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How Instrumented Mouthguards Measure Head Impacts

Instrumented mouthguards place accelerometers and gyroscopes close to the skull by coupling them to the teeth. They can estimate straight-line and rotational head motion more directly than loose helmet sensors, but fitting, calibration, filtering and impact validation determine data quality.

An instrumented mouthguard is a fitted protective device containing motion sensors, a small processor, storage or wireless communication and a battery. Researchers use it to record how an athlete's head moves during collisions.

Why place sensors in a mouthguard?

A helmet can move relative to the head when it is struck. A fitted upper mouthguard is coupled to the teeth and therefore follows the skull more closely. That mechanical connection can reduce measurement error, although jaw motion and a poor fit can still contaminate a recording.

What do the sensors measure?

Accelerometers measure changes in straight-line motion along several axes. Gyroscopes measure angular velocity, from which researchers can analyze rotation and rotational acceleration. Combining the axes produces a time history of the impact rather than one isolated number.

How is a real impact identified?

The electronics usually trigger when acceleration passes a threshold. Researchers then filter electrical noise and non-impact events such as dropping or handling the mouthguard. Video review helps confirm that the athlete was actually struck and identifies impact direction and activity.

How does motion become a risk estimate?

Sensor measurements can be compared with medically assessed concussions to fit a statistical risk function. Such a function estimates the probability of injury for a group at a given motion level. It cannot diagnose one athlete from one reading because susceptibility, previous injury, age and impact details vary.

What limits the technology?

Accuracy depends on fit, calibration, sampling rate, sensor range and the algorithms used to reconstruct head motion. Concussion datasets also contain far fewer injuries than ordinary impacts, which can make risk thresholds unstable. Independent datasets and consistent clinical diagnoses are needed before a model is used to change safety standards.

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100 g Head Impacts Carried 50% Concussion Risk in Mouthguard Data

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