The new teeth grinding sensor model that Eric, Kei, Austin, and Jay are currently prototyping.
Jay Huber, Austin Lim, Eric Hu, and Kei Takanami are fourth-year Berkeley undergrads that are currently working on a project that they hope will help researchers develop a better understanding of bruxism, or teeth grinding. Teeth grinding is the often subconscious grinding of the teeth that is sometimes caused by stress. When done repetitively, it can lead to various and uncomfortable symptoms such as headaches, jaw pain, fatigue from lack of quality sleep, and dental damage. Because it often occurs while one sleeps, teeth grinding has been difficult to monitor – much less treat.
The team met through Professor Grace O’Connell’s Designing for the Human Body course (ME 178 / BioE 137) during the Fall 2019 semester, where they were introduced to the project. Since then, they’ve been actively prototyping, building, and revising their design to measure and track teeth grinding during a full night’s sleep. Jay, Austin, Eric, and Kei’s degree goals are quite diverse, including mechanical engineering, bioengineering, and architecture. They used their diverse perspectives and backgrounds to collaborate on a sensor that measures muscle activity in the face to track teeth grinding patterns. For their initial design, they decided to prioritize and optimize comfort, ease of use, and functionality. Their prototyping process consisted of entertaining ideas ranging from sensors between the teeth, acoustic sensors, face masks, night caps, and even an earpiece. Inspired by the earpiece idea, which would operate externally by the user’s ear rather than directly on the teeth (thereby promoting greater user comfort), the team eventually landed on a headband-esque design.
The current headband model that Jay, Austin, Eric, and Kei have designed and continue to develop.
The wearable headband detects teeth grinding through electromyography (EMG), which senses electrical signals from activated muscles near the temple. By detecting muscular movement from muscles that are needed to clench or move the jaw, the team has been able to track teeth grinding overnight. Electrical signals are recorded by the headband through three electrodes placed at each temple and the forehead. An elastic band allows some pressure to be applied to hold the sensors securely in place on the user’s forehead for more accurate recordings. Overall, the headband has been a success: it’s comfortable, easy-to-use, and non-invasive while also being accurate and able to differentiate between different types of jaw movement such as chewing, clenching, talking, and grinding.
The headband was tested with multiple activities such as talking, chewing, clenching, and grinding.
Before the COVID-19 pandemic hit, the team was working on their latest iteration of the design, which would make the device wireless, increasing usability and to ensure that the headband could be worn safely during a full night’s rest (when grinding typically occurs). The team hopes that such a device can be used to establish relationships between teeth grinding and treatment strategies. Until they’re fully satisfied with their work, it looks like the team will be on the grind – once campus activities are resumed post COVID-19, that is!
For more information about this project, please email Professor Grace O’Connell (g.oconnell@berkeley.edu).
Left to right Jay Huber, Kei Takanami, Eric Hu, Austin Lim