Name
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. |
Year | DOI | Venue |
|---|---|---|
2016 | 10.3390/s16030361 | SENSORS |
Keywords | Field | DocType |
smartphone-integrated,unobtrusive sensing,opportunistic sensing,ECG,phone case-type,sensor | Monitoring system,Heart rate variability,Real-time computing,Feature extraction,Engineering,Embedded system | Journal |
Volume | Issue | Citations |
16 | 3.0 | 4 |
PageRank | References | Authors |
0.41 | 5 | 7 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Sungjun Kwon | 1 | 15 | 2.18 |
| Dongseok Lee | 2 | 4 | 0.41 |
| Jeehoon Kim | 3 | 4 | 1.43 |
| Youngki Lee | 4 | 832 | 70.33 |
| Seungwoo Kang | 5 | 558 | 37.84 |
| Sangwon Seo | 6 | 4 | 0.41 |
| Kwang Suk Park | 7 | 266 | 46.43 |