Contactless Fall Detection using Doppler Radar Doppler Radar ile Temazsiz Dusme Algilama


28th Signal Processing and Communications Applications Conference, SIU 2020, Gaziantep, Turkey, 5 - 07 October 2020 identifier

  • Publication Type: Conference Paper / Full Text
  • Volume:
  • Doi Number: 10.1109/siu49456.2020.9302065
  • City: Gaziantep
  • Country: Turkey
  • Keywords: Doppler Radar, elderly care, Fall detection, machine learning, vital signs
  • Yıldız Technical University Affiliated: Yes


© 2020 IEEE.Falling is the main cause of disability and the fatality of elderly. In this work, a 24 GHz continuous wave (CW) Doppler Radar-based novel system is proposed as a cheap, easy to use and effective solution for elderly fall detection. A set of features extracted from both time and frequency domains is examined and features that contribute most to distinguish between fall and non-fall samples are selected. Finally, different learning techniques including support vector machine (SVM), k nearest neighborhood (kNN), Naïve Bayes (NB), linear discriminant analysis (LDA)and decision tree (DT) are evaluated and linear discriminant analysis method is selected as the most accurate classication model. The proposed system performed fall detection with 88% accuracy.