date: 2021-08-25T08:03:08Z pdf:PDFVersion: 1.6 pdf:docinfo:title: Classification of Complex Emotions Using EEG and Virtual Environment: Proof of Concept and Therapeutic Implication xmp:CreatorTool: LaTeX with hyperref package + hypdvips access_permission:can_print_degraded: true subject: During the last decades, neurofeedback training for emotional self-regulation has received significant attention from scientific and clinical communities. language: en dc:format: application/pdf; version=1.6 pdf:docinfo:creator_tool: LaTeX with hyperref package + hypdvips access_permission:fill_in_form: true pdf:encrypted: false dc:title: Classification of Complex Emotions Using EEG and Virtual Environment: Proof of Concept and Therapeutic Implication modified: 2021-08-25T08:03:08Z cp:subject: During the last decades, neurofeedback training for emotional self-regulation has received significant attention from scientific and clinical communities. pdf:docinfo:subject: During the last decades, neurofeedback training for emotional self-regulation has received significant attention from scientific and clinical communities. pdf:docinfo:creator: Eleonora De Filippi meta:author: Eleonora De Filippi meta:creation-date: 2021-08-25T05:54:25Z created: 2021-08-25T05:54:25Z access_permission:extract_for_accessibility: true Creation-Date: 2021-08-25T05:54:25Z Author: Eleonora De Filippi producer: dvips + MiKTeX GPL Ghostscript 9.0 pdf:docinfo:producer: dvips + MiKTeX GPL Ghostscript 9.0 pdf:unmappedUnicodeCharsPerPage: 0 dc:description: During the last decades, neurofeedback training for emotional self-regulation has received significant attention from scientific and clinical communities. Keywords: emotions, electroencephalography, classification, machine-learning, neuro-feedback, multimodal virtual scenario access_permission:modify_annotations: true dc:creator: Eleonora De Filippi description: During the last decades, neurofeedback training for emotional self-regulation has received significant attention from scientific and clinical communities. dcterms:created: 2021-08-25T05:54:25Z Last-Modified: 2021-08-25T08:03:08Z dcterms:modified: 2021-08-25T08:03:08Z title: Classification of Complex Emotions Using EEG and Virtual Environment: Proof of Concept and Therapeutic Implication xmpMM:DocumentID: uuid:acb13aaa-7993-4067-9284-19d24b739917 Last-Save-Date: 2021-08-25T08:03:08Z pdf:docinfo:keywords: emotions, electroencephalography, classification, machine-learning, neuro-feedback, multimodal virtual scenario pdf:docinfo:modified: 2021-08-25T08:03:08Z meta:save-date: 2021-08-25T08:03:08Z Content-Type: application/pdf X-Parsed-By: org.apache.tika.parser.DefaultParser creator: Eleonora De Filippi dc:language: en dc:subject: emotions, electroencephalography, classification, machine-learning, neuro-feedback, multimodal virtual scenario access_permission:assemble_document: true xmpTPg:NPages: 14 pdf:charsPerPage: 3624 access_permission:extract_content: true access_permission:can_print: true meta:keyword: emotions, electroencephalography, classification, machine-learning, neuro-feedback, multimodal virtual scenario access_permission:can_modify: true pdf:docinfo:created: 2021-08-25T05:54:25Z