The nocturnal enuresis is challenging due to the increased social activities of the children. This disorder significantly bothers both the children and their parents in psychological, behavioral, social, and financial manners. However, the primary treatments have limitations and further are not able to completely cure the disorder. In order to reduce pain and burdens of patients and their parents, it is important to accurately estimate when the enuretic incident occurs in advance. For the estimation, we have comprehensively investigated various studies of the nocturnal enuresis in the diverse fields. Through the investigations, we have summarized four hypotheses of the physiological signals related to the enuretic moment. In order to conquer the nocturnal enuresis, we design a preliminary framework sensing and investigating the physiological signals with the sensors. Our synthesized approach to understand and estimate the moments of the enuretic incidents can establish a foothold to complete the promising prediction system.
|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/Territory||Korea, Republic of|
|Period||17/7/11 → 17/7/15|
Bibliographical noteFunding Information:
ACKNOWLEGMENT This work was partly supported by Institute for Information & Communications Technology Promotion(IITP) grant funded by the Korea government(MSIP) (R0124-16-0002, Emotional Intelligence Technology to Infer Human Emotion and Carry on Dialogue Accordingly) and the National Research Foundation of Korea(NRF) Grant funded by the Korean Government(MSIP)(NRF-2017R1C1B5018075).
© 2017 IEEE.
All Science Journal Classification (ASJC) codes
- Signal Processing
- Biomedical Engineering
- Computer Vision and Pattern Recognition
- Health Informatics