CardioWheel: ECG Biometrics on the Steering Wheel
- 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
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.
KeywordsElectrocardiographic signals (ECG) Biometrics Automotive industry Personalization Security
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