Zvika Ben-haim

03-05-1998, 07:59 AM

First of all, we would like to sincerely thank the many people who

responded to our question. The responses were serious and well-focused,

and have helped us a great deal in attempting to solve our problem.

Attached is a summary of the responses we received for our query.

Original Query

> I am interested to know what is the preferred method to remove heart

> beat signals from EMG recordings of trunk muscles. with minimum loss

or

> distortion of the EMG signal itself. A summary of the responses I will

> submit to the list members.

(Original question posted by Dr. Ruth Dickstein)

Summary of responses on removal of ECG artifacts from EMG signals

Highpass Filtering: The most common reply was to use some form of

highpass filtering, with suggested cutoffs ranging between 1 and 40 Hz.

Many suggested performing an FFT and zeroing the lower frequencies, then

performing an inverse FFT, in order to obtain a sharper cutoff than by

using ordinary analog filters. An article describing the trade-off in

choice of cutoff frequency is: Redfern et al, "High-pass filtering to

remove electrocardiographic interference from torso EMG recordings,"

Clin. Biomech. 1993; 8; 44-48.

Gating: A simple and usually satisfactory method is known as gating. The

idea is that values above a trigger value are assumed to be heartbeat

signals, and are treated as missing values. This has the advantage of

fast and automatic data processing. The gating should be performed

before integration or any other method of smoothing to avoid data loss.

Subtraction: Another common reply suggested subtracting the data of a

'clean' heartbeat from all occurances of heartbeats in the data. Better

results can apparently be achieved by selecting as a 'clean' heartbeat

an average 'template' of many heartbeats recorded with no muscle

activity.

Bartolo et al (see "Analysis of diaphragm EMG signals: comparison of

gating vs. subtraction for removal of ECG contamination", J. Appl.

Physiol. 80(6); 1898-1902) compared the gating and subtraction methods

using several common numerical processing techniques, such as mean

power, zero crossing frequency and so on. They found no significant

difference in results between signals processed using these two methods,

and concluded that the added computational power required to use the

more complex method of subtraction does not yield significantly better

results.

A combination of the subtraction and filtering techniques was also

suggested. In this method the subtraction would be performed in the

frequency domain (on an FFT signal). In other words, the FFT of a clean

heartbeat would be subtrated from the FFT of the data, and the result

converted back using an inverse FFT. As far as we know this has not been

attempted yet with EMG signals.

Wavelets: Another suggestion was to use wavelet smoothing to remove

heartbeat signal frequencies without distorting EMG data at the same

frequency. For a technical introduction to wavelet theory, see Chui

(1994): "Wavelets: Theory, Algorithms and Applications", San Diego:

Academic Press.

Adaptive Noise Cancellation: Using adaptive noise cancellation with an

extra channel in which only the ECG is collected. For details on this

method see Medical Engineering and Physics, 1997, Vol 19 No 3 pp

279-285, "A comparison of ECG cancellation techniques applied to the

surface recording of somatosensory evoked potentials", J. S. Black and

D. F. Lovely.

Use of histograms: Finding a histogram of the EMG amplitudes, and

removing (or keeping as missing values) all amplitudes which clearly do

not belong to the EMG.

Improved electrode placement: Positioning the ground electrode in such a

manner that the heartbeat reaches the ground and active electrodes

simultaneously and does not get recorded.

Thanks again to all who responded to our question.

Sincerely,

Zvika Ben-Haim

zvikabh@aluf.technion.ac.il

First of all, we would like to sincerely thank the many people who responded

to our question. The responses were serious and well-focused, and have

helped us a great deal in attempting to solve our problem. Attached is

a summary of the responses we received for our query.

Original Query

> I am interested to know what is the preferred method to remove heart

> beat signals from EMG recordings of trunk muscles. with minimum loss

or

> distortion of the EMG signal itself. A summary of the responses I

will

> submit to the list members.

(Original question posted by Dr. Ruth Dickstein)

Summary of responses on removal of ECG artifacts from EMG signals

Highpass Filtering: The most common reply was to use some form

of highpass filtering, with suggested cutoffs ranging between 1 and 40

Hz. Many suggested performing an FFT and zeroing the lower frequencies,

then performing an inverse FFT, in order to obtain a sharper cutoff than

by using ordinary analog filters. An article describing the trade-off in

choice of cutoff frequency is: Redfern et al, "High-pass filtering

to remove electrocardiographic interference from torso EMG recordings,"

Clin. Biomech. 1993; 8; 44-48.

Gating: A simple and usually satisfactory method is known as

gating. The idea is that values above a trigger value are assumed to be

heartbeat signals, and are treated as missing values. This has the advantage

of fast and automatic data processing. The gating should be performed before

integration or any other method of smoothing to avoid data loss.

Subtraction: Another common reply suggested subtracting the data

of a 'clean' heartbeat from all occurances of heartbeats in the data. Better

results can apparently be achieved by selecting as a 'clean' heartbeat

an average 'template' of many heartbeats recorded with no muscle activity.

Bartolo et al (see "Analysis of diaphragm EMG signals: comparison

of gating vs. subtraction for removal of ECG contamination", J. Appl. Physiol.

80(6); 1898-1902) compared the gating and subtraction methods using several

common numerical processing techniques, such as mean power, zero crossing

frequency and so on. They found no significant difference in results between

signals processed using these two methods, and concluded that the added

computational power required to use the more complex method of subtraction

does not yield significantly better results.

A combination of the subtraction and filtering techniques was also suggested.

In this method the subtraction would be performed in the frequency domain

(on an FFT signal). In other words, the FFT of a clean heartbeat would

be subtrated from the FFT of the data, and the result converted back using

an inverse FFT. As far as we know this has not been attempted yet with

EMG signals.

Wavelets: Another suggestion was to use wavelet smoothing to

remove heartbeat signal frequencies without distorting EMG data at the

same frequency. For a technical introduction to wavelet theory, see Chui

(1994): "Wavelets: Theory, Algorithms and Applications", San Diego:

Academic Press.

Adaptive Noise Cancellation: Using adaptive noise cancellation

with an extra channel in which only the ECG is collected. For details on

this method see Medical Engineering and Physics, 1997, Vol 19 No

3 pp 279-285, "A comparison of ECG cancellation techniques applied to the

surface recording of somatosensory evoked potentials", J. S. Black and

D. F. Lovely.

Use of histograms: Finding a histogram of the EMG amplitudes,

and removing (or keeping as missing values) all amplitudes which clearly

do not belong to the EMG.

Improved electrode placement: Positioning the ground electrode

in such a manner that the heartbeat reaches the ground and active electrodes

simultaneously and does not get recorded.

Thanks again to all who responded to our question.

Sincerely,

Zvika Ben-Haim

zvikabh@aluf.technion.ac.il

responded to our question. The responses were serious and well-focused,

and have helped us a great deal in attempting to solve our problem.

Attached is a summary of the responses we received for our query.

Original Query

> I am interested to know what is the preferred method to remove heart

> beat signals from EMG recordings of trunk muscles. with minimum loss

or

> distortion of the EMG signal itself. A summary of the responses I will

> submit to the list members.

(Original question posted by Dr. Ruth Dickstein)

Summary of responses on removal of ECG artifacts from EMG signals

Highpass Filtering: The most common reply was to use some form of

highpass filtering, with suggested cutoffs ranging between 1 and 40 Hz.

Many suggested performing an FFT and zeroing the lower frequencies, then

performing an inverse FFT, in order to obtain a sharper cutoff than by

using ordinary analog filters. An article describing the trade-off in

choice of cutoff frequency is: Redfern et al, "High-pass filtering to

remove electrocardiographic interference from torso EMG recordings,"

Clin. Biomech. 1993; 8; 44-48.

Gating: A simple and usually satisfactory method is known as gating. The

idea is that values above a trigger value are assumed to be heartbeat

signals, and are treated as missing values. This has the advantage of

fast and automatic data processing. The gating should be performed

before integration or any other method of smoothing to avoid data loss.

Subtraction: Another common reply suggested subtracting the data of a

'clean' heartbeat from all occurances of heartbeats in the data. Better

results can apparently be achieved by selecting as a 'clean' heartbeat

an average 'template' of many heartbeats recorded with no muscle

activity.

Bartolo et al (see "Analysis of diaphragm EMG signals: comparison of

gating vs. subtraction for removal of ECG contamination", J. Appl.

Physiol. 80(6); 1898-1902) compared the gating and subtraction methods

using several common numerical processing techniques, such as mean

power, zero crossing frequency and so on. They found no significant

difference in results between signals processed using these two methods,

and concluded that the added computational power required to use the

more complex method of subtraction does not yield significantly better

results.

A combination of the subtraction and filtering techniques was also

suggested. In this method the subtraction would be performed in the

frequency domain (on an FFT signal). In other words, the FFT of a clean

heartbeat would be subtrated from the FFT of the data, and the result

converted back using an inverse FFT. As far as we know this has not been

attempted yet with EMG signals.

Wavelets: Another suggestion was to use wavelet smoothing to remove

heartbeat signal frequencies without distorting EMG data at the same

frequency. For a technical introduction to wavelet theory, see Chui

(1994): "Wavelets: Theory, Algorithms and Applications", San Diego:

Academic Press.

Adaptive Noise Cancellation: Using adaptive noise cancellation with an

extra channel in which only the ECG is collected. For details on this

method see Medical Engineering and Physics, 1997, Vol 19 No 3 pp

279-285, "A comparison of ECG cancellation techniques applied to the

surface recording of somatosensory evoked potentials", J. S. Black and

D. F. Lovely.

Use of histograms: Finding a histogram of the EMG amplitudes, and

removing (or keeping as missing values) all amplitudes which clearly do

not belong to the EMG.

Improved electrode placement: Positioning the ground electrode in such a

manner that the heartbeat reaches the ground and active electrodes

simultaneously and does not get recorded.

Thanks again to all who responded to our question.

Sincerely,

Zvika Ben-Haim

zvikabh@aluf.technion.ac.il

First of all, we would like to sincerely thank the many people who responded

to our question. The responses were serious and well-focused, and have

helped us a great deal in attempting to solve our problem. Attached is

a summary of the responses we received for our query.

Original Query

> I am interested to know what is the preferred method to remove heart

> beat signals from EMG recordings of trunk muscles. with minimum loss

or

> distortion of the EMG signal itself. A summary of the responses I

will

> submit to the list members.

(Original question posted by Dr. Ruth Dickstein)

Summary of responses on removal of ECG artifacts from EMG signals

Highpass Filtering: The most common reply was to use some form

of highpass filtering, with suggested cutoffs ranging between 1 and 40

Hz. Many suggested performing an FFT and zeroing the lower frequencies,

then performing an inverse FFT, in order to obtain a sharper cutoff than

by using ordinary analog filters. An article describing the trade-off in

choice of cutoff frequency is: Redfern et al, "High-pass filtering

to remove electrocardiographic interference from torso EMG recordings,"

Clin. Biomech. 1993; 8; 44-48.

Gating: A simple and usually satisfactory method is known as

gating. The idea is that values above a trigger value are assumed to be

heartbeat signals, and are treated as missing values. This has the advantage

of fast and automatic data processing. The gating should be performed before

integration or any other method of smoothing to avoid data loss.

Subtraction: Another common reply suggested subtracting the data

of a 'clean' heartbeat from all occurances of heartbeats in the data. Better

results can apparently be achieved by selecting as a 'clean' heartbeat

an average 'template' of many heartbeats recorded with no muscle activity.

Bartolo et al (see "Analysis of diaphragm EMG signals: comparison

of gating vs. subtraction for removal of ECG contamination", J. Appl. Physiol.

80(6); 1898-1902) compared the gating and subtraction methods using several

common numerical processing techniques, such as mean power, zero crossing

frequency and so on. They found no significant difference in results between

signals processed using these two methods, and concluded that the added

computational power required to use the more complex method of subtraction

does not yield significantly better results.

A combination of the subtraction and filtering techniques was also suggested.

In this method the subtraction would be performed in the frequency domain

(on an FFT signal). In other words, the FFT of a clean heartbeat would

be subtrated from the FFT of the data, and the result converted back using

an inverse FFT. As far as we know this has not been attempted yet with

EMG signals.

Wavelets: Another suggestion was to use wavelet smoothing to

remove heartbeat signal frequencies without distorting EMG data at the

same frequency. For a technical introduction to wavelet theory, see Chui

(1994): "Wavelets: Theory, Algorithms and Applications", San Diego:

Academic Press.

Adaptive Noise Cancellation: Using adaptive noise cancellation

with an extra channel in which only the ECG is collected. For details on

this method see Medical Engineering and Physics, 1997, Vol 19 No

3 pp 279-285, "A comparison of ECG cancellation techniques applied to the

surface recording of somatosensory evoked potentials", J. S. Black and

D. F. Lovely.

Use of histograms: Finding a histogram of the EMG amplitudes,

and removing (or keeping as missing values) all amplitudes which clearly

do not belong to the EMG.

Improved electrode placement: Positioning the ground electrode

in such a manner that the heartbeat reaches the ground and active electrodes

simultaneously and does not get recorded.

Thanks again to all who responded to our question.

Sincerely,

Zvika Ben-Haim

zvikabh@aluf.technion.ac.il