Joint European Conference on Machine Learning and Knowledge Discovery in Databases

ECML PKDD 2015: Machine Learning and Knowledge Discovery in Databases pp 267-270

CardioWheel: ECG Biometrics on the Steering Wheel

  • André Lourenço
  • Ana Priscila Alves
  • Carlos Carreiras
  • Rui Policarpo Duarte
  • Ana Fred
Conference paper

DOI: 10.1007/978-3-319-23461-8_27

Part of the Lecture Notes in Computer Science book series (LNCS, volume 9286)
Cite this paper as:
Lourenço A., Alves A.P., Carreiras C., Duarte R.P., Fred A. (2015) CardioWheel: ECG Biometrics on the Steering Wheel. In: Bifet A. et al. (eds) Machine Learning and Knowledge Discovery in Databases. ECML PKDD 2015. Lecture Notes in Computer Science, vol 9286. Springer, Cham

Abstract

Monitoring physiological signals while driving is a recent trend in the automotive industry. We present CardioWheel, a state-of-the-art machine learning solution for driver biometrics based on electrocardiographic signals (ECG). The presented system pervasively acquires heart signals from the users hands through sensors embedded in the steering wheel, to recognize the driver’s identity. It combines unsupervised and supervised machine learning algorithms, and is being tested in real-world scenarios, illustrating one of the potential uses of this technology.

Keywords

Electrocardiographic signals (ECG) Biometrics Automotive industry Personalization Security 

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Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • André Lourenço
    • 1
    • 2
  • Ana Priscila Alves
    • 1
    • 2
  • Carlos Carreiras
    • 1
    • 2
  • Rui Policarpo Duarte
    • 1
  • Ana Fred
    • 1
    • 2
  1. 1.CardioID Technologies LdaLisbonPortugal
  2. 2.Instituto de TelecomunicaçõesLisbonPortugal

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