TY - GEN
T1 - The survey of image generation from EEG signals based on deep learning
AU - Yang, Delong
AU - Su, Dongnan
AU - Luo, Zhaohui
AU - Shang, Peng
AU - Hu, Zhigang
N1 - Publisher Copyright:
© 2021 Association for Computing Machinery. All rights reserved.
PY - 2021/8/13
Y1 - 2021/8/13
N2 - China has become a high-risk region of stroke. Most patients with stroke suffer regular bouts of post-stroke limb dyskinesia. Nowadays, there isn't an effective treatment for these patients. Brain computer interface (BCI) establishes a new pathway to connect human brains and device, which provide an innovation method to repair the human brain nervous systems through rehabilitation training. However, one of the mainly brain activity recordings, Electroencephalogram (EEG), cannot be represented accurately by other algorithms. With the development of deep learning techniques, the topic of EEG signals' representation by image generation technique has become an important research area. This paper we introduced the basic concepts of BCI systems first, then we give a survey of image generation techniques from EEG signals. At last, we proposed an experimental scheme of dataset establishment which is used for post-stroke patients with upper limb dyskinesia.
AB - China has become a high-risk region of stroke. Most patients with stroke suffer regular bouts of post-stroke limb dyskinesia. Nowadays, there isn't an effective treatment for these patients. Brain computer interface (BCI) establishes a new pathway to connect human brains and device, which provide an innovation method to repair the human brain nervous systems through rehabilitation training. However, one of the mainly brain activity recordings, Electroencephalogram (EEG), cannot be represented accurately by other algorithms. With the development of deep learning techniques, the topic of EEG signals' representation by image generation technique has become an important research area. This paper we introduced the basic concepts of BCI systems first, then we give a survey of image generation techniques from EEG signals. At last, we proposed an experimental scheme of dataset establishment which is used for post-stroke patients with upper limb dyskinesia.
KW - Brain computer interface (BCI)
KW - Deep learning
KW - Electroencephalograph (EEG)
KW - Image generation
UR - http://www.scopus.com/inward/record.url?scp=85125659284&partnerID=8YFLogxK
U2 - 10.1145/3502060.3502151
DO - 10.1145/3502060.3502151
M3 - 会议稿件
AN - SCOPUS:85125659284
T3 - ACM International Conference Proceeding Series
BT - Proceedings - 2021 International Symposium on Biomedical Engineering and Computational Biology, BECB 2021
PB - Association for Computing Machinery
T2 - 2021 International Symposium on Biomedical Engineering and Computational Biology, BECB 2021
Y2 - 13 August 2021 through 15 August 2021
ER -