Electromyography is a means of tracking the activation of muscle tissue by the electrical potential generated by cells when they are active or at rest. EMG has been studied since the 17th century, but has become wide spread for research and clinical purposes over the last twenty five years with improvements to cables and amplifiers. Outside of the lab and clinic, EMG has been used by individuals as biofeedback, i.e. to help them develop control over muscle states of which they might otherwise not be aware. The Pop-O-Metre is a biofeedback tool for the purpose of training the user in muscle controls relevant to the dance form with aural feedback (rather than the more common visual feedback). While intramuscular electrodes (long needles) are still useful for inspecting individual cells and deep muscle tissue, surface electrodes are more popular for biofeedback and are sufficient for the contractions of popping.
This Pop-O-Metre was put together using the ProComp Inifiniti and sEMG sensors by Thought Technology Ltd. This system tracks changes in electrical potential using two electrodes on the active muscle and one reference electrode on a neutral body part. The ProComp Inifiniti tracks the change in potential and communicates this serially to a computer (in this case a MacBook Pro). Some code in C by Bennett Smith transforms this information into OSC messages which are the received by PureData to control sound information through various patches.
Throughout the human body we have layers of muscles that contract for different purposes so the placement of sEMG sensors depends on anatomical details. For example, abdominal muscles are notably thin and layered, making it difficult to avoid crosstalk, and for that reason, the Pop-O-Metre does not track chest pops. After some experimentation, four muscle groups were chosen for this version of the Pop-O-Metre: biceps brachii (arms), trapezius (shoulders), quadriceps fermoris (thighs) and soleus (calf). The graphic below gives a better idea about their placement. Sensor positioning was determined in consultation with the recommendations of the SENIAM project.
In theory, the action potential of a single cell is very clear to follow, with a sharp increase above some threshold followed by a fall below resting potential and then some duration of calm before the next jump in potential. sEMG measures the change in potential of large number of proximate muscle cells. This results in a very jumpy graph that obfuscates individual rising and falling phases.
With a sample rate of 256 hz, this system give enough information to around noticable delays, but still yeilds a somewhat choppy picture of this fast changing biosignal. An example of the variation in muscle activation potential collected shows the changes in potential over a minute of my dancing around while hooked up.