Skip to content Skip to navigation Skip to collection information

OpenStax-CNX

You are here: Home » Content » ELEC 301 Projects Fall 2008 » Collecting and Filtering Live ECG Signal

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.
 

Collecting and Filtering Live ECG Signal

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

Summary: How to build a circuit that allows for the live collection of ECG signals using the three lead set-up. Also, this module describes the filters used to remove noise from the signal. Since the ECG is a relatively low frequency signal, most of the high frequency noise can be filtered out. However, due to arm muscle movements, there will also be low frequency noise that will always remain with the signal.

Collecting ECG Signal: Hardware

Using the NI Elvis breadboard and data acquisition system, the ECG signal is collected from the three leads. Lead 1 is connected to the right arm, Lead 2 is connected to the left wrist and Lead 3 is connected to the right ankle (see Introduction: Building an ECG Based Diagnostic System for more information about lead placement). The diodes placed between the input leads and the rest of the circuit are to protect the patient from any backflowing current.

Figure 1: ECG signal collection circuit adapted from that of Radio Locman (www.rlocman.ru). The AD620 is used as a differential amplifier with a gain of ~7 in order to combine the electrical signals from each of the leads into one easily readable signal.
ECG Signal Collection Circuit
ECG Signal Collection Circuit (graphics1.png)

In NI LabVIEW, the Data Acquisition Assistant (DAQ Assistant) is used to collect the signal after preliminary band pass filtering. The data is sampled at a rate of 1 kHz. Our LabVIEW VI is available here.

Signal Conditioning

Signal filtering is necessary to help isolate the frequencies found in the ECG signal from the noise. With a three lead system, the majority of the noise comes from the electrical activity in the muscles on the arm, or electromyography (EMG) noise. EMG signals are present in a wide frequency band which overlaps with the ECG signal in the lower frequencies. Therefore, with this set-up, it is impossible to completely remove EMG noise from the ECG signal. Therefore, it is helpful for the patient to relax and remain still while the data is being collected. In addition, 60 Hz noise is present from power line interference which also must be removed.

Analog Band Pass Filter Design

The first stage of filtering is an analog filter built onto the NI Elvis breadboard. It is a bandpass filter with cut-off frequencies of 0.5 and 150 Hz. This will help eliminate the high frequency noise from the muscles before the signal is greatly amplified.

Figure 2
Analog Bandpass Filter Circuit Diagram
Analog Bandpass Filter Circuit Diagram (graphics2.png)
Figure 3
Bode Plot – Analog Band Pass Filter
Bode Plot – Analog Band Pass Filter (graphics3.png)

Digital Filters Using LabVIEW

Once the signal has been acquired by the DAQ Assistant into LabVIEW, it is processed by two additional filters and amplification of 100 times. The first filter is a band stop filter between 55 and 65 Hz to eliminate power line interference. A third order Butterworth (IIR) was used to implement this filter because it is low order and has a good frequency response for this signal.

Figure 4
Magnitude of the Frequency Response – Digital Band Stop Filter
Magnitude of the Frequency Response – Digital Band Stop Filter (graphics4.png)

The second is a tenth order Butterworth low pass filter. The cutoff frequency of this filter is 80 Hz to further eliminate EMG noise. The ECG signal is located between 0.5 Hz and about 70-80 Hz depending on the individual.

Figure 5
Magnitude of the Frequency Response – Digital Low Pass Filter
Magnitude of the Frequency Response – Digital Low Pass Filter (graphics5.png)

The resulting signal is displayed in real time in the graphical user interface, also designed in LabVIEW.

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