Determination of Personalized Asthma Triggers From Multimodal Sensing and a Mobile App: Observational Study

TitleDetermination of Personalized Asthma Triggers From Multimodal Sensing and a Mobile App: Observational Study
Publication TypeJournal Article
Year of Publication2019
AuthorsRevathy Venkataramanan, Krishnaprasad Thirunarayan, Utkarshani Jaimini, Dipesh Kadariya, Hong Yung Yip, Maninder Kalra, Amit Sheth
JournalJMIR Pediatr Parent
Volume2
Paginatione14300
Date Published06/2019
ISSN Number2561-6722
KeywordsAsthma Management, childhood asthma, medical internet of things, medication adherence, patient-generated health data, pediatric asthma; asthma control, Personalized Digital Health, understanding and treatment of asthma
Abstract

Background: Asthma is a chronic pulmonary disease with multiple triggers. It can be managed by strict adherence to an asthma care plan and by avoiding these triggers. Clinicians cannot continuously monitor their patients’ environment and their adherence to an asthma care plan, which poses a significant challenge for asthma management.

Objective: In this study, pediatric patients were continuously monitored using low-cost sensors to collect asthma-relevant information. The objective of this study was to assess whether kHealth kit, which contains low-cost sensors, can identify personalized triggers and provide actionable insights to clinicians for the development of a tailored asthma care plan.

Methods: The kHealth asthma kit was developed to continuously track the symptoms of asthma in pediatric patients and monitor the patients’ environment and adherence to their care plan for either 1 or 3 months. The kit consists of an Android app–based questionnaire to collect information on asthma symptoms and medication intake, Fitbit to track sleep and activity, the Peak Flow meter to monitor lung functions, and Foobot to monitor indoor air quality. The data on the patient’s outdoor environment were collected using third-party Web services based on the patient’s zip code. To date, 107 patients consented to participate in the study and were recruited from the Dayton Children’s Hospital, of which 83 patients completed the study as instructed.

Results: Patient-generated health data from the 83 patients who completed the study were included in the cohort-level analysis. Of the 19% (16/83) of patients deployed in spring, the symptoms of 63% (10/16) and 19% (3/16) of patients suggested pollen and particulate matter (PM2.5), respectively, to be their major asthma triggers. Of the 17% (14/83) of patients deployed in fall, symptoms of 29% (4/17) and 21% (3/17) of patients suggested pollen and PM2.5, respectively, to be their major triggers. Among the 28% (23/83) of patients deployed in winter, PM2.5 was identified as the major trigger for 83% (19/23) of patients. Similar correlations were not observed between asthma symptoms and factors such as ozone level, temperature, and humidity. Furthermore, 1 patient from each season was chosen to explain, in detail, his or her personalized triggers by observing temporal associations between triggers and asthma symptoms gathered using the kHealth asthma kit.

Conclusions: The continuous monitoring of pediatric asthma patients using the kHealth asthma kit generates insights on the relationship between their asthma symptoms and triggers across different seasons. This can ultimately inform personalized asthma management and intervention plans.

DOI10.2196/14300
Full Text

Citation:
Venkataramanan R, Thirunarayan K, Jaimini U, Kadariya D, Yip HY, Kalra M, Sheth A. "Determination of Personalized Asthma Triggers From Multimodal Sensing and a Mobile App: Observational Study" JMIR Pediatr Parent 2019;2(1):e14300, DOI: 10.2196/14300.

URL:=http://pediatrics.jmir.org/2019/1/e14300/

Projects: 
kHealth