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

Leire Moreno-Alsasua1, Begonya Garcia-Zapirain1, J David Rodrigo-Carbonero2

  • 1eVIDA - DeustoTechLIFE Research Group, Universidad de Deusto, Avda/Universidades 24, 48007, Bilbao, Spain.

Insights

A new technology solution uses sensors to monitor cardiovascular disease risk factors in asymptomatic individuals. This system promotes heart health awareness through self-feedback, aiding in early detection and prevention strategies.

Area of Science:

  • Biomedical Engineering
  • Cardiovascular Health Technology
  • Preventive Medicine

Background:

  • Cardiovascular disease (CVD) is a leading cause of death and disability globally.
  • Increasing CVD prevalence necessitates innovative primary prevention strategies for asymptomatic individuals.
  • Current prevention methods lack integrated, real-time monitoring of key risk factors.

Purpose of the Study:

  • To design and develop a technology solution for the primary prevention of cardiovascular disease.
  • To enhance public awareness of healthy heart habits using self-feedback mechanisms.
  • To enable early detection of cardiovascular risk factors in asymptomatic patients.

Main Methods:

  • Development of a modular system comprising an iOS app, sensors, server, and web interface.
  • Utilized Bluetooth 4.0 (CoreBluetooth) for sensor-app connectivity.
  • Integrated sensors to measure heart rate, blood pressure, SpO2 (oxygen saturation), and body temperature.
  • Employed CoreData and SQL for data storage on iPad and server.
  • Validated the system with 20 healthy volunteers and 10 patients with structural heart disease.

Main Results:

  • Identified 32 statistically significant correlations (p < 0.01) between physiological variables and risk factors.
  • Demonstrated an inverse relationship between daily step count and high blood pressure (p = 0.008).
  • Found significant correlations between cardiovascular risk and age (p = 0.013) among other findings (24 cases, p < 0.05).

Conclusions:

  • The developed system effectively collects data on cardiovascular risk factors via physiological sensors and activity tracking.
  • The technology facilitates primary prevention by increasing awareness and enabling self-monitoring of heart health.
  • This solution offers a promising approach for proactive cardiovascular disease management in the general population.

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