BCI-based neurorehabilitation and prediction system for stroke patients

Dollaporn Anopas; Massamon Horapong; Yodchanan Wongsawat

BCI-based neurorehabilitation and prediction system for stroke patients

Dollaporn Anopas
, Massamon Horapong
, Yodchanan Wongsawat

Mahidol University

Research output: Contribution to conference › Paper › peer-review

2 Citations (Scopus)

Abstract

Many stroke patients are suffered from motor disability and unable to carry out the activity of daily living. The purpose of this project is to develop the prediction and neurorehabitation system for pre-and post-stroke patients. Our system includes twomodules; Human-Computer Interface based stroke early prediction system (iSEP) and the upper limb rehabilitation device controlled by EEG through the use of Virtual Reality (iSRE). ERD/ERS is the phenomenon occurs in the brain that we used to classify motor imagery into left or right side. The virtual hand in the developed flash game will move to the side that the user imagined as well as the device will raise the user's upper limb on the same side of imagery. The results showed that the accuracy of left/right classification algorithm depends on user and training time, approximately 71.25 %.

Original language	English
Publication status	Published - 2013
Event	7th International Convention on Rehabilitation Engineering and Assistive Technology, i-CREATe 2013, in Conjunction with SENDEX 2013 - Gyeonggi-do, Korea, Republic of Duration: 29 Aug 2013 → 31 Aug 2013

Conference

Conference	7th International Convention on Rehabilitation Engineering and Assistive Technology, i-CREATe 2013, in Conjunction with SENDEX 2013
Country/Territory	Korea, Republic of
City	Gyeonggi-do
Period	29/08/13 → 31/08/13

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 3 Good Health and Well-being

Keywords

BCI
EEG
ERD/ERS
Neurorehabilitation
Prediction system
Stroke
Virtual reality

Cite this

@conference{101d8299a1cb452c8a2da356051e9309,

title = "BCI-based neurorehabilitation and prediction system for stroke patients",

abstract = "Many stroke patients are suffered from motor disability and unable to carry out the activity of daily living. The purpose of this project is to develop the prediction and neurorehabitation system for pre-and post-stroke patients. Our system includes twomodules; Human-Computer Interface based stroke early prediction system (iSEP) and the upper limb rehabilitation device controlled by EEG through the use of Virtual Reality (iSRE). ERD/ERS is the phenomenon occurs in the brain that we used to classify motor imagery into left or right side. The virtual hand in the developed flash game will move to the side that the user imagined as well as the device will raise the user's upper limb on the same side of imagery. The results showed that the accuracy of left/right classification algorithm depends on user and training time, approximately 71.25 \%.",

keywords = "BCI, EEG, ERD/ERS, Neurorehabilitation, Prediction system, Stroke, Virtual reality",

author = "Dollaporn Anopas and Massamon Horapong and Yodchanan Wongsawat",

year = "2013",

language = "English",

note = "7th International Convention on Rehabilitation Engineering and Assistive Technology, i-CREATe 2013, in Conjunction with SENDEX 2013 ; Conference date: 29-08-2013 Through 31-08-2013",

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BCI-based neurorehabilitation and prediction system for stroke patients. / Anopas, Dollaporn; Horapong, Massamon; Wongsawat, Yodchanan.
2013. Paper presented at 7th International Convention on Rehabilitation Engineering and Assistive Technology, i-CREATe 2013, in Conjunction with SENDEX 2013, Gyeonggi-do, Korea, Republic of.

Research output: Contribution to conference › Paper › peer-review

TY - CONF

T1 - BCI-based neurorehabilitation and prediction system for stroke patients

AU - Anopas, Dollaporn

AU - Horapong, Massamon

AU - Wongsawat, Yodchanan

PY - 2013

Y1 - 2013

N2 - Many stroke patients are suffered from motor disability and unable to carry out the activity of daily living. The purpose of this project is to develop the prediction and neurorehabitation system for pre-and post-stroke patients. Our system includes twomodules; Human-Computer Interface based stroke early prediction system (iSEP) and the upper limb rehabilitation device controlled by EEG through the use of Virtual Reality (iSRE). ERD/ERS is the phenomenon occurs in the brain that we used to classify motor imagery into left or right side. The virtual hand in the developed flash game will move to the side that the user imagined as well as the device will raise the user's upper limb on the same side of imagery. The results showed that the accuracy of left/right classification algorithm depends on user and training time, approximately 71.25 %.

AB - Many stroke patients are suffered from motor disability and unable to carry out the activity of daily living. The purpose of this project is to develop the prediction and neurorehabitation system for pre-and post-stroke patients. Our system includes twomodules; Human-Computer Interface based stroke early prediction system (iSEP) and the upper limb rehabilitation device controlled by EEG through the use of Virtual Reality (iSRE). ERD/ERS is the phenomenon occurs in the brain that we used to classify motor imagery into left or right side. The virtual hand in the developed flash game will move to the side that the user imagined as well as the device will raise the user's upper limb on the same side of imagery. The results showed that the accuracy of left/right classification algorithm depends on user and training time, approximately 71.25 %.

KW - BCI

KW - EEG

KW - ERD/ERS

KW - Neurorehabilitation

KW - Prediction system

KW - Stroke

KW - Virtual reality

UR - https://www.scopus.com/pages/publications/84894548195

M3 - Paper

AN - SCOPUS:84894548195

T2 - 7th International Convention on Rehabilitation Engineering and Assistive Technology, i-CREATe 2013, in Conjunction with SENDEX 2013

Y2 - 29 August 2013 through 31 August 2013

ER -

BCI-based neurorehabilitation and prediction system for stroke patients

Abstract

Conference

UN SDGs

Keywords

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