Skip to content Skip to navigation Skip to collection information

OpenStax-CNX

You are here: Home » Content » ELEC 301 Projects Fall 2008 » Introduction: Building an Electrocardiogram (ECG) Based Diagnostic System

Navigation

Table of Contents

Lenses

What is a lens?

Definition of a lens

Lenses

A lens is a custom view of the content in the repository. You can think of it as a fancy kind of list that will let you see content through the eyes of organizations and people you trust.

What is in a lens?

Lens makers point to materials (modules and collections), creating a guide that includes their own comments and descriptive tags about the content.

Who can create a lens?

Any individual member, a community, or a respected organization.

What are tags? tag icon

Tags are descriptors added by lens makers to help label content, attaching a vocabulary that is meaningful in the context of the lens.

This content is ...

Affiliated with (What does "Affiliated with" mean?)

This content is either by members of the organizations listed or about topics related to the organizations listed. Click each link to see a list of all content affiliated with the organization.
  • Rice University ELEC 301 Projects

    This collection is included inLens: Rice University ELEC 301 Project Lens
    By: Rice University ELEC 301

    Click the "Rice University ELEC 301 Projects" link to see all content affiliated with them.

Also in these lenses

  • Lens for Engineering

    This collection is included inLens: Lens for Engineering
    By: Sidney Burrus

    Click the "Lens for Engineering" link to see all content selected in this lens.

Recently Viewed

This feature requires Javascript to be enabled.
 

Introduction: Building an Electrocardiogram (ECG) Based Diagnostic System

Module by: Christine Moran, Yuheng Chen, Leslie Goldberg. E-mail the authors

Summary: Background information necessary to build an ECG that automatically detects heart arrhythmias and abnormalities. This includes the physiologic background of the ECG, how it works and the ECG characteristics of two heart abnormalities that our system can detect.

Introduction: Building an Electrocardiogram (ECG) Based Diagnostic System

Our goal is to build an Electrocardiogram (ECG) that not only calculates the heart rate automatically, but can also detect other heart abnormalities as well. This requires more advanced analysis of the ECG Signal. There are several steps that need to be accomplished in order to achieve this goal, as outlined in the flowchart below.

Figure 1: Breaks down the different steps which need to be accomplished in order to accomplish ECG signal analysis
Overall Data Flowchart for an Automatic ECG
Overall Data Flowchart for an Automatic ECG (graphics1.png)

Data acquisition and signal conditioning are covered in Collecting and Filtering Live ECG Signal. The remaining phases, which are all related to signal analysis are covered in Algorithms for ECG Signal Analysis.

Before we go into more detail about how to build an ECG, it is helpful to understand how the ECG works and how to interpret the data you receive.

Physiological Background of the ECG

An ECG is a non-invasive diagnostic device to monitor the condition of the heart through its electrical activity. This signal is acquired through externally located electrodes that adhere to the skin. A simple, clinical lead placement uses three leads: left arm, right arm and left leg (Figure 2). The electrical activity versus time forms an electrograph and can be used to determine and diagnose heart abnormalities and arrhythmias. This principle is based on Einthoven’s law.

Figure 2: Lead 1 is attached to the right wrist, Lead 2 to the left wrist and Lead 3 is attached to the right ankle as a ground electrode.
Electrode Placement for Three-Lead ECG
Electrode Placement for Three-Lead ECG (graphics2.png)

All recorded electrical activity of the electrocardiogram corresponds to the net electrical current in the heart over time, depolarizing parts of the heart in sequence. The electrical impulse is initiated by the sinoatrial (SA) node. This causes the atria to contract and is evident on the ECG as the P wave. Next, there is a delay caused by the conduction of the impulse to the atrioventricular (AV) node such that the physical contraction of the atria have time to complete before the contraction of the ventricles. The QRS complex on the ECG is due to the depolarization of the ventricles, and occurs when the ventricles contract. Finally, the T wave on the ECG is due to the repolarization of the ventricles (Pflanzer, 2004). Therefore, each heartbeat corresponds to a pulse on the ECG beginning with each P wave and the ending with each T wave. The heart rate can be determined by determining the time it takes to complete one beat and is typically reported in beats per minute. Figure 3 demonstrates the characteristic shape of the waveform in a healthy patient.

Figure 3: An example of the typical shape and location of the various components of an ECG signal.
Typical ECG Signal
Typical ECG Signal (graphics3.png)

Background Information on Monitored Heart Conditions

To perform automatic detection of an ECG signal, there needs to be something that clearly delineates a certain abnormality from other signals. Therefore, the signal processing selected is to detect ventricular hypertrophy and old myocardial infarctions. Luckily, these types of abnormalities are both very useful for doctors to diagnose a patient and have distinguishable ECG features.

Ventricular hypertrophy is the enlargement of either of the ventricles. Left ventricular hypertrophy is particularly common in athletes as well as an indicator of hypertension. It is also used in the Framingham risk equation to predict future cardiac problems the patient may face (ECG Abnormalities, 2006). One of its characteristic ECG patterns is the inverted T wave (Figure 4).

Figure 4
An Example of an ECG Signal with an Inverted T-wave
An Example of an ECG Signal with an Inverted T-wave (graphics4.png)

A myocardial infarction (a.k.a. heart attack) is caused by the complete blockage of one of the coronary arteries. The coronary artery is what supplies the heart muscle with blood. A blockage prevents blood from reaching the surrounding muscular tissue resulting in necrosis. This damage is permanent so the resulting ECG characteristic will remain with the patient. Therefore, the doctor can easily tell if a patient has had a heart attack in the past. The ECG of an old myocardial infarction is characterized by a significant Q wave (Figure 5). This means that the Q peak is unusually deep, usually with amplitude of about one-third that of the R peak (Dubin, 2000).

Figure 5
An Example of an ECG Signal with a Significant Q-wave
An Example of an ECG Signal with a Significant Q-wave (graphics5.png)

By building an ECG that can automatically detect these and potentially other heart abnormalities, it will be easier for doctors to monitor multiple patients. This is especially important in third world countries where there are often far too many patients in one clinic than one doctor or nurse can adequately care for.

Collection Navigation

Content actions

Download:

Collection as:

PDF | EPUB (?)

What is an EPUB file?

EPUB is an electronic book format that can be read on a variety of mobile devices.

Downloading to a reading device

For detailed instructions on how to download this content's EPUB to your specific device, click the "(?)" link.

| More downloads ...

Module as:

PDF | More downloads ...

Add:

Collection to:

My Favorites (?)

'My Favorites' is a special kind of lens which you can use to bookmark modules and collections. 'My Favorites' can only be seen by you, and collections saved in 'My Favorites' can remember the last module you were on. You need an account to use 'My Favorites'.

| A lens I own (?)

Definition of a lens

Lenses

A lens is a custom view of the content in the repository. You can think of it as a fancy kind of list that will let you see content through the eyes of organizations and people you trust.

What is in a lens?

Lens makers point to materials (modules and collections), creating a guide that includes their own comments and descriptive tags about the content.

Who can create a lens?

Any individual member, a community, or a respected organization.

What are tags? tag icon

Tags are descriptors added by lens makers to help label content, attaching a vocabulary that is meaningful in the context of the lens.

| External bookmarks

Module to:

My Favorites (?)

'My Favorites' is a special kind of lens which you can use to bookmark modules and collections. 'My Favorites' can only be seen by you, and collections saved in 'My Favorites' can remember the last module you were on. You need an account to use 'My Favorites'.

| A lens I own (?)

Definition of a lens

Lenses

A lens is a custom view of the content in the repository. You can think of it as a fancy kind of list that will let you see content through the eyes of organizations and people you trust.

What is in a lens?

Lens makers point to materials (modules and collections), creating a guide that includes their own comments and descriptive tags about the content.

Who can create a lens?

Any individual member, a community, or a respected organization.

What are tags? tag icon

Tags are descriptors added by lens makers to help label content, attaching a vocabulary that is meaningful in the context of the lens.

| External bookmarks