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Summary of EMG spectral analysis

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  • Summary of EMG spectral analysis

    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
    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).


    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
    Tel: +44 161 2475659

    From: "Jim Potvin"
    Organization: Animal & Poultry Science
    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

    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
    The Netherlands
    Phone: (31) 50 3632645
    Fax: (31) 50 3632751

    To: Randy Schmitz
    From: (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.

    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


    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

    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.



    Randy J. Schmitz
    Ph.D. student in Sports Medicine
    University of Virginia
    (804) 984-5243