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Mobile Health pp 791-812 | Cite as

Motion Capture: From Radio Signals to Inertial Signals

  • Matteo Giuberti
  • Gianluigi Ferrari
Part of the Springer Series in Bio-/Neuroinformatics book series (SSBN, volume 5)

Abstract

The study of the motion of individuals allows to gather relevant information on a person status, to be used in several fields (e.g., medical, sport, and entertainment). Over the past decade, the research activity in motion capture has benefited from the progress of portable and mobile sensors, paving the way toward the use of motion capture techniques in mHealth applications (e.g., remote monitoring of patients, and telerehabilitation). Indeed, even if the optical motion capture, which typically relies on a set of fixed cameras and body-worn reflecting markers, is generally perceived as the standard reference approach, other motion capture techniques, such as radio and inertial, are attracting an increasing attention because of their suitability in remote mHealth applications.

Moreover, several hybrid approaches have been studied and proposed in order to overcome the limitations of component technologies considered independently. In this chapter, we present an overview of possible integration strategies between radio and inertial motion capture techniques. We start by investigating a radio-based approach, based on the fingerprinting radio localization technique. Then, the previous approach is improved by integrating inertial measurements: namely, accelerometers are used to provide an estimate of the nodes’ pitches. Finally, the radio signals are abandoned in favor of only inertialmeasurements (obtained through accelerometers, gyroscopes, and magnetometers). The advantages and limitations of all approaches are discussed in a comparative way, characterizing the similarities and differences between the various approaches.

Keywords

Motion capture radio fingerprinting inertial sensors remote monitoring body area network body sensor network sensor fusion 

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Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  1. 1.Xsens Technologies B.V.EnschedeThe Netherlands
  2. 2.Department of Information EngineeringUniversity of ParmaParmaItaly

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