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

A Multimodal dataset for authoring and editing multimedia content: The MAMEM project
A Multimodal dataset for authoring and editing multimedia content: The MAMEM project
In this report 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 along with demographic, clinical and behavioral data collected from 36 individuals (18 able-bodied and 18 motor-impaired). Data were collected during the interaction with specifically designed interface for web browsing and multimedia content manipulation and during imaginary movement tasks. Alongside these data we also include evaluation reports both from the subjects and the experimenters as far as the experimental procedure and
collected dataset are concerned. We believe that 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.
2352-3409
Nikolopoulos, Spiros
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Georgiadis, Kostas
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Kalaganis, Fotis
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Liaros, Georgios
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Lazarou, Ioulietta
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Adam, Katerina
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Papazoglou-Chalikias, Anastasios
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Chatzilari, Elisavet
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Oikonomou, Vangelis
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Petrantonakis, Panagiotis
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Kompatsiaris, Ioannis
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Kumar, Chandan
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Menges, Raphael
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Staab, Steffen
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Müller, Daniel
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Sengupta, Korok
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Bostantjopoulou, Sevasti
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Katsarou, Zoe
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Zeilig, Gabi
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Plotnik, Meir
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Gotlieb, Amihai
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Ham, Jaap
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Athanasiou, Dimitrios
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Mariakaki, Agnes
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Comandicci, Dario
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Sabatini, Edoardo
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Nistico, Walter
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Plank, Markus
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Nikolopoulos, Spiros
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Georgiadis, Kostas
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Kalaganis, Fotis
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Liaros, Georgios
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Lazarou, Ioulietta
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Adam, Katerina
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Papazoglou-Chalikias, Anastasios
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Chatzilari, Elisavet
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Oikonomou, Vangelis
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Petrantonakis, Panagiotis
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Kompatsiaris, Ioannis
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Kumar, Chandan
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Menges, Raphael
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Staab, Steffen
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Müller, Daniel
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Sengupta, Korok
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Bostantjopoulou, Sevasti
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Katsarou, Zoe
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Zeilig, Gabi
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Plotnik, Meir
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Gotlieb, Amihai
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Fountoukidou, Sofia
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Ham, Jaap
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Athanasiou, Dimitrios
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Mariakaki, Agnes
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Comandicci, Dario
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Sabatini, Edoardo
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Nistico, Walter
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Plank, Markus
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Nikolopoulos, Spiros, Georgiadis, Kostas, Kalaganis, Fotis, Liaros, Georgios, Lazarou, Ioulietta, Adam, Katerina, Papazoglou-Chalikias, Anastasios, Chatzilari, Elisavet, Oikonomou, Vangelis, Petrantonakis, Panagiotis, Kompatsiaris, Ioannis, Kumar, Chandan, Menges, Raphael, Staab, Steffen, Müller, Daniel, Sengupta, Korok, Bostantjopoulou, Sevasti, Katsarou, Zoe, Zeilig, Gabi, Plotnik, Meir, Gotlieb, Amihai, Fountoukidou, Sofia, Ham, Jaap, Athanasiou, Dimitrios, Mariakaki, Agnes, Comandicci, Dario, Sabatini, Edoardo, Nistico, Walter and Plank, Markus (2017) A Multimodal dataset for authoring and editing multimedia content: The MAMEM project Data in Brief (doi:10.1016/j.dib.2017.10.072). (Submitted).

Record type: Article

Abstract

In this report 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 along with demographic, clinical and behavioral data collected from 36 individuals (18 able-bodied and 18 motor-impaired). Data were collected during the interaction with specifically designed interface for web browsing and multimedia content manipulation and during imaginary movement tasks. Alongside these data we also include evaluation reports both from the subjects and the experimenters as far as the experimental procedure and
collected dataset are concerned. We believe that 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.

Text MAMEM_Phase_I_Dataset_Paper_pre-final - Author's Original
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Text 1-s2.0-S2352340917305930-main - Accepted Manuscript
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More information

Submitted date: 1 August 2017
Accepted/In Press date: 31 October 2017
e-pub ahead of print date: 3 November 2017

Identifiers

Local EPrints ID: 415264
URI: http://eprints.soton.ac.uk/id/eprint/415264
ISSN: 2352-3409
PURE UUID: a52ccc92-9f93-4786-954a-a16b9437b58b
ORCID for Steffen Staab: ORCID iD orcid.org/0000-0002-0780-4154

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Date deposited: 06 Nov 2017 17:30
Last modified: 06 Nov 2017 17:30

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Contributors

Author: Spiros Nikolopoulos
Author: Kostas Georgiadis
Author: Fotis Kalaganis
Author: Georgios Liaros
Author: Ioulietta Lazarou
Author: Katerina Adam
Author: Anastasios Papazoglou-Chalikias
Author: Elisavet Chatzilari
Author: Vangelis Oikonomou
Author: Panagiotis Petrantonakis
Author: Ioannis Kompatsiaris
Author: Chandan Kumar
Author: Raphael Menges
Author: Steffen Staab ORCID iD
Author: Daniel Müller
Author: Korok Sengupta
Author: Sevasti Bostantjopoulou
Author: Zoe Katsarou
Author: Gabi Zeilig
Author: Meir Plotnik
Author: Amihai Gotlieb
Author: Sofia Fountoukidou
Author: Jaap Ham
Author: Dimitrios Athanasiou
Author: Agnes Mariakaki
Author: Dario Comandicci
Author: Edoardo Sabatini
Author: Walter Nistico
Author: Markus Plank

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