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. 2017 Nov 3:15:1048-1056.
doi: 10.1016/j.dib.2017.10.072. eCollection 2017 Dec.

A multimodal dataset for authoring and editing multimedia content: The MAMEM project

Affiliations

A multimodal dataset for authoring and editing multimedia content: The MAMEM project

Spiros Nikolopoulos et al. Data Brief. .

Abstract

We present a dataset that combines multimodal biosignals and eye tracking information gathered under a human-computer interaction framework. The dataset was developed in the vein of the MAMEM project that aims to endow people with motor disabilities with the ability to edit and author multimedia content through mental commands and gaze activity. The dataset includes EEG, eye-tracking, and physiological (GSR and Heart rate) signals collected from 34 individuals (18 able-bodied and 16 motor-impaired). Data were collected during the interaction with specifically designed interface for web browsing and multimedia content manipulation and during imaginary movement tasks. The presented dataset will contribute towards the development and evaluation of modern human-computer interaction systems that would foster the integration of people with severe motor impairments back into society.

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Figures

Fig. 1
Fig. 1
Timing events of a trial during calibration step.
Fig. 2
Fig. 2
Timing events of a trial during feedback step.
Fig. 3
Fig. 3
Experimental procedure timeline.
Fig. 4
Fig. 4
Database structure.

References

    1. Nikolopoulos S. 2017. The Mamem Project - A Dataset For Multimodal Human-Computer Interaction Using Biosignals And Eye Tracking Information.
    1. C. Kumar, R. Menges, M. Daniel, S. Staab, Chromium based Framework to Include Gaze Interaction in Web Browser, in: Proceedings of the 26th International Conference on World Wide Web Companion, pp. 219–223, 2017.
    1. Kumar C., Menges R., Staab S. Eye-controlled interfaces for multimedia interaction. IEEE Multimed. 2016;23(4):6–13.

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