Bruxism is a condition in which those who suffer from it inadvertently clench or grind their teeth with excessive force. This can happen during the day (awake bruxism) or while sleeping (sleep bruxism). Depending on the frequency and severity of bruxism, it can cause jaw disorders, headaches or tooth wear.
A way to stop severe bruxism from causing health problems is by automatically detecting the periods of clenching/grinding and alerting the bruxer in the case of awake bruxism, or waking him up in the case of sleep bruxism. As bruxism is caused by an unconscious contraction of the temporalis and masseter muscles, an episode could be detected by measuring the EMG signals generated by one of those muscles. The detection of an abnormally large EMG signal could trigger some kind of alarm, such as a beeping sound or a vibration, in order to alert or to wake up the bruxer.
With all the above in mind, I have developed a simple prototype of a bruxism alarm using one Mumai EMG circuit, as an example of what can be done with this myoelectric interface. The video below shows the elements that compose the prototype and how it works.
The operation of this system is very simple. The measuring electrodes are located over the masseter muscle and the reference electrode is placed over the bony area behind the ear. After turning on the system, it has to be calibrated. First, the EMG signal baseline is measured by having the masseter muscle at rest during 30 s. This value is subtracted from all the measurements taken from this moment, to have a baseline of 0 V. This step needs to be performed in order to calculate the running moving average of the measured EMG signal. The running moving average is used to process the raw EMG signal provided by the Mumai EMG circuit by computing its amplitude.
During the second calibration step, the user performs a strong contraction with the masseter muscle by strongly clenching his teeth. This gives a measure of the maximum force the user is able to exert, which is known as maximum voluntary contraction (MVC). The activation threshold (the value which will trigger the bruxism alarm) is computed as a percentage of the MVC.
After calibration, the system enters into operation mode during which an audible alarm, provided by a buzzer, is triggered every time the amplitude of the EMG signal exceeds the activation threshold. This mode could be improved by activating the alarm only when the amplitude of the EMG signal exceeds the activation threshold during a predefined period of time. In this way, false positives would be avoided and the system would be more robust.
The code I have used to implement the bruxism alarm is hosted on the Mumai repository.