A multimodal dataset for authoring and editing multimedia content: The MAMEM project
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 con...
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2017-12-01
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Series: | Data in Brief |
Online Access: | http://www.sciencedirect.com/science/article/pii/S2352340917305930 |
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author |
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 |
spellingShingle |
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 A multimodal dataset for authoring and editing multimedia content: The MAMEM project Data in Brief |
author_facet |
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 |
author_sort |
Spiros Nikolopoulos |
title |
A multimodal dataset for authoring and editing multimedia content: The MAMEM project |
title_short |
A multimodal dataset for authoring and editing multimedia content: The MAMEM project |
title_full |
A multimodal dataset for authoring and editing multimedia content: The MAMEM project |
title_fullStr |
A multimodal dataset for authoring and editing multimedia content: The MAMEM project |
title_full_unstemmed |
A multimodal dataset for authoring and editing multimedia content: The MAMEM project |
title_sort |
multimodal dataset for authoring and editing multimedia content: the mamem project |
publisher |
Elsevier |
series |
Data in Brief |
issn |
2352-3409 |
publishDate |
2017-12-01 |
description |
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. |
url |
http://www.sciencedirect.com/science/article/pii/S2352340917305930 |
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doaj-9fadec5bb00e4e7e814c80c3dbd6fd002020-11-25T02:13:19ZengElsevierData in Brief2352-34092017-12-011510481056A multimodal dataset for authoring and editing multimedia content: The MAMEM projectSpiros Nikolopoulos0Panagiotis C. Petrantonakis1Kostas Georgiadis2Fotis Kalaganis3Georgios Liaros4Ioulietta Lazarou5Katerina Adam6Anastasios Papazoglou-Chalikias7Elisavet Chatzilari8Vangelis P. Oikonomou9Chandan Kumar10Raphael Menges11Steffen Staab12Daniel Müller13Korok Sengupta14Sevasti Bostantjopoulou15Zoe Katsarou16Gabi Zeilig17Meir Plotnik18Amihai Gotlieb19Racheli Kizoni20Sofia Fountoukidou21Jaap Ham22Dimitrios Athanasiou23Agnes Mariakaki24Dario Comanducci25Edoardo Sabatini26Walter Nistico27Markus Plank28Ioannis Kompatsiaris29Information Technologies Institute, Centre for Research & Technologies Hellas, Greece; Corresponding to: Information Technologies Institute, Centre for Research & Technologies Hellas, 6th km Charilaou-Thermi, GR 570 01, Thessaloniki, Greece.Information Technologies Institute, Centre for Research & Technologies Hellas, GreeceInformation Technologies Institute, Centre for Research & Technologies Hellas, Greece; Aristotle University of Thessaloniki, School of Sciences, Department of Informatics, GreeceInformation Technologies Institute, Centre for Research & Technologies Hellas, Greece; Aristotle University of Thessaloniki, School of Sciences, Department of Informatics, GreeceInformation Technologies Institute, Centre for Research & Technologies Hellas, GreeceInformation Technologies Institute, Centre for Research & Technologies Hellas, GreeceInformation Technologies Institute, Centre for Research & Technologies Hellas, GreeceInformation Technologies Institute, Centre for Research & Technologies Hellas, GreeceInformation Technologies Institute, Centre for Research & Technologies Hellas, GreeceInformation Technologies Institute, Centre for Research & Technologies Hellas, GreeceInstitute for Web Science and Technologies, University of Koblenz-Landau, GermanyInstitute for Web Science and Technologies, University of Koblenz-Landau, GermanyInstitute for Web Science and Technologies, University of Koblenz-Landau, Germany; WAIS Research Group, University of Southampton, UKInstitute for Web Science and Technologies, University of Koblenz-Landau, GermanyInstitute for Web Science and Technologies, University of Koblenz-Landau, Germany3rd University Department of Neurology, Aristotle University of Thessaloniki, GreeceDepartment of Neurology, Hippokration General Hospital, Thessaloniki, GreeceDepartment of Physiology and Pharmacology, Sackler Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel; Department of Neurological Rehabilitation, The Chaim Sheba Medical Center at Tel-HaShomer, Tel-HaShomer, IsraelCenter of Advanced Technologies in Rehabilitation, Sheba Medical Center, Tel Hashomer, Israel; Department of Physiology and Pharmacology, Sackler Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel; Sagol School of Neuroscience, Tel Aviv University, Tel Aviv, IsraelCenter of Advanced Technologies in Rehabilitation, Sheba Medical Center, Tel Hashomer, Israel; Department of Neurological Rehabilitation, The Chaim Sheba Medical Center at Tel-HaShomer, Tel-HaShomer, IsraelCenter of Advanced Technologies in Rehabilitation, Sheba Medical Center, Tel Hashomer, Israel; Department of Occupational Therapy, University of Haifa, Haifa, IsraelHuman-Technology Interaction, Eindhoven University of Technology, The NetherlandsHuman-Technology Interaction, Eindhoven University of Technology, The NetherlandsMuscular Dystrophy Association, MDA Hellas, GreeceMuscular Dystrophy Association, MDA Hellas, GreeceEB Neuro S.p.A, ItalyEB Neuro S.p.A, ItalySenso Motoric Instruments - SMI, GermanySenso Motoric Instruments - SMI, GermanyInformation Technologies Institute, Centre for Research & Technologies Hellas, GreeceWe 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.http://www.sciencedirect.com/science/article/pii/S2352340917305930 |