Publication
Personalized Physical Activity Monitoring Using Wearable Sensors
Gabriele Bleser; Daniel Steffen; Attila Reiss; Markus Weber; Gustaf Hendeby; Laetitia Fradet
In: Andreas Holzinger; Carsten Röcker; Martina Ziefle (Hrsg.). Smart Health - Open Problems and Future Challenges. Pages 99-124, Lecture Notes in Computer Science (LNCS), Vol. 8700, ISBN 978-3-319-16225-6, Springer, 2015.
Abstract
It is a well-known fact that exercising helps people improve
their overall well-being; both physiological and psychological health. Regular
moderate physical activity improves the risk of disease progression,
improves the chances for successful rehabilitation, and lowers the levels
of stress hormones. Physical fitness can be categorized in cardiovascular
fitness, and muscular strength and endurance. A proper balance between
aerobic activities and strength exercises are important to maximize the
positive effects. This balance is not always easily obtained, so assistance
tools are important. Hence, ambient assisted living (AAL) systems that
support and motivate balanced training are desirable. This chapter
presents methods to provide this, focusing on the methodologies and concepts
implemented by the authors in the physical activity monitoring for
aging people (PAMAP) platform. The chapter sets the stage for an architecture
to provide personalized activity monitoring using a network of
wearable sensors, mainly inertial measurement units (IMU). The main
focus is then to describe how to do this in a personalizable way: (1) monitoring
to provide an estimate of aerobic activities performed, for which
a boosting based method to determine activity type, intensity, frequency,
and duration is given; (2) supervise and coach strength activities. Here,
methodologies are described for obtaining the parameters needed to provide
real-time useful feedback to the user about how to exercise safely
using the right technique.