Online driver's drowsiness estimation using domain adaptation with model fusion

Drowsy driving is a pervasive problem among drivers, and is also an important contributor to motor vehicle accidents. It is very important to be able to estimate a driver's drowsiness level online so that preventative actions could be taken to avoid accidents. However, because of large individual differences, it is very challenging to design an estimation algorithm whose parameters fit all subjects. Some subject-specific calibration data must be used to tailor the algorithm for each new subject. This paper proposes a domain adaptation with model fusion (DAMF) online drowsiness estimation approach using EEG signals. By making use of EEG data from other subjects in a transfer learning framework, DAMF requires very little subject-specific calibration data, which significantly increases its utility in practice. We demonstrate using a simulated driving experiment and 15 subjects that DAMF can achieve much better performance than several other approaches.

[1]  Dongrui Wu,et al.  Speech emotion estimation in 3D space , 2010, 2010 IEEE International Conference on Multimedia and Expo.

[2]  P. Welch.  The use of fast Fourier transform for the estimation of power spectra: A method based on time averaging over short, modified periodograms , 1967 .

[3]  Qiang Yang,et al.  A Survey on Transfer Learning , 2010, IEEE Transactions on Knowledge and Data Engineering.

[4]  S. Makeig,et al.  Lapses in alertness: coherence of fluctuations in performance and EEG spectrum. , 1993, Electroencephalography and clinical neurophysiology.

[5]  Yuan-Pin Lin,et al.  Co-modulatory spectral changes in independent brain processes are correlated with task performance , 2012, NeuroImage.

[6]  Tzyy-Ping Jung,et al.  Kinesthesia in a sustained-attention driving task , 2014, NeuroImage.

[7]  Eric R. Ziegel,et al.  The Elements of Statistical Learning , 2003, Technometrics.

[8]  Yuan-Pin Lin,et al.  Selective Transfer Learning for EEG-Based Drowsiness Detection , 2015, 2015 IEEE International Conference on Systems, Man, and Cybernetics.

[9]  Cataldo Guaragnella,et al.  A visual approach for driver inattention detection , 2007, Pattern Recognit..

[10]  Miguel Ángel Sotelo,et al.  Real-time system for monitoring driver vigilance , 2004, Proceedings of the IEEE International Symposium on Industrial Electronics, 2005. ISIE 2005..

[11]  T. Jung,et al.  Developing an EEG-based on-line closed-loop lapse detection and mitigation system , 2014, Front. Neurosci..

[12]  A. Nijholt,et al.  A survey of affective brain computer interfaces: principles, state-of-the-art, and challenges , 2014 .

[13]  Tzyy-Ping Jung,et al.  Adaptive EEG-Based Alertness Estimation System by Using ICA-Based Fuzzy Neural Networks , 2006, IEEE Transactions on Circuits and Systems I: Regular Papers.

[14]  Brian C Tefft.  Asleep at the Wheel: The Prevalence and Impact of Drowsy Driving , 2010 .

[15]  Brent Lance,et al.  Reducing BCI calibration effort in RSVP tasks using online weighted adaptation regularization with source domain selection , 2015, 2015 International Conference on Affective Computing and Intelligent Interaction (ACII).

[16]  Chin-Teng Lin,et al.  Computational intelligent brain computer interaction and its applications on driving cognition , 2009, IEEE Computational Intelligence Magazine.

[17]  Brent Lance,et al.  Transfer learning and active transfer learning for reducing calibration data in single-trial classification of visually-evoked potentials , 2014, 2014 IEEE International Conference on Systems, Man, and Cybernetics (SMC).

[18]  T. Jung,et al.  Tonic, phasic, and transient EEG correlates of auditory awareness in drowsiness. , 1996, Brain research. Cognitive brain research.

[19]  Brent Lance,et al.  Reducing Offline BCI Calibration Effort Using Weighted Adaptation Regularization with Source Domain Selection , 2015, 2015 IEEE International Conference on Systems, Man, and Cybernetics.

[20]  Arnaud Delorme,et al.  EEGLAB: an open source toolbox for analysis of single-trial EEG dynamics including independent component analysis , 2004, Journal of Neuroscience Methods.

[21]  Philip S. Yu,et al.  Adaptation Regularization: A General Framework for Transfer Learning , 2014, IEEE Transactions on Knowledge and Data Engineering.

[22]  Luis M. Bergasa,et al.  Real-time system for monitoring driver vigilance , 2005, ISIE 2005.

[23]  Gamini Dissanayake,et al.  Driver Drowsiness Classification Using Fuzzy Wavelet-Packet-Based Feature-Extraction Algorithm , 2011, IEEE Transactions on Biomedical Engineering.