Autonomic Nervous System Dynamics for Mood and Emotional-State Recognition: Significant Advances in Data Acquisition, Signal Processing and Classification
Gespeichert in:
| 1. Verfasser: | |
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| Format: | Elektronisch E-Book |
| Sprache: | English |
| Veröffentlicht: |
2014
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| Schriftenreihe: | Series in BioEngineering
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| Schlagworte: | |
| Online-Zugang: | BTU01 FHA01 FHI01 FHN01 FHR01 FKE01 FRO01 FWS01 FWS02 UBY01 Volltext Inhaltsverzeichnis Abstract |
| Beschreibung: | This monograph reports on advances in the measurement and study of autonomic nervous system (ANS) dynamics as a source of reliable and effective markers for mood state recognition and assessment of emotional responses. Its primary impact will be in affective computing and the application of emotion-recognition systems. Applicative studies of biosignals such as: electrocardiograms; electrodermal responses; respiration activity; gaze points; and pupil-size variation are covered in detail, and experimental results explain how to characterize the elicited affective levels and mood states pragmatically and accurately using the information thus extracted from the ANS. Nonlinear signal processing techniques play a crucial role in understanding the ANS physiology underlying superficially noticeable changes and provide important quantifiers of cardiovascular control dynamics. These have prognostic value in both healthy subjects and patients with mood disorders. Moreover, Autonomic Nervous System Dynamics for Mood and Emotional-State Recognition proposes a novel probabilistic approach based on the point-process theory in order to model and characterize the instantaneous ANS nonlinear dynamics providing a foundation from which machine "understanding" of emotional response can be enhanced. Using mathematics and signal processing, this work also contributes to pragmatic issues such as emotional and mood-state modeling, elicitation, and non-invasive ANS monitoring. Throughout the text a critical review on the current state-of-the-art is reported, leading to the description of dedicated experimental protocols, novel and reliable mood models, and novel wearable systems able to perform ANS monitoring in a naturalistic environment. Biomedical engineers will find this book of interest, especially those concerned with nonlinear analysis, as will researchers and industrial technicians developing wearable systems and sensors for ANS monitoring |
| Beschreibung: | 1 Online-Ressource (XIX, 162 p.) 49 illus., 36 illus. in color |
| ISBN: | 9783319026398 |
| DOI: | 10.1007/978-3-319-02639-8 |
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Datensatz im Suchindex
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| _version_ | 1806174812433809408 |
| adam_text | AUTONOMIC NERVOUS SYSTEM DYNAMICS FOR MOOD AND EMOTIONAL-STATE
RECOGNITION
/ VALENZA, GAETANO
: 2014
TABLE OF CONTENTS / INHALTSVERZEICHNIS
EMOTIONS AND MOOD STATES: MODELING, ELICITATION, AND CLASSIFICATION
THROUGH AUTONOMIC PATTERNS
GATHERING DATA FROM THE AUTONOMIC NERVOUS SYSTEM: EXPERIMENTAL
PROCEDURES AND WEARABLE MONITORING SYSTEMS
METHODOLOGY OF ADVANCED SIGNAL PROCESSING AND MODELING
EXPERIMENTAL EVIDENCES ON HEALTHY SUBJECTS AND BIPOLAR PATIENTS
DISCUSSION ON MOOD AND EMOTIONAL-STATE RECOGNITION USING THE AUTONOMIC
NERVOUS SYSTEM DYNAMICS
SUMMARY OF THE BOOK AND DIRECTION FOR FUTURE RESEARCH
DIESES SCHRIFTSTUECK WURDE MASCHINELL ERZEUGT.
AUTONOMIC NERVOUS SYSTEM DYNAMICS FOR MOOD AND EMOTIONAL-STATE
RECOGNITION
/ VALENZA, GAETANO
: 2014
ABSTRACT / INHALTSTEXT
THIS MONOGRAPH REPORTS ON ADVANCES IN THE MEASUREMENT AND STUDY OF
AUTONOMIC NERVOUS SYSTEM (ANS) DYNAMICS AS A SOURCE OF RELIABLE AND
EFFECTIVE MARKERS FOR MOOD STATE RECOGNITION AND ASSESSMENT OF EMOTIONAL
RESPONSES. ITS PRIMARY IMPACT WILL BE IN AFFECTIVE COMPUTING AND THE
APPLICATION OF EMOTION-RECOGNITION SYSTEMS. APPLICATIVE STUDIES OF
BIOSIGNALS SUCH AS: ELECTROCARDIOGRAMS; ELECTRODERMAL RESPONSES;
RESPIRATION ACTIVITY; GAZE POINTS; AND PUPIL-SIZE VARIATION ARE COVERED
IN DETAIL, AND EXPERIMENTAL RESULTS EXPLAIN HOW TO CHARACTERIZE THE
ELICITED AFFECTIVE LEVELS AND MOOD STATES PRAGMATICALLY AND ACCURATELY
USING THE INFORMATION THUS EXTRACTED FROM THE ANS. NONLINEAR SIGNAL
PROCESSING TECHNIQUES PLAY A CRUCIAL ROLE IN UNDERSTANDING THE ANS
PHYSIOLOGY UNDERLYING SUPERFICIALLY NOTICEABLE CHANGES AND PROVIDE
IMPORTANT QUANTIFIERS OF CARDIOVASCULAR CONTROL DYNAMICS. THESE HAVE
PROGNOSTIC VALUE IN BOTH HEALTHY SUBJECTS AND PATIENTS WITH MOOD
DISORDERS. MOREOVER, AUTONOMIC NERVOUS SYSTEM DYNAMICS FOR MOOD AND
EMOTIONAL-STATE RECOGNITION PROPOSES A NOVEL PROBABILISTIC APPROACH
BASED ON THE POINT-PROCESS THEORY IN ORDER TO MODEL AND CHARACTERIZE THE
INSTANTANEOUS ANS NONLINEAR DYNAMICS PROVIDING A FOUNDATION FROM WHICH
MACHINE “UNDERSTANDING” OF EMOTIONAL RESPONSE CAN BE ENHANCED. USING
MATHEMATICS AND SIGNAL PROCESSING, THIS WORK ALSO CONTRIBUTES TO
PRAGMATIC ISSUES SUCH AS EMOTIONAL AND MOOD-STATE MODELING, ELICITATION,
AND NON-INVASIVE ANS MONITORING. THROUGHOUT THE TEXT A CRITICAL REVIEW
ON THE CURRENT STATE-OF-THE-ART IS REPORTED, LEADING TO THE DESCRIPTION
OF DEDICATED EXPERIMENTAL PROTOCOLS, NOVEL AND RELIABLE MOOD MODELS, AND
NOVEL WEARABLE SYSTEMS ABLE TO PERFORM ANS MONITORING IN A NATURALISTIC
ENVIRONMENT. BIOMEDICAL ENGINEERS WILL FIND THIS BOOK OF INTEREST,
ESPECIALLY THOSE CONCERNED WITH NONLINEAR ANALYSIS, AS WILL RESEARCHERS
AND INDUSTRIAL TECHNICIANS DEVELOPING WEARABLE SYSTEMS AND SENSORS FOR
ANS MONITORING
DIESES SCHRIFTSTUECK WURDE MASCHINELL ERZEUGT.
|
| any_adam_object | 1 |
| author | Valenza, Gaetano |
| author_facet | Valenza, Gaetano |
| author_role | aut |
| author_sort | Valenza, Gaetano |
| author_variant | g v gv |
| building | Verbundindex |
| bvnumber | BV041470997 |
| collection | ZDB-2-ENG |
| contents | Emotions and Mood States: Modeling, Elicitation, and Classification through Autonomic Patterns -- Gathering Data from the Autonomic Nervous System: Experimental Procedures and Wearable Monitoring Systems -- Methodology of Advanced Signal Processing and Modeling -- Experimental Evidences on Healthy Subjects and Bipolar Patients -- Discussion on mood and emotional-state recognition using the Autonomic Nervous System Dynamics -- Summary of the Book and Direction for Future Research |
| ctrlnum | (OCoLC)874381653 (DE-599)BVBBV041470997 |
| dewey-full | 610.28 |
| dewey-hundreds | 600 - Technology (Applied sciences) |
| dewey-ones | 610 - Medicine and health |
| dewey-raw | 610.28 |
| dewey-search | 610.28 |
| dewey-sort | 3610.28 |
| dewey-tens | 610 - Medicine and health |
| discipline | Medizin |
| doi_str_mv | 10.1007/978-3-319-02639-8 |
| format | Electronic eBook |
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| id | DE-604.BV041470997 |
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| indexdate | 2024-08-01T10:55:28Z |
| institution | BVB |
| isbn | 9783319026398 |
| language | English |
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| spellingShingle | Valenza, Gaetano Autonomic Nervous System Dynamics for Mood and Emotional-State Recognition Significant Advances in Data Acquisition, Signal Processing and Classification Emotions and Mood States: Modeling, Elicitation, and Classification through Autonomic Patterns -- Gathering Data from the Autonomic Nervous System: Experimental Procedures and Wearable Monitoring Systems -- Methodology of Advanced Signal Processing and Modeling -- Experimental Evidences on Healthy Subjects and Bipolar Patients -- Discussion on mood and emotional-state recognition using the Autonomic Nervous System Dynamics -- Summary of the Book and Direction for Future Research Engineering Neurosciences Artificial intelligence Biomedical engineering Applied psychology Biomedical Engineering Artificial Intelligence (incl. Robotics) Biological Psychology Signal, Image and Speech Processing Computational Intelligence Ingenieurwissenschaften Künstliche Intelligenz |
| title | Autonomic Nervous System Dynamics for Mood and Emotional-State Recognition Significant Advances in Data Acquisition, Signal Processing and Classification |
| title_auth | Autonomic Nervous System Dynamics for Mood and Emotional-State Recognition Significant Advances in Data Acquisition, Signal Processing and Classification |
| title_exact_search | Autonomic Nervous System Dynamics for Mood and Emotional-State Recognition Significant Advances in Data Acquisition, Signal Processing and Classification |
| title_full | Autonomic Nervous System Dynamics for Mood and Emotional-State Recognition Significant Advances in Data Acquisition, Signal Processing and Classification by Gaetano Valenza, Enzo Pasquale Scilingo |
| title_fullStr | Autonomic Nervous System Dynamics for Mood and Emotional-State Recognition Significant Advances in Data Acquisition, Signal Processing and Classification by Gaetano Valenza, Enzo Pasquale Scilingo |
| title_full_unstemmed | Autonomic Nervous System Dynamics for Mood and Emotional-State Recognition Significant Advances in Data Acquisition, Signal Processing and Classification by Gaetano Valenza, Enzo Pasquale Scilingo |
| title_short | Autonomic Nervous System Dynamics for Mood and Emotional-State Recognition |
| title_sort | autonomic nervous system dynamics for mood and emotional state recognition significant advances in data acquisition signal processing and classification |
| title_sub | Significant Advances in Data Acquisition, Signal Processing and Classification |
| topic | Engineering Neurosciences Artificial intelligence Biomedical engineering Applied psychology Biomedical Engineering Artificial Intelligence (incl. Robotics) Biological Psychology Signal, Image and Speech Processing Computational Intelligence Ingenieurwissenschaften Künstliche Intelligenz |
| topic_facet | Engineering Neurosciences Artificial intelligence Biomedical engineering Applied psychology Biomedical Engineering Artificial Intelligence (incl. Robotics) Biological Psychology Signal, Image and Speech Processing Computational Intelligence Ingenieurwissenschaften Künstliche Intelligenz |
| url | https://doi.org/10.1007/978-3-319-02639-8 http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=026917139&sequence=000001&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=026917139&sequence=000003&line_number=0002&func_code=DB_RECORDS&service_type=MEDIA |
| work_keys_str_mv | AT valenzagaetano autonomicnervoussystemdynamicsformoodandemotionalstaterecognitionsignificantadvancesindataacquisitionsignalprocessingandclassification AT scilingoenzopasquale autonomicnervoussystemdynamicsformoodandemotionalstaterecognitionsignificantadvancesindataacquisitionsignalprocessingandclassification |