PMData: a sports logging dataset
| Autor: | Martin Kristoffer Svensen, Michael Riegler, Christine Claudi, Anders Tungeland Gjerdrum, Vajira Thambawita, Per Morten Fredriksen, Svein Arne Pettersen, Siri Fagernes, Sigurd Pedersen, Steven Alexander Hicks, Hugo Lewi Hammer, Hanna Borgli, Debesh Jha, Pål Halvorsen, Ragnhild Eg, Tor-Morten Grønli, Tomas Kupka, Duc Tien Dang Nguyen, Dag Johansen, Kjeld S. Hansen, Ramesh Jain, Simon Nordvang, Andreas Biørn-Hansen, Håkon Kvale Stensland, Susann Dahl Pettersen, Håvard D. Johansen |
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| Jazyk: | angličtina |
| Rok vydání: | 2020 |
| Předmět: |
Computer science
business.industry Logging Context (language use) 030229 sport sciences Lifelog Smartphone application Machine learning computer.software_genre Sleep patterns Smartwatch 03 medical and health sciences 0302 clinical medicine Sensor data Food pictures Multimedia datasets 030212 general & internal medicine Artificial intelligence Sports logging business computer Neural networks |
| Zdroj: | MMSys |
| Popis: | 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. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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