Biological Signal Processing
ECE 157
Subject & Catalog Number
Course Information
Description
This is the first course on Biological Signal Processing, the science of collection, representation, manipulation, transformation, storing of biological signals, and the use of modern scientific computing tools (Python, Jupyter notebooks) to interpret biological signals and tell engaging and informative stories using biological data. The signals of interest can be deterministic, semi-periodic, transient, random, stationary, non-stationary, etc., depending on their source and generation mechanism. We will use EEG, EKG, temperature data, neural spiking data, and data from Covid-19 as examples. Our focus will be on foundational signal processing concepts that can be applied in a variety of biological applications. Examples include the Fourier Transform, Principal Component Analysis, Clustering, etc. Applications include those to patient monitoring, diagnostics, patient prognostics, online monitoring, and the computation of wellness measures. For many of us, one frustrating aspect of Covid-19 is our inability to understand figures that are reported, such as infection rates and numbers. We will introduce you to a powerful suite of mathematical and scientific computing tools will enable you to evaluate and make decisions based on evidence and data.
Course Notes
This course was formerly numbered Engineering Sciences 157 (ES 157).
Recommended Prep
It is helpful, but not necessary, for students to have taken ECE 150/ES 150 or ECE 156/ES 156.
Available for Harvard Cross Registration
NOTE: This course requires additional sections; you will be prompted to choose secondary components during the Add to Cart process
