NEW! FuggBit device now available for pre-order

I am delighted to announce that my research lab is now releasing beta versions of a tracking device for mental fitness. Similar to other tracking devices this one is collecting data about your activity throughout the day. You can share the data via your smartphone with your family and friends and of course with your therapist. The idea being that with measurable data you will increase your awareness and be more likely to change your thinking and behaviour.

Lets go right in and find out more about many useful features. The integrated microphone enables you to count the total amount of words spoken in a day. If you want to improve your listening skills, then start by talking less. The app will also indicate the total amount of swear-words and the percentage in relation to your overall verboseness. As rule of thumb: venting the occasional tension by swearing can keep you sane, while the week on week trend should point downwards. 

In ‘sensitive’ mode you can track the number of self-disclosures, I statements and constructive feedbacks (given on request only). The word detector in the microphone is connected to the motion sensor on your wrist. Hence, some standard reports will automatically combine the words counted with correlating hand-gestures like hugging, padding, caressing and hand-holding.

The newly developed finger-pointing index (see below) allows for better transparency on when you acted agressively or made a push-over out of yourself. It detects typical motion of your index finger, back-paddling, nervous scratching of your forehead and interprets fast steps as ‘running away from responsibility’. 

 finger-pointing  assertiveness psychology 
The function that allows for small electro-shocks as immediate feedback embedded in the device is planned for the next generation. The idea is to help people prevent from stupid and unnessessary behaviour – like the compulsion to give advice or to compare themselves to others. Here – in addition to some ethical challenges – it proves difficult for state-of-the-art sensors to differentiate between well-meant and unsolicited advice.