ArticleSensors (Basel, Switzerland)2017
Feasibility of a Secure Wireless Sensing Smartwatch Application for the Self-Management of Pediatric Asthma.
Article in Sensors (Basel, Switzerland), 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 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
19 citing papers in PubMed, 2 syntheses or guidelines pooled it, 47 citations in OpenAlex.
- Exploring the Use of Smartwatches and Activity Trackers for Health-Related Purposes for Children Aged 5 to 11 years: Systematic Review.Journal of medical Internet research · 2025Pooled it
- A Systematic Review of Patient-Facing Visualizations of Personal Health Data.Applied clinical informatics · 2019Pooled it
- Artificial Intelligence in Asthma and COPD: Current Status and Future Potential.Journal of clinical medicine · 2026Review
- Monitoring Respiratory Health in Children With Acute Asthma Using Wearable Electrical Bioimpedance and Breath Sounds: Observational Case-Control Study.JMIR mHealth and uHealth · 2026Observational
- Artificial Intelligence in Medicine.Thoracic research and practice · 2025Article
- Leveraging artificial intelligence for the management of preschool wheeze: A narrative review.Pediatric allergy and immunology : official publication of the European Society of Pediatric Allergy and Immunology · 2025Review
- Human Factors, Human-Centered Design, and Usability of Sensor-Based Digital Health Technologies: Scoping Review.Journal of medical Internet research · 2024Article
- Exploring Machine Learning Applications in Pediatric Asthma Management: Scoping Review.JMIR AI · 2024Article
- Clinical efficacy and satisfaction of a digital wheeze detector in a multicentre randomised controlled trial: the WheezeScan study.ERJ open research · 2024Article
- eHealth Technologies for Monitoring Pediatric Asthma at Home: Scoping Review.Journal of medical Internet research · 2023Article
- Digital Technologies for Children and Parents Sharing Self-Management in Childhood Chronic or Long-Term Conditions: A Scoping Review.Children (Basel, Switzerland) · 2021Article
- Semantic Data Mining in Ubiquitous Sensing: A Survey.Sensors (Basel, Switzerland) · 2021Review
- Artificial Intelligence and Machine Learning in Chronic Airway Diseases: Focus on Asthma and Chronic Obstructive Pulmonary Disease.International journal of medical sciences · 2021Review
- Machine Learning Within Studies of Early-Life Environmental Exposures and Child Health: Review of the Current Literature and Discussion of Next Steps.Current environmental health reports · 2020Review
- Biosensors in Occupational Safety and Health Management: A Narrative Review.International journal of environmental research and public health · 2020Review
- The Features of Mobile-Based Software in Self-Management of Patients with Asthma: A Review Article.Tanaffos · 2020Review
- Applying Multivariate Segmentation Methods to Human Activity Recognition From Wearable Sensors' Data.JMIR mHealth and uHealth · 2019Article
- Children Activity Recognition: Challenges and Strategies.Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference · 2018Article
- Automated Quality Control for Sensor Based Symptom Measurement Performed Outside the Lab.Sensors (Basel, Switzerland) · 2018Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
9 authors at 1 institution in 1 country.
Funding
Abstract
To address the need for asthma self-management in pediatrics, the authors present the feasibility of a mobile health (mHealth) platform built on their prior work in an asthmatic adult and child. Real-time asthma attack risk was assessed through physiological and environmental sensors. Data were sent to a cloud via a smartwatch application (app) using Health Insurance Portability and Accountability Act (HIPAA)-compliant cryptography and combined with online source data. A risk level (high, medium or low) was determined using a random forest classifier and then sent to the app to be visualized as animated dragon graphics for easy interpretation by children. The feasibility of the system was first tested on an adult with moderate asthma, then usability was examined on a child with mild asthma over several weeks. It was found during feasibility testing that the system is able to assess asthma risk with 80.10 ± 14.13% accuracy. During usability testing, it was able to continuously collect sensor data, and the child was able to wear, easily understand and enjoy the use of the system. If tested in more individuals, this system may lead to an effective self-management program that can reduce hospitalization in those who suffer from asthma.
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.