Diagnosis and monitoring of bruxism using earbud motion sensors

A system comprising:

• at least one processor;
• memory storing instructions, that when executed by the at least one processor, causes the processor to perform operations comprising:
• receiving a signal derived from a motion sensor in an earbud, wherein the signal is captured while the earbud is inserted in an ear of a user, and wherein the signal comprises windows of signal samples;
• computing an energy of each window of signal samples;
• computing a median value of the energies of the windows of signal samples;
• determining a portion of the median value as a power threshold;
• and
• adding together windows having an average energy that exceeds the power threshold to reconstruct the signal;
• segmenting the signal into segments;
• extracting features from the segments;
• classifying the features;
• and
• determining that orofacial activity is predicted based on the classifying.

A method comprising:

• receiving, with at least one processor, a signal derived from a motion sensor in an earbud, wherein the signal is captured while the earbud is inserted in an ear of a user;
• segmenting, with the at least one processor, the signal into segments;
• extracting, with the at least one processor, features from the segments, wherein extracting features from the segments includes:
• extracting short-term features using a first sampling window;
• extracting mid-term statistical features using a second sampling window longer than the first sampling window;
• and
• long-term averaging the mid-term statistical features using a third sampling window longer than the first and second sampling windows;
• classifying, the at least one processor, the short-term features and the long-term averaged mid-term statistical features;
• and
• determining, with the at least one processor, that orofacial activity is predicted based on the classifying.