MA/DS 4635: Data Analytics and Statistical Learning The focus of this class will be on statistical learning - the intersection of applied statistics and modeling techniques used to analyze and to make predictions and inferences from complex real-world data. Topics covered include: regression; classification/clustering; sampling methods (bootstrap and cross validation); and decision tree learning. Students may not receive credit for both MA 463X and MA 4635. Units: 1/3 Category: Category I Recommended Background: Linear Algebra (MA 2071 or equivalent), Applied Statistics and Regression (MA 2612 or equivalent), Probability (MA 2631 or equivalent). The ability to write computer programs in a scientific language is assumed.
299
Electrical and Computer Engineering
BME/ECE 4011: Biomedical Signal Analysis Introduction to biomedical signal processing and analysis. Fundamental techniques to analyze and process signals that originate from biological sources: ECGs, EMGs, EEGs, blood pressure signals, etc. Course integrates physiological knowledge with the information useful for physiologic investigation and medical diagnosis and processing. Biomedical signal characterization, time domain analysis techniques (transfer functions, convolution, auto- and cross-correlation), frequency domain (Fourier analysis), continuous and discrete signals, deterministic and stochastic signal analysis methods. Analog and digital filtering. This course will be offered in 2022-23, and in alternating years thereafter. Units: 1/3 Category: Category II Recommended Background: ECE 2311, ECE 2312, or equivalent.
BME/ECE 4023: Biomedical Instrumentation Design This course builds on the fundamental knowledge of instrumentation and sensors. Lectures cover the principles of designing, building and testing analog instruments to measure and process biomedical signals. The course is intended for students interested in the design and development of electronic bioinstrumentation. Emphasis is placed on developing the student’s ability to design a simple medical device to perform real-time physiological measurements. Units: 1/3 Category: Category I Recommended Background: BME 3012, BME 3013, ECE 2010 or ECE 2019. ECE/BME 4011: Biomedical Signal Analysis Introduction to biomedical signal processing and analysis. Fundamental techniques to analyze and process signals that originate from biological sources: ECGs, EMGs, EEGs, blood pressure signals, etc. Course integrates physiological knowledge with the information useful for physiologic investigation and medical diagnosis and processing. Biomedical signal characterization, time domain analysis techniques (transfer functions, convolution, auto- and cross-correlation), frequency domain (Fourier analysis), continuous and discrete signals, deterministic and stochastic signal analysis methods. Analog and digital filtering. This course will be offered in 2022-23, and in alternating years thereafter. Units: 1/3 Category: Category II Recommended Background: ECE 2311, ECE 2312, or equivalent.
WPI 2021-22 Catalog
