8th International Conference on Body Area Networks

Research Article

Classification of daily-life postural transitions using trunk-worn wearable barometric pressure sensor

  • @INPROCEEDINGS{10.4108/icst.bodynets.2013.253552,
        author={Fabien Mass\^{e} and Alan Bourke and Anisoara Paraschiv-Ionescu and Kamiar Aminian},
        title={Classification of daily-life postural transitions using trunk-worn wearable barometric pressure sensor},
        proceedings={8th International Conference on Body Area Networks},
        publisher={ICST},
        proceedings_a={BODYNETS},
        year={2013},
        month={10},
        keywords={activity barometric pressure wearable sensor inertial sensor},
        doi={10.4108/icst.bodynets.2013.253552}
    }
    
  • Fabien Massé
    Alan Bourke
    Anisoara Paraschiv-Ionescu
    Kamiar Aminian
    Year: 2013
    Classification of daily-life postural transitions using trunk-worn wearable barometric pressure sensor
    BODYNETS
    ACM
    DOI: 10.4108/icst.bodynets.2013.253552
Fabien Massé1,*, Alan Bourke1, Anisoara Paraschiv-Ionescu1, Kamiar Aminian1
  • 1: Laboratory of Movement Analysis and Measurement (LMAM) / Ecole Polytechnique Fédérale de Lausanne (EPFL)
*Contact email: fabien.masse@epfl.ch

Abstract

Distinguishing sedentary from dynamic behavior is essential in addressing disease conditions that are influenced by mobility. Event-based activity recognition algorithms essentially rely on accurate classification of siting and standing postural transitions to distinguish whether the subject is sitting or standing. In this paper, the use of barometric pressure, to estimate altitude, is investigated. It enabled a correct classification of postural transitions with a sensitivity of 92.31% and specificity of 98.06%. The type (sit-to-stand or stand-to-sit) of transition was also accurately identified.