Fig 1.
The user walks on a treadmill while a screen located at the eye-level provides guidance to perform different attention-related tasks. During the experiment, EEG signals are recorded from 32 channels located over the cortex through the g.GAMMAcap. Electrical signals are preamplified through 2 g.GAMMAboxes located in the user hip and digitalized in the g.USBamplifiers. An antistatic wrist strap connects the user’s wrist with the amplifiers ground to remove treadmill’s electrical noise. The digitalized data are recorded in a computer system.
Fig 2.
A single run is divided into 4 different tasks related to the attention level during gait: Normal walking as Standard Attention Level, performing mathematical operation and watching a video during walking as Low Attention Level, and following marks on the threadmill as High Attention Level.
Fig 3.
Noisy channels reconstruction.
Graph A shows 100 samples of the 32 electrodes time signals from the first session of User 1. Solid lines represent the artifact-free electrodes (±50 uV, common range of EEG signals), dotted and dashed lines represent the noisy channels (PO7, C5 and CPZ, out of ±50 uV range). Each noisy channel is replaced by the average value of the surrounding channels. Graph B shows the reconstructed signal.
Fig 4.
Graph A shows 160 seconds of a single channel EEG signal (in blue) and the MV Threshold computed for that signal with a epoch width (L) of 1200 samples (1 second) (in red). Graph B shows the evolution of the MV Threshold depending on the width L of the epochs for the same EEG channel. The black point shows the value selected and shown in graph A.
Fig 5.
Features Spatial Distribution.
Spatial distribution is represented for each task and frequency. Features used are computed by averaging the features of every subject (healthy users and patients) and sessions for each task and frequency band. Tasks are arranged according to the increasing attentional demand.
Table 1.
Values of bdist for the paired combination of tasks on each frequency band. All bdist values > 3 are marked in bold. Highest bdist values for each task combinations are marked with * and second highest bdist values are marked with **.
Table 2.
Success Rates and Standard Deviation.
Success rates for all subjects (10 healthy and 3 patients) and classifiers for both frequency band features.
Fig 6.
The range of variation of the chance level for a 4-task classification system is shown depending on the number of epochs classified. The top and bottom lines represent the highest and the minimum values admissible to consider the current classification random. These values are selected for the number of epochs of the current work (n = 960).
Fig 7.
The graphs show the average success rate of each classifier and the computed chance level for 4 equally distributed tasks and the amount of epochs used during the cross validation. Graph A shows the results for γhigh features, while graph B shows the results for γlow features.
Table 3.
Significance between classifiers.
Significance values for the paired combination of classifiers for healthy and patient both using γlow and γhigh features.
Table 4.
Significance between bands and users.
Rows 1 and 2: Significance values for both frequency features between healthy and patients. Rows 3 and 4: Significance values for both healthy and patients between frequency bands.