Literature DB >> 29354688

HIPAA Compliant Wireless Sensing Smartwatch Application for the Self-Management of Pediatric Asthma.

Anahita Hosseini1, Chris M Buonocore1, Sepideh Hashemzadeh1, Hannaneh Hojaiji2, Haik Kalantarian1, Costas Sideris1, Alex A T Bui3, Christine E King1, Majid Sarrafzadeh1.   

Abstract

Asthma is the most prevalent chronic disease among pediatrics, as it is the leading cause of student absenteeism and hospitalization for those under the age of 15. To address the significant need to manage this disease in children, the authors present a mobile health (mHealth) system that determines the risk of an asthma attack through physiological and environmental wireless sensors and representational state transfer application program interfaces (RESTful APIs). The data is sent from wireless sensors to a smartwatch application (app) via a Health Insurance Portability and Accountability Act (HIPAA) compliant cryptography framework, which then sends data to a cloud for real-time analytics. The asthma risk is then sent to the smartwatch and provided to the user via simple graphics for easy interpretation by children. After testing the safety and feasibility of the system in an adult with moderate asthma prior to testing in children, it was found that the analytics model is able to determine the overall asthma risk (high, medium, or low risk) with an accuracy of 80.10±14.13%. Furthermore, the features most important for assessing the risk of an asthma attack were multifaceted, highlighting the importance of continuously monitoring different wireless sensors and RESTful APIs. Future testing this asthma attack risk prediction system in pediatric asthma individuals may lead to an effective self-management asthma program.

Entities:  

Year:  2016        PMID: 29354688      PMCID: PMC5772883          DOI: 10.1109/BSN.2016.7516231

Source DB:  PubMed          Journal:  Int Conf Wearable Implant Body Sens Netw        ISSN: 2376-8886


  17 in total

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6.  Costs of asthma in the United States: 2002-2007.

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7.  Internet-based home monitoring and education of children with asthma is comparable to ideal office-based care: results of a 1-year asthma in-home monitoring trial.

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Journal:  Pediatrics       Date:  2007-03       Impact factor: 7.124

8.  Internet-based monitoring of asthma: a long-term, randomized clinical study of 300 asthmatic subjects.

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9.  A data encryption solution for mobile health apps in cooperation environments.

Authors:  Bruno M Silva; Joel J P C Rodrigues; Fábio Canelo; Ivo C Lopes; Liang Zhou
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10.  The evolution of mobile apps for asthma: an updated systematic assessment of content and tools.

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Journal:  BMC Med       Date:  2015-03-23       Impact factor: 8.775

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  7 in total

1.  A smartwatch-based framework for real-time and online assessment and mobility monitoring.

Authors:  Matin Kheirkhahan; Sanjay Nair; Anis Davoudi; Parisa Rashidi; Amal A Wanigatunga; Duane B Corbett; Tonatiuh Mendoza; Todd M Manini; Sanjay Ranka
Journal:  J Biomed Inform       Date:  2018-11-07       Impact factor: 6.317

2.  Wireless Sensor-Dependent Ecological Momentary Assessment for Pediatric Asthma mHealth Applications.

Authors:  Chris M Buonocore; Rosemary A Rocchio; Alfonso Roman; Christine E King; Majid Sarrafzadeh
Journal:  IEEE Int Conf Connect Health Appl Syst Eng Technol       Date:  2017-08-17

3.  A SURVEY OF SMARTWATCHES IN REMOTE HEALTH MONITORING.

Authors:  Christine E King; Majid Sarrafzadeh
Journal:  J Healthc Inform Res       Date:  2017-12-18

4.  Temperature and Humidity Calibration of a Low-Cost Wireless Dust Sensor for Real-Time Monitoring.

Authors:  Hannaneh Hojaiji; Haik Kalantarian; Alex A T Bui; Christine E King; Majid Sarrafzadeh
Journal:  2017 IEEE Sens Appl Symp (SAS) (2017)       Date:  2017-04-12

5.  Feasibility of a Secure Wireless Sensing Smartwatch Application for the Self-Management of Pediatric Asthma.

Authors:  Anahita Hosseini; Chris M Buonocore; Sepideh Hashemzadeh; Hannaneh Hojaiji; Haik Kalantarian; Costas Sideris; Alex A T Bui; Christine E King; Majid Sarrafzadeh
Journal:  Sensors (Basel)       Date:  2017-08-03       Impact factor: 3.576

6.  Applying Multivariate Segmentation Methods to Human Activity Recognition From Wearable Sensors' Data.

Authors:  Kenan Li; Rima Habre; Huiyu Deng; Robert Urman; John Morrison; Frank D Gilliland; José Luis Ambite; Dimitris Stripelis; Yao-Yi Chiang; Yijun Lin; Alex At Bui; Christine King; Anahita Hosseini; Eleanne Van Vliet; Majid Sarrafzadeh; Sandrah P Eckel
Journal:  JMIR Mhealth Uhealth       Date:  2019-02-07       Impact factor: 4.773

Review 7.  Predictive models for personalized asthma attacks based on patient's biosignals and environmental factors: a systematic review.

Authors:  Eman T Alharbi; Farrukh Nadeem; Asma Cherif
Journal:  BMC Med Inform Decis Mak       Date:  2021-12-09       Impact factor: 2.796

  7 in total

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