Tweet
Thanks to everyone who responded to my request. Below is the Original
inquiry and the list of responses.
Once again thanks to all to contributed.
-------------
>I'm currently designing a project that is to look at the decline of power
>production of the quadriceps following a fatigue protocol. The post test
>will be a dynamic knee extension performed on an isotonic dynamometer. My
>question to the forum is can I obtain spectral EMG data from the quads on a
>contraction that will generally take less that 1 second? I've seen several
>studies that have measured spectral alterations in a dynamic contraction of
>the muscle, although these contractions were of a longer duration. (Muro et
>al, Amer. J. Physical Med. 1982 & Moritani et al, Amer. J. Physical Med.
>1988) 2 and 5 sec dynamic contractions respectively.
>
>I know I can obtain the data, but is it a valid measurement?
>
-------------------
To: Randy Schmitz
From: Brian Bergemann
Subject: Re: EMG Spectral analysis
HI Randy: I did a power spectrum analysis in my dissertation, Brian
Bergemann, Penn State University, 1977. It should be on microfiche,
University of Oregon. In the Appendix is a fortran program that does
fourier analysis. If you need a program that will give you the power
spectrum of the frequencies of the EMG go to that dissertation and try it.
The duration of contractions were 3 seconds.
----------------------------
From: "A.Mannion"
Subject: Re: EMG Spectral analysis
To: rjs5s@curry.edschool.virginia.edu
Date: Mon, 20 Jan 1997 18:33:29 +0000 (GMT)
MIME-Version: 1.0
You usually need at least 1024 data points to do a decent FFT but if you
sample very rapidly then this should be possible in less than a second.
But why do you have to use an isotonic contraction? Could you not do a
little isometric contraction for about 10 s at the start and end of the
fatiguing protocol? This would then get round the problems of both the
short sampling time and the nature of the movement being dynamic
(non-stationary signal).
---------------------------
From: "V.BALTZOPOULOS"
Organization: ALSAGER, CREWE+ALSAGER FACULTY, MMU
To: rjs5s@curry.edschool.virginia.edu
Date: Wed, 22 Jan 1997 14:31:51 GMT
Subject: Re: EMG Spectral analysis
Priority: normal
Dear Randy
Assuming that the phenomenon you are recording is contained in your
time interval (say 0.5 s) then you can analyse your data, but the
sampling rate is crucial. If for example your sampling rate is 1000
Hz then you will end up with 500 points which means that the FFT will
calculate 250 harmonics in the frequency range 2-500 Hz. If your fs
is 100 Hz then you will collect 50 points and you will only be able
to see 25 harmonics in the range 2-50 Hz. If the signal contained
higher frequencies then these will appear distorted inside the above
range (leakage). Generally speaking with a high fs you should be ok.
What the time period does affect, however, is the frequency increment
(df). For example with a sampling frequency of 1000 Hz a period of
0.5 s will give a resolution of 2 Hz (i.e. 250 harmonics at
2,4,6..500 Hz) whereas a period of 1 s will give you a resolution of
1 Hz (i.e. 500 harmonics at 1,2,3..500 Hz). I don't think however
that you will want to observe say two distinct phenomena occuring at
frequencies that are less than 1 Hz apart?!
In view of the short record, and contrary to popular advice, you
should not pad your data with zeros if N is not a power of 2 and you
only have access to a radix 2 FFT. Although this does not alter the
SHAPE of the power spectrum if the frequency axis is normalised (i.e.
0-1, where 1 is the maximum frequency), the frequency of the
harmonics (and df) will be affected.
I hope that this is helpful and let me know if you require any
further assistance.
Best wishes
Dr V. (Bill) Baltzopoulos
Biomechanics Group
Manchester Metropolitan University
baltz@mmu.ac.uk
Tel: +44 161 2475659
----------------------------------
From: "Jim Potvin"
Organization: Animal & Poultry Science
To: rjs5s@curry.edschool.virginia.edu
Date: Sun, 26 Jan 1997 09:04:57 EDT
Subject: EMG Spectral analysis
Priority: normal
Hi Randy
With regards to using dynamic EMG to calculate the spectrum, the main
issue is stationarity. It is actually better to use shorter samples
during the dynamic contractions because the amplitude will likely
vary over time and this will adversely affect your stationarity.
Shankar et al (1989) Electro. Clin. Neurophys 73:142-150 is the only
paper I have found that has tested the stationarity during dynamic
contractions. They studied the biceps brachii during flexion
rotations between 40 and 160 deg/s. Their sample durations ranged
from 0.25 to 1.0 seconds and they found that 96% of their data
records were at least weakly stationary. We have a paper coming out in
J. Electromyography and Kinesiology showing that the changes in MnPF
from 250 ms segments recorded continuously throughout a fatiguing
contraction are similar to those recorder isometrically before and
after the trial. I also have a paper coming out in the Journal of
Applied Physiology (this month I think) that looks at the effects of
muscle length and velocity (concentric vs. eccentric) on the EMG
spectrum and amplitude at rest and under fatigued conditions. These
articles and the references cited may be of further help to you.
__________________________________________________ _________
Jim Potvin, PhD
Biomechanics Laboratory
Department of Human Biology and Nutritional Sciences
University of Guelph
Guelph, Ontario, Canada
N1G 2W1
Tel 519-824-4120 ext 4589
Fax 519-763-5902
---------------------------------------
Dear Randy,
In my opinion this can be safely done. Just use a FFT over
the complete EMG burst. The median frequency has of course some
random error (1), but you have to cope with that anyay. With some
others I have done similar experiments on the triceps surae (2,3) and
the vastus lateralis (4). If your reviewer happens to be a signal
processing 'fundamentalist' , he will ask you difficult questions on
stationarity etc. For that case you may try some more complicated
time-frequency transforms (5). Our main problem was that we did
find only very small spectral effects, even in very hard exercise
(2,3,4). As a consequence, I personally am hesitant to couple fatigue
with any EMG frequency effect.
Good Luck anyway,
At Hof
Refs.
1) Hof,A.L. IEEE Trans BME 38: 1077-1088 (1991)
2) Ament, W, et al. J. Electromyogr. Kinesiol. 3: 214-220 (1993)
3) Ament, W. et al. Eur J Appl Physiol 74: 180-186 (1996)
4) Jansen, R. et al Eur J. Appl Physiol (in press)
5) Bonato, P. et al IEEE EMBS Magazine 15/6:102-111 (1996).
At Hof
Department of Medical Physiology
University of Groningen
Bloemsingel 10
NL-9712 KZ GRONINGEN
The Netherlands
Phone: (31) 50 3632645
Fax: (31) 50 3632751
e-mail: a.l.hof@med.rug.nl
---------------------------------------------------
To: Randy Schmitz
From: iallison@info.curtin.edu.au (Garry Allison)
Subject: Re: EMG Spectral analysis
You can always argue the case of validity the trade off will be the
*reliability* of the derived variable.
Good luck.
GTA.
--------------------------------------------
From: "John P. Peach"
To: "'Randy Schmitz'"
Subject: RE: EMG Spectral analysis
Date: Sat, 18 Jan 1997 13:17:06 -0500
MIME-Version: 1.0
Hello;
In order to use spectral parameters of EMG you have to take your
EMG and perform a fast fourier transformation (FFT) on it. The harmonics
of the FFT (or if you like, its resolution) is a function of the sample
rate (SR) and the number of samples collected (N). There is restrictions
on the value of N. N must be a value of 2^n, so you are looking at numbers
like, 2,4,8,16,32,64,128,256,512,1024,2048 etc... so you will have to
choose your sampling rate (for a given collection time) to optimize the
value of N.
Now for the real problem. The harmonics are determined by:
SR / N = harmonic
this can also be expressed as
SR/ (Time * SR) = harmonic
this simplifies to;
1/Time = harmonic
This means that the FFT harmonic (i.e. the resolution of the FFT)
is a function of the collection time. So if you are looking at the fatigue
rate of the quads the smallest change you can detect is 1 Hz if the
movement takes a full second. With out knowing your protocol I cannot
really comment on how good this is. My gut feeling is that it is going to
be problematic.
The use of MPF as a measure of fatigue is only valid if the
contraction is isometric. If the contraction is dynamic the motor pool
changes and this violates one of the basic assumptions of the MPF
calculation.
I just submitted a paper to the Journal of Electromyography and
Kinesiology looking at the reliability of the MedianPF decay rate
calculation. There is some problems with it in that it is quite variable.
On the back extensor muscles the intercept values are reliable if you have
5 or more samples and the slope (decay rate) is not reliable unless you
have several hundred measures.
John
----------------------------------------------------------
Randy J. Schmitz
Ph.D. student in Sports Medicine
University of Virginia
rjs5s@virginia.edu
(804) 984-5243
inquiry and the list of responses.
Once again thanks to all to contributed.
-------------
>I'm currently designing a project that is to look at the decline of power
>production of the quadriceps following a fatigue protocol. The post test
>will be a dynamic knee extension performed on an isotonic dynamometer. My
>question to the forum is can I obtain spectral EMG data from the quads on a
>contraction that will generally take less that 1 second? I've seen several
>studies that have measured spectral alterations in a dynamic contraction of
>the muscle, although these contractions were of a longer duration. (Muro et
>al, Amer. J. Physical Med. 1982 & Moritani et al, Amer. J. Physical Med.
>1988) 2 and 5 sec dynamic contractions respectively.
>
>I know I can obtain the data, but is it a valid measurement?
>
-------------------
To: Randy Schmitz
From: Brian Bergemann
Subject: Re: EMG Spectral analysis
HI Randy: I did a power spectrum analysis in my dissertation, Brian
Bergemann, Penn State University, 1977. It should be on microfiche,
University of Oregon. In the Appendix is a fortran program that does
fourier analysis. If you need a program that will give you the power
spectrum of the frequencies of the EMG go to that dissertation and try it.
The duration of contractions were 3 seconds.
----------------------------
From: "A.Mannion"
Subject: Re: EMG Spectral analysis
To: rjs5s@curry.edschool.virginia.edu
Date: Mon, 20 Jan 1997 18:33:29 +0000 (GMT)
MIME-Version: 1.0
You usually need at least 1024 data points to do a decent FFT but if you
sample very rapidly then this should be possible in less than a second.
But why do you have to use an isotonic contraction? Could you not do a
little isometric contraction for about 10 s at the start and end of the
fatiguing protocol? This would then get round the problems of both the
short sampling time and the nature of the movement being dynamic
(non-stationary signal).
---------------------------
From: "V.BALTZOPOULOS"
Organization: ALSAGER, CREWE+ALSAGER FACULTY, MMU
To: rjs5s@curry.edschool.virginia.edu
Date: Wed, 22 Jan 1997 14:31:51 GMT
Subject: Re: EMG Spectral analysis
Priority: normal
Dear Randy
Assuming that the phenomenon you are recording is contained in your
time interval (say 0.5 s) then you can analyse your data, but the
sampling rate is crucial. If for example your sampling rate is 1000
Hz then you will end up with 500 points which means that the FFT will
calculate 250 harmonics in the frequency range 2-500 Hz. If your fs
is 100 Hz then you will collect 50 points and you will only be able
to see 25 harmonics in the range 2-50 Hz. If the signal contained
higher frequencies then these will appear distorted inside the above
range (leakage). Generally speaking with a high fs you should be ok.
What the time period does affect, however, is the frequency increment
(df). For example with a sampling frequency of 1000 Hz a period of
0.5 s will give a resolution of 2 Hz (i.e. 250 harmonics at
2,4,6..500 Hz) whereas a period of 1 s will give you a resolution of
1 Hz (i.e. 500 harmonics at 1,2,3..500 Hz). I don't think however
that you will want to observe say two distinct phenomena occuring at
frequencies that are less than 1 Hz apart?!
In view of the short record, and contrary to popular advice, you
should not pad your data with zeros if N is not a power of 2 and you
only have access to a radix 2 FFT. Although this does not alter the
SHAPE of the power spectrum if the frequency axis is normalised (i.e.
0-1, where 1 is the maximum frequency), the frequency of the
harmonics (and df) will be affected.
I hope that this is helpful and let me know if you require any
further assistance.
Best wishes
Dr V. (Bill) Baltzopoulos
Biomechanics Group
Manchester Metropolitan University
baltz@mmu.ac.uk
Tel: +44 161 2475659
----------------------------------
From: "Jim Potvin"
Organization: Animal & Poultry Science
To: rjs5s@curry.edschool.virginia.edu
Date: Sun, 26 Jan 1997 09:04:57 EDT
Subject: EMG Spectral analysis
Priority: normal
Hi Randy
With regards to using dynamic EMG to calculate the spectrum, the main
issue is stationarity. It is actually better to use shorter samples
during the dynamic contractions because the amplitude will likely
vary over time and this will adversely affect your stationarity.
Shankar et al (1989) Electro. Clin. Neurophys 73:142-150 is the only
paper I have found that has tested the stationarity during dynamic
contractions. They studied the biceps brachii during flexion
rotations between 40 and 160 deg/s. Their sample durations ranged
from 0.25 to 1.0 seconds and they found that 96% of their data
records were at least weakly stationary. We have a paper coming out in
J. Electromyography and Kinesiology showing that the changes in MnPF
from 250 ms segments recorded continuously throughout a fatiguing
contraction are similar to those recorder isometrically before and
after the trial. I also have a paper coming out in the Journal of
Applied Physiology (this month I think) that looks at the effects of
muscle length and velocity (concentric vs. eccentric) on the EMG
spectrum and amplitude at rest and under fatigued conditions. These
articles and the references cited may be of further help to you.
__________________________________________________ _________
Jim Potvin, PhD
Biomechanics Laboratory
Department of Human Biology and Nutritional Sciences
University of Guelph
Guelph, Ontario, Canada
N1G 2W1
Tel 519-824-4120 ext 4589
Fax 519-763-5902
---------------------------------------
Dear Randy,
In my opinion this can be safely done. Just use a FFT over
the complete EMG burst. The median frequency has of course some
random error (1), but you have to cope with that anyay. With some
others I have done similar experiments on the triceps surae (2,3) and
the vastus lateralis (4). If your reviewer happens to be a signal
processing 'fundamentalist' , he will ask you difficult questions on
stationarity etc. For that case you may try some more complicated
time-frequency transforms (5). Our main problem was that we did
find only very small spectral effects, even in very hard exercise
(2,3,4). As a consequence, I personally am hesitant to couple fatigue
with any EMG frequency effect.
Good Luck anyway,
At Hof
Refs.
1) Hof,A.L. IEEE Trans BME 38: 1077-1088 (1991)
2) Ament, W, et al. J. Electromyogr. Kinesiol. 3: 214-220 (1993)
3) Ament, W. et al. Eur J Appl Physiol 74: 180-186 (1996)
4) Jansen, R. et al Eur J. Appl Physiol (in press)
5) Bonato, P. et al IEEE EMBS Magazine 15/6:102-111 (1996).
At Hof
Department of Medical Physiology
University of Groningen
Bloemsingel 10
NL-9712 KZ GRONINGEN
The Netherlands
Phone: (31) 50 3632645
Fax: (31) 50 3632751
e-mail: a.l.hof@med.rug.nl
---------------------------------------------------
To: Randy Schmitz
From: iallison@info.curtin.edu.au (Garry Allison)
Subject: Re: EMG Spectral analysis
You can always argue the case of validity the trade off will be the
*reliability* of the derived variable.
Good luck.
GTA.
--------------------------------------------
From: "John P. Peach"
To: "'Randy Schmitz'"
Subject: RE: EMG Spectral analysis
Date: Sat, 18 Jan 1997 13:17:06 -0500
MIME-Version: 1.0
Hello;
In order to use spectral parameters of EMG you have to take your
EMG and perform a fast fourier transformation (FFT) on it. The harmonics
of the FFT (or if you like, its resolution) is a function of the sample
rate (SR) and the number of samples collected (N). There is restrictions
on the value of N. N must be a value of 2^n, so you are looking at numbers
like, 2,4,8,16,32,64,128,256,512,1024,2048 etc... so you will have to
choose your sampling rate (for a given collection time) to optimize the
value of N.
Now for the real problem. The harmonics are determined by:
SR / N = harmonic
this can also be expressed as
SR/ (Time * SR) = harmonic
this simplifies to;
1/Time = harmonic
This means that the FFT harmonic (i.e. the resolution of the FFT)
is a function of the collection time. So if you are looking at the fatigue
rate of the quads the smallest change you can detect is 1 Hz if the
movement takes a full second. With out knowing your protocol I cannot
really comment on how good this is. My gut feeling is that it is going to
be problematic.
The use of MPF as a measure of fatigue is only valid if the
contraction is isometric. If the contraction is dynamic the motor pool
changes and this violates one of the basic assumptions of the MPF
calculation.
I just submitted a paper to the Journal of Electromyography and
Kinesiology looking at the reliability of the MedianPF decay rate
calculation. There is some problems with it in that it is quite variable.
On the back extensor muscles the intercept values are reliable if you have
5 or more samples and the slope (decay rate) is not reliable unless you
have several hundred measures.
John
----------------------------------------------------------
Randy J. Schmitz
Ph.D. student in Sports Medicine
University of Virginia
rjs5s@virginia.edu
(804) 984-5243