Classification of Motor Imagery and Synchronization of Post-Stroke Patient EEG Signal
作者： Arifah Ummul Fadiyah , Esmeralda C. Djamal
DOI: 10.23919/EECSI48112.2019.8977076
关键词:
摘要: Stroke attacks often cause disability, so the need for rehabilitation to restore patient's motor skills. Electroencephalogram (EEG) is an instrument that can capture electrical activity in brain. Some post-stroke patients have brain dysfunction EEG signal achieve such as amplitude decrease, and wave differences from symmetric channels. However, analysis not easy because it has high complexity small amplitude. information signals beneficial, including stroke identification. This study proposes identification of using wavelet extraction Backpropagation Levernberg-Marquardt. are recorded, extracted imagery variables, synchronization The results provide accuracy identifying 100% training data 79.69 % new data. Research also shows use learning rates affects accuracy. smaller rate provided better. had consequences computing time optimal 0.0001.
portalgaruda.org参考文章(18)
Yue Chen, Shaobai Zhang, Research on EEG Classification with Neural Networks Based on the Levenberg-Marquardt Algorithm international conference on information computing and applications. pp. 195- 202 ,(2012) , 10.1007/978-3-642-34041-3_29
Abdelhaq Ouelli, Benachir Elhadadi, Hicham Aissaoui, Belaid Bouikhalene, Epilepsy Seizure Detection Using Autoregressive Modelling and Multiple Layer Perceptron Neural Network American Journal of Computer Science and Engineering. ,vol. 2, pp. 26- ,(2015)
Endro Yulianto, Adhi Susanto, Thomas Sri Widodo, Samekto Wibowo, Spektrum Frekuensi Sinyal EEG Terhadap Pergerakan Motorik dan Imajinasi Pergerakan Motorik Forum Teknik. ,vol. 35, ,(2013)
Shahjahan Shahid, Rakesh Kumar Sinha, Girijesh Prasad, Mu and beta rhythm modulations in motor imagery related post-stroke EEG: a study under BCI framework for post-stroke rehabilitation BMC Neuroscience. ,vol. 11, pp. 127- ,(2010) , 10.1186/1471-2202-11-S1-P127
Yinxia Liu, Weidong Zhou, Qi Yuan, Shuangshuang Chen, Automatic Seizure Detection Using Wavelet Transform and SVM in Long-Term Intracranial EEG international conference of the ieee engineering in medicine and biology society. ,vol. 20, pp. 749- 755 ,(2012) , 10.1109/TNSRE.2012.2206054
Mehrnaz Kh. Hazrati, Abbas Erfanian, An online EEG-based brain-computer interface for controlling hand grasp using an adaptive probabilistic neural network Medical Engineering & Physics. ,vol. 32, pp. 730- 739 ,(2010) , 10.1016/J.MEDENGPHY.2010.04.016
Peter Langhorne, Julie Bernhardt, Gert Kwakkel, Stroke Care 2: Stroke rehabilitation The Lancet. ,vol. 377, pp. 1693- 1702 ,(2011) , 10.1016/S0140-6736(11)60325-5
Ye Liu, Mingfen Li, Hao Zhang, Hang Wang, Junhua Li, Jie Jia, Yi Wu, Liqing Zhang, A tensor-based scheme for stroke patients' motor imagery EEG analysis in BCI-FES rehabilitation training. Journal of Neuroscience Methods. ,vol. 222, pp. 238- 249 ,(2014) , 10.1016/J.JNEUMETH.2013.11.009
Scott E Kasner, Clinical interpretation and use of stroke scales Lancet Neurology. ,vol. 5, pp. 603- 612 ,(2006) , 10.1016/S1474-4422(06)70495-1
Rahmat Rahmat, Mauridhi Hery Purnomo, Rachmad Setiawan, Perbandingan Algoritma Levenberg-Marquardt dengan Metoda Backpropagation pada Proses Learning Jaringan Saraf Tiruan untuk Pengenalan Pola Sinyal Elektrokardiograf Seminar Nasional Aplikasi Teknologi Informasi (SNATI). pp. 88610- ,(2006)