A Framework for Crowd-Sourced Exercise Data Collection and Processing
Natheer Khasawneh, Schulte Christoph, Mohammad Fraiwan · 2020
The prevalence of wearable mobile personal health devices and their everyday use enables great possibilities in the development of health-related applications and the research/studying of a plethora of behavioral habits and healthy/unhealthy lifestyle correlates. Strava is fitness-related social network, which is mainly concerned with running and cycling activities. Such platform contains a wealth of health data that, if accessed security and responsibly, can drive innovation in health informatics, urban planning based on exercise geolocations, and pattern recognition.In this paper, we present a generic framework for the collection of crowd-sourced exercise-related data. We present the overall architecture and the detailed implementation of how we collect, structure, prepare the data from crowd-sourced platform. The feasibility and efficacy of the proposed methods are demonstrated by building a prototype based on Strava.