PMData
Vajira Thambawita, Steven A. Hicks, Hanna Borgli, Håkon Kvale Stensland, Debesh Jha, Martin Kristoffer Svensen, Svein-Arne Pettersen, Dag Johansen, Håvard D. Johansen, Susann Dahl Pettersen, Simon Nordvang, Sigurd Pedersen, Anders T. Gjerdrum, Tor‐Morten Grønli, Per Morten Fredriksen, Ragnhild Eg, Kjeld Hansen, Siri Fagernes, Christine Claudi, Andreas Biørn-Hansen, Duc T. Nguyen, Tomáš Kupka, Hugo L. Hammer, Ramesh Jain, Michael A. Riegler, Pål Halvorsen
Abstract
In this paper, we present PMData: a dataset that combines traditional lifelogging data with sports-activity data. Our dataset enables the development of novel data analysis and machine-learning applications where, for instance, additional sports data is used to predict and analyze everyday developments, like a person's weight and sleep patterns; and applications where traditional lifelog data is used in a sports context to predict athletes' performance. PMData combines input from Fitbit Versa 2 smartwatch wristbands, the PMSys sports logging smartphone application, and Google forms. Logging data has been collected from 16 persons for five months. Our initial experiments show that novel analyses are possible, but there is still room for improvement.