Movement prediction with sensory feedback and environmental interaction

Chun Kee Chung, Hong Gi Yeom, Hyeongrae Lee, Seokyun Ryun, June Sic Kim

Research output: Contribution to conferencePaperResearchpeer-review

Abstract

In the last decade, numerous brain-computer interface (BCI) studies have been performed to help disabled people. However, previous BCI methods have several limitations. First, the BCI system has a time delay which makes user inconvenience. Second, user of the BCI only can select a choice among limited options. Last, accuracy of the BCI is low which is a barrier to practical use. Here, we suggested a novel BCI method to solve these problems. Our results demonstrated that BCI response time can be reduced by predicting motor intentions from the readiness potential (Bereitschaftspotential; RP or BP) signals. We also showed that movement trajectory could be predicted from the non-invasive MEG signals with considerably high accuracy. In addition, our results revealed that the BCI performance will be improved by combining feedback information. Furthermore, we showed possibility of a BCI with tactile feedback. Our results will promote the development of a practical BCI system.

Original languageEnglish
DOIs
StatePublished - 1 Jan 2014
Event2014 International Winter Workshop on Brain-Computer Interface, BCI 2014 - Gangwon, Korea, Republic of
Duration: 17 Feb 201419 Feb 2014

Other

Other2014 International Winter Workshop on Brain-Computer Interface, BCI 2014
CountryKorea, Republic of
CityGangwon
Period17/02/1419/02/14

Fingerprint

Sensory feedback
Brain computer interface
brain
interaction
Feedback
Time delay
Trajectories

Keywords

  • Brain-Computer interface
  • component
  • Movement trajectory prediction
  • Readiness potential
  • Sensory feedback

Cite this

Chung, C. K., Yeom, H. G., Lee, H., Ryun, S., & Kim, J. S. (2014). Movement prediction with sensory feedback and environmental interaction. Paper presented at 2014 International Winter Workshop on Brain-Computer Interface, BCI 2014, Gangwon, Korea, Republic of. https://doi.org/10.1109/iww-BCI.2014.6782546
Chung, Chun Kee ; Yeom, Hong Gi ; Lee, Hyeongrae ; Ryun, Seokyun ; Kim, June Sic. / Movement prediction with sensory feedback and environmental interaction. Paper presented at 2014 International Winter Workshop on Brain-Computer Interface, BCI 2014, Gangwon, Korea, Republic of.
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abstract = "In the last decade, numerous brain-computer interface (BCI) studies have been performed to help disabled people. However, previous BCI methods have several limitations. First, the BCI system has a time delay which makes user inconvenience. Second, user of the BCI only can select a choice among limited options. Last, accuracy of the BCI is low which is a barrier to practical use. Here, we suggested a novel BCI method to solve these problems. Our results demonstrated that BCI response time can be reduced by predicting motor intentions from the readiness potential (Bereitschaftspotential; RP or BP) signals. We also showed that movement trajectory could be predicted from the non-invasive MEG signals with considerably high accuracy. In addition, our results revealed that the BCI performance will be improved by combining feedback information. Furthermore, we showed possibility of a BCI with tactile feedback. Our results will promote the development of a practical BCI system.",
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Chung, CK, Yeom, HG, Lee, H, Ryun, S & Kim, JS 2014, 'Movement prediction with sensory feedback and environmental interaction' Paper presented at 2014 International Winter Workshop on Brain-Computer Interface, BCI 2014, Gangwon, Korea, Republic of, 17/02/14 - 19/02/14, . https://doi.org/10.1109/iww-BCI.2014.6782546

Movement prediction with sensory feedback and environmental interaction. / Chung, Chun Kee; Yeom, Hong Gi; Lee, Hyeongrae; Ryun, Seokyun; Kim, June Sic.

2014. Paper presented at 2014 International Winter Workshop on Brain-Computer Interface, BCI 2014, Gangwon, Korea, Republic of.

Research output: Contribution to conferencePaperResearchpeer-review

TY - CONF

T1 - Movement prediction with sensory feedback and environmental interaction

AU - Chung, Chun Kee

AU - Yeom, Hong Gi

AU - Lee, Hyeongrae

AU - Ryun, Seokyun

AU - Kim, June Sic

PY - 2014/1/1

Y1 - 2014/1/1

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AB - In the last decade, numerous brain-computer interface (BCI) studies have been performed to help disabled people. However, previous BCI methods have several limitations. First, the BCI system has a time delay which makes user inconvenience. Second, user of the BCI only can select a choice among limited options. Last, accuracy of the BCI is low which is a barrier to practical use. Here, we suggested a novel BCI method to solve these problems. Our results demonstrated that BCI response time can be reduced by predicting motor intentions from the readiness potential (Bereitschaftspotential; RP or BP) signals. We also showed that movement trajectory could be predicted from the non-invasive MEG signals with considerably high accuracy. In addition, our results revealed that the BCI performance will be improved by combining feedback information. Furthermore, we showed possibility of a BCI with tactile feedback. Our results will promote the development of a practical BCI system.

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Chung CK, Yeom HG, Lee H, Ryun S, Kim JS. Movement prediction with sensory feedback and environmental interaction. 2014. Paper presented at 2014 International Winter Workshop on Brain-Computer Interface, BCI 2014, Gangwon, Korea, Republic of. https://doi.org/10.1109/iww-BCI.2014.6782546