Micro Doppler Radar and Depth Sensor Fusion for Human Activity Monitoring in AAL

  • Susanna SpinsanteEmail author
  • Matteo Pepa
  • Stefano Pirani
  • Ennio Gambi
  • Francesco Fioranelli
Conference paper
Part of the Lecture Notes in Electrical Engineering book series (LNEE, volume 539)


Among the older adults population, falls represent a serious health problem, and a considerable economic issue for the society as a whole, due to their many consequences. In order to design reliable systems for automatic fall detection, able to distinguish falls from activities of daily living, the sensor fusion approach may be exploited. In this paper, the quite innovative fusion of Micro Doppler Radar and Kinect sensors to achieve acceptable accuracy and sensitivity in fall detection is investigated. The results show that by fusion, it is possible to provide a 100% fall detection sensitivity, over a dataset collected by taking into account ten different actions, with proper configuration of the acquisition setup and algorithmic parameters.


Fall detection Sensor fusion Depth Micro doppler radar 



M. Pepa was partially supported by COST Action IC1303 under the Short Term Scientific Mission ECOST-STSM-IC1303-200317-084684.


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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Susanna Spinsante
    • 1
    Email author
  • Matteo Pepa
    • 1
  • Stefano Pirani
    • 1
  • Ennio Gambi
    • 1
  • Francesco Fioranelli
    • 2
  1. 1.Dipartimento di Ingegneria dell’InformazioneUniversita’ Politecnica delle MarcheAnconaItaly
  2. 2.School of EngineeringUniversity of GlasgowGlasgowUK

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