Heart rate variability-derived features based on deep neural network for distinguishing different anaesthesia states.
Jian ZhanZhuo-Xi WuZhen-Xin DuanGui-Ying YangZhi-Yong DuXiao-Hang BaoHong LiPublished in: BMC anesthesiology (2021)
The incorporation of four HRV-derived features in the time and frequency domain and a deep neural network could accurately distinguish between different anaesthesia states; however, this study is a pilot feasibility study. The proposed method-with other evaluation methods, such as EEG-is expected to assist anaesthesiologists in the accurate evaluation of the DoA.