Literature DB >> 29295062

Using Cloud-Based Physical Activity Data from Google Fit and Apple Healthkit to Expand Recording of Physical Activity Data in a Population Study.

André Henriksen1, Laila Arnesdatter Hopstock1, Gunnar Hartvigsen2, Sameline Grimsgaard1.   

Abstract

Large population studies are important sources for medical research. These studies are well planned, well organized, and costly. However, people record health data themselves using different sensors, which are mostly unplanned, unorganized and inexpensive. Nevertheless, self-recorded data might be an important supplement to population studies. The question is how to access and use this data. In the seventh survey of the Tromsøcohort study, questionnaires and accelerometers were used to collect data on physical activity (PA). We now plan to collect historical PA data from these participants, using mobile sensor data already stored in the cloud. We will examine the feasibility of this approach and the quality of this data. Objectively measured historical data will provide valuable insights in the potential and limitations of mobile sensors as new data collection tools in medical research.

Entities:  

Keywords:  Cohort studies; Fitness Trackers; Human Activity

Mesh:

Year:  2017        PMID: 29295062

Source DB:  PubMed          Journal:  Stud Health Technol Inform        ISSN: 0926-9630


  2 in total

1.  Multi-Sensor-Fusion Approach for a Data-Science-Oriented Preventive Health Management System: Concept and Development of a Decentralized Data Collection Approach for Heterogeneous Data Sources.

Authors:  Sebastian Neubert; André Geißler; Thomas Roddelkopf; Regina Stoll; Karl-Heinz Sandmann; Julius Neumann; Kerstin Thurow
Journal:  Int J Telemed Appl       Date:  2019-10-08

2.  Enhancing mHealth data collection applications with sensing capabilities.

Authors:  Maximilian Karthan; Robin Martin; Felix Holl; Walter Swoboda; Hans A Kestler; Rüdiger Pryss; Johannes Schobel
Journal:  Front Public Health       Date:  2022-09-15
  2 in total

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