Publication Type

Journal Article

Publication Date

3-2016

Abstract

In our preliminary study, we proposed a smartphone-integrated, unobtrusive electrocardiogram (ECG) monitoring system, Sinabro, which monitors a user's ECG opportunistically during daily smartphone use without explicit user intervention. The proposed system also monitors ECG-derived features, such as heart rate (HR) and heart rate variability (HRV), to support the pervasive healthcare apps for smartphones based on the user's high-level contexts, such as stress and affective state levels. In this study, we have extended the Sinabro system by: (1) upgrading the sensor device; (2) improving the feature extraction process; and (3) evaluating extensions of the system. We evaluated these extensions with a good set of algorithm parameters that were suggested based on empirical analyses. The results showed that the system could capture ECG reliably and extract highly accurate ECG-derived features with a reasonable rate of data drop during the user's daily smartphone use.

Keywords

smartphone-integrated, unobtrusive sensing, opportunistic sensing, ECG, phone case-type, sensor

Discipline

Computer Sciences | Medicine and Health Sciences | Software Engineering

Research Areas

Software and Cyber-Physical Systems

Publication

Sensors

Volume

16

Issue

3

First Page

1

Last Page

16

ISSN

1424-8220

Identifier

10.3390/s16030361

Publisher

MDPI

Creative Commons License

Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License
This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License.

Additional URL

http://dx.doi.org/10.3390/s16030361

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