deficits during Remote Patient Monitoring.Sensors (Basel, Switzerland) · 2024Review
- Non-Invasive Data Acquisition and IoT Solution for Human Vital Signs Monitoring: Applications, Limitations and Future Prospects.Sensors (Basel, Switzerland) · 2022Review
- Machine learning empowered COVID-19 patient monitoring using non-contact sensing: An extensive review.Journal of pharmaceutical analysis · 2022Review
- Non-Contact Smart Sensing of Physical Activities during Quarantine Period Using SDR Technology.Sensors (Basel, Switzerland) · 2022Article
- Improving Machine Learning Classification Accuracy for Breathing Abnormalities by Enhancing Dataset.Sensors (Basel, Switzerland) · 2021Article
- SARS-CoV-2 RNA Detection with Duplex-Specific Nuclease Signal Amplification.Micromachines · 2021Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
Abstract
The rapid spread of the novel coronavirus disease, COVID-19, and its resulting situation has garnered much effort to contain the virus through scientific research. The tragedy has not yet fully run its course, but it is already clear that the crisis is thoroughly global, and science is at the forefront in the fight against the virus. This includes medical professionals trying to cure the sick at risk to their own health; public health management tracking the virus and guardedly calling on such measures as social distancing to curb its spread; and researchers now engaged in the development of diagnostics, monitoring methods, treatments and vaccines. Recent advances in non-contact sensing to improve health care is the motivation of this study in order to contribute to the containment of the COVID-19 outbreak. The objective of this study is to articulate an innovative solution for early diagnosis of COVID-19 symptoms such as abnormal breathing rate, coughing and other vital health problems. To obtain an effective and feasible solution from existing platforms, this study identifies the existing methods used for human activity and health monitoring in a non-contact manner. This systematic review presents the data collection technology, data preprocessing, data preparation, features extraction, classification algorithms and performance achieved by the various non-contact sensing platforms. This study proposes a non-contact sensing platform for the early diagnosis of COVID-19 symptoms and monitoring of the human activities and health during the isolation or quarantine period. Finally, we highlight challenges in developing non-contact sensing platforms to effectively control the COVID-19 situation.
Indexed as
Identifiers
What OpenQuestion holds
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.