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Train your FOCI to read you

When it comes to nudging you when you are distracted, or to take a rest, or even generating biofeedback in real time, to help you regulate emotion states, these all depend on FOCI's ability to accurately differentiate your breathing physiological characteristics. People can be tall, short, fat or thin, similarly physiological characteristics of breathing also vary from person to person. Even for the same person, under different conditions, physiological characteristics of breathing can become very different.

Therefore, FOCI requires training, that is, machine learning, in order to accurately recognize emotion states. This is like training a customs police dog to distinguish milk and ham.

Training FOCI is actually very simple, just follow the guide on wearing FOCI correctly to get good signal, the training will start automatically. However, in order to accurately recognize emotions, there are two precautions in training FOCI that require your special attention.

First, don't wear FOCI when you are not working or studying. FOCI is designed only to identify the physiological characteristics of breathing during work and study, and this is different from breathing during sleep, talking or exercising. For example, running will cause you to pant, speaking long sentences may cause you to subconsciously hold your breath. Therefore, in order to prevent false data from skewing machine learning, don’t wear FOCI when you are not working or studying.


Secondly, turn off machine learning when you are not wearing FOCI. Turning it off is very simple. Place the FOCI's metal clip downwards, and the machine learning will automatically turn off. Alternatively you can turn it off manually in the app to prevent FOCI from learning false data, caused by slight vibrations in the environment, such as from the shaking of an unsteady table or from typing of keyboards. Just remember, when you are not wearing it, place the FOCI's metal clip facing down to turn off machine learning.

If the training is not done right, a customs police dog could wrongly recognize ham as milk. This requires it to be retrained. Similarly, if FOCI's machine learning is skewed, it would result in inaccurate emotion recognition, and machine learning needs to be reset and start over again. Or alternatively, you would need to train machine learning directly using ’train machine learning feature’.

In a nutshell it is an interactive machine learning that allows you to calibrate machine learning accuracy, or sensitivity to emotion state detection. Your input can stabilize machine learning against data skewing.

Let’s get the show on the road.


If you feel like you're more stressed than what FOCI tells you. Tell FOCI that your fatigues or distractions are more like stress. And voila! See the difference, before and after training machine learning with your input.

What’s better, once you are satisfied with machine learning’s accuracy, by telling it that for example, ‘focus’, ‘flow’, ‘calm’ are generally reflective of your expectation, this would let machine learning know that it is doing well and thus stabilize it against skewing.

After all, giving machine learning your input is the surest way to get it to work just as you want.

Now, you just need to wear it for FOCI's machine learning to begin. As machine learning reads more data, FOCI will understand you better. In about 3-7 days, the machine learning will be completed, and FOCI will be able to read you accurately.

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Don't wear FOCI incorrectly