Regulatory Science for Engineering Intuitive, Engaging, Safe and Effective Human-Device Interaction
(Ahmad Suliman, FDA)
Background: Wearable devices for cardiovascular health monitoring use photoplethysmography (PPG) and accelerometers to measure heart rate, SpO₂, blood pressure, and other cardiovascular health parameters. Accelerometers play a dual role in these systems: they detect motion artifact that corrupts PPG and other motion sensitive signals and capture motion-based cardiovascular signatures like seismocardiography and ballistocardiography that reflect cardiac mechanical activity. Current evaluation methods rely heavily on clinical studies with specific hardware configurations. Non-clinical bench methods to characterize accelerometer outputs have not been well established, making it difficult to validate algorithms across different device makes and models without clinical testing. A set of motion test scenarios can provide a foundation for non-clinical testbed methods to evaluate accelerometry-based algorithms in cardiovascular wearables.
Research Plan: The student will identify and characterize motion scenarios relevant to cardiovascular wearable testing through analysis of existing accelerometer data. Activities include analyzing accelerometer datasets from wearable devices during daily activities, extracting motion features such as amplitude and frequency content for different activity types, creating visualizations comparing motion characteristics across activities, and documenting representative motion test scenarios. Specific tasks may include writing MATLAB or Python scripts for signal processing and feature extraction, generating statistical summaries of motion patterns, and developing technical documentation of findings. The learning objectives include gaining experience with wearable sensor data analysis, understanding signal processing techniques for motion characterization, and developing technical communication skills for regulatory science applications.
Prerequisites: Engineering coursework in signals and systems; 1+ year programming experience in MATLAB or Python. Interest in wearable technologies and data analysis is a plus.
Dr. Ahmad Suliman is an electrical engineer and research scientist at the U.S. FDA's Center for Devices and Radiological Health (CDRH). His research focuses on developing regulatory science tools for cardiac monitoring algorithms and wearable medical devices. He has expertise in physiological signal processing, ballistocardiography, seismocardiography, and other noncontact modalities aimed at vital signs monitoring. Dr. Suliman serves as a subject matter expert in reviewing patient monitoring devices and his expertise includes clinical data collection, embedded systems development, and performance assessment of cardiovascular monitoring algorithms. He holds a Ph.D. in Electrical and Computer Engineering from Kansas State University.