{"title":"扩散:基于脑电生物反馈控制的情绪可视化","authors":"Shuai Xu, Zhe Wang","doi":"10.7238/ARTNODES.V0I28.385717","DOIUrl":null,"url":null,"abstract":"Diffusion is an area of research exploring the interactive relationship between human consciousness and computational practice by analyzing human brain data from electroencephalogram (EEG)-based brain-computer interfaces and interactive devices that can generate music and synchronized visual images by biofeedback. Although interactive experience is not a new topic in computational art, it has provoked thought due to the significant influence of technology on human ideology, emotions, morality, ethics, etc. Diffusion is the result of attempts to establish a connection between human physiological information and digital technology. As well as experimental research, it based on the ethical level of artificial intelligence (AI). Diffusion uses music visualization to transform intangible brain activity (thoughts or emotions) into perceivable things (sounds or objects). The research emphasizes human consciousness in AI and points out the blurred boundaries between AI and human creativity. Therefore, the installation evaluates human motivation, which can present as abstract structures—like creativity, emotion, and insight—which enhance the interactive experience of participants and deconstructs the inherent meaning of the material and spiritual, reality and virtual reality or humans and machines. By reviewing and contextualizing EEG and digital music development research, we finally outline a future research area that will involve deep collaboration across interdisciplinary and multiple technologies to realize emotion recognition.","PeriodicalId":42030,"journal":{"name":"Artnodes","volume":" ","pages":""},"PeriodicalIF":0.2000,"publicationDate":"2021-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Diffusion: Emotional Visualization Based on Biofeedback Control by EEG\",\"authors\":\"Shuai Xu, Zhe Wang\",\"doi\":\"10.7238/ARTNODES.V0I28.385717\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Diffusion is an area of research exploring the interactive relationship between human consciousness and computational practice by analyzing human brain data from electroencephalogram (EEG)-based brain-computer interfaces and interactive devices that can generate music and synchronized visual images by biofeedback. Although interactive experience is not a new topic in computational art, it has provoked thought due to the significant influence of technology on human ideology, emotions, morality, ethics, etc. Diffusion is the result of attempts to establish a connection between human physiological information and digital technology. As well as experimental research, it based on the ethical level of artificial intelligence (AI). Diffusion uses music visualization to transform intangible brain activity (thoughts or emotions) into perceivable things (sounds or objects). The research emphasizes human consciousness in AI and points out the blurred boundaries between AI and human creativity. Therefore, the installation evaluates human motivation, which can present as abstract structures—like creativity, emotion, and insight—which enhance the interactive experience of participants and deconstructs the inherent meaning of the material and spiritual, reality and virtual reality or humans and machines. By reviewing and contextualizing EEG and digital music development research, we finally outline a future research area that will involve deep collaboration across interdisciplinary and multiple technologies to realize emotion recognition.\",\"PeriodicalId\":42030,\"journal\":{\"name\":\"Artnodes\",\"volume\":\" \",\"pages\":\"\"},\"PeriodicalIF\":0.2000,\"publicationDate\":\"2021-07-09\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Artnodes\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.7238/ARTNODES.V0I28.385717\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"0\",\"JCRName\":\"HUMANITIES, MULTIDISCIPLINARY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Artnodes","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.7238/ARTNODES.V0I28.385717","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"0","JCRName":"HUMANITIES, MULTIDISCIPLINARY","Score":null,"Total":0}
Diffusion: Emotional Visualization Based on Biofeedback Control by EEG
Diffusion is an area of research exploring the interactive relationship between human consciousness and computational practice by analyzing human brain data from electroencephalogram (EEG)-based brain-computer interfaces and interactive devices that can generate music and synchronized visual images by biofeedback. Although interactive experience is not a new topic in computational art, it has provoked thought due to the significant influence of technology on human ideology, emotions, morality, ethics, etc. Diffusion is the result of attempts to establish a connection between human physiological information and digital technology. As well as experimental research, it based on the ethical level of artificial intelligence (AI). Diffusion uses music visualization to transform intangible brain activity (thoughts or emotions) into perceivable things (sounds or objects). The research emphasizes human consciousness in AI and points out the blurred boundaries between AI and human creativity. Therefore, the installation evaluates human motivation, which can present as abstract structures—like creativity, emotion, and insight—which enhance the interactive experience of participants and deconstructs the inherent meaning of the material and spiritual, reality and virtual reality or humans and machines. By reviewing and contextualizing EEG and digital music development research, we finally outline a future research area that will involve deep collaboration across interdisciplinary and multiple technologies to realize emotion recognition.