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EEG Analysis from M...
EEG Analysis from Motor Imagery to Control a Forestry Crane
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- Augustian, Midhumol (författare)
- Umeå universitet,Institutionen för tillämpad fysik och elektronik,immersive interaction Lab (i2lab)
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- ur Réhman, Shafiq (författare)
- Umeå universitet,Institutionen för tillämpad fysik och elektronik,immersive interaction Lab (i2lab)
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- Sandvig, Axel (författare)
- Umeå universitet,Klinisk neurovetenskap,Norwegian University of Science and Technology (NTNU), Norway
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- Kotikawatte, Thivra (författare)
- Umeå universitet,Klinisk neurovetenskap
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- Yongcui, Mi (författare)
- Umeå universitet,Institutionen för tillämpad fysik och elektronik
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- Evensmoen, Hallvard Røe (författare)
- Norwegian University of Science and Technology (NTNU), Norway
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(creator_code:org_t)
- 2017-12-31
- 2018
- Engelska.
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Ingår i: Intelligent Human Systems Integration (IHSI 2018). - Cham : Springer. - 9783319738871 - 9783319738888 ; , s. 281-286
- Relaterad länk:
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https://urn.kb.se/re...
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https://doi.org/10.1...
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Abstract
Ämnesord
Stäng
- 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.
Ämnesord
- TEKNIK OCH TEKNOLOGIER -- Annan teknik -- Interaktionsteknik (hsv//swe)
- ENGINEERING AND TECHNOLOGY -- Other Engineering and Technologies -- Interaction Technologies (hsv//eng)
- TEKNIK OCH TEKNOLOGIER -- Elektroteknik och elektronik -- Kommunikationssystem (hsv//swe)
- ENGINEERING AND TECHNOLOGY -- Electrical Engineering, Electronic Engineering, Information Engineering -- Communication Systems (hsv//eng)
- TEKNIK OCH TEKNOLOGIER -- Elektroteknik och elektronik -- Signalbehandling (hsv//swe)
- ENGINEERING AND TECHNOLOGY -- Electrical Engineering, Electronic Engineering, Information Engineering -- Signal Processing (hsv//eng)
- TEKNIK OCH TEKNOLOGIER -- Elektroteknik och elektronik -- Robotteknik och automation (hsv//swe)
- ENGINEERING AND TECHNOLOGY -- Electrical Engineering, Electronic Engineering, Information Engineering -- Robotics (hsv//eng)
- NATURVETENSKAP -- Data- och informationsvetenskap -- Människa-datorinteraktion (hsv//swe)
- NATURAL SCIENCES -- Computer and Information Sciences -- Human Computer Interaction (hsv//eng)
- MEDICIN OCH HÄLSOVETENSKAP -- Klinisk medicin -- Neurologi (hsv//swe)
- MEDICAL AND HEALTH SCIENCES -- Clinical Medicine -- Neurology (hsv//eng)
- NATURVETENSKAP -- Fysik (hsv//swe)
- NATURAL SCIENCES -- Physical Sciences (hsv//eng)
Nyckelord
- Brain-computer interface (BCI)
- Mu-wave Motor imagery
- Event-related desynchronization (ERD)
- Event-related synchronization (ERS)
- Forestry crane
- Assistive technologies
- HCI
- data- och systemvetenskap
- computer and systems sciences
- Computer Systems
- datorteknik
- Clinical Neurophysiology
- klinisk neurofysiologi
- elektronik
- Electronics
Publikations- och innehållstyp
- ref (ämneskategori)
- kon (ämneskategori)
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