Non intrusive physiological measurement for driver cognitive distraction detection: Eye and mouth movements

  • Azman A
  • Edirisinghe E
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Abstract

Driver distractions can be categorized into 3 major parts:-visual, cognitive and manual. Visual and manual distraction on a driver can be physically detected. However, assessing cognitive distraction is difficult since it is more of an “internal” distraction rather than any easily measured “external” distraction. There are several methods available that can be used to detect cognitive driver distraction. Physiological measurements, performance measures (primary and secondary tasks) and rating scales are some of the well-known measures to detect cognitive distraction. This study focused on physiological measurements, specifically on a driver's eye and mouth movements. Six different participants were involved in our experiment. The duration of the experiment was 8 minutes and 49 seconds for each participant. Eye and mouth movements were obtained using the FaceLab Seeing Machine cameras and their magnitude of the r-values were found more than 60% thus proving that they are strongly correlated to each other.

Author-supplied keywords

  • - driving safety
  • bayesian network
  • cognitive distraction
  • correlation
  • pearson-r

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Authors

  • Afizan Azman

  • Eran Edirisinghe

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