A real-time wireless wearable electroencephalography system based on Support Vector Machine for encephalopathy daily monitoring

Qing Zhang, Pingping Wang, Yan Liu, Bo Peng, Yufu Zhou, Zhiyong Zhou, Baotong Tong, Bensheng Qiu, Yishan Zheng and Yakang Dai

International Journal of Distributed Sensor Networks, 2018, vol. 14, issue 5, 1550147718779562

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.

Keywords: Wearable system; wireless; electroencephalography; encephalopathy; Support Vector Machine; daily monitoring (search for similar items in EconPapers)
Date: 2018
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Persistent link: https://EconPapers.repec.org/RePEc:sae:intdis:v:14:y:2018:i:5:p:1550147718779562

DOI: 10.1177/1550147718779562

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