Full metadata record
DC Field | Value | Language |
---|---|---|
dc.contributor.author | 권규현 | - |
dc.date.accessioned | 2016-12-12T02:28:09Z | - |
dc.date.available | 2016-12-12T02:28:09Z | - |
dc.date.issued | 2015-05 | - |
dc.identifier.citation | IEEE TRANSACTIONS ON NEURAL SYSTEMS AND REHABILITATION ENGINEERING, v. 23, Page. 351-362 | en_US |
dc.identifier.issn | 1534-4320 | - |
dc.identifier.issn | 1558-0210 | - |
dc.identifier.uri | http://ieeexplore.ieee.org/document/6901279/ | - |
dc.identifier.uri | http://hdl.handle.net/20.500.11754/24782 | - |
dc.description.abstract | We propose a novel method for monitoring cognitive engagement in stroke patients during motor rehabilitation. Active engagement reflects implicit motivation and can enhance motor recovery. In this study, we used electroencephalography (EEG) to assess cognitive engagement in 11 chronic stroke patients while they executed active and passive motor tasks involving grasping and supination hand movements. We observed that the active motor task induced larger event-related desynchronization (ERD) than the passive task in the bilateral motor cortex and supplementary motor area (SMA). ERD differences between tasks were observed during both initial and post-movement periods (p ˂ 0.01). Additionally, differences in beta band activity were larger than differences in mu band activity (p ˂ 0.01). EEG data was used to help classify each trial as involving the active or passive motor task. Average classification accuracy was 80.7 +/- 0.1% for grasping movement and 82.8 +/- 0.1% for supination movement. Classification accuracy using a combination of movement and post-movement periods was higher than in other cases (p ˂ 0.05). Our results support using EEG to assess cognitive engagement in stroke patients during motor rehabilitation. | en_US |
dc.description.sponsorship | Manuscript received December 29, 2013; revised June 16, 2014; accepted August 12, 2014. Date of publication September 17, 2014; date of current version May 06, 2015. This work was supported in part by the IT R&D program of MOTIE/MISP/KEIT (10045452, the Development of Multimodal Brain-Machine Interface System Based on User Intent Recognition), in part by the Development of Robot-Assisted Motor Rehabilitation of the Upper Limb Using Bio-Signal Interfaces Project of the Korea Institute of Science and Technology (KIST), in part by the IT R&D Program of MSIP/KEIT, "Development of Cultural Contents Evaluation Technology based on Real-Time Bio-Signal in Human Populations." (10045461), in part by the Mid-career Researcher program (NRF-2012R1A2A2A04047239) through the National Research Foundation of Korea funded by the Ministry of Science, ICT and Future Planning. Asterisk indicates corresponding author. | en_US |
dc.language.iso | en | en_US |
dc.publisher | IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC | en_US |
dc.subject | Brain-computer interface | en_US |
dc.subject | BCI | en_US |
dc.subject | cognitive engagement | en_US |
dc.subject | electroencephalography | en_US |
dc.subject | EEG | en_US |
dc.subject | rehabilitation | en_US |
dc.subject | stroke | en_US |
dc.title | Assessment of Cognitive Engagement in Stroke Patients From Single-Trial EEG During Motor Rehabilitation | en_US |
dc.type | Article | en_US |
dc.relation.volume | 23 | - |
dc.identifier.doi | 10.1109/TNSRE.2014.2356472 | - |
dc.relation.page | 351-362 | - |
dc.relation.journal | IEEE TRANSACTIONS ON NEURAL SYSTEMS AND REHABILITATION ENGINEERING | - |
dc.contributor.googleauthor | Park, Wanjoo | - |
dc.contributor.googleauthor | Kwon, Gyu Hyun | - |
dc.contributor.googleauthor | Kim, Da-Hye | - |
dc.contributor.googleauthor | Kim, Yun-Hee | - |
dc.contributor.googleauthor | Kim, Sung-Phil | - |
dc.contributor.googleauthor | Kim, Laehyun | - |
dc.relation.code | 2015008205 | - |
dc.sector.campus | S | - |
dc.sector.daehak | GRADUATE SCHOOL OF TECHNOLOGY & INNOVATION MANAGEMENT[S] | - |
dc.identifier.pid | ghkwon | - |
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.