Research

Overview

This research investigates how human states, experiences, and interactions with technology can be measured, modeled, and translated into better design and evaluation. Human-factors theory is combined with multimodal physiological and behavioral data, controlled experiments, statistical modeling, and machine learning across three related areas: Human Factors & User Experience, Psychophysiological Assessment, and Human–AI Interaction.

Research Areas

Human Factors & User Experience

Research in human factors and user experience examines how products, work systems, and interactive technologies affect human performance, safety, comfort, and experience. This work spans physical ergonomics, usability evaluation, occupational risk assessment, automotive interfaces, and display-based interaction, using performance measures, questionnaires, eye tracking, EMG, and experimental or field-based evaluation as appropriate to the research question.

The applied approach identifies measurable human requirements, evaluates systems under realistic conditions, and translates findings into evidence for product, interface, workplace, or evaluation-method development.

Research Topics

• Physical ergonomics and musculoskeletal assessment
• Usability and UX evaluation
• Automotive interfaces and driver response
• Display interaction and gaming performance
• Occupational and industrial human factors

Psychophysiological Assessment

Psychophysiological assessment uses physiological and behavioral signals to characterize human states that are difficult to observe directly. EEG, ECG/HRV, EMG, eye tracking, and subjective measures support the study of gaming-disorder risk, stress, affect, fatigue, and cognitive or behavioral responses.

A central theme is the identification of interpretable physiological parameters that support quantitative assessment while remaining meaningful in the context of human behavior and experience. Domain-specific analyses include EEG event and spectral analysis, ECG/HRV-based human-state assessment, and EMG-based muscle-fatigue analysis; statistical modeling and machine learning are applied when appropriate.

Research Topics

• Gaming-disorder risk and in-game behavior
• Stress, affect, relaxation, and multisensory experience
• Fatigue and physiological response
• Human-state and individual-difference assessment

Human–AI Interaction

Current and Emerging Research Direction

Current and emerging work in human–AI interaction examines how AI-enabled systems can account for differences among users while remaining understandable, usable, and human-centered. Physiological, behavioral, and subjective evidence provides a basis for evaluating user responses to adaptive and explainable AI systems.

An ongoing project explores an adaptive XAI safety model for predicting and responding to sudden or unstable driving behaviors among users with diverse cognitive and sensory characteristics.

Research Topics

• Human behavior in AI-enabled systems
• Adaptive and explainable AI
• User diversity and individual differences
• Human-centered AI evaluation
• Physiological and behavioral evidence for Human–AI Interaction

Background

The research program has developed from engineering performance evaluation and applied ergonomics toward physiological computing and data-driven human-state assessment, with a current and emerging direction in human–AI interaction. Across these stages, the common goal is to produce reliable and interpretable evidence about people that can inform safer, more usable, and more adaptive systems.

Approach

The research follows an end-to-end process that connects a human-centered question to interpretable evidence for system design and evaluation. Each study aligns its design, measurement, processing, and analysis with the problem under investigation.

Human-centered question → Experimental design → Multimodal measurement → Signal and data processing → Statistical/ML analysis → Interpretation for design and evaluation

Methods & Expertise

Physiological & Behavioral Measurement

EEG · ECG/HRV · EMG · Eye Tracking · Questionnaires

Experimental & User Research

Experimental Design · User Studies · Usability & UX Evaluation · Psychophysiological Evaluation

Quantitative Analysis

Psychophysiological Signal Analysis · Statistical Modeling · Machine Learning