Literature DB >> 29075920

Primary Prevention of Asymptomatic Cardiovascular Disease Using Physiological Sensors Connected to an iOS App.

Leire Moreno-Alsasua1, Begonya Garcia-Zapirain1, J David Rodrigo-Carbonero2, Ibon Oleagordia Ruiz1, Sofiane Hamrioui3, Isabel de la Torre Díez4.   

Abstract

Cardiovascular disease is the first cause of death and disease and one of the leading causes of disability in developed countries. The prevalence of this disease is expected to increase in coming years although the death rate may be lower due to better treatment. To present the design and development of a technology solution for primary prevention of cardiovascular disease in asymptomatic patients. The system aims to raise the population's awareness of the importance of adopting healthy heart habits by using self-feedback techniques. A series of sensors which makes it possible to detect cardiovascular risk factors in asymptomatic patients were used. These sensors enable evaluation of heart rate, blood pressure, SpO2 -oxygen saturation in blood- and body temperature. This work has developed a modular solution centred on four parts: iOS app, sensors, server and web. The CoreBluetooth library, which carries out Bluetooth 4.0 communication, was used for the connection between the app and the sensors. The data files are stored on the iPad and the server by using CoreData and SQL mechanisms. The system was validated with 20 healthy volunteers and 10 patients with established structural heart disease. Once the samples had been obtained, a comparison of all the significant data was run, in addition to a statistical analysis. The result of this calculation was a total of 32 cases of first level significance correlations (p < 0.01), for example, the inverse relationship between the daily step count and high blood pressure (p = 0.008) and 24 s level cases (p < 0.05) such as the significant correlation between risk and age (p = 0.013). The system designed in this paper has made it possible to create an application capable of collecting data on cardiovascular risk factors through a sensor system that measures physiological variables and records physical activity and diet.

Entities:  

Keywords:  Monitoring; Primary detection; Withings blood pressure monitor; iHealth pulse oximeter; iOS

Mesh:

Year:  2017        PMID: 29075920     DOI: 10.1007/s10916-017-0840-2

Source DB:  PubMed          Journal:  J Med Syst        ISSN: 0148-5598            Impact factor:   4.460


  10 in total

1.  Epidemic of cardiovascular disease and stroke: the three main challenges. Presented at the 71st scientific sessions of the American Heart Association. Dallas, Texas.

Authors:  V Fuster
Journal:  Circulation       Date:  1999-03-09       Impact factor: 29.690

2.  Developing healthcare rule-based expert systems: case study of a heart failure telemonitoring system.

Authors:  Emily Seto; Kevin J Leonard; Joseph A Cafazzo; Jan Barnsley; Caterina Masino; Heather J Ross
Journal:  Int J Med Inform       Date:  2012-03-31       Impact factor: 4.046

3.  A comparative evaluation between conditions of the wrist band capacitively-coupled ECG recording through signal-to-noise ratio.

Authors:  Hideo Nakamura; Koichiro Shimada; Tatsuro Fujie
Journal:  Conf Proc IEEE Eng Med Biol Soc       Date:  2007

4.  Cost comparison between home telemonitoring and usual care of older adults: a randomized trial (Tele-ERA).

Authors:  Benjavan Upatising; Douglas L Wood; Walter K Kremers; Sharon L Christ; Yuehwern Yih; Gregory J Hanson; Paul Y Takahashi
Journal:  Telemed J E Health       Date:  2014-12-02       Impact factor: 3.536

Review 5.  27th Bethesda Conference: matching the intensity of risk factor management with the hazard for coronary disease events. Task Force 8. Organization of preventive cardiology service.

Authors:  T A Pearson; P E McBride; N H Miller; S C Smith
Journal:  J Am Coll Cardiol       Date:  1996-04       Impact factor: 24.094

6.  Analysis of myocardial infarction using discrete wavelet transform.

Authors:  E S Jayachandran; Paul Joseph K; R Acharya U
Journal:  J Med Syst       Date:  2009-05-20       Impact factor: 4.460

7.  From an expert-driven paper guideline to a user-centred decision support system: a usability comparison study.

Authors:  Ellen Kilsdonk; Linda W Peute; Rinke J Riezebos; Leontien C Kremer; Monique W M Jaspers
Journal:  Artif Intell Med       Date:  2013-05-15       Impact factor: 5.326

8.  Features and usability assessment of a patient-centered mobile application (HeartMapp) for self-management of heart failure.

Authors:  Ponrathi Athilingam; Miguel A Labrador; Elizabeth Frances J Remo; Laureen Mack; Alyanna Bianca San Juan; Amanda F Elliott
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Review 9.  The Framingham Heart Study and the epidemiology of cardiovascular disease: a historical perspective.

Authors:  Syed S Mahmood; Daniel Levy; Ramachandran S Vasan; Thomas J Wang
Journal:  Lancet       Date:  2013-09-29       Impact factor: 79.321

Review 10.  Mobile apps in cardiology: review.

Authors:  Borja Martínez-Pérez; Isabel de la Torre-Díez; Miguel López-Coronado; Jesús Herreros-González
Journal:  JMIR Mhealth Uhealth       Date:  2013-07-24       Impact factor: 4.773

  10 in total
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1.  A mobile app for Glaucoma diagnosis and its possible clinical applications.

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  1 in total

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