Bite-Guard Bruxism Detector

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Bite-Guard Bruxism Detector

ISEF Category: Biomedical Engineering

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Subcategory: Biomedical Devices  ·  Difficulty: Advanced  ·  Setup: Home Setup  ·  Time: 1 to 2 Months

The Hook

Tooth grinders wake up with sore jaws and cracked enamel without knowing they spent the night clenching. A bite guard with a tiny accelerometer and an EMG channel could log every episode and buzz a gentle reminder. The result is an n-of-1 sleep study you run from your bedroom.

What Is It?

Bruxism is nighttime clenching and grinding of teeth. A standard bite guard is a soft dental tray. Embedding a small accelerometer and EMG electrodes turns it into a sensor.

The accelerometer picks up jaw clench and motion. EMG records masseter activity. A coin motor in the tray delivers haptic biofeedback when activity crosses a threshold.

For science fair purposes, the project is a personal study (n-of-1) plus close family with informed consent. The model compares nights with vs. without biofeedback and reports event counts and tooth wear self-ratings.

Why This Is a Good Topic

Bruxism research is a clinical niche with cheap hardware. You will learn embedded biosensing, sleep-study design, and personal-experiment analysis.

Research Questions

  • How does haptic feedback change bruxism event counts?
  • What is the effect of EMG threshold on detection sensitivity?
  • Does the accelerometer alone suffice without EMG?
  • To what extent does sleep stage shift event timing?
  • Which feedback intensity is most accepted by the wearer?
  • How does the device affect subjective sleep quality?
  • What is the effect of guard fit on sensor stability?

Basic Materials

  • MPU-6050 IMU.
  • MyoWare EMG sensor with mouth-safe electrode wires.
  • ESP32 with low-power mode.
  • Coin vibration motor.
  • Dental-grade tray base (over-the-counter sport guard).
  • LiPo battery and food-safe enclosure.
  • Sleep-quality survey form.

Advanced Materials

  • Polysomnography lab access.
  • Clinical dental mentor.
  • Custom dental tray.
  • Calibrated EMG amplifier.

Software & Tools

  • Arduino IDE or PlatformIO: Programs the ESP32.
  • Python (NumPy and SciPy): Detects events offline.
  • Matplotlib: Plots event counts vs. condition.
  • Google Forms: Collects nightly self-reports.

Experiment Steps

  1. Get dental supervision and document materials safety.
  2. Calibrate sensors against a known clench force on a bite plate.
  3. Decide thresholds, feedback patterns, and randomized condition order.
  4. Wear the guard for a baseline period before activating feedback.
  5. Log nightly events and complete the survey each morning.
  6. Compare event counts and survey scores statistically.

Common Pitfalls

  • Skipping dental review and using non-food-safe materials.
  • Letting the threshold drift across nights.
  • Reporting one night per condition.
  • Treating any jaw motion as bruxism.
  • Ignoring subjective sleep-quality changes.

What Makes This Competitive

A competitive entry documents safety, ensures dental supervision before any in-mouth electronics, runs at least 14 nights per condition, randomizes condition order, and compares results to published actigraphy-style bruxism literature. Sensor calibration against a known load matters.

Project Variations

  • Compare biofeedback timing (immediate vs. delayed).
  • Add a saliva-pH strip readout each morning.
  • Run a tinnitus-overlap study because bruxism and tinnitus often co-occur.

Learn More

  • PubMed: Search portable bruxism detection reviews.
  • NIH PubMed Central: Open-access dental sleep medicine papers.
  • American Academy of Sleep Medicine: Open guidelines.
  • MyoWare documentation: Free wiring guides.
  • MIT OpenCourseWare: Course 6.555 Biomedical Signal and Image Processing.
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