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| DC Field | Value | Language |
|---|---|---|
| dc.contributor.author | Mathilde C., van Rossum | - |
| dc.contributor.author | Pedro M. Alves da, Silva | - |
| dc.contributor.author | Ying, Wang | - |
| dc.date.accessioned | 2023-03-24T03:52:11Z | - |
| dc.date.available | 2023-03-24T03:52:11Z | - |
| dc.date.issued | 2023 | - |
| dc.identifier.uri | https://link.springer.com/article/10.1007/s10877-023-00975-w | - |
| dc.identifier.uri | https://dlib.phenikaa-uni.edu.vn/handle/PNK/7131 | - |
| dc.description | CC BY | vi |
| dc.description.abstract | Wireless vital signs sensors are increasingly used for remote patient monitoring, but data analysis is often challenged by missing data periods. This study explored the performance of various imputation techniques for continuous vital signs measurements. Wireless vital signs measurements (heart rate, respiratory rate, blood oxygen saturation, axillary temperature) from surgical ward patients were used for repeated random simulation of missing data periods (gaps) of 5–60 min in two-hour windows. | vi |
| dc.language.iso | en | vi |
| dc.publisher | Springer | vi |
| dc.subject | patient monitoring | vi |
| dc.subject | missing data periods | vi |
| dc.title | Missing data imputation techniques for wireless continuous vital signs monitoring | vi |
| dc.type | Book | vi |
| Appears in Collections | ||
| OER- Y học- Điều dưỡng | ||
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