NIU GROUP
Teaching
Biosignal Processing and Biomedical Image Processing
Rutgers University, 16:125:571, Graduate Core Course
This course introduces biosignal processing and medical image analysis, specifically in the context of biomedical engineering systems. It focuses on applying numerical algorithms to solve problems related to pattern classification in biosignals and medical imaging. Detailed contents include the Discrete Fourier Transform, time-frequency analysis (such as the short-time Fourier transform and wavelets), digital filters, spatial and frequency domain image processing, medical image segmentation, and more.
Spring 2023, Teaching Effectiveness: 4.5/5, Department Average: 4.26/5. Course Quality: 4.5/5. Department Average: 4.22/5.
Spring 2024, Teaching Effectiveness: 4.2/5, Department Average: 4.06/5. Course Quality: 4.3/5. Department Average: 3.92/5.
Wearable Electronics for Biomedical Applications
Rutgers University, 16:125:621:H1, Graduate/Senior Undergraduate Elective Course
This course provides students with the essential knowledge and skills to understand and design wearable sensor systems for a variety of biomedical applications. Key topics include basic circuit principles, the fundamentals of electrophysiology and biopotential sensors, the design of amplifiers and analog filters using operational amplifiers, and the analog-to-digital conversion process. Additionally, the course explores wearable bioimpedance, biomechanical, bio-optical, and biochemical sensors, focusing on the sensing principle and analog frontend design. Finally, the course also introduces basic wearable energy harvesting principles.
Fall 2024, Teaching Effectiveness: 4.83/5, Department Average: 4.33/5. Course Quality: 4.83/5. Department Average: 4.17/5.