{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,10]],"date-time":"2026-02-10T16:01:02Z","timestamp":1770739262282,"version":"3.49.0"},"reference-count":25,"publisher":"Emerald","issue":"6","license":[{"start":{"date-parts":[[2008,10,17]],"date-time":"2008-10-17T00:00:00Z","timestamp":1224201600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.emerald.com\/insight\/site-policies"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2008,10,17]]},"abstract":"<jats:sec><jats:title content-type=\"abstract-heading\">Purpose<\/jats:title><jats:p>This paper aims to present a novel embedded\u2010internet robot system based on an internet robot agent and the brain\u2010computer interface (BCI) scheme.<\/jats:p><\/jats:sec><jats:sec><jats:title content-type=\"abstract-heading\">Design\/methodology\/approach<\/jats:title><jats:p>A highly flexible and well\u2010integrated embedded ethernet robot (eRobot) was designed with enhanced mobility. In the eRobot, a circuit core module called a tiny network bridge (TNB) is designed to reduce robotic system cost and increase its mobility and developmental flexibility. The TNB enables users to control eRobot motion via embedded ethernet technology. Through electroencephalogram (EEG) feedback training, the command translation unit (CTU) and alertness level detection unit (ADU) allow the eRobot to perform specific motions (for example, lying down or standing up) to reflect alertness levels of the user, and move forward, turn left or right following the user's command.<\/jats:p><\/jats:sec><jats:sec><jats:title content-type=\"abstract-heading\">Findings<\/jats:title><jats:p>After a short training period, subjects could achieve at least 70 percent accuracy in the CTU game testing. And the error rate of ADU, estimated from the results of classifying 496 labeled EEG epochs, was approximately 10.7 percent. Combining an encoding procedure, the commands issued from the CTU could prevent the robot from performing undesired actions.<\/jats:p><\/jats:sec><jats:sec><jats:title content-type=\"abstract-heading\">Originality\/value<\/jats:title><jats:p>The eRobot could reflect some physiological human states and be controlled by users with our economical design and only two bipolar EEG channels adopted. Thus, users could make the EEG\u2010based eRobot agent his or her representative. Based on the proposed EEG\u2010based eRobot system, a robot with increased sophistication will be developed in the future for use by disabled patients.<\/jats:p><\/jats:sec>","DOI":"10.1108\/01439910810909501","type":"journal-article","created":{"date-parts":[[2008,11,1]],"date-time":"2008-11-01T08:08:00Z","timestamp":1225526880000},"page":"507-519","source":"Crossref","is-referenced-by-count":6,"title":["Brain\u2010controlled robot agent: an EEG\u2010based eRobot agent"],"prefix":"10.1108","volume":"35","author":[{"given":"Li\u2010Wei","family":"Wu","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Hsien\u2010Cheng","family":"Liao","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jwu\u2010Sheng","family":"Hu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Pei\u2010Chen","family":"Lo","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"140","reference":[{"key":"key2022030720214724700_b1","unstructured":"Bentham, J. 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