基于睡眠心电数据的人工智能抑郁评估系统-《中国医学物理学杂志》

文章信息/Info

Title:: Artificial intelligence system for depression assessment based on sleep ECG data

作者:: 肖碧波1; 唐健豪2; 曾加玉3; 王肖文2; 魏晓滨1; 1.佛山市第三人民医院设备科，广东佛山 528041； 2.佛山市第一人民医院设备科，广东佛山528000； 3.南部战区空军医院医学工程科，广东广州 510062

Author(s):: XIAO Bibo1; TANG Jianhao2; ZENG Jiayu3; WANG Xiaowen2; WEI Xiaobin1; 1. Department of Equipment, the Third Peoples Hospital of Foshan, Foshan 528041, China 2. Department of Equipment, the First Peoples Hospital of Foshan, Foshan 528000, China 3. Department of Medical Engineering, Air Force Hospital of Southern Theatre Command, Guangzhou 510062, China

摘要:: 睡眠障碍是抑郁症的评估因素之一，可从心电数据中提取特征值用于抑郁评估，辅助临床诊断。设计开发一种基于睡眠心电数据的人工智能抑郁评估系统，其中包含心电数据的分析、心电滤波和心电R波的定位。其间并进行数图转换，生成心电RR间期图。利用TensorFlow进行图像的增强处理后，构建卷积神经网络，最终得出睡眠心电数据的人工智能抑郁评估模型。

Abstract:: Abstract: Sleep disorder is one of the evaluation factors of depression, and the characteristic values can be extracted from ECG data for depression assessment and clinical diagnosis. An artificial intelligence system using sleep ECG data to carry out depression assessment is designed and developed, with the functions of ECG data analysis, ECG filtering and ECG R wave localization. The ECG RR interval graph is generated through the conversion from data to graph. After image enhancement with TensorFlow, a convolution neural network is constructed, and finally an artificial intelligence model for depression assessment based on sleep ECG data is obtained.