Name: ALEPH CAMPOS DA SILVEIRA
Publication date: 24/03/2025
Examining board:
Name |
Role |
|---|---|
| ANDRE GEORGHTON CARDOSO PACHECO | Examinador Interno |
| CELSO ALBERTO SAIBEL SANTOS | Presidente |
| DIEGO ROBERTO COLOMBO DIAS | Examinador Interno |
| MYLÈNE CHRISTINE QUEIROZ DE FARIAS | Examinador Externo |
| WINDSON VIANA DE CARVALHO | Examinador Externo |
Summary: Traditional multimedia systems predominantly engage vision and audition, yet human
interaction inherently involves multiple senses. Mulsemedia, multisensory media, advances
this paradigm by integrating tactile, thermal, olfactory, and other stimuli synchronized
with audiovisual content to create immersive experiences. Evaluating user experience (UX)
and quality of experience (QoE) in such environments presents unique challenges, including
sensory synchronization complexities, environmental masking effects, and limitations of
subjective methods such as questionnaires, which risk biases and immersion disruption.
This research addresses these challenges by proposing a physiologically enhanced evaluation
framework that combines objective physiological metrics (e.g. heart rate, galvanic skin
response) with subjective feedback to uncover latent cognitive-emotional states and refine
sensory integration. Through experiments in 360-degree videos, serious games and thermal-
haptic scenarios, physiological signals revealed discrepancies between reported tolerance
and subconscious strain, such as elevated arousal during audiovisual desynchronization
undetected by self-reports, and exposed inefficacies in static sensory delivery systems. The
findings advocate for real-time biosignal monitoring and dynamic sensory alignment to
optimize immersive realism and evaluative accuracy. By bridging subjective perception
with physiological responses, this work establishes a multimodal framework for holistic UX
assessment, allowing personalized adaptive multimedia design. Future directions emphasize
integrating diverse biosensors, machine learning-driven analysis, and standardized protocols
to advance user-centric predictive evaluation methodologies in evolving multisensory
ecosystems.
