Fitbit Mind - Case Study
Providing mental health information in a motivational manner
Design Features
 

Effectively informs 'Stress Levels'

The tracker detects the stress levels of the users through sensors in the band. However, it conveys the 'Mindfulness Quotient' which is the exact inverse of the stress levels.

 

If the user is stressed the wearable informs that the user is less mindful. Information provided in this manner would prove to be more encouraging.

Stress

Mindfulness

'Mindfulness Quotient' represents a person's calmness of mind as compared to the statistical norm - calculated using the required vital signs at a particular age.

Patterns of Mindfulness Quotient helps the user to learn which activities are more stress inducing.

The band offers haptic guided meditation sessions. The vibration motors create a pattern as per the blue arrows. 

Compare Physical Activity with the Mindfulness Quotient and learn the relationship between each other.

Phone switches to DND mode during the guided meditation session.

Conceptualization Process
 

Using the technologies associated with Affective Computing it is possible to detect human emotions, determine mental stress levels and much more (Using a unique computation and interpolation of data acquired from GSR, Heart rate sensors and such). But technology capable of reading human emotions can prove to be scary for people and would lead to rejection. 

What are the factors associated with successfully commercially launching such new technologies? How can products/services be designed so that its users feel comfortable and safe around it? This project is aimed towards learning facets associated with a successful commercialization of new technology: USER ACCEPTABILITY/ ADOPTION. Simultaneously, working with Affective Computing and learning its possibilities.