Brain-Computer Interface-Based Feasibility of Entering Customer Code on Ticket Vending Machines

Dénes Simonyi, Tibor Kovács
2018 Interdisciplinary Description of Complex Systems  
The availability of EEG-based Brain-Computer Interface (BCI) devices, which are also available in everyday applications, has widened the application environment. Many manufacturers have marketed their own mobile device, which will become virtually accessible to everyone in the near future, opening up new perspectives in the modern world of human-machine interaction. One of its potential areas is to broaden the communication capabilities of people with physical disabilities, providing them with
more » ... ata inputs that they had previously not been able to. Such a feature is a keyboardless text input. In Hungary, in case of online shopping, the receipt of a train ticket through the MÁV ticket sales machines is also possible to be received by entering the customer code by typing numbers on a touch screen. However, due to disability, physical injury or other reasons, there are cases where the user is unable to use hands, therefore this possibility is virtually impossible to access for them. This omission may, in our opinion, be eliminated by alternative identification methods. The purpose of this research is to assess the feasibility of entering characters using EEG based BCI techniques on those machines. The research consists of two parts. In the first part, the technical parameters of railway ticket vending machines were surveyed to determine whether or not they provide an opportunity to connect external devices and provide backgrounds for software communication with BCI. The second part of the research is a questionnaire research. We visited institutions that care for people with reduced mobility and asked them to fill out our questionnaire with their patients to assess the need for a possible BCI tool on rail ticket vending machines. We have also prepared a second questionnaire to measure the attitude of healthy individuals to the use of this device.
doi:10.7906/indecs.16.3.7 fatcat:ixceecvq5zda5d6ftvtnylhpi4