Logging what we eat and accurately keeping track of calorie consumption is a strong component in pretty much any diet. The thing is though, it’s hassle.. I spend half my life eating too much and the other half dieting, normally managing to shed about 10 KG during a diet, without counting calories.

I think getting into the routine of counting my calorie intake may well reduce the amount of diets I need to go on. Ignorance is sin when it comes to putting on flab! it’s easy enough to pretend that 6th sausage never happened, but try explaining it to your love handles..

I’ve been getting quite serious with my latest diet; using a Garmin Vivosmart HR to track my active calorie burn and logging down what I eat with MyFitnessPal. The first thing I did was gauge how many calories my body could burn without losing or gaining weight. After a couple of weeks of annoyingly close observation I settled for 2,200Kcal which is 300Kcal less than the recommended daily average for a man.

Closely monitoring calorie intake combined with the active calorie burn data from a decent fitness tracker like the Vivosmart HR definitely works. But, despite the best efforts of barcode scanners and auto-complete, it’s hassle opening up an app and logging calories manually. There has to be a better way..

Researchers from China’s Northeastern University are working on an alternative with their smart necklace that listens to the sounds of different foods as they’re being ground up in your mouth, and identifies what you’re eating.

The necklace which is still in the prototype stage is called AutoDietary. A growing audio library of foods being chewed is being created on the premise that everything has a unique sound.

Inside the AutoDietary necklace is a mini Hi Fi microphone. The chomping sounds it records are sent over Bluetooth to a companion app where they’re compared to the sounds in the library. If the app recognizes what’s being munched, it can then automatically assign the calorific intake.

According to test results from 12 people who were asked to eat cookies, crisps, apples, carrots, peanuts and walnuts, AutoDietary has a recognition accuracy rate of 85%. Wenyao Xu, the brains behind AutoDietary, plans to increase the accuracy by refining the algorithms used to differentiate the foods.

AutoDietary can’t tell the difference between foods that are very similar, such as regular cheddar and low-fat cheddar. Recognizing these limitations, Wenyao Xu, is planning to incorporate a biomonitoring device to assist the necklace by measuring blood sugar levels and other metrics to determine the nutritional value of the food being chomped.

Devices that can automatically log our calorie intake are certainly arriving.. But, is AutoDietary’s method of listening to your neck the best way to do it?