1 resultado para Predicting Multicomponent Diffusivities
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Resumo:
This thesis aimed at designing and developing a system that can a) infer individuals’ need for a break from sedentary behaviour in the workplace, and b) persuade them to take a break through the use of different techniques from persuasive psychology. We postulated three variables, namely, individuals’ posture, stress levels and involvement in their computer mediated activity. We developed and field-studied a system that could infer these using a web camera and a key presses and mouse clicks log. We found that the system could predict posture from viewing depth and stress from the movement detected. We then created a general formula that predicts individuals’ need for a break using only the posture and stress predictors. Once the first objective was set, we built and field-studied a system that used three ways to communicate a recommendation for a break to a user: implicit, just-in time and ambient feedback. The implicit feedback was operationalized through changes in the users’ computer wallpaper that provided subtle visual cues. The just-in time feedback employed prompting at the bottom right side of the user’s screen. In addition, we implemented an intuitive behind-screen interaction technique where people can snooze a notification using simple gestures. The ambient feedback mechanism employed an origami sculpture sitting on the user’s desk. This prototype was continuously reflecting the user’s posture and performed rhythmic movements when to recommend breaks. A field study demonstrated the overall success of the system, with 69% of the break recommendations received by users were accepted. The study further revealed the strengths and weaknesses of the three persuasive mechanisms.