A real-time Brain-Computer Interface (BCI) framework for sleep state stimulation using a deep-learning technique: proposal
Sleep disturbance can cause mental illnesses such as depression, hypertension, metabolic syndrome, and cognitive impairment. To date, various methods have been proposed as intervention measures for sleep disturbance, including taking a short mid-day nap. Falling asleep depends on several external fa...
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Online Access: | http://irep.iium.edu.my/99371/1/Sleeping_ICEPEE2022.pdf http://irep.iium.edu.my/99371/2/IEC%20Program%20Book%202022%20Finalized.pdf http://irep.iium.edu.my/99371/ |
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my.iium.irep.993712022-08-17T05:20:42Z http://irep.iium.edu.my/99371/ A real-time Brain-Computer Interface (BCI) framework for sleep state stimulation using a deep-learning technique: proposal Handayani, Dini Yaacob, Hamwira Sakti Attarbashi, Zainab Osmani, Noor Mohammad Jamaludin, Mohammad Aizat Altaleb, Abdulazeez E. BP188 Islamic religious life QA75 Electronic computers. Computer science Sleep disturbance can cause mental illnesses such as depression, hypertension, metabolic syndrome, and cognitive impairment. To date, various methods have been proposed as intervention measures for sleep disturbance, including taking a short mid-day nap. Falling asleep depends on several external factors, such as the ambience, temperature, sound, and lighting. On top of that, the factors that affect the quality and period of falling asleep can be subjective. The attempt to provide feedback based on the configuration of those external factors is time-consuming. Additionally, if those external factors are incorrectly configured, the intended short nap as a solution may have the opposite effects. As such, research on real-time sleep analysis plays an important role. However, the current study on deep-learning techniques regarding the sleep analysis that can give real-time results is still scarce compared to the offline sleep analysis. Therefore, this study aims to design and develop a real-time BCI framework for sleep state stimulation. 2022-08-09 Conference or Workshop Item PeerReviewed application/pdf en http://irep.iium.edu.my/99371/1/Sleeping_ICEPEE2022.pdf application/pdf en http://irep.iium.edu.my/99371/2/IEC%20Program%20Book%202022%20Finalized.pdf Handayani, Dini and Yaacob, Hamwira Sakti and Attarbashi, Zainab and Osmani, Noor Mohammad and Jamaludin, Mohammad Aizat and Altaleb, Abdulazeez E. (2022) A real-time Brain-Computer Interface (BCI) framework for sleep state stimulation using a deep-learning technique: proposal. In: 5th International Conference on Engineering Professional Ethics and Education (ICEPEE'22), 9-10 August 2022, Online. (Unpublished) |
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BP188 Islamic religious life QA75 Electronic computers. Computer science Handayani, Dini Yaacob, Hamwira Sakti Attarbashi, Zainab Osmani, Noor Mohammad Jamaludin, Mohammad Aizat Altaleb, Abdulazeez E. A real-time Brain-Computer Interface (BCI) framework for sleep state stimulation using a deep-learning technique: proposal |
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Sleep disturbance can cause mental illnesses such as depression, hypertension, metabolic syndrome, and cognitive impairment. To date, various methods have been proposed as intervention measures for sleep disturbance, including taking a short mid-day nap. Falling asleep depends on several external factors, such as the ambience, temperature, sound, and lighting. On top of that, the factors that affect the quality and period of falling asleep can be subjective. The attempt to provide feedback based on the configuration of those external factors is time-consuming. Additionally, if those external factors are incorrectly configured, the intended short nap as a solution may have the opposite effects. As such, research on real-time sleep analysis plays an important role. However, the current study on deep-learning techniques regarding the sleep analysis that can give real-time results is still scarce compared to the offline sleep analysis. Therefore, this study aims to design and develop a real-time BCI framework for sleep state stimulation. |
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Conference or Workshop Item |
author |
Handayani, Dini Yaacob, Hamwira Sakti Attarbashi, Zainab Osmani, Noor Mohammad Jamaludin, Mohammad Aizat Altaleb, Abdulazeez E. |
author_facet |
Handayani, Dini Yaacob, Hamwira Sakti Attarbashi, Zainab Osmani, Noor Mohammad Jamaludin, Mohammad Aizat Altaleb, Abdulazeez E. |
author_sort |
Handayani, Dini |
title |
A real-time Brain-Computer Interface (BCI) framework for sleep state stimulation using a deep-learning technique: proposal |
title_short |
A real-time Brain-Computer Interface (BCI) framework for sleep state stimulation using a deep-learning technique: proposal |
title_full |
A real-time Brain-Computer Interface (BCI) framework for sleep state stimulation using a deep-learning technique: proposal |
title_fullStr |
A real-time Brain-Computer Interface (BCI) framework for sleep state stimulation using a deep-learning technique: proposal |
title_full_unstemmed |
A real-time Brain-Computer Interface (BCI) framework for sleep state stimulation using a deep-learning technique: proposal |
title_sort |
real-time brain-computer interface (bci) framework for sleep state stimulation using a deep-learning technique: proposal |
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2022 |
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http://irep.iium.edu.my/99371/1/Sleeping_ICEPEE2022.pdf http://irep.iium.edu.my/99371/2/IEC%20Program%20Book%202022%20Finalized.pdf http://irep.iium.edu.my/99371/ |
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1743106827921391616 |
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13.18916 |