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  • EMG onset determination summary

    Thanks for the replies I received regarding my query. I had many replies
    from list serv members saything they had nothing to contribute but were very
    interested in our summary.

    Again, thanks to all!
    Sujani

    Original query:
    I am Sujani,a research engineer at the ADAM Center at Long Island
    University, NY. The ADAM Center is a small laboratory that does research on
    human movement. To date, we have focused on 3D kinematics and force
    platform data capture and analysis.

    Currently, I have started looking at the surface EMG data that we have
    collected. We are particularly interested in onset and offset EMG
    timing and would like to develop a computerized algorithm that allows us to
    evaluate differing filters, threshold criteria (SD from baseline, etc),
    samples assessed, etc. I particularly enjoyed the articles by Hodges
    and Bui (1996): ³A comparison of computer-based methods for the
    determination of onset of muscle contraction using electromyography² in
    Electroencephalography and Neurophysiology.

    I was wondering if I could get the latest updates and details on EMG
    onset determination. As I was browsing the web, I came across a lot of
    literature. It looks like each person uses a different value for
    threhold, frequency for filtering,sample rate etc. What is the best way to
    determine the onset?

    I found out that some work has been done in MATLAB in this regard.
    Before I start to write a new program in Labview, I was wondering if anyone
    know about any shareware that may be available? Any ideas or
    suggestions are welcome.

    *******************************
    Responses:
    Paolo Bonato developed a method that he published in IEEE (A statistical
    method for the measurement of muscle activation intervals from surface
    myoelectric signal during gait. IEEE Trans Biomed Eng. 1998
    Mar;45(3):287-99.). It develops an optimal criterion, based on the
    statistics of the EMG signal and background noise. I had coded it in MATLAB
    (enclosed --- the comments are limited, but I used the terms from his
    article). PLEASE retest if you use the m-file --- I did the work a year or
    two ago. In the end, we decided to manually annotate ensemble profiles,
    since our work used cyclic activity (normal gait). Annotating individual
    muscle actions can be rather challenging.

    You might also look at some work by Dario Farina (A fast and reliable
    technique for muscle activity detection from surface EMG signals. IEEE Trans
    Biomed Eng. 2003 Mar;50(3):316-23.) This work is another approach.

    Best of luck,
    Ted Clancy
    ted@ece.wpi.edu
    ******************************
    Mega EMG system's MegaWin software has the onset analysis integrated in our
    software. For further information, please contact our USA distributor, Peak
    Performance Inc, Centennial, CO as follows:

    Peak Performance Technologies, Inc.
    7388 South Revere Parkway, Suite 901
    Centennial, CO 80112

    Mr Larry Scheirman
    Mr Doug Reinke
    Mr George Miller
    Mr Christian Reist
    Tel. +1-303-799 8686
    Tel. 1-800-PIK-PEAK (USA only)
    Fax. +1-303-799 8690
    lscheirman@peakperform.com (Mr Scheirman)
    dreinke@peakperform.com (Mr Reinke)
    gmiller@peakperform.com (Mr Miller)
    creist@2peakperform.com (Mr Reist)
    Best regards
    Mega Electronics Ltd

    Kari Tiihonen
    Export Manager
    kari.tiihonen@meltd.fi
    ******************************
    HI,

    I'm a grad student in Kinesiology in Canada. I think, so far, we don't have
    a gold standard for EMG onset threshold. To my knowledge, it all depends on
    how neat is your data. In my project, I collect the EMG from gastro and
    soleus and I used Baseline mean+3S.D to determine the onset. I saw couple of
    literature used 4S.D. If you find any conlusion regrading it, could you let
    me know? Since that's part of my thesis I need to write. Thanks!

    Tony
    church1026@yahoo.ca

    ******************************
    In the following recently published paper a matlab application is described
    Roetenberg D, Buurke JH, Veltink PH, Forner Cordero A, Hermens HJ.
    Surface electromyography analysis for variable gait.
    Gait Posture. 2003 Oct;18(2):109-17.

    Priv. Doz. Dr. Dieter Rosenbaum
    Funktionsbereich Bewegungsanalytik
    Klinik und Poliklinik fuer Allgemeine Orthopaedie
    Universitaetsklinikum Muenster
    Domagkstr. 3
    D-48149 Muenster

    Fon: +49 (0)251 - 8352970
    Fax: +49 (0)251 - 8352993
    Email: diro@uni-muenster.de
    http://medweb.uni-muenster.de/institute/orth/motionlab

    ******************************
    Hi Sujani,

    You are facing a "conflicting task". I discussed some of that in a
    recent paper:

    Morey-Klapsing G, Arampatzis A, Bruggemann GP. Choosing EMG parameters:
    comparison of different onset determination algorithms and EMG integrals
    in a joint stability study. Clinical Biomechanics. 2004, 19(2): 196-201

    In the paper you will get several useful references.

    Some advices from my side ... just test several filters and you will see...

    1. Most filters introduce a time lag.
    2. You can avoid this by filtering forwards and backwards, but you will
    see that this widens the curve on the time axis.
    3. I found (as suggested to me by At Hof) that the median filter pretty
    much preserves the rises and falls, I use a 7 points back and forth
    median filter (sampling at 1000 Hz).
    4. It might be useful to include a further criterion in addition to only
    signal amplitude. This would be above the threshold for at least some
    time.
    5. I would say (even if I didn't that way in my paper) that it is
    preferable to take the mean and SD during a "zero" measurement ...
    subject sitting or better lying flat and relaxed ... than whilst
    standing, as backround actrivity might vary a lot.

    In general I still prefer the integral of the signal in a fixed, self
    defined interval comprising the interesting zone (for example during the
    last 50 or 100 ms prior to ground contact). This will provide more
    useful information and is not subject to the criticism of onset time
    determination.
    However for some issues Onset times are what we really want. And when
    differences are big enough (lets say above 15 ms) and background
    activity is determined in a relaxed condition this should be possible.

    One more paper that might be useful:

    Bonato, P.; D'Alessio, T; Knaflitz, M. A statistical method for the
    measurement of muscle activation intervals from surface myoelectric
    signal during gait. IEEE Transactions on Biomedical Engineering. 1988,
    45(3), 287-299.

    Good luck,
    Gaspar
    morey@dshs-koeln.de

    ******************************
    Sujani,

    For onset detection you can use the AGLR algorithm described in the
    following article.

    Objective motor response onset detection in surface myoelectric signals.
    Staude G, Wolf W. Medical Engineering & Physics 21, pp 449-467, 1999.

    Used for gait:

    Surface electromyography analysis for variable gait

    D. Roetenberg, J.H. Buurke, P.H. Veltink, A. Forner-Cordero, H.J. Hermens

    Gait & Posture, Vol 18/2, pp 109-117, 2003

    In those articles you will find information on threhold, frequency for
    filtering,sample rate etc.

    Daniel
    D.Roetenberg@utwente.nl

    ******************************

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