Smart Health pp 99-124

Part of the Lecture Notes in Computer Science book series (LNCS, volume 8700) | Cite as

Personalized Physical Activity Monitoring Using Wearable Sensors

  • Gabriele Bleser
  • Daniel Steffen
  • Attila Reiss
  • Markus Weber
  • Gustaf Hendeby
  • Laetitia Fradet
Chapter

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.

Keywords

Physical activity monitoring ADL Strength exercises Personalization Wearable sensors Inertial sensors HCI Ambient assisted living 

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Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • Gabriele Bleser
    • 1
  • Daniel Steffen
    • 1
  • Attila Reiss
    • 2
  • Markus Weber
    • 1
  • Gustaf Hendeby
    • 3
    • 4
  • Laetitia Fradet
    • 5
  1. 1.German Research Center for Artificial IntelligenceKaiserslauternGermany
  2. 2.ACTLabUniversity of PassauPassauGermany
  3. 3.Department of Electrical EngineeringLinköping UniversityLinköpingSweden
  4. 4.Department of Sensor and EW SystemsSwedish Defence Research Agency (FOI)LinköpingSweden
  5. 5.Université de PoitiersPoitiersFrance

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