One of the defining topics for biomedical engineering, signal processing is playing an increasingly important role in modern times, mostly due to the ever-increasing popularity of portable, wearable, implantable, wireless, and miniature medical sensors/ devices. The primary function of all the medical devices is acquisition and analysis of some kind of physiological data, often in a semi continuous real-time manner. From a medical stand point, the benefits that the devices offer pertain to complementing the physician in diagnosis, prognosis, and therapeutics. High-quality signal processing algorithm is a vital part of this process. On the research side, accurate signal processing plays a fundamentally important role in a medical device’s validation and translation from bench to bedside. Mastering this important topic can equip the student with skills that can be immediately applied in real-life technological innovations. This new online course will primarily focus on advanced topics in signal processing, including linear and nonlinear analysis of primary electro-physiological signals. Topics will include more traditional Auto-regressive Moving Average Analysis, spectral analysis, and singular value decomposition as well as advanced methods such as entropy computation, dimensionality estimation, state-space reconstruction, recurrence time analysis, parameter estimation, etc. Students will be challenged to write their own algorithms to reproduce select published research results.
Course Prerequisite(s)
EN.585.615 Mathematical Methods for Applied Biomedical Engineering; EN.535.641 Mathematical Methods for Engineers; or written permission from the instructor. Knowledge of MATLAB is strongly recommended.
Course Offerings
There are no sections currently offered, however you can view a sample syllabus from a prior section of this course.