View Full Version : Summary: Minimum muscle off set

Michael Dillon
08-02-1998, 11:32 PM

Thankyou to all who contributed responses to my question about minimum
periods of muscle inactivity. It's nice to know that there are a few
people tackling the same hurdle.

There are some useful references contained within the summary below.

Again thankyou for your contribution.


Mick Dillon



0000,0000,ffffGood afternoon.

I am currently completing some software to analysed EMG data including
muscle on/off times. This topic has received much attention both within
the literature and Biomech-l postings but despite our best efforts
remains a dubious practice.

Periods of muscle activity have been determined in numerous ways. After
much consideration I have chosen the following 2 criteria for my

1. Mean resting level + 3 SD above that mean to define a resting
threshold for each muscle.

2. The muscle must remain 'on' for a minimum of ~50 m/s. This
t-value has been specifically selected for each muscle
analysed based on previous literature.

My concern is that multiple bursts of activity which meet the above 2
criteria are interspersed with very small periods of inactivity (about
9-22 ms). The muscles most affected are Tibialis Anterior and Biceps
femoris during late swing.

I wish to set another test condition to examine the muscle 'off' times to
alleviate this problem, but have been unable to find any literature to
provide a physiological basis for a test condition.

I hope someone may be able to point me in the direction of some further
literature which defines the minimum period of muscle inactivity
between contractions.

Thank you in anticipation

Kindest regards,

Mick Dillon.




Probably the most comprehensive review of the subject is in:

1. Hodges, P.W., & Bui, B.H. (1996). A comparison of computer-based

methods for determination of onset of muscle contraction using

electromyography. Electroencephalography and Clinical Neurophysiology,

101, 511-519.

You are correct that the end of an EMG burst is more difficult to

determine. However, if you have clean EMG signals and a knowledge of

how your EMG activity relates to kinematic events, you should be able

develop an efficient algorithm based on the combination of the two.

Finally, it is important to develop a program that will allow you to

manually correct the points selected by the computer algorithm should

they be wrong.

Best Wishes,

David A. Gabriel

__________________________________________________ ____

Dear Mick,

I had similar dilemma with determining muscle off times. I used the

criterion for "off" that the muscle had to fall below the threshold for

least 100 msec in order to be considered off. The 100 msec duration

chosen subjectively based on the assumption that the activity I was

investigating (muscle activity around initial contact of a stride of

walking) was rather slow and that 100 msec would be between 10-15% of

cycle. I felt that if the muscle was inactive for that long then when

turned on again it was for another functional reason. I would have

ignored the little blips in between since they would likely have little

functional contribution to movement.

Also, you might be using a threshold that is too low. I had to use a

threshold of 2.5 times the resting value, not the standard deviation of

the resting value. (we were using a telemetered system with rather high


I'll be interested in the summary of responses. Will you post them?


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

Katy Rudolph, PhD, PT Ph: 617-353-5463

Center for BioDynamics fax: 617-353-5462

Department of Biomedical Engineering krudolph@bu.edu

Boston University

44 Cummington Street

Boston, MA 01887


I think that you may go to find out a paper in literature:

"Computer algorithms to characterize individual subject EMG profiles

gait," by Ross A. Bogey, Lee A. Barnes and Jacquelin Perry in

Arch Phys Med Rehabil Vol.73, pp.835-841, Sept 1992.

The paper would provide some interesting criteria which might fit to



Szi-Wen Chen, Ph.D.

Post-Doctoral Researcher

1027 Dodd Hall

Gait Analysis Laboratory, Department of Surgery

The Ohio State University

480 W. 9th Ave., Columbus OH 43210

Tel: 614-293-4832

Fax: 614-293-4834




I read your post on the biomechanics list serve. Although I can't help

you with the question you posted, I have an interest in the software

are developing to measure muscle onset. I am currently working on a

project looking at reflex latencies to imposed joint perturbation at

ankle (an inversion perturbation device) as part of a larger

considering ankle sensorimotor characheristics. Several authors have

reported with similar methodologies, however the exact methods utilized

to determine muscle onset have varied. Several have reported extremely

high reliability using several filters (high pass, low pass, followed by

smoothing filter) with either a visual inspection or 5SD above

noise to determine onset. In fear of introducing a bias through

and processing the EMG data too much I have tried using 5SD for a

of 50ms burst as the criteria for onset, however I have gotton

amounts of variablity between trials. I suspect that this may be

to several factors concerning the onset definitions, and other

methodological considerations (number of trials being averaged for

example). I am interested in any insight you may be able to share

on your experiences with the software development. Is your software

appropriate for an application in reflex latencies? Thank you in

for any insight. I will be traveling over the course of the next week

I may be away from email temporarily. Bryan

Bryan L. Riemann, MA, ATC

Doctoral Student

Neuromuscular Research Laboratory

University of Pittsburgh




I am grappling with the same problem with EMG data from cervical muscles.
I would appreciate receiving any information you gather on the topic.




John Brault

Biomechanics Research & Consulting, Inc.

840 Apollo St., Suite 218

El Segundo, CA 90245

Phone: 310-615-3112

Fax: 310-615-3038

Email: john@brcinc.com


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