{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,4]],"date-time":"2025-10-04T08:11:40Z","timestamp":1759565500066},"reference-count":24,"publisher":"SAGE Publications","issue":"5","license":[{"start":{"date-parts":[[2018,5,1]],"date-time":"2018-05-01T00:00:00Z","timestamp":1525132800000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/journals.sagepub.com\/page\/policies\/text-and-data-mining-license"}],"funder":[{"name":"Postdoctoral Research Funding of Jiangsu Province","award":["1501089C"],"award-info":[{"award-number":["1501089C"]}]},{"name":"National 863 program of China","award":["2015AA020514"],"award-info":[{"award-number":["2015AA020514"]}]},{"name":"Jiangsu Key Technology RD Program","award":["BE2016613, BE2016010, BE2016010-3, BE2016010-4"],"award-info":[{"award-number":["BE2016613, BE2016010, BE2016010-3, BE2016010-4"]}]},{"name":"Jiangsu Key Research and Development Program","award":["BE2016010, BE2016613"],"award-info":[{"award-number":["BE2016010, BE2016613"]}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["81371537, 91432301"],"award-info":[{"award-number":["81371537, 91432301"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Industry Technological Innovation Projects","award":["SYG201606"],"award-info":[{"award-number":["SYG201606"]}]}],"content-domain":{"domain":["journals.sagepub.com"],"crossmark-restriction":true},"short-container-title":["International Journal of Distributed Sensor Networks"],"published-print":{"date-parts":[[2018,5]]},"abstract":"<jats:p> 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\u2019s 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\u2019 health self-management. <\/jats:p>","DOI":"10.1177\/1550147718779562","type":"journal-article","created":{"date-parts":[[2018,5,30]],"date-time":"2018-05-30T14:05:26Z","timestamp":1527689126000},"page":"155014771877956","update-policy":"http:\/\/dx.doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":12,"title":["A real-time wireless wearable electroencephalography system based on Support Vector Machine for encephalopathy daily monitoring"],"prefix":"10.1177","volume":"14","author":[{"given":"Qing","family":"Zhang","sequence":"first","affiliation":[{"name":"Center for Biomedical Engineering, University of Science and Technology of China, Hefei, 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