Sinabro: A Smartphone-Integrated Opportunistic Electrocardiogram Monitoring System
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...
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doaj-28d4684b3fb642f7a540fadd0aa73be32020-11-25T00:46:31ZengMDPI AGSensors1424-82202016-03-0116336110.3390/s16030361s16030361Sinabro: A Smartphone-Integrated Opportunistic Electrocardiogram Monitoring SystemSungjun Kwon0Dongseok Lee1Jeehoon Kim2Youngki Lee3Seungwoo Kang4Sangwon Seo5Kwangsuk Park6Interdisciplinary Program in Bioengineering, Graduate School, Seoul National University, Seoul 08826, KoreaInterdisciplinary Program in Bioengineering, Graduate School, Seoul National University, Seoul 08826, KoreaInterdisciplinary Program in Bioengineering, Graduate School, Seoul National University, Seoul 08826, KoreaSchool of Information Systems, Singapore Management University, Singapore 178902, SingaporeSchool of Computer Science and Engineering, KOREATECH, Cheonan, 31253, KoreaThe 7th R&D Institute, Agency for Defense Development, Daejeon, 32024, KoreaDepartment of Biomedical Engineering, College of Medicine, Seoul National University, Seoul 03080, KoreaIn 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.http://www.mdpi.com/1424-8220/16/3/361opportunistic sensingunobtrusive sensingsmartphone-integratedphone case-typeECGsensor |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Sungjun Kwon Dongseok Lee Jeehoon Kim Youngki Lee Seungwoo Kang Sangwon Seo Kwangsuk Park |
spellingShingle |
Sungjun Kwon Dongseok Lee Jeehoon Kim Youngki Lee Seungwoo Kang Sangwon Seo Kwangsuk Park Sinabro: A Smartphone-Integrated Opportunistic Electrocardiogram Monitoring System Sensors opportunistic sensing unobtrusive sensing smartphone-integrated phone case-type ECG sensor |
author_facet |
Sungjun Kwon Dongseok Lee Jeehoon Kim Youngki Lee Seungwoo Kang Sangwon Seo Kwangsuk Park |
author_sort |
Sungjun Kwon |
title |
Sinabro: A Smartphone-Integrated Opportunistic Electrocardiogram Monitoring System |
title_short |
Sinabro: A Smartphone-Integrated Opportunistic Electrocardiogram Monitoring System |
title_full |
Sinabro: A Smartphone-Integrated Opportunistic Electrocardiogram Monitoring System |
title_fullStr |
Sinabro: A Smartphone-Integrated Opportunistic Electrocardiogram Monitoring System |
title_full_unstemmed |
Sinabro: A Smartphone-Integrated Opportunistic Electrocardiogram Monitoring System |
title_sort |
sinabro: a smartphone-integrated opportunistic electrocardiogram monitoring system |
publisher |
MDPI AG |
series |
Sensors |
issn |
1424-8220 |
publishDate |
2016-03-01 |
description |
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. |
topic |
opportunistic sensing unobtrusive sensing smartphone-integrated phone case-type ECG sensor |
url |
http://www.mdpi.com/1424-8220/16/3/361 |
work_keys_str_mv |
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_version_ |
1725264841153708032 |