Pain & Electrodermal Activity
Optimization of EDA signal acquisition and analysis.
Capturing objective measures of pain to better treat pain-inducing diseases/conditions
- Using EDA to validate multilevel pain stimulation
- Pain and stress classification through EMG/EDA
- Deep learning models for acute pain detection based on EDA
- Development of highly sensitive EDA index of sympathetic activity through time-frequency analysis
Sleep Deprivation
Understanding the effects of sleep deprivation & fatigue on the human body through analysis of physiological signals and performance metrics
- Observing the correlation between brain activity & cognitive performance during 24hr period of no sleep
- Transcranial Direct Current Stimulation to counteract effects of sleep deprivation
- Identification of metrics sensitive to prolonged wakefulness
- Characterization of performance tests for measuring sleep fatigue
Disorder Detection
Development of tools and methodologies to detect various physiological disorders and diseases with greater efficiency to better develop treatments/therapies
- Detecting ASD and ADHD through a Machine Learning approach using Electroretinography
- ASD and ADHD differentiation through spectral analysis
- EEG seizure detection proposal based on Variable-Frequency Complex Demodulation and CNNs
- Development of an Objective Integrated Multimodal Electrophysiological index (OIME) of visceral pain in IBS patients
Emotion Detection
Detection of emotional states to improve understanding of human decision making in daily and healthcare settings
- Nonlinear Signal Processing methods for emotion recognition through EDA
- Effect of verbal intervention of Bilateral EMG recording during physical activity
- Development of Objective Biomarker of Trust to quantify Nurses reliance on AI healthcare technology