Article...IEEE...International Conference on Connected Health: Applications, Systems and Engineering Technologies. IEEE International Conference on Connected Health: Applications, Systems and Engineering Technologies2017
Wireless Sensor-Dependent Ecological Momentary Assessment for Pediatric Asthma mHealth Applications.
Article in ...IEEE...International Conference on Connected Health: Applications, Systems and Engineering Technologies. IEEE International Conference on Connected Health: Applications, Systems and Engineering Technologies, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers, 1 of them a synthesis 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
5 citing papers in PubMed, 1 synthesis or guideline pooled it.
- A Systematic Review on the Use of Wearable Body Sensors for Health Monitoring: A Qualitative Synthesis.Sensors (Basel, Switzerland) · 2020Pooled it
- Using Digital Health Technologies to Monitor Pain, Medication Adherence and Physical Activity in Young People with Juvenile Idiopathic Arthritis: A Feasibility Study.Healthcare (Basel, Switzerland) · 2024Article
- eHealth Technologies for Monitoring Pediatric Asthma at Home: Scoping Review.Journal of medical Internet research · 2023Article
- Memory-Aware Active Learning in Mobile Sensing Systems.IEEE transactions on mobile computing · 2022Article
- Personal information and public health: Design tensions in sharing and monitoring wellbeing in pregnancy.International journal of human-computer studies · 2020Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
Abstract
Pediatric asthma is a prevalent chronic disease condition that can benefit from wireless health systems through constant symptom management. In this paper, we propose a smart watch based wireless health system that incorporates wireless sensing and ecological momentary assessment (EMA) to determine an individual's asthma symptoms. Since asthma is a multifaceted disease, this approach provides individualized symptom assessments through various physiological and environmental wireless sensor based EMA triggers specific to common asthma exacerbations. Furthermore, the approach described here improves compliance to use of the system through insightful EMA scheduling related to sensor detected environmental and physiological changes, as well as the patient's own schedule. After testing under several real world conditions, it was found that the system is sensitive to both physiological and environmental conditions that would cause asthma symptoms. Furthermore, the EMA questionnaires that were triggered based on these changes were specific to the asthma trigger itself, allowing for invaluable context behind the data to be collected.
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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.