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. 2013 May 16;13(5):6524-41.
doi: 10.3390/s130506524.

Mobile monitoring and reasoning methods to prevent cardiovascular diseases

Ramón Hervás  1 , Jesús Fontecha, David Ausín, Federico Castanedo, José Bravo, Diego López-de-Ipiña
Affiliations

Mobile monitoring and reasoning methods to prevent cardiovascular diseases

Ramón Hervás et al. Sensors (Basel). .

Abstract

With the recent technological advances, it is possible to monitor vital signs using Bluetooth-enabled biometric mobile devices such as smartphones, tablets or electric wristbands. In this manuscript, we present a system to estimate the risk of cardiovascular diseases in Ambient Assisted Living environments. Cardiovascular disease risk is obtained from the monitoring of the blood pressure by means of mobile devices in combination with other clinical factors, and applying reasoning techniques based on the Systematic Coronary Risk Evaluation Project charts. We have developed an end-to-end software application for patients and physicians and a rule-based reasoning engine. We have also proposed a conceptual module to integrate recommendations to patients in their daily activities based on information proactively inferred through reasoning techniques and context-awareness. To evaluate the platform, we carried out usability experiments and performance benchmarks.

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Figures

Figure 1.
Figure 1.
Sequence diagram: A new measure of blood pressure has been taken.
Figure 2.
Figure 2.
Sequence diagram: CVD Risk calculation.
Figure 3.
Figure 3.
Ontological concepts and properties involved in the example of axiomatic inference.
Figure 4.
Figure 4.
System Overview.
Figure 5.
Figure 5.
Summarized results about the use of the applications to monitoring patients with CVD. According to the ease of use, patients feel that the application is easy to use because the interaction is very simple and short and the mobile application responds mostly automatically.
Figure 6.
Figure 6.
Mobile application graphical user interface.
Figure 7.
Figure 7.
Mean and standard error of time queries for different combination of users.
Figure 8.
Figure 8.
Obtained throughput results for different combination of users.
See this image and copyright information in PMC

References

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