A Mutlimodal Approach to Measure the Distraction Levels of Pedestrians using Mobile Sensing

The emergence of smart phones has had a positive impact on society as the range of features and automation has allowed people to become more productive while they are on the move. On the contrary, the use of these devices has also become a distraction and hindrance, especially for pedestrians who use their phones whilst walking on the streets. This is reinforced by the fact that pedestrian injuries due to the use of mobile phones has now exceeded mobile phone related driver injuries. This paper describes an approach that measures the different levels of distraction encountered by pedestrians whilst they are walking. To distinguish between the distractions within the brain the proposed work analyses data collected from mobile sensors (accelerometers for movement, mobile EEG for electroencephalogram signals from the brain). The long-term motivation of the proposed work is to provide pedestrians with notifications as they approach potential hazards while they walk on the street conducting multiple tasks such as using a smart phone.