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To improve the understanding of human gait and to facilitate noveldevelopments in gait rehabilitation, the neural correlates of human gait asmeasured by means of non-invasive electroencephalography (EEG) have beeninvestigated recently. Particularly, gait-related event-related brainpotentials (gERPs) may provide information about the functional role ofcortical brain regions in human gait control. The purpose of this paper is toexplore possible experimental and technical solutions for time-sensitiveanalysis of human gait-related ERPs during spontaneous and instructed treadmillwalking. A solution (HW/SW) for synchronous recording of gait- and EEG data wasdeveloped, tested and piloted. The solution consists of a custom-made USBsynchronization interface, a time-synchronization module and a data mergingmodule, allowing temporal synchronization of recording devices fortime-sensitive extraction of gait markers for analysis of gait-related ERPs andfor the training of artificial neural networks. In the present manuscript, thehardware and software components were tested with the following devices: Atreadmill with an integrated pressure plate for gait analysis (zebris FDM-T)and an Acticap non-wireless 32-channel EEG-system (Brain Products GmbH). Theusability and validity of the developed solution was tested in a pilot study (n= 3 healthy participants, n=3 females, mean age = 22.75 years). Recorded EEGdata was segmented and analyzed according to the detected gait markers for theanalysis of gait-related ERPs. Finally, EEG periods were used to train a deeplearning artificial neural network as classifier of gait phases. The resultsobtained in this pilot study, although preliminary, support the feasibility ofthe solution for the application of gait-related EEG analysis..

Analysis of Gait-Event-related Brain Potentials During Instructed And Spontaneous Treadmill Walking -- Technical Affordances and used Methods