Next Article in Journal
Integration with 3D Visualization and IoT-Based Sensors for Real-Time Structural Health Monitoring
Next Article in Special Issue
Data Enhancement via Low-Rank Matrix Reconstruction in Pulsed Thermography for Carbon-Fibre-Reinforced Polymers
Previous Article in Journal
Unmanned Vehicles’ Placement Optimisation for Internet of Things and Internet of Unmanned Vehicles
Previous Article in Special Issue
Corona Discharge Characteristics under Variable Frequency and Pressure Environments
Study Protocol

Mobile 5P-Medicine Approach for Cardiovascular Patients

Instituto de Telecomunicações, Universidade da Beira Interior, 6200-001 Covilhã, Portugal
Escola de Ciências e Tecnologias, University of Trás-os-Montes e Alto Douro, Quinta de Prados, 5001-801 Vila Real, Portugal
Centro Hospitalar do Baixo Vouga, 3810-164 Aveiro, Portugal
Faculty of Health Sciences, Universidade da Beira Interior, 6200-506 Covilhã, Portugal
Centro Hospitalar e Universitário do Porto, 4099-001 Oporto, Portugal
Faculty of Computer Science and Engineering, SS. Cyril and Methodius University, 1000 Skopje, North Macedonia
Computer Science Department, Polytechnic Institute of Viseu, 3504-510 Viseu, Portugal
Author to whom correspondence should be addressed.
Academic Editor: Manuel José Cabral dos Santos Reis
Sensors 2021, 21(21), 6986;
Received: 16 September 2021 / Revised: 16 October 2021 / Accepted: 18 October 2021 / Published: 21 October 2021
(This article belongs to the Special Issue Data, Signal and Image Processing and Applications in Sensors II)
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. View Full-Text
Keywords: 5P-Medicine; digital health; mobile bio-sensing for medicine; patient empowerment technologies; artificial intelligence; cardiovascular diseases 5P-Medicine; digital health; mobile bio-sensing for medicine; patient empowerment technologies; artificial intelligence; cardiovascular diseases
Show Figures

Figure 1

MDPI and ACS Style

Pires, I.M.; Denysyuk, H.V.; Villasana, M.V.; Sá, J.; Lameski, P.; Chorbev, I.; Zdravevski, E.; Trajkovik, V.; Morgado, J.F.; Garcia, N.M. Mobile 5P-Medicine Approach for Cardiovascular Patients. Sensors 2021, 21, 6986.

AMA Style

Pires IM, Denysyuk HV, Villasana MV, Sá J, Lameski P, Chorbev I, Zdravevski E, Trajkovik V, Morgado JF, Garcia NM. Mobile 5P-Medicine Approach for Cardiovascular Patients. Sensors. 2021; 21(21):6986.

Chicago/Turabian Style

Pires, Ivan M., Hanna V. Denysyuk, María V. Villasana, Juliana Sá, Petre Lameski, Ivan Chorbev, Eftim Zdravevski, Vladimir Trajkovik, José F. Morgado, and Nuno M. Garcia 2021. "Mobile 5P-Medicine Approach for Cardiovascular Patients" Sensors 21, no. 21: 6986.

Find Other Styles
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Article Access Map by Country/Region

Back to TopTop