Course Description
From the cellular to the systemic level, computers can help us understand biological systems or assist in performing specific tasks. This class covers interfacing techniques and instruments from the cellular level (e.g., patchclamp method) to the systemic level (e.g., ECG and EEG) and includes discussion of topical applications.
Athena Title
Bioinstrumentation
Prerequisite
ECSE 2170-2170L or ECSE 2170H or ENGR 2170-2170L
Semester Course Offered
Offered spring
Grading System
A - F (Traditional)
Course Objectives
By the end of this course, students should have – Obtained an overview of biological measurands ranging from intracellular ion current to EEG waves – gained knowledge of the necessary hardware to measure the biological measurands and convert them into digital signals – gained an understanding of computer algorithms that are used to further enhance or analyze signals – understood the role of the computer in measuring, analyzing, monitoring, or feedback systems
Topical Outline
1. Biopotentials - the origin of biomedical signals 2. Overview of biomedical signals from the cell to the human body 3. Techniques and instrumentation to measure biopotentials on the cellular scale 4. Techniques and instrumentation to measure biopotentials and to induce stimuli in larger organic units (cultured neurons, muscle fibers) 5. Techniques and instrumentation to noninvasively measure biopotentials in the human body (ECG, EEG, EMG...) 6. Survey of digital signal acquisition techniques: A/D converters, sampling theorem, filtering. Creation of stimuli through D/A conversion. 7. Digital signal processing: Digital filters in the spatial domain 8. Digital signal processing: Digital filters in the frequency domain 9. Signal quantification techniques and event detection in noisy signals 10. Classification of biological signals 11. Analysis of random and stochastic signals – spectral estimation 12. Special characterization and analysis methods: Self- similarity, fractal- and wavelet-based analysis 13. Practical application I: The patch-clamp technique 14. Practical application II: Monitoring of patients by measuring their ECG and EEG signals, biofeedback 15. Practical application III: Interfacing sensors to the visual cortex, embedded sensors in humans or animals