Biosystems Analysis

(3-0-0-3)

CMPE Degree: This course is Selected Elective for the CMPE degree.

EE Degree: This course is Selected Elective for the EE degree.

Lab Hours: 0 supervised lab hours and 0 unsupervised lab hours.

Technical Interest Groups / Course Categories: Threads / ECE Electives

Course Coordinator: Omer T Inan

Prerequisites: BMED 3510 [min D] or CHBE 4400 [min D] or ECE 2040 [min C] or ME 3015 [min D] or ME 3017 [min D]

Catalog Description

Signal processing and modeling tools are presented for analyzing biomedical signals, with a particular focus on physiologic monitoring for human health and performance. Crosslisted with CHE and ME 4782.

Course Outcomes

Design and implement pre-processing algorithms for reducing noise and artifacts from biosignal recordings

Describe challenges in real-world biomedical signal processing problems such as motion artifacts and low signal-to-noise ratio 

Develop strategies for mitigating these real-world challenges including through the design of multi-modal signal processing and machine learning techniques 

Communicate the design of biosignal processing algorithms to a diverse audience of engineers and / or clinicians via written and oral presentation

Strategic Performance Indicators (SPIs)

N/A

Topic List

  1. Fundamentals of digital signals and systems
    1. Convolution
    2. Fourier transform
    3. Digital filters
  2. Fundamentals of probability and statistics, and basic machine learning for biosignals
    1. Probability distribution and density functions
    2. Basics of machine learning
    3. Regression and classification
    4. Signal modeling techniques
  3. Physiologic monitoring
    1. Cardiovascular and pulmonary physiological and signals
    2. Nervous system and neurological disorders
    3. Biomechanics: posture, balance, and movement
    4. Acoustic signals: speech, heart sounds, snoring
    5. Trauma, hemorrhage and other acute monitoring
  4. Special topics in biosignal processing and modeling
    1. Cuffless blood pressure estimation
    2. Extreme environment human performance augmentation