Intelligent Biological Alarm Clock for Monitoring Autonomic Nervous Recovery During Nap
Corresponding author. Email: cwenwanh@swu.edu.cn
- DOI
- 10.2991/ijcis.d.190304.001How to use a DOI?
- Keywords
- Intelligent biological alarm clock; ECG; Heart rate; Heart rate variability; Autonomic nervous system
- Abstract
Nap is an effective way to reduce daily-level fatigue after several hours of work. However, no alarm clock, which intelligently manages the nap duration with good autonomic nervous recovery (ANR) from fatigue, has been reported in literature. In this work, an intelligent biological alarm clock algorithm was designed on the basis of electrocardiogram (ECG) and electroencephalogram (EEG) data acquisition and analysis. ECG data samples were collected from 31 subjects in 278 times of nap experiments and categorized into good, moderate, and poor ANR datasets according to the degree of sympathetic withdrawal and parasympathetic activation during the nap. In practice, the alarm clock automatically classified the new-coming ECG data as good, moderate, or poor ANR with a classifier trained by the abovementioned ANR datasets. A prototype system of the intelligent alarm clock algorithm was implemented and validated in real-scene naps. The prototype system detected falling asleep during the closed-eye naps with a true positive rate of 93.55% and a true negative rate of 100%.
- Copyright
- © 2019 The Authors. Published by Atlantis Press SARL.
- Open Access
- This is an open access article distributed under the CC BY-NC 4.0 license (http://creativecommons.org/licenses/by-nc/4.0/).
Download article (PDF)
View full text (HTML)
Cite this article
TY - JOUR AU - Jialan Xie AU - Wanhui Wen AU - Guangyuan Liu AU - Yongtao Li PY - 2019 DA - 2019/04/11 TI - Intelligent Biological Alarm Clock for Monitoring Autonomic Nervous Recovery During Nap JO - International Journal of Computational Intelligence Systems SP - 453 EP - 459 VL - 12 IS - 2 SN - 1875-6883 UR - https://doi.org/10.2991/ijcis.d.190304.001 DO - 10.2991/ijcis.d.190304.001 ID - Xie2019 ER -