Recognition Of Various Inducement Unfitted Driving States Based On Fusion Of Cerebral Blood Oxygen Saturation And Facial Expression

Abstract:With the aging of human society and the diversity of cultural development, the subjective reasons of traffic accident become more and more complex, which include not only the traditional fatigue and distraction behavior, but also alcohol, drugs, disease and medicine etc. All these incentives take the drivers into Various Inducement Unfitted Driving States(VIUDS), which reduces the driver's cognitive abilities of the driving environment, and eventually leads to the traffic accidents. At present, the traditional methods can only detect a single inducement but not all the inducements under the unified technical architecture at the same time. In this dissertation, in order to solve the problem, the commonality negative effects of cognitive ability of the central nervous system was analyzed based on the latest research of biomedical and cognition. By selecting the facial expressions and the prefrontal cerebral oxygen saturation as the basic characteristic to implement the fusion assessment of cognitive ability with Bayesian networks, the uniform detection of the inducements of VIUDS was ultimately achieved. The main innovations are summarized as follows.1. The nature of VIUDS under various subjective inducements is found to be a status of cognitive decline of central nervous system based on the analysis of the traffic accidents. The facial expressions and cerebral oxygen saturation are selected as the basic characteristic of the reflection of the cognitive ability after analyzing the limitations of the detection with a single characteristic and the existing methods, which establishes the foundation for the fusion evaluation of the cognitive ability.2. The assessment method of the cognitive ability was proposed. In this method, the prefrontal cerebral oxygenation saturation scaling exponents (COSSE) of the prefrontal blood oxygen saturation time series is calculated by the detrended fluctuation analysis method. As a result, the evaluation of cognitive abilities of driver's central nervous system is ultimately realized.3. A detection method of the prefrontal cerebral oxygenation saturation was proposed based on the photoacoustic sensing architecture with quartz tuning fork and ellipsoid acoustic focusing. In the process of detection, the prefrontal organization and the quartz tuning fork are located at the ellipsoid's two different focuses. Under the stimulus of the excitation laser pulse, the prefrontal organization at one of the focuses generates the weak photoacoustic signal, which is focused by the ellipsoid and collected by the quartz tuning fork located at the other focus. At last, the far-field non-invasive measurement of the prefrontal cerebral oxygenation saturation is fulfilled according to the quantitative relationship between the excitation light intensity, ultrasonic intensity and the oxygenation saturation.4. An orthogonal manifold preserving projections method was proposed. In order to solve the limitations of the locality preserving projections method that can't preserve the invariance of the global manifold structure in the low dimensional space, and the projection matrix is non-orthogonal, an orthogonal manifold preserving projections method was proposed by redefining the objective constraint function and recalculating the projection matrix by Gramm-Schmidt orthogonalization process. This improvement does not only effectively maintain the global and local manifold structure in the projection space, but also reduces the characteristic dimension and improves the accuracy of the expression recognition.5. A multi-feature fusion evaluation method of the cognitive ability was proposed based on the Bayesian network. In this method, COSSE, fatigue expressions and blink frequency are used as the basic characteristics for the fusion detection. The posterior probability corresponding to these random variables is calculated by the Bayesian network. Using the posterior probability as the basis for the cognitive ability assessment, the detection limitations with the single feature is overcome and the precision of the evaluation is improved.In the last chapter, the contents of this dissertation were summarized and the future research direction and work were also discussed. This dissertation contains33figures,10tables and159references.