Fuzzy-Logic Inference for Early Detection of Sleep Onset in Car Driver

  • Mario Malcangi
  • Salvatore Smirne
Part of the Communications in Computer and Information Science book series (CCIS, volume 311)


Heart rate variability (HRV) is an important sign because it reflects the activity of the autonomic nervous system (ANS), which controls most of the physiological activity of the subjects, including sleep. The balance between the sympathetic and parasympathetic branches of the nervous system is an effective indicator of heart rhythm and, indirectly, heart rhythm is related to a patient’s state of wakefulness or sleep. In this paper we present a research that models a fuzzy logic inference engine for early detection of the onset of sleep in people driving a car or a public transportation vehicle. ANS activity reflected in the HRV signal is measured by electrocardiogram (ECG). Power spectrum density (PSD) is computed from the HRV signal and ANS frequency activity is then measured. Crisp measurements such as very low, low, and high HRV and low-to-high frequency ratio variability are fuzzified and evaluated by a set of fuzzy-logic rules that make inferences about the onset of sleep in automobile drivers. An experimental test environment has been developed to evaluate this method and its effectiveness.


onset sleep heart rate variability power spectrum density fuzzy logic autonomic nervous system 


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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Mario Malcangi
    • 1
  • Salvatore Smirne
    • 2
  1. 1.DICo - Dipartimento di Informatica e ComunicazioneUniversità degli Studi di MilanoMilanoItaly
  2. 2.Dipartimento di Tecnologie per la SaluteUniversità degli Studi di MilanoMilanoItaly

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