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arxiv_cv 90% Match Research Paper Psychologists,Neuroscientists,Music therapists,AI researchers in affective computing 5 days ago

Exploring the correlation between the type of music and the emotions evoked: A study using subjective questionnaires and EEG

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πŸ“„ Abstract

Abstract: The subject of this work is to check how different types of music affect human emotions. While listening to music, a subjective survey and brain activity measurements were carried out using an EEG helmet. The aim is to demonstrate the impact of different music genres on emotions. The research involved a diverse group of participants of different gender and musical preferences. This had the effect of capturing a wide range of emotional responses to music. After the experiment, a relationship analysis of the respondents' questionnaires with EEG signals was performed. The analysis revealed connections between emotions and observed brain activity.
Authors (4)
Jelizaveta Jankowska
BoΕΌena Kostek
Fernando Alonso-Fernandez
Prayag Tiwari
Submitted
October 30, 2025
arXiv Category
cs.CV
arXiv PDF

Key Contributions

Investigates the relationship between different music genres and evoked emotions by combining subjective self-reports with objective EEG measurements. The study performs correlation analysis between questionnaire responses and brain activity, aiming to demonstrate the impact of music genres on emotions.

Business Value

Provides insights into how music affects human emotions, which can inform the design of personalized music experiences, therapeutic applications, and marketing strategies.

Paper Metadata

Innovation Type

Experimental/Empirical

Deployment Feasibility

Low for direct product deployment, high for research and understanding. Requires specialized EEG equipment.

Limitations Addressed

Subjectivity of emotion perception,Lack of objective measures for music-induced emotions

Technical Tags

music emotionEEGsubjective questionnairesemotion recognitionbrain activitymusic genresaffective computingsignal processingcorrelation analysisneuroscience

Research Topics

Affective ComputingMusic PsychologyNeuroscienceSignal ProcessingHuman-Computer Interaction

Methods & Architectures

Subjective QuestionnairesElectroencephalography (EEG)Correlation AnalysisSignal Processing

Applications & Tasks

Music Therapy Entertainment Psychology Neuroscience Research Emotion RecognitionUnderstanding Music Perception Correlating music types with evoked emotionsAnalyzing brain activity during music listening

Related Fields

PsychologyNeuroscienceMusicologySignal ProcessingMachine Learning (for analysis)

Keywords

musicemotionEEGbrain activitysubjectivequestionnairegenresaffective computingneurosciencepsychologycorrelation

Academic Context

#Affective Computing#Music Psychology#Neuroscience#Signal Processing#Human-Computer Interaction

Commercial Potential

Potential Products
Emotionally adaptive music playersMusic therapy toolsPersonalized music recommendation systems
Target Industries
Music StreamingHealthcare (Therapy)EntertainmentAdvertising
Use Case Examples
Creating playlists that evoke specific moodsDeveloping music-based therapies for mental healthAnalyzing audience emotional response to music
Competitive Edge
Offers a multi-modal approach combining subjective and objective measures, providing a more comprehensive understanding than studies relying solely on self-reports.
Market Opportunity
Growing interest in personalized experiences and mental wellness tech.
Revenue Models
N/A (research focus)

Resource Requirements

Compute Needs
Moderate for EEG data analysis, potentially requiring signal processing libraries.
Data Requirements
Participant data including music stimuli, subjective ratings, and synchronized EEG recordings.
Deployment Constraints
Requires specialized hardware (EEG), controlled listening environments, ethical considerations for human subject research.
Scalability
Scalability is limited by the need for controlled experiments and EEG equipment.
Regulatory Considerations
Human subject research ethicsdata privacy.

Production Readiness

Maturity Level

Research

Time to Market

N/A (research focus)

Patent Potential

Low, primarily foundational research.

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