Abstract: The present application discloses methods and systems for mobility device control by capturing electroencephalogram (EEG) brain wave data to extract steady-state visually evoked potential (SSVEP) signal data and decoding the SSVEP signal data into at least one command for controlling the mobility device. The SSVEP signals are triggered through visual stimuli on a screen of a device, such as a user device, and are decoded through a machine learning pipeline. At least one of cloud, edge or fog principles may be utilized to enhance response time. The use of the machine learning pipeline and at least one of cloud, edge or fog technology provides an improved mobility device control system response time when compared to the current and prior alternatives for mobility device control systems.

Abstract: A code transforming method is provided for use in an operation system of a computer prior to displaying and printing out a text document and includes the steps: (i) transforming content of the text document into a temporary text file utilizing a data transformation service; (ii) coding each character of the temporary text file into a sequence of 16-bit words; (iii) encoding the sequence of 16-bit words in accordance with a transformation table for displaying or printing; and (iv) outputting the encoded sequence of 16-bit words to a Dynamic Link Library in order to display or printout the text document.