EEGLog: Lifelogging EEG Data When You Listen to Music
Self-tracking has been long discussed, which can monitor daily activities and help users to recall previous experiences. Such data-capturing technique is no longer limited to photos, text messages, or personal diaries in recent years. With the development of wearable EEG devices, we introduce a nove...
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| creator | Li, Jiyang Konnayil, Ann Gina Russell, Adam Wang, Dingran Jin, Yincheng Choi, Seokmin Jin, Zhanpeng |
| description | Self-tracking has been long discussed, which can monitor daily activities and
help users to recall previous experiences. Such data-capturing technique is no
longer limited to photos, text messages, or personal diaries in recent years.
With the development of wearable EEG devices, we introduce a novel modality of
logging EEG data while listening to music, and bring up the idea of the
neural-centric way of life with the designed data analysis application named
EEGLog. Four consumer-grade wearable EEG devices are explored by collecting EEG
data from 24 participants. Three modules are introduced in EEGLog, including
the summary module of EEG data, emotion reports, music listening activities,
and memorial moments, the emotion detection module, and the music
recommendation module. Feedback from interviews about using EEG devices and
EEGLog were obtained and analyzed for future EEG logging development. |
| doi_str_mv | 10.48550/arxiv.2211.14608 |
| format | Article |
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help users to recall previous experiences. Such data-capturing technique is no
longer limited to photos, text messages, or personal diaries in recent years.
With the development of wearable EEG devices, we introduce a novel modality of
logging EEG data while listening to music, and bring up the idea of the
neural-centric way of life with the designed data analysis application named
EEGLog. Four consumer-grade wearable EEG devices are explored by collecting EEG
data from 24 participants. Three modules are introduced in EEGLog, including
the summary module of EEG data, emotion reports, music listening activities,
and memorial moments, the emotion detection module, and the music
recommendation module. Feedback from interviews about using EEG devices and
EEGLog were obtained and analyzed for future EEG logging development.</description><identifier>DOI: 10.48550/arxiv.2211.14608</identifier><language>eng</language><subject>Computer Science - Human-Computer Interaction</subject><creationdate>2022-11</creationdate><rights>http://arxiv.org/licenses/nonexclusive-distrib/1.0</rights><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>228,230,780,885</link.rule.ids><linktorsrc>$$Uhttps://arxiv.org/abs/2211.14608$$EView_record_in_Cornell_University$$FView_record_in_$$GCornell_University$$Hfree_for_read</linktorsrc><backlink>$$Uhttps://doi.org/10.48550/arXiv.2211.14608$$DView paper in arXiv$$Hfree_for_read</backlink></links><search><creatorcontrib>Li, Jiyang</creatorcontrib><creatorcontrib>Konnayil, Ann Gina</creatorcontrib><creatorcontrib>Russell, Adam</creatorcontrib><creatorcontrib>Wang, Dingran</creatorcontrib><creatorcontrib>Jin, Yincheng</creatorcontrib><creatorcontrib>Choi, Seokmin</creatorcontrib><creatorcontrib>Jin, Zhanpeng</creatorcontrib><title>EEGLog: Lifelogging EEG Data When You Listen to Music</title><description>Self-tracking has been long discussed, which can monitor daily activities and
help users to recall previous experiences. Such data-capturing technique is no
longer limited to photos, text messages, or personal diaries in recent years.
With the development of wearable EEG devices, we introduce a novel modality of
logging EEG data while listening to music, and bring up the idea of the
neural-centric way of life with the designed data analysis application named
EEGLog. Four consumer-grade wearable EEG devices are explored by collecting EEG
data from 24 participants. Three modules are introduced in EEGLog, including
the summary module of EEG data, emotion reports, music listening activities,
and memorial moments, the emotion detection module, and the music
recommendation module. Feedback from interviews about using EEG devices and
EEGLog were obtained and analyzed for future EEG logging development.</description><subject>Computer Science - Human-Computer Interaction</subject><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2022</creationdate><recordtype>article</recordtype><sourceid>GOX</sourceid><recordid>eNotjs1qwkAUhWfjomgfoKvOCyTOzdzMjzux0RYi3Qilq3A7mUkH1JQkFn17U-vqHM4Hh4-xJxApmjwXc-rO8TfNMoAUUAnzwPKi2JRts-BlDH7fNk08Nnzc-AsNxD--_ZF_tqeR9sNYh5ZvT310MzYJtO_94z2nbLcudqvXpHzfvK2WZUJKm4SMsiC0lVpjDVajxDqgrEFmFhxah05ZEbQLFhWA8YLoS3thvSOUJOSUPf_f3ryrny4eqLtUf_7VzV9eARfCPP8</recordid><startdate>20221126</startdate><enddate>20221126</enddate><creator>Li, Jiyang</creator><creator>Konnayil, Ann Gina</creator><creator>Russell, Adam</creator><creator>Wang, Dingran</creator><creator>Jin, Yincheng</creator><creator>Choi, Seokmin</creator><creator>Jin, Zhanpeng</creator><scope>AKY</scope><scope>GOX</scope></search><sort><creationdate>20221126</creationdate><title>EEGLog: Lifelogging EEG Data When You Listen to Music</title><author>Li, Jiyang ; Konnayil, Ann Gina ; Russell, Adam ; Wang, Dingran ; Jin, Yincheng ; Choi, Seokmin ; Jin, Zhanpeng</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-a678-a86910793774d197434df43d13291c49c4c690f7cf946118e0aab7e09eca43a03</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2022</creationdate><topic>Computer Science - Human-Computer Interaction</topic><toplevel>online_resources</toplevel><creatorcontrib>Li, Jiyang</creatorcontrib><creatorcontrib>Konnayil, Ann Gina</creatorcontrib><creatorcontrib>Russell, Adam</creatorcontrib><creatorcontrib>Wang, Dingran</creatorcontrib><creatorcontrib>Jin, Yincheng</creatorcontrib><creatorcontrib>Choi, Seokmin</creatorcontrib><creatorcontrib>Jin, Zhanpeng</creatorcontrib><collection>arXiv Computer Science</collection><collection>arXiv.org</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Li, Jiyang</au><au>Konnayil, Ann Gina</au><au>Russell, Adam</au><au>Wang, Dingran</au><au>Jin, Yincheng</au><au>Choi, Seokmin</au><au>Jin, Zhanpeng</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>EEGLog: Lifelogging EEG Data When You Listen to Music</atitle><date>2022-11-26</date><risdate>2022</risdate><abstract>Self-tracking has been long discussed, which can monitor daily activities and
help users to recall previous experiences. Such data-capturing technique is no
longer limited to photos, text messages, or personal diaries in recent years.
With the development of wearable EEG devices, we introduce a novel modality of
logging EEG data while listening to music, and bring up the idea of the
neural-centric way of life with the designed data analysis application named
EEGLog. Four consumer-grade wearable EEG devices are explored by collecting EEG
data from 24 participants. Three modules are introduced in EEGLog, including
the summary module of EEG data, emotion reports, music listening activities,
and memorial moments, the emotion detection module, and the music
recommendation module. Feedback from interviews about using EEG devices and
EEGLog were obtained and analyzed for future EEG logging development.</abstract><doi>10.48550/arxiv.2211.14608</doi><oa>free_for_read</oa></addata></record> |
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| subjects | Computer Science - Human-Computer Interaction |
| title | EEGLog: Lifelogging EEG Data When You Listen to Music |
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