Mobile 5P-Medicine Approach for Cardiovascular Patients.

Journal: Sensors (Basel, Switzerland)
Published Date:

Abstract

Medicine is heading towards personalized care based on individual situations and conditions. With smartphones and increasingly miniaturized wearable devices, the sensors available on these devices can perform long-term continuous monitoring of several user health-related parameters, making them a powerful tool for a new medicine approach for these patients. Our proposed system, described in this article, aims to develop innovative solutions based on artificial intelligence techniques to empower patients with cardiovascular disease. These solutions will realize a novel 5P (Predictive, Preventive, Participatory, Personalized, and Precision) medicine approach by providing patients with personalized plans for treatment and increasing their ability for self-monitoring. Such capabilities will be derived by learning algorithms from physiological data and behavioral information, collected using wearables and smart devices worn by patients with health conditions. Further, developing an innovative system of smart algorithms will also focus on providing monitoring techniques, predicting extreme events, generating alarms with varying health parameters, and offering opportunities to maintain active engagement of patients in the healthcare process by promoting the adoption of healthy behaviors and well-being outcomes. The multiple features of this future system will increase the quality of life for cardiovascular diseases patients and provide seamless contact with a healthcare professional.

Authors

  • Ivan Miguel Pires
    Instituto de Telecomunicações, Universidade da Beira Interior, 6200-001 Covilhã, Portugal; Computer Science Department, Polytechnic Institute of Viseu, 3504-510 Viseu, Portugal; UICISA:E Research Centre, School of Health, Polytechnic Institute of Viseu, 3504-510 Viseu, Portugal. Electronic address: impires@it.ubi.pt.
  • Hanna Vitaliyivna Denysyuk
    Instituto de Telecomunicações, Universidade da Beira Interior, 6200-001 Covilhã, Portugal.
  • María Vanessa Villasana
    Centro Hospitalar do Baixo Vouga, 3810-164 Aveiro, Portugal.
  • Juliana Sá
    Faculty of Health Sciences, Universidade da Beira Interior, 6200-506 Covilhã, Portugal.
  • Petre Lameski
    Faculty of Computer Science and Engineering, SS. Cyril and Methodius University, 1000 Skopje, North Macedonia.
  • Ivan Chorbev
    Faculty for Computer Science and Engineering, University Ss Cyril and Methodius in Skopje, North Macedonia working in the area of eHealth and assistive technologies.
  • Eftim Zdravevski
    Faculty of Computer Science and Engineering, Saints Cyril and Methodius University, Skopje, Macedonia.
  • Vladimir Trajkovik
    Faculty of Computer Science and Engineering, University "Ss Cyril and Methodius", 1000 Skopje, Macedonia. trvlado@finki.ukim.mk.
  • José Francisco Morgado
    Computer Science Department, Polytechnic Institute of Viseu, 3504-510 Viseu, Portugal.
  • Nuno M Garcia
    Department of Informatics, Instituto de Telecomunicações and ALLab Assisted Living Computing and Telecommunications Laboratory, Universidade da Beira Interior, Covilhã, Portugal.