|Electromyography Vs Vibromyography to Assess Muscle Activity
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|Author:||icegirlclaire [ Mon Dec 13, 2010 2:45 am ]|
|Post subject:||Electromyography Vs Vibromyography to Assess Muscle Activity|
Surface electromyography has enjoyed an almost magnetic appeal ever since its inception. Sports medicine practitioners, physical therapists, sports trainers and EMG researchers have all used the surface electromyogram (SEMG) to assess muscle activity and activation patterns. It is important for practitioners in all of these fields (and more) to have insight into patients/subjects usage of the major movers surrounding joints in order to optimize strength training, assess injury risk as well as plan and execute rehabilitation after injury.
Invasive EMG techniques (involving insertion of fine wires and needles into the muscle body) can yield valuable information regarding muscle activity, but are not favored because of the time necessary for preparation, risk of infection and discomfort.
Unfortunately, the SEMG techniques available to these practitioners are limited in their applicability and usability because of fundamental disconnects between observable parameters of the SMEG and muscle activity.
Here is a brief summary of what we have learned from invasive EMG techniques. Generally speaking, all of the fibers in a given muscle are not active until the muscle is producing about 80% of its force generating capacity. Until this point, these fibers are used on a sort of rotating (some might say stochastic, but that is a simplification) basis to avoid fatigue. After this 80% point, all of the muscle fibers are in use on an almost constant basis; therefore the only way to generate more force is to use the fibers more frequently.
Unfortunately, despite the efforts of hundreds of researchers over the last century, it is still not possible to tease this information out of a myogram from the surface of the skin for the full range of muscle activity levels. This disconnect results in a blind spot for professionals that leads to increased risk of injury because of imbalanced muscle training/usage as well as rehabilitation techniques that lack specificity and are often not as effective as either the PT or patient would hope for.
Until about 30 years ago, there was a lack of alternative tools available for examining muscle activity from the surface of the skin, and so electromyographers were left using the only tool at their disposal. Around that time mechanical devices for measuring small vibration were becoming sensitive enough that their potential for measuring muscle activity at the skin surface came under serious investigation. There are many types of devices for measuring vibration (pressure pads, laser position sensors, velocimeters, accelerometers, piezoelectric contact sensors, etc.), and so the term "mechanomyogram" was proposed as a catch all term for this purpose. In contrast, Sonostics uses the term vibromyography (VMG) or vibromyogram for measurements taken with an accelerometer to distinguish them from other forms of mechanomyography.
Early research focused on the idea that recruitment and firing rate would be measurable from the skin surface with the mechanomyogram and so the analyses tended to be very similar to those used to examine SEMG data. Namely, using amplitude of the raw signal as well as power and frequency metrics derived from the FFT (fast Fourier transform). These types of analyses yielded measurements of muscle activity that were sometimes as good, but not often better than EMG analyses of the time.
As an example of this type of analysis, we recorded SEMG and VMG data from the Vastus Lateralis of three adult male participants during dynamic isometric knee extension while using a dynamometer to record the extension torques. Below is a graphic representation of the data.
When we examine the classical EMG analyses applied to this data and plot them against torques, it is clear that none have the ability to track muscle activity.
In contrast, when we track the known twitch frequency of type IIb muscle fibers using Sonostics’ proprietary wavelet packet analyses we find a direct relationship between the VMG and muscle effort.
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