Exploring the Use of Mobile Electroencephalogram (EEG) in Driving Assessment: A Case Study

Brain imaging has been used in research to understand brain activity during the occupation of driving, but there are limitations to current practice. Brain imaging methods, such as fMRI or electroencephalogram (EEG), restrict the driver from performing occupations in a natural environment (Gramann, Ferris, Gwin, & Makeig, 2014; Protzak & Gramann, 2018; Schweizer et al., 2013). Mobile EEG is a tool that can overcome this limitation. Mobile EEG is a wireless headset that allows for measurement of electrical activity while participating in occupations in any environment. While there is emerging evidence using brain imaging to understand brain activation patterns with healthy drivers (Protzak & Gramann, 2018; Schweizer et al., 2013), no evidence was located describing brain activation patterns in individuals following a neurological disorder. Tools that can explore brain activation patterns during contextual driving assessment and intervention are necessary for establishing evidence-based practice for this population. The purpose of this exploratory case study is to explore brain activation patterns in an individual with mild residual hemispatial neglect during the occupation of driving and to pilot the use of mobile EEG as a measurement tool. A purposive sampling technique was used. The participant was a 55 year old male who completed a driver rehabilitation program approximately two years prior following a right hemispheric stroke. He had no visual field deficits and at the time of the study had not experienced any additional health conditions that could impact driving. The participant completed three driving tasks in a parking lot requiring varying levels of visual spatial skills while wearing a mobile EEG headset. The mobile EEG detected electrical activity which was uploaded and saved to a laptop via Bluetooth using brain mapping software. Video recordings were used to align actions with brain mapping data during analysis. An observation form was used to document errors made while driving. Finally, a brief clinical evaluation was performed to assess for residual hemispatial neglect symptoms. The evaluation results indicated mild residual symptoms. Delta, theta, alpha, and beta waves were represented visually using a brain map, displaying the location and intensity of each wave across the cerebral lobes. The brain activity was analyzed by identifying patterns of wave location and intensity during various components of the driving tasks. Tasks that elicited the strongest beta wave activity, indicating concentration, were those with increased planning and visual spatial demands. Increased beta waves were also found to be attributed to increased anxiety or novelty of the task. When challenged with complex visual spatial demands, theta waves, often associated with a daydreaming state, were also high in intensity in the occipital and parietal lobes associated with visual attention, attentional shifting, and visual spatial skills. Because each task was performed accurately, the theta waves could indicate adequate compensation for any residual hemispatial neglect symptoms for the requested driving tasks as opposed to reduced attention to task. This study demonstrates how mobile EEG can be used in driver assessment to provide valuable insights into cognitive aspects of driving. The tool can contribute to evidence-based practice for contextual driving evaluation and intervention and lead to a greater understanding of the relationship between the person, the occupation, and the environment. This case study not only describes the first attempt to explore brain activation patterns with hemispatial neglect, but it also describes a new method for assessing brain activation patterns during the occupation of driving, as opposed to a simulation.

References

Gramann, K., Ferris, D. P., Gwin, J., & Makeig, S. (2014). Imaging natural cognition in action. International Journal of Psychophysiology, 91, 22-29. doi:10.1016/j.ijpsycho.2013.09.003

Protzak, J., & Gramann, K. (2018). Investigating established EEG parameter during real-world driving. Frontiers in Psychology, 9(2289), 1-11. doi:10.3389/fpsyg.2018.02289

Schweizer, T. A., Kan, K., Hung, Y., Tam, F., Naglie, G., & Graham, S. J. (2013). Brain activity during driving with distraction: An immersive fMRI study. Frontiers in Human Neuroscience, 7(53), 1-11. doi:10.3389/fnhum.2013.00053