Claim up to $1,000 in flight credits!
Get up to $1,000 in flight credits or grants toward study or internship programs abroad when you apply by September 12, 2024. See our Official Rules for full details.
Introduction to the Design of Medical Instrumentation
Engineering & Social Sciences Program
Madrid, Spain
Dates: 1/18/24 - 6/5/24
Introduction to the Design of Medical Instrumentation
OVERVIEW
CEA CAPA Partner Institution: Universidad Carlos III de Madrid
Location: Madrid, Spain
Primary Subject Area: Biomedical Engineering
Instruction in: English
Course Code: 15554
Transcript Source: Partner Institution
Course Details: Level 300
Recommended Semester Credits: 3
Contact Hours: 42
Prerequisites: Introduction to bioengineering, Electronic technology in biomedicine, Measuring instrumentation, Signals and Systems o Digital Signal Processing
DESCRIPTION
1. Basic concepts on biomedical instrumentation.
1.1. Design cycle protocol.
1.2. Regulations and marking.
2. Electrical safety.
2.1. Physiological Effects of Electricity.
2.2. The ground in biomedical instruments.
2.3. Isolated instruments and batteries.
3. Origin of Biopotentials. Techniques to record Biopotentials.
3.1. Principles of bioelectricity.
3.2. Transmembrane Action Potential.
3.3. Transmembrane Resting Potential.
3.4. Ion Channels, Pumps and Exchangers.
4. Electrocardiology. ECG characteristics.
4.1. Anatomy and Physiology of the Heart.
4.2. Electrophysiological Cardiac Behavior.
4.3. Cardiac Transmembrane Action Potential.
4.4. The electrocardiogram (ECG).
4.5. Diagnosis based on the ECG.
4.6. Recording the ECG.
4.7. Invasive Cardiac Mapping Instruments.
5. Signal amplification.
5.1. Operational Amplifiers and applications.
5.2. Output and Input Impedance.
5.3. Instrumentation amplifiers.
6. Signal filtering.
6.1. Frequency domain.
6.2. Ideal Filters.
6.3. Dealing with the Noise.
6.4. Passive Analog Filters.
6.5. Active Analog Filters.
7. Electrodes and Electrolytes.
7.1. Oxidation and reduction.
7.2. Polarizable and Nonpolarizable Electrodes.
7.3. Electrode Behavior and Circuit Models.
8. Sensors: biophysics, design, applications.
8.1. Resistive sensors.
8.2. Capacitive sensors.
8.3. Piezoelectric Sensors.
8.4. Thermocouples.
8.5. Wheatstone Bridge.
9. Electroencephalogram and Magnetroencephalogram.
9.1. Action potentials in Neurons.
9.2. Electric and Magnetic Fields in the brain.
9.3. Electroencephalography (EEG).
9.4. Magnetoencephalography: MEG.
9.5. EEG and MEG signals and applications.
10. Electromyogram, electroneurogram, electrooculogram and electroretinogram.
10.1. Electromyogram (EMG): Principles, instrumentation and applications.
10.2. Electroneurogram (ENG): Principles, instrumentation and applications.
10.3. Electrooculogram (EOG): Principles, instrumentation and applications.
10.4. Electroretinogram (ERG): Principles, instrumentation and applications.
11. Implantable devices.
11.1. Cardiac Pacemakers.
11.2. Brain Pacemakers
11.3. Defibrillators.
12. Optical and light based measurement system.
12.1. Basis of Light Propagation in Tissues.
12.2. Light Scattering.
12.3. Light Absorption.
12.4. Optical Contrast Agents.
13. Introduction to Digital Signal Processing.
13.1. Analog-to-digital converter.
13.2. Digital Frequency.
13.3. Digital Filtering.
13.4. Changing sampling rate.
13.5. Spectral estimation.
14. Applications of Digital Signal Processing.
14.1. Preprocessing signals.
14.2. Automatic detection of events.
14.3. Classification of events.
14.4. Nonlinear analysis of a sequence of events.
15. LabVIEW
15.1. LabVIEW Environment.
15.2. Data Acquisition in LabVIEW.
15.3. Typical structures and data analysis.
1.1. Design cycle protocol.
1.2. Regulations and marking.
2. Electrical safety.
2.1. Physiological Effects of Electricity.
2.2. The ground in biomedical instruments.
2.3. Isolated instruments and batteries.
3. Origin of Biopotentials. Techniques to record Biopotentials.
3.1. Principles of bioelectricity.
3.2. Transmembrane Action Potential.
3.3. Transmembrane Resting Potential.
3.4. Ion Channels, Pumps and Exchangers.
4. Electrocardiology. ECG characteristics.
4.1. Anatomy and Physiology of the Heart.
4.2. Electrophysiological Cardiac Behavior.
4.3. Cardiac Transmembrane Action Potential.
4.4. The electrocardiogram (ECG).
4.5. Diagnosis based on the ECG.
4.6. Recording the ECG.
4.7. Invasive Cardiac Mapping Instruments.
5. Signal amplification.
5.1. Operational Amplifiers and applications.
5.2. Output and Input Impedance.
5.3. Instrumentation amplifiers.
6. Signal filtering.
6.1. Frequency domain.
6.2. Ideal Filters.
6.3. Dealing with the Noise.
6.4. Passive Analog Filters.
6.5. Active Analog Filters.
7. Electrodes and Electrolytes.
7.1. Oxidation and reduction.
7.2. Polarizable and Nonpolarizable Electrodes.
7.3. Electrode Behavior and Circuit Models.
8. Sensors: biophysics, design, applications.
8.1. Resistive sensors.
8.2. Capacitive sensors.
8.3. Piezoelectric Sensors.
8.4. Thermocouples.
8.5. Wheatstone Bridge.
9. Electroencephalogram and Magnetroencephalogram.
9.1. Action potentials in Neurons.
9.2. Electric and Magnetic Fields in the brain.
9.3. Electroencephalography (EEG).
9.4. Magnetoencephalography: MEG.
9.5. EEG and MEG signals and applications.
10. Electromyogram, electroneurogram, electrooculogram and electroretinogram.
10.1. Electromyogram (EMG): Principles, instrumentation and applications.
10.2. Electroneurogram (ENG): Principles, instrumentation and applications.
10.3. Electrooculogram (EOG): Principles, instrumentation and applications.
10.4. Electroretinogram (ERG): Principles, instrumentation and applications.
11. Implantable devices.
11.1. Cardiac Pacemakers.
11.2. Brain Pacemakers
11.3. Defibrillators.
12. Optical and light based measurement system.
12.1. Basis of Light Propagation in Tissues.
12.2. Light Scattering.
12.3. Light Absorption.
12.4. Optical Contrast Agents.
13. Introduction to Digital Signal Processing.
13.1. Analog-to-digital converter.
13.2. Digital Frequency.
13.3. Digital Filtering.
13.4. Changing sampling rate.
13.5. Spectral estimation.
14. Applications of Digital Signal Processing.
14.1. Preprocessing signals.
14.2. Automatic detection of events.
14.3. Classification of events.
14.4. Nonlinear analysis of a sequence of events.
15. LabVIEW
15.1. LabVIEW Environment.
15.2. Data Acquisition in LabVIEW.
15.3. Typical structures and data analysis.