1 resultado para EEG, fMRI, sinestesia
em Digital Commons - Michigan Tech
Filtro por publicador
- University of Cagliari UniCA Eprints (1)
- Aberdeen University (2)
- AMS Tesi di Dottorato - Alm@DL - Università di Bologna (5)
- AMS Tesi di Laurea - Alm@DL - Università di Bologna (9)
- Aquatic Commons (2)
- ArchiMeD - Elektronische Publikationen der Universität Mainz - Alemanha (1)
- Archivo Digital para la Docencia y la Investigación - Repositorio Institucional de la Universidad del País Vasco (4)
- Aston University Research Archive (36)
- Biblioteca Digital da Produção Intelectual da Universidade de São Paulo (4)
- Biblioteca Digital da Produção Intelectual da Universidade de São Paulo (BDPI/USP) (3)
- Biblioteca Digital de Teses e Dissertações Eletrônicas da UERJ (5)
- BORIS: Bern Open Repository and Information System - Berna - Suiça (156)
- Boston University Digital Common (2)
- Brock University, Canada (13)
- Bucknell University Digital Commons - Pensilvania - USA (2)
- Bulgarian Digital Mathematics Library at IMI-BAS (1)
- CaltechTHESIS (5)
- Cambridge University Engineering Department Publications Database (17)
- CentAUR: Central Archive University of Reading - UK (131)
- Chinese Academy of Sciences Institutional Repositories Grid Portal (26)
- Cochin University of Science & Technology (CUSAT), India (8)
- Coffee Science - Universidade Federal de Lavras (1)
- Collection Of Biostatistics Research Archive (2)
- CORA - Cork Open Research Archive - University College Cork - Ireland (5)
- Deakin Research Online - Australia (22)
- DI-fusion - The institutional repository of Université Libre de Bruxelles (1)
- Digital Commons - Michigan Tech (1)
- DigitalCommons@The Texas Medical Center (2)
- Diposit Digital de la UB - Universidade de Barcelona (2)
- DRUM (Digital Repository at the University of Maryland) (1)
- Duke University (31)
- Helda - Digital Repository of University of Helsinki (22)
- Indian Institute of Science - Bangalore - Índia (26)
- Instituto Politécnico do Porto, Portugal (3)
- Lume - Repositório Digital da Universidade Federal do Rio Grande do Sul (1)
- Ministerio de Cultura, Spain (8)
- National Aerospace Laboratory (NLR) Reports Repository (1)
- National Center for Biotechnology Information - NCBI (1)
- Nottingham eTheses (2)
- QSpace: Queen's University - Canada (1)
- QUB Research Portal - Research Directory and Institutional Repository for Queen's University Belfast (39)
- Queensland University of Technology - ePrints Archive (136)
- ReCiL - Repositório Científico Lusófona - Grupo Lusófona, Portugal (1)
- Repositório Aberto da Universidade Aberta de Portugal (1)
- Repositório Científico do Instituto Politécnico de Lisboa - Portugal (1)
- Repositório Institucional da Universidade de Aveiro - Portugal (1)
- Repositório Institucional da Universidade Federal do Rio Grande do Norte (1)
- Repositório Institucional UNESP - Universidade Estadual Paulista "Julio de Mesquita Filho" (15)
- Repositorio Institucional Universidad EAFIT - Medelin - Colombia (1)
- School of Medicine, Washington University, United States (1)
- Universidad Autónoma de Nuevo León, Mexico (2)
- Universidad del Rosario, Colombia (12)
- Universidad Politécnica de Madrid (10)
- Universidade de Lisboa - Repositório Aberto (5)
- Universidade Federal do Pará (1)
- Universidade Federal do Rio Grande do Norte (UFRN) (4)
- Universita di Parma (1)
- Universitat de Girona, Spain (1)
- Universitätsbibliothek Kassel, Universität Kassel, Germany (2)
- Université de Lausanne, Switzerland (19)
- Université de Montréal (1)
- Université de Montréal, Canada (82)
- University of Canberra Research Repository - Australia (4)
- University of Queensland eSpace - Australia (14)
- University of Washington (1)
- WestminsterResearch - UK (4)
Resumo:
Geospatial information systems are used to analyze spatial data to provide decision makers with relevant, up-to-date, information. The processing time required for this information is a critical component to response time. Despite advances in algorithms and processing power, we still have many “human-in-the-loop” factors. Given the limited number of geospatial professionals, analysts using their time effectively is very important. The automation and faster humancomputer interactions of common tasks that will not disrupt their workflow or attention is something that is very desirable. The following research describes a novel approach to increase productivity with a wireless, wearable, electroencephalograph (EEG) headset within the geospatial workflow.