Zobrazeno 1 - 10
of 166
pro vyhledávání: '"Khademul Islam Molla"'
Autor:
Abdullah Al Shiam, Kazi Mahmudul Hassan, Md. Rabiul Islam, Ahmed M. M. Almassri, Hiroaki Wagatsuma, Md. Khademul Islam Molla
Publikováno v:
Brain Sciences, Vol 14, Iss 5, p 462 (2024)
Electroencephalography (EEG) is effectively employed to describe cognitive patterns corresponding to different tasks of motor functions for brain–computer interface (BCI) implementation. Explicit information processing is necessary to reduce the co
Externí odkaz:
https://doaj.org/article/ef28a4aa8cb84e63bb3e97289c552398
Publikováno v:
IEEE Access, Vol 11, Pp 44019-44033 (2023)
Automatic recognition of human emotion has become an interesting topic among brain-computer interface (BCI) researchers. Emotion is one of the most fundamental features of a human subject. With proper analysis of emotion, the inner state of a human s
Externí odkaz:
https://doaj.org/article/d4b09f22703d41888e4bcf8263156ca6
Publikováno v:
Mathematics, Vol 11, Iss 17, p 3801 (2023)
Electrical activities of the human brain can be recorded with electroencephalography (EEG). To characterize motor imagery (MI) tasks for brain–computer interface (BCI) implementation is an easy and cost-effective tool. The MI task is represented by
Externí odkaz:
https://doaj.org/article/f9519f5e73a4436da6b7a343b450177f
Autor:
Md. Humaun Kabir, Shabbir Mahmood, Abdullah Al Shiam, Abu Saleh Musa Miah, Jungpil Shin, Md. Khademul Islam Molla
Publikováno v:
Mathematics, Vol 11, Iss 8, p 1921 (2023)
Analyzing electroencephalography (EEG) signals with machine learning approaches has become an attractive research domain for linking the brain to the outside world to establish communication in the name of the Brain-Computer Interface (BCI). Many res
Externí odkaz:
https://doaj.org/article/4b0c7074347a474aba44c641cdc7be82
Publikováno v:
IEEE Access, Vol 9, Pp 7632-7642 (2021)
Electroencephalography (EEG) captures the electrical activities of human brain. It is an easy and cost effective tool to characterize motor imager (MI) task used in brain computer interface (BCI) implementation. The MI task is represented by short ti
Externí odkaz:
https://doaj.org/article/aa3b7318cb5243889316cb5e4bab2633
Publikováno v:
IEEE Access, Vol 9, Pp 167744-167755 (2021)
Brain-computer interface (BCI) refers to the recognition of brain activity leading to generate corresponding commands to interact with external devices. Due to its safety and high time resolution, electroencephalogram (EEG) based BCIs have become pop
Externí odkaz:
https://doaj.org/article/adc949b271594e8683af9811148c357b
Publikováno v:
IEEE Access, Vol 8, Pp 98255-98265 (2020)
Achieving a reliable classification of motor imagery (MI) tasks is a major challenge in brain-computer interface (BCI) implementation. The set of relevant and discriminative features plays an important role in the classification scheme. This paper pr
Externí odkaz:
https://doaj.org/article/82cae30d7ad64c80a7ebe9b4ccf81f08
Publikováno v:
International Journal of Advanced Robotic Systems, Vol 18 (2021)
This article presents a hybrid wavelet-based algorithm to suppress the ocular artifacts from electroencephalography (EEG) signals. The hybrid wavelet transform (HWT) method is designed by the combination of discrete wavelet decomposition and wavelet
Externí odkaz:
https://doaj.org/article/b4fa9c6bd59c49d9aee289601ae83fb8
Publikováno v:
BioTechnologia, Vol 98, Iss 2, Pp 85-96 (2017)
The prediction of subcellular locations of proteins can provide useful hints for revealing their functions as well as for understanding the mechanisms of some diseases and, finally, for developing novel drugs. As the number of newly discovered protei
Externí odkaz:
https://doaj.org/article/e9c3f4fbdcc04d128df7216ff1372b3a
Autor:
Most. Sheuli Akter, Md. Rabiul Islam, Toshihisa Tanaka, Yasushi Iimura, Takumi Mitsuhashi, Hidenori Sugano, Duo Wang, Md. Khademul Islam Molla
Publikováno v:
Entropy, Vol 22, Iss 12, p 1415 (2020)
The design of a computer-aided system for identifying the seizure onset zone (SOZ) from interictal and ictal electroencephalograms (EEGs) is desired by epileptologists. This study aims to introduce the statistical features of high-frequency component
Externí odkaz:
https://doaj.org/article/2d917931be0043c080c74a8dde127633