@article{a09e5648c72e40b683f85ce1e581504c,
title = "Editorial: AI empowered cerebro-cardiovascular health engineering",
keywords = "artificial intelligence, cerebro-cardiovascular health, diagnosis and treatment, identification and modeling, neurophysiological signal and image, rehabilitation, signal processing, wearable device",
author = "Lisheng Xu and Zengzhi Guo and Dingchang Zheng and Jianbao Zhang and Fei Chen and Rong Liu and Chunsheng Li and Wenjun Tan",
note = "Copyright {\textcopyright} 2023 Xu, Guo, Zheng, Zhang, Chen, Liu, Li and Tan. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.",
year = "2023",
month = dec,
day = "12",
doi = "10.3389/fphys.2023.1335573",
language = "English",
volume = "14",
journal = "Frontiers in Physiology",
issn = "1664-042X",
publisher = "Frontiers Media",
}