Research Assistantship (AI/ML-based Healthcare Monitoring System)
I performed data cleaning, normalization, and statistical analysis on physiological data collected from Empatica smartwatches for use in AI/ML model construction. The focus was on enhancing the reliability of models developed to detect mental health anomalies and chronic disease patterns. Data labeling centered around preparing and classifying HRV, BrE, and EDA signals for physiological wellness analysis. • Labeled physiological signals to construct a comprehensive Physiological Wellness Index (PWI). • Tagging of anomalies and trends for early mental health risk detection. • Utilized Python for preprocessing and trend analysis of large biometric data sets. • Supported model training and validation through careful preparation of annotated data.