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EEG Analysis from Motor Imagery to Control a Forestry Crane
Umeå University, Faculty of Science and Technology, Department of Applied Physics and Electronics. (immersive interaction Lab (i2lab))
Umeå University, Faculty of Science and Technology, Department of Applied Physics and Electronics. (immersive interaction Lab (i2lab))
Umeå University, Faculty of Medicine, Department of Pharmacology and Clinical Neuroscience. Norwegian University of Science and Technology (NTNU), Norway.
Umeå University, Faculty of Medicine, Department of Pharmacology and Clinical Neuroscience.
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2018 (English)In: Intelligent Human Systems Integration (IHSI 2018) / [ed] Karwowski, Waldemar, Ahram, Tareq, 2018, Vol. 722, p. 281-286Conference paper, Published paper (Refereed)
Abstract [en]

Brain-computer interface (BCI) systems can provide people with ability to communicate and control real world systems using neural activities. Therefore, it makes sense to develop an assistive framework for command and control of a future robotic system which can assist the human robot collaboration. In this paper, we have employed electroencephalographic (EEG) signals recorded by electrodes placed over the scalp. The human-hand movement based motor imagery mentalization is used to collect brain signals over the motor cortex area. The collected µ-wave (8–13 Hz) EEG signals were analyzed with event-related desynchronization/synchronization (ERD/ERS) quantification to extract a threshold between hand grip and release movement and this information can be used to control forestry crane grasping and release functionality. The experiment was performed with four healthy persons to demonstrate the proof-of concept BCI system. From this study, it is demonstrated that the proposed method has potential to assist the manual operation of crane operators performing advanced task with heavy cognitive work load.

Place, publisher, year, edition, pages
2018. Vol. 722, p. 281-286
Series
Advances in Intelligent Systems and Computing (AISC), ISSN 2194-5357 ; 722
Keywords [en]
Brain-computer interface (BCI), Mu-wave Motor imagery, Event-related desynchronization (ERD), Event-related synchronization (ERS), Forestry crane, Assistive technologies, HCI
National Category
Interaction Technologies Communication Systems Signal Processing Robotics Human Computer Interaction Neurology
Research subject
Computer and Information Science; Computer Systems; Clinical Neurophysiology; Electronics
Identifiers
URN: urn:nbn:se:umu:diva-143918DOI: 10.1007/978-3-319-73888-8_44Scopus ID: 2-s2.0-85040229502ISBN: 978-3-319-73887-1 (print)ISBN: 978-3-319-73888-8 (electronic)OAI: oai:DiVA.org:umu-143918DiVA, id: diva2:1173942
Conference
1st International Conference on Intelligent Human Systems Integration: Integrating People and Intelligent Systems, (IHSI 2018), January 7-9, 2018, Dubai, United Arab Emirates
Available from: 2018-01-15 Created: 2018-01-15 Last updated: 2018-06-09Bibliographically approved

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ur Réhman, ShafiqSandvig, Axel

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Department of Applied Physics and ElectronicsDepartment of Pharmacology and Clinical Neuroscience
Interaction TechnologiesCommunication SystemsSignal ProcessingRoboticsHuman Computer InteractionNeurology

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