A real-time wireless wearable electroencephalography system based on Support Vector Machine for encephalopathy daily monitoring. (May 2018)

• Record Type: Journal Article
• Authors: Zhang, Qing; Wang, Pingping; Liu, Yan; Peng, Bo; Zhou, Yufu; Zhou, Zhiyong; Tong, Baotong; Qiu, Bensheng; Zheng, Yishan; Dai, Yakang
• Is Part Of: International journal of distributed sensor networks. Volume 14:Number 5(2018)
• Publication Date: 2018-05
• Subjects: Wearable system -- wireless -- electroencephalography -- encephalopathy -- Support Vector Machine -- daily monitoring; Sensor networks -- Periodicals; Intelligent agents (Computer software) -- Periodicals; Multisensor data fusion -- Periodicals; 681.2
• DOI: 10.1177/1550147718779562
• Languages: English
• ISSNs: 1550-1329

Abstract

Wearable electroencephalography systems of out-of-hospital can both provide complementary recordings and offer several benefits over long-term monitoring. However, several limitations were present in these new-born systems, for example, uncomfortable for wearing, inconvenient for retrieving the recordings by patients themselves, unable to timely provide accurate classification, and early warning information. Therefore, we proposed a wireless wearable electroencephalography system for encephalopathy daily monitoring, named as Brain-Health, which focused on the following three points: (a) the monitoring device integrated with electroencephalography acquisition sensors, signal processing chip, and Bluetooth, attached to a sport hat or elastic headband; (b) the mobile terminal with dedicated application, which is not only for continuous recording and displaying electroencephalography signal but also for early warning in real time; and (c) the encephalopathy's classification algorithm based on intelligent Support Vector Machine, which is used in a new application of wearable electroencephalography for encephalopathy daily monitoring. The results showed a high mean accuracy of 91.79% and 93.89% in two types of classification for encephalopathy. In conclusion, good performance of our Brain-Health system indicated the feasibility and effectiveness for encephalopathy daily monitoring and patients' health self-management.