Healthcare Algorithms Intern (May - Dec 2020)

• Researched & developed an algorithm for i) Diabetes detection using Photoplethysmography (PPG) data and ii) Transfer learning based Blood Pressure (BP) monitoring across different PPG datasets using Convolutional Neural Network (CNN).

• Performed signal quality check using template matching to neglect corrupted data from the dataset.
• Interpreted BP estimation results using Scatter & Bland-Altman plots and Diabetes classification results using ROC curve.

• Developed a signal processing based algorithm that estimates the time domain and frequency domain features of PPG and ECG signals to analyze the mental health of patients using Heart Rate Variability.

• Submitted the work on diabetes detection to IEEE ICASSP'21.