EEG-Based Detection Model for Evaluating and Improving Learning Attention
People are often tempted by external factors which lead to decreased attention. Failing to concentrate over the long term will gradually cause the inability to focus, which creates obstacles for learning and decreases one’s ability to learn. However, using the proper recovery method, attention can b...
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Veröffentlicht in: | Journal of medical and biological engineering 2018-12, Vol.38 (6), p.847-856 |
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creator | Chiang, Hsiu-Sen Hsiao, Kuo-Lun Liu, Liang-Chi |
description | People are often tempted by external factors which lead to decreased attention. Failing to concentrate over the long term will gradually cause the inability to focus, which creates obstacles for learning and decreases one’s ability to learn. However, using the proper recovery method, attention can be restored, thereby improving learning effectiveness. Thus, how to measure a student’s attention level precisely, and how to provide an effective attention recovery method for are topics worth attention in the field of learning. An attention level assessment model based on EEG analysis is developed to measure subjects’ attention level precisely during learning exercises. The study also observes the relationship between brain wave changes and varying attention levels during learning, and provides attention recovery methods that can help students restore attention and improve their learning efficiency. The study finds that napping is a good recovery method which can help male and female leaners recover their focus states. Conversely, adopting a recovery method which the participant finds more attractive (e.g., playing mobile games or watching YouTube) leads to increased focus on the more attractive activity, and fails to restore attention to the original task. |
doi_str_mv | 10.1007/s40846-017-0344-z |
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Failing to concentrate over the long term will gradually cause the inability to focus, which creates obstacles for learning and decreases one’s ability to learn. However, using the proper recovery method, attention can be restored, thereby improving learning effectiveness. Thus, how to measure a student’s attention level precisely, and how to provide an effective attention recovery method for are topics worth attention in the field of learning. An attention level assessment model based on EEG analysis is developed to measure subjects’ attention level precisely during learning exercises. The study also observes the relationship between brain wave changes and varying attention levels during learning, and provides attention recovery methods that can help students restore attention and improve their learning efficiency. The study finds that napping is a good recovery method which can help male and female leaners recover their focus states. 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The study finds that napping is a good recovery method which can help male and female leaners recover their focus states. Conversely, adopting a recovery method which the participant finds more attractive (e.g., playing mobile games or watching YouTube) leads to increased focus on the more attractive activity, and fails to restore attention to the original task.</description><subject>Attention</subject><subject>Attention task</subject><subject>Biomedical Engineering and Bioengineering</subject><subject>Brain</subject><subject>Cell Biology</subject><subject>EEG</subject><subject>Engineering</subject><subject>Imaging</subject><subject>Learning</subject><subject>Original Article</subject><subject>Radiology</subject><subject>Recovery</subject><issn>1609-0985</issn><issn>2199-4757</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2018</creationdate><recordtype>article</recordtype><recordid>eNp1kE9LAzEQxYMoWLQfwNuC52j-Z3Osda2Fihc9h2STLS1ttiZpwX56s6zgybnMDLzfm-EBcIfRA0ZIPiaGaiYgwhIiyhg8X4AJwUpBJrm8BBMskIJI1fwaTFPaolJUCYHrCVg2zQI-meRd9eyzb_OmD9Vb7_yu6vpYNSezO5q8CevKBFct94fYn4Zt5U0MwzDL2YeBugVXndklP_3tN-DzpfmYv8LV-2I5n61gy7DKEBNJpXS2bW2LHO0odtxyYSw3gtXWCtlhq6wnStVCcq4kI5QgySjF3jtPb8D96Fte-Tr6lPW2P8ZQTmqCKWVCKYGKCo-qNvYpRd_pQ9zsTfzWGOkhND2GpktoeghNnwtDRiYVbVj7-Of8P_QDrNduSw</recordid><startdate>20181201</startdate><enddate>20181201</enddate><creator>Chiang, Hsiu-Sen</creator><creator>Hsiao, Kuo-Lun</creator><creator>Liu, Liang-Chi</creator><general>Springer Berlin Heidelberg</general><general>Springer Nature B.V</general><scope>AAYXX</scope><scope>CITATION</scope><scope>K9.</scope></search><sort><creationdate>20181201</creationdate><title>EEG-Based Detection Model for Evaluating and Improving Learning Attention</title><author>Chiang, Hsiu-Sen ; Hsiao, Kuo-Lun ; Liu, Liang-Chi</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c419t-127377dbccbc0d3f31d5b56ab5a648bb67f1b9be29986755974232074331eede3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2018</creationdate><topic>Attention</topic><topic>Attention task</topic><topic>Biomedical Engineering and Bioengineering</topic><topic>Brain</topic><topic>Cell Biology</topic><topic>EEG</topic><topic>Engineering</topic><topic>Imaging</topic><topic>Learning</topic><topic>Original Article</topic><topic>Radiology</topic><topic>Recovery</topic><toplevel>online_resources</toplevel><creatorcontrib>Chiang, Hsiu-Sen</creatorcontrib><creatorcontrib>Hsiao, Kuo-Lun</creatorcontrib><creatorcontrib>Liu, Liang-Chi</creatorcontrib><collection>CrossRef</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><jtitle>Journal of medical and biological engineering</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Chiang, Hsiu-Sen</au><au>Hsiao, Kuo-Lun</au><au>Liu, Liang-Chi</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>EEG-Based Detection Model for Evaluating and Improving Learning Attention</atitle><jtitle>Journal of medical and biological engineering</jtitle><stitle>J. Med. Biol. Eng</stitle><date>2018-12-01</date><risdate>2018</risdate><volume>38</volume><issue>6</issue><spage>847</spage><epage>856</epage><pages>847-856</pages><issn>1609-0985</issn><eissn>2199-4757</eissn><abstract>People are often tempted by external factors which lead to decreased attention. Failing to concentrate over the long term will gradually cause the inability to focus, which creates obstacles for learning and decreases one’s ability to learn. However, using the proper recovery method, attention can be restored, thereby improving learning effectiveness. Thus, how to measure a student’s attention level precisely, and how to provide an effective attention recovery method for are topics worth attention in the field of learning. An attention level assessment model based on EEG analysis is developed to measure subjects’ attention level precisely during learning exercises. The study also observes the relationship between brain wave changes and varying attention levels during learning, and provides attention recovery methods that can help students restore attention and improve their learning efficiency. The study finds that napping is a good recovery method which can help male and female leaners recover their focus states. Conversely, adopting a recovery method which the participant finds more attractive (e.g., playing mobile games or watching YouTube) leads to increased focus on the more attractive activity, and fails to restore attention to the original task.</abstract><cop>Berlin/Heidelberg</cop><pub>Springer Berlin Heidelberg</pub><doi>10.1007/s40846-017-0344-z</doi><tpages>10</tpages></addata></record> |
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subjects | Attention Attention task Biomedical Engineering and Bioengineering Brain Cell Biology EEG Engineering Imaging Learning Original Article Radiology Recovery |
title | EEG-Based Detection Model for Evaluating and Improving Learning Attention |
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