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

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

doi:10.1016/j.dib.2017.10.072

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

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

Department of Occupational Therapy

Research output: Contribution to journal › Article › peer-review

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.

Original language	English
Pages (from-to)	1048-1056
Number of pages	9
Journal	Data in Brief
Volume	15
DOIs	https://doi.org/10.1016/j.dib.2017.10.072
State	Published - Dec 2017

Bibliographical note

Funding Information:
This work is part of project MAMEM that has received funding from the European Unions Horizon 2020 research and innovation programme under grant agreement No 644780 . Transparency document

Publisher Copyright:
© 2017 The Authors

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10.1016/j.dib.2017.10.072

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Nikolopoulos, S., Petrantonakis, P. C., Georgiadis, K., Kalaganis, F., Liaros, G., Lazarou, I., Adam, K., Papazoglou-Chalikias, A., Chatzilari, E., Oikonomou, V. P., Kumar, C., Menges, R., Staab, S., Müller, D., Sengupta, K., Bostantjopoulou, S., Katsarou, Z., Zeilig, G., Plotnik, M., ... Kompatsiaris, I. (2017). A multimodal dataset for authoring and editing multimedia content: The MAMEM project. Data in Brief, 15, 1048-1056. https://doi.org/10.1016/j.dib.2017.10.072

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title = "A multimodal dataset for authoring and editing multimedia content: The MAMEM project",

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.",

author = "Spiros Nikolopoulos and Petrantonakis, {Panagiotis C.} and Kostas Georgiadis and Fotis Kalaganis and Georgios Liaros and Ioulietta Lazarou and Katerina Adam and Anastasios Papazoglou-Chalikias and Elisavet Chatzilari and Oikonomou, {Vangelis P.} and Chandan Kumar and Raphael Menges and Steffen Staab and Daniel M{\"u}ller and Korok Sengupta and Sevasti Bostantjopoulou and Zoe Katsarou and Gabi Zeilig and Meir Plotnik and Amihai Gotlieb and Racheli Kizoni and Sofia Fountoukidou and Jaap Ham and Dimitrios Athanasiou and Agnes Mariakaki and Dario Comanducci and Edoardo Sabatini and Walter Nistico and Markus Plank and Ioannis Kompatsiaris",

note = "Funding Information: This work is part of project MAMEM that has received funding from the European Unions Horizon 2020 research and innovation programme under grant agreement No 644780 . Transparency document Publisher Copyright: {\textcopyright} 2017 The Authors",

year = "2017",

month = dec,

doi = "10.1016/j.dib.2017.10.072",

language = "English",

volume = "15",

pages = "1048--1056",

journal = "Data in Brief",

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Nikolopoulos, S, Petrantonakis, PC, Georgiadis, K, Kalaganis, F, Liaros, G, Lazarou, I, Adam, K, Papazoglou-Chalikias, A, Chatzilari, E, Oikonomou, VP, Kumar, C, Menges, R, Staab, S, Müller, D, Sengupta, K, Bostantjopoulou, S, Katsarou, Z, Zeilig, G, Plotnik, M, Gotlieb, A, Kizoni, R, Fountoukidou, S, Ham, J, Athanasiou, D, Mariakaki, A, Comanducci, D, Sabatini, E, Nistico, W, Plank, M & Kompatsiaris, I 2017, 'A multimodal dataset for authoring and editing multimedia content: The MAMEM project', Data in Brief, vol. 15, pp. 1048-1056. https://doi.org/10.1016/j.dib.2017.10.072

TY - JOUR

T1 - A multimodal dataset for authoring and editing multimedia content

T2 - The MAMEM project

AU - Nikolopoulos, Spiros

AU - Petrantonakis, Panagiotis C.

AU - Georgiadis, Kostas

AU - Kalaganis, Fotis

AU - Liaros, Georgios

AU - Lazarou, Ioulietta

AU - Adam, Katerina

AU - Papazoglou-Chalikias, Anastasios

AU - Chatzilari, Elisavet

AU - Oikonomou, Vangelis P.

AU - Kumar, Chandan

AU - Menges, Raphael

AU - Staab, Steffen

AU - Müller, Daniel

AU - Sengupta, Korok

AU - Bostantjopoulou, Sevasti

AU - Katsarou, Zoe

AU - Zeilig, Gabi

AU - Plotnik, Meir

AU - Gotlieb, Amihai

AU - Kizoni, Racheli

AU - Fountoukidou, Sofia

AU - Ham, Jaap

AU - Athanasiou, Dimitrios

AU - Mariakaki, Agnes

AU - Comanducci, Dario

AU - Sabatini, Edoardo

AU - Nistico, Walter

AU - Plank, Markus

AU - Kompatsiaris, Ioannis

N1 - Funding Information: This work is part of project MAMEM that has received funding from the European Unions Horizon 2020 research and innovation programme under grant agreement No 644780 . Transparency document Publisher Copyright: © 2017 The Authors

PY - 2017/12

Y1 - 2017/12

N2 - 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.

AB - 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.

UR - http://www.scopus.com/inward/record.url?scp=85034082151&partnerID=8YFLogxK

U2 - 10.1016/j.dib.2017.10.072

DO - 10.1016/j.dib.2017.10.072

M3 - Article

AN - SCOPUS:85034082151

SN - 2352-3409

VL - 15

SP - 1048

EP - 1056

JO - Data in Brief

JF - Data in Brief

ER -

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

Abstract

Bibliographical note

ASJC Scopus subject areas

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