Delirium is an important syndrome in intensive care unit (ICU) patients, however, its characteristics are still unclear. Many evidences showed that this syndrome can be related to the autonomic instability. In this study, we aimed to investigate the possible alterations of autonomic nervous system (ANS) in delirium patients in ICU. Electrocardiography (ECG) of every ICU patient was measured during routine daily ICU care, and the data were gathered to evaluate the heart rate variability (HRV). HRV of total 60 patients were analyzed in time, frequency and non-linear domains. As a result, we found that heart rates of delirium patients were more variable and irregular than non-delirium patients. These findings may facilitate early detection and prevention of delirium in ICU.
|Title of host publication||2017 39th Annual International Conference of the IEEE Engineering in Medicine and Biology Society|
|Subtitle of host publication||Smarter Technology for a Healthier World, EMBC 2017 - Proceedings|
|Publisher||Institute of Electrical and Electronics Engineers Inc.|
|Number of pages||4|
|Publication status||Published - 2017 Sep 13|
|Event||39th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2017 - Jeju Island, Korea, Republic of|
Duration: 2017 Jul 11 → 2017 Jul 15
|Name||Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS|
|Other||39th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2017|
|Country||Korea, Republic of|
|Period||17/7/11 → 17/7/15|
Bibliographical noteFunding Information:
* This research was supported by a grant of the Korea Health Technology R&D Project through the Korea Health Industry Development Institute(KHIDI), funded by the Ministry of Health & Welfare, Republic of Korea (grant number: HI16C0132), and it was also supported by the GIST Research Institute (GRI) in 2017.
© 2017 IEEE.
All Science Journal Classification (ASJC) codes
- Signal Processing
- Biomedical Engineering
- Computer Vision and Pattern Recognition
- Health Informatics