Automatic quantitative food intake tracking

A computer-readable storage medium storing instructions that, when executed by a computing system, cause the computing system to perform a process for quantitatively tracking food intake using smart glasses, the process comprising:

• capturing motion data indicative of motion by a user of the smart glasses;
• identifying a plurality of hand-to-mouth motions by the user by analyzing the motion data;
• identifying a plurality of chewing motions by the user using the smart glasses;
• calculating a weighted average of a number of the plurality of hand-to-mouth motions and a number of the plurality of chewing motions, wherein calculating the weighted average includes weighing the number of the plurality of hand-to-mouth motions more heavily than the number of the plurality of chewing motions;
• generating food intake frequency data by comparing the weighted average of the number of the plurality of hand-to-mouth motions and the number of the plurality of chewing motions to baseline metrics;
• and
• displaying the food intake frequency data to the user on the smart glasses.

A computing system for quantitatively tracking food intake using smart glasses, the computing system comprising:

• one or more processors;
• and
• one or more memories storing instructions that, when executed by the one or more processors, cause the computing system to perform a process comprising:
• capturing at least one image of food;
• identifying a type of the food by performing object recognition on the at least one image of food;
• determining a volume of the food by performing volume estimation on the at least one image of food;
• obtaining nutritional data associated with the type of the food and the volume of the food;
• generating nutritional performance data by comparing the nutritional data to a nutritional benchmark for a user of the smart glasses;
• identifying a plurality of hand-to-mouth motions by the user by analyzing the motion data;
• identifying a plurality of chewing motions by the user using the smart glasses;
• calculating a weighted average of a number of the plurality of hand-to-mouth motions and a number of the plurality of chewing motions, wherein calculating the weighted average includes weighing the number of the plurality of hand-to-mouth motions more heavily than the number of the plurality of chewing motions;
• generating food intake frequency data by comparing the weighted average of the number of the plurality of hand-to-mouth motions and the number of the plurality of chewing motions to baseline metrics;
• and
• displaying the nutritional performance data and the food intake frequency data to the user on the smart glasses.