You are all cordially invited to the AMLab seminar on Thursday October 18 at 16:00 in C3.163, where Shihan Wang will give a talk titled “Apply Machine Learning and Data Mining to Promote Physical Activity”. Afterwards there are the usual drinks and snacks!
Abstract: In this talk, we will introduce our research work in the “playful data-driven active urban living” (PAUL) project. Targeting on physical inactivity issue in modern society, we aim to motive less active people to participate in more physical activity. Given an overview of this project, we will mainly present recent papers.
Driven by a large-scale dataset of Dutch people’s running records (over 10K people in about 4 years), we start with characterizing runners based on their different temporal activity patterns. Then, in respect of diverse users, we studied how environmental situations (time, weather, geographical and social information) at the start time of a run affect the running distance. A rule-based machine learning method is applied to capture combined situations frequently associated with relevant long-distance runs. These environmental situations are going to be used in a mobile system, to identify the ‘right timing’ for motivating people to start longer-distance runs via message interventions.