Detection of anticipatory brain potentials during car driving

Abstract

Abstract-Recognition of driver's intention from electroencephalogram (EEG) can be helpful in developing an in-car brain computer interface (BCI) systems for intelligent cars. This could be beneficial in enhancing the quality of interaction between the driver and the car to provide the response of the intelligent cars in line with driver's intention. We proposed investigating anticipation as the cognitive state leading to specific actions during car driving. An experimental protocol is designed for recording EEG from 6 subjects while driving the virtual reality driving simulator. The experimental protocol is a variant of the contingent negative variation (CNV) paradigm with Go and No-go conditions in driving framework. The results presented in this study support the presence of the slow cortical anticipatory potentials in EEG grand averages and also confirm the discriminability of these potentials in offline single trial classification with the average of 0.76 ± 0.12 in area under the curve (AUC).

Brain Correlates of Lane Changing Reaction Time in Simulated Driving

“…Concluding, the current findings complement recent studies that have identified correlates of other cognitive processes in realistic driving, including drowsiness [6], [21], [22], [23], emergency braking [9], [24], error-awareness [25], anticipation of self-motivated steering [8] and braking actions [7], as well as visual attention [26]. We purport that future driving assistive systems can exploit information derived from these signals -decoded through a brain-machine interface system-, in combination with information from in-car sensors to tailor the support they provide both to the perceived conditions of the environment as well as the internal state of the driver [27].…”

“…This activity reflects underlying cognitive processes and can potentially be exploited to improve driving assistance systems for intelligent cars [6], [7], [8]. For example, recent studies have focused on detecting anticipated and emergency braking [7], [9], steering actions [8] as well as workload and levels of attention [10].…”

EEG correlates of active visual search during simulated driving: An exploratory study

“…A zero phase fourth order Butterworth bandpass filter in the range [2,12] Hz was applied to remove slow oscillations and high frequency noise. EOG artifact correction methods were not applied since they may corrupt the EFRPs.…”

“…For instance, smart cars could use it to provide tailored support for each driver [1]- [3]. Existing works in these lines have focused on detecting anticipated and emergency braking [2], [4], steering actions [3] as well as workload and levels of attention [5]. Here we focus on identifying neural patterns related to visual processing and recognition during driving.…”

Hardware Simulator for Seizure, Preseizure and Normal Mode Signal Generation in LabVIEW Environment for Research

“…The EEG bio-signal hardware simulator is intended for designing, to develop algorithms, signal processing as a portable system [1], [2], by utilizing the power of LabVIEW and to implement it into an embedded Data Acquisition System (DAQ). The user can view the signal and transmit the EEG data to a remote microcontroller system for inhouse data processing and identification, this can be used for validating wearable bio signal system before implementing the actual wearable epilepsy detection system, moreover this simulator can be used as a virtual environment simulator [3]for generating EEG signals and can be used for fine tuning the and rehearse theproduct (wearable system).This can also be built on the approach of dataflow in graphical form, with the integration of hardware signal output.…”