@inproceedings{42338f5b6c6c42fcbd442648ead55312,
title = "Ubiquitous blood pressure monitoring using EEG and PPG signals",
abstract = "The Vita-H1 system represents an innovative way of accurately predicting systolic and diastolic blood pressures using PPG and ECG signals. As a cuff-less system, Vita-H1 allows convenient continuous BP monitoring throughout the day. Based on a test set of 90 people, the mean absolute bias for SBP (|H1 - true|) is 5.4mmHg and for DBP is 4.4mmHg, which complies with the IEEE1708-2014standard (MAD<=7mmHg). The Vita-H1 combines big data analytics based on a large training data and individual predictive analytics based on individual caliber data. The big data analytic is performed on a remote server and the results are downloaded to the smart-phone app. Individual updates can be computed off-line and real-time on the smart-phone.",
keywords = "Cloud computing, Cuff-less blood pressure (BP), Internet of things, Pulse transmit time, Pulse wave velocity (PWV), Supervised learning, Ubiquitous sensing, Wearable computing",
author = "Ying Lu and Heng Peng and Jiwei Zhao and Ziming Deng and Zijian Huang and Jinchuan Zhang and Jian Deng and Zhiyong Wang and Chuanmin Wei",
year = "2017",
month = sep,
day = "11",
doi = "10.1145/3123024.3123187",
language = "English (US)",
series = "UbiComp/ISWC 2017 - Adjunct Proceedings of the 2017 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2017 ACM International Symposium on Wearable Computers",
publisher = "Association for Computing Machinery, Inc",
pages = "257--260",
booktitle = "UbiComp/ISWC 2017 - Adjunct Proceedings of the 2017 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2017 ACM International Symposium on Wearable Computers",
note = "2017 ACM International Joint Conference on Pervasive and Ubiquitous Computing and ACM International Symposium on Wearable Computers, UbiComp/ISWC 2017 ; Conference date: 11-09-2017 Through 15-09-2017",
}