Abstract
Happiness has been an overarching goal of mankind at least since Aristotle spoke of Eudaimonia. However measuring happiness has been elusive and until now has almost exclusively been done by asking survey questions about self-perceived happiness. We propose a novel approach, tracking happiness and stress through changes in body signals with a smartwatch, the “Happimeter”. It predicts individual emotions from sensor data collected by an Android Wear smartwatch, such as acceleration, heartbeat, and activity. The Happimeter was used over three months in the innovation lab of a bank with 22 employees to measure individual happiness, activity, and stress. The participants were randomly divided into an experimental and a control group of similar size. Both groups wore the watch and entered their subjective happiness, activity and stress levels several times a day. The user-entered ratings were then used to train a machine learning system using the sensors of the smartwatch to subsequently automatically predict happiness, activity, and stress. The experimental group received ongoing feedback about their mood and which activity, sensor signals, or other people, made them happier or unhappier, while the control group did not get any feedback about their predicted and manually entered emotions. Just like in quantum physics we observed a “Heisenberg Effect”, where the participants made aware of their measurements changed their behavior: Members of the experimental group that received happiness feedback were 16% happier, and 26% more active than the control group at the end of the experiment. No effect was observed for stress.
Highlights
Most people think they know when they are happy, sad, or stressed
Being aware of one’s own emotions is of great help in coping with the challenges of daily life
The predictions are based on a machine learning algorithm which uses the user-entered mood and smartwarch sensor data
Summary
Most people think they know when they are happy, sad, or stressed. emotional awareness is far from given [1]. Previous studies mainly surveyed and interviewed individuals in order to access their overall well-being [5, 6, 8] All of these approaches suffer from problems of self-assessment and cognitive bias [9]. To make individuals aware of their emotions and increase their well-being we employ a process called “virtual mirroring” It has been introduced in [13], referring to a process in which individuals are shown metrics of their own communication behavior while they are told which communication behavior is desirable. The measurement is not correct anymore due to people’s change in behavior Based on these findings, it is desirable to (a) measure and predict happiness, stress, and activity to make individuals aware of their positive or negative feelings, and (b) find ways to increase individual well-being
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