RESEARCH ARTICLE


CaRiSMA 1.0: Cardiac Risk Self-Monitoring Assessment



Angela Agostinelli, Micaela Morettini, Agnese Sbrollini, Elvira Maranesi, Lucia Migliorelli, Francesco Di Nardo, Sandro Fioretti, Laura Burattini*
Department of Information Engineering, Università Politecnica delle Marche, via Brecce Bianche 60131, Ancona, Italy


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© 2017 Ing. Laura Burattini.

open-access license: This is an open access article distributed under the terms of the Creative Commons Attribution 4.0 International Public License (CC-BY 4.0), a copy of which is available at: https://creativecommons.org/licenses/by/4.0/legalcode. This license permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

* Address correspondence to this author at the Department of Information Engineering (Università Politecnica delle Marche) via Brecce Bianche, 60131 Ancona, Italy, Tel: +39 071 220 4461, Fax: +39 071 220 4224; E-mail: l.burattini@univpm.it


Abstract

Background:

Sport-related sudden cardiac death (SRSCD) can only be fought through prevention.

Objective:

The aim of this study is to propose an innovative software application, CaRiSMA 1.0 (Cardiac Risk Self-Monitoring Assessment), as a potential tool to help contrasting SRSCD and educating to a correct training.

Methods:

CaRiSMA 1.0 analyzes the electrocardiographic and heart-rate (HR) signals acquired during a training session through wearable sensors and provides intuitive graphical outputs consisting of two traffic lights, one related to cardiac health, based on resting QTc (a parameter quantifying the duration of ventricular contraction and subsequent relaxation), and one related to training, based on exercise HR. Safe and worthwhile training sessions have green traffic lights. A red QTc traffic light indicates the need of a medical consultation, whereas a red HR traffic light indicate the need of a reduction of training intensity. By way of example, CaRiSMA 1.0 was applied to sample data acquired in 10 volunteers (age= 27±11 years; males/females 3/7).

Results:

Two acquisitions (20.0%) were rejected because too noisy, indicating that wearable sensors may record poor quality signals. The QTc traffic light was red in 1 case, indicating that people practicing sport may not be aware of being at risk. The HR traffic light was red in 0 cases.

Conclusion:

CaRiSMA 1.0 is a software application that, for the first time in the sport context, uses QTc, the most important index of cardiac risk in clinics. Thus, it has the potential for giving a contribution in the fight against SRSCD.

Keywords: Sport-related sudden cardiac death, Prevention, Wearable sensors, Software application, Athletes cardiac risk self-monitoring, QTc interval.