EEG Headset


The TEEP-headset is a custom open source and low-cost EEG acquisition system exploiting the open source acquisition board Cyton (plus Daisy module) by OpenBCI. This part of the TEEP-SLA project includes the design and development of both passive and active semi-dry sensors for EEG recordings, based on the coupling between golden cup electrodes and felt pads to be humidified to ensure a good electorde-skin contact. A specific electronic module compatible with the Cyton+Daisy system was developed, to allow the connection of both customized passive and active electrodes. All project files and material will be made available as open source.

Malvicino, S., Schiatti, L., Tessadori, J., Barresi, G., Casadio, M., & Mattos, L. S. (accepted). Low-cost and Open-source Semi-dry electrodes for assistive BCIs. In 2019 IEEE Engineering in Medicine and Biology conference (EMBC 2019) – poster presentation.

Biosignal Processing


Scheme of the MI adaptive classifier’s functioning. EEG signals are used both to extract an active control signal from a motor imagery task (green phase), and a passive information (Error) on user’s evaluation of the MI classifier’s output, after feedback is provided (orange phase). The output of a static ErrP classifier is then used to update the MI adaptive classifier’s parameters.


User Interface Features


Eye-tracking is an intuitive and acceptable solution to enable paralyzed patients to move a cursor across a user interface by means of their gaze, and to activate a selectable UI object after looking at it for a certain dwell time. Nevertheless, such control function of gaze can become prone to errors if the dwell time duration is too short, not customized for each specific user. Considering this issue TEEP-SLA designed the hybrid EyeBCI (eye-tracking and brain-computer interface) system to improve the performance and the usability of the gaze control through the EEG monitoring of the mental focus. Specifically, EyeBCI adapts the duration of the dwell time to the level of mental focus of the user when he/she wants to select and activate any UI item: the dwell time shortens according to the raise of the observer's concentration, improving the system precision and responsiveness.


A pilot study evaluated the effects of a relaxation biofeedback system on the user experience in the context of a gaze-controlled task that is mentally and temporally demanding: ET-based gaming. Different aspects of the subjects’ experience were investigated under two conditions of a gaze-controlled game. In the Biofeedback group (BF), the user triggered a command by means of voluntary relaxation, monitored through Galvanic Skin Response (GSR) and represented by visual feedback. In the No Biofeedback group (NBF), the same feedback was timed according to the average frequency of commands in BF. After the experiment, each subject filled out a user experience questionnaire. The results showed a general appreciation for BF, with a significant between-group difference in the perceived session time duration, with the latter being shorter for subjects in BF than for the ones in NBF. This result implies a lower mental workload for BF than for NBF subjects. Other results point toward a potential role of user’s engagement in the improvement of user experience in BF. Such an effect highlights the value of relaxation biofeedback for improving the user experience in a demanding gaze-controlled task.


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