{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,11,1]],"date-time":"2025-11-01T22:08:17Z","timestamp":1762034897212,"version":"build-2065373602"},"publisher-location":"New York, NY, USA","reference-count":30,"publisher":"ACM","license":[{"start":{"date-parts":[[2020,10,30]],"date-time":"2020-10-30T00:00:00Z","timestamp":1604016000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"funder":[{"name":"The National Key Research and Development Program of China under Grant","award":["2017YFB1300303"],"award-info":[{"award-number":["2017YFB1300303"]}]}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2020,10,30]]},"DOI":"10.1145\/3436369.3437433","type":"proceedings-article","created":{"date-parts":[[2021,1,12]],"date-time":"2021-01-12T03:48:53Z","timestamp":1610423333000},"page":"73-79","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":4,"title":["EEG-Based Hand Motion Pattern Recognition Using Deep Learning Network Algorithms"],"prefix":"10.1145","author":[{"given":"Yongyu","family":"Jiang","sequence":"first","affiliation":[{"name":"Xi'an Jiaotong University, Xi'an, China"}]},{"given":"Christine","family":"Chen","sequence":"additional","affiliation":[{"name":"Department of Computer Science, University of Michigan at Ann Arbor, Ann Arbor, Michigan, USA"}]},{"given":"Xiaodong","family":"Zhang","sequence":"additional","affiliation":[{"name":"Xi'an Jiaotong University, Xi'an, China"}]},{"given":"Wei","family":"Zhou","sequence":"additional","affiliation":[{"name":"Ximen University, Xiamen, China"}]},{"given":"Chaoyang","family":"Chen","sequence":"additional","affiliation":[{"name":"Department of Biomedical Engineering, Wayne State University, Detroit, Michigan, USA"}]},{"given":"Stephen","family":"Lemos","sequence":"additional","affiliation":[{"name":"Orthopedic Surgery and Sports Medicine, DMC Detroit, MI USA"}]}],"member":"320","published-online":{"date-parts":[[2021,1,11]]},"reference":[{"key":"e_1_3_2_1_1_1","volume-title":"Neurosci.","author":"Agashe H. A.","year":"2015","unstructured":"H. A. Agashe , A. Y. Paek , Y. Zhang , and J. L. Contreras-Vidal , \" Global cortical activity predicts shape of hand during grasping,\" Front . Neurosci. , 2015 , doi: 10.3389\/fnins.2015.00121. 10.3389\/fnins.2015.00121 H. A. Agashe, A. Y. Paek, Y. Zhang, and J. L. Contreras-Vidal, \"Global cortical activity predicts shape of hand during grasping,\" Front. Neurosci., 2015, doi: 10.3389\/fnins.2015.00121."},{"key":"e_1_3_2_1_2_1","volume-title":"Brain-computer interfaces for communication and rehabilitation,\" Nature Reviews Neurology","author":"Chaudhary U.","year":"2016","unstructured":"U. Chaudhary , N. Birbaumer , and A. Ramos-Murguialday , \" Brain-computer interfaces for communication and rehabilitation,\" Nature Reviews Neurology . 2016 , doi: 10.1038\/nrneurol.2016.113. 10.1038\/nrneurol.2016.113 U. Chaudhary, N. Birbaumer, and A. Ramos-Murguialday, \"Brain-computer interfaces for communication and rehabilitation,\" Nature Reviews Neurology. 2016, doi: 10.1038\/nrneurol.2016.113."},{"key":"e_1_3_2_1_3_1","volume-title":"What is the Bereitschaftspotential?,\" Clinical Neurophysiology","author":"Shibasaki H.","year":"2006","unstructured":"H. Shibasaki and M. Hallett , \" What is the Bereitschaftspotential?,\" Clinical Neurophysiology . 2006 , doi: 10.1016\/j.clinph.2006.04.025. 10.1016\/j.clinph.2006.04.025 H. Shibasaki and M. Hallett, \"What is the Bereitschaftspotential?,\" Clinical Neurophysiology. 2006, doi: 10.1016\/j.clinph.2006.04.025."},{"key":"e_1_3_2_1_4_1","volume-title":"Gesamte Physiol. Menschen Tiere","author":"Kornhuber H. H.","year":"1965","unstructured":"H. H. Kornhuber and L. Deecke , \" Hirnpotential\u00e4nderungen bei Willk\u00fcrbewegungen und passiven Bewegungen des Menschen: Bereitschaftspotential und reafferente Potentiale,\" Pflugers Arch . Gesamte Physiol. Menschen Tiere , 1965 , doi: 10.1007\/BF00412364. 10.1007\/BF00412364 H. H. Kornhuber and L. Deecke, \"Hirnpotential\u00e4nderungen bei Willk\u00fcrbewegungen und passiven Bewegungen des Menschen: Bereitschaftspotential und reafferente Potentiale,\" Pflugers Arch. Gesamte Physiol. Menschen Tiere, 1965, doi: 10.1007\/BF00412364."},{"key":"e_1_3_2_1_5_1","doi-asserted-by":"crossref","unstructured":"G. R. M\u00fcller-Putz \"Electroencephalography \" in Handbook of Clinical Neurology 2020.  G. R. M\u00fcller-Putz \"Electroencephalography \" in Handbook of Clinical Neurology 2020.","DOI":"10.1016\/B978-0-444-63934-9.00018-4"},{"key":"e_1_3_2_1_6_1","volume-title":"Decoding individual finger movements from one hand using human EEG signals,\" PLoS One","author":"Liao K.","year":"2014","unstructured":"K. Liao , R. Xiao , J. Gonzalez , and L. Ding , \" Decoding individual finger movements from one hand using human EEG signals,\" PLoS One , 2014 , doi: 10.1371\/journal.pone.0085192. 10.1371\/journal.pone.0085192 K. Liao, R. Xiao, J. Gonzalez, and L. Ding, \"Decoding individual finger movements from one hand using human EEG signals,\" PLoS One, 2014, doi: 10.1371\/journal.pone.0085192."},{"key":"e_1_3_2_1_7_1","doi-asserted-by":"publisher","DOI":"10.1523\/JNEUROSCI.6107-09.2010"},{"key":"e_1_3_2_1_8_1","volume-title":"Rep.","author":"Meng J.","year":"2016","unstructured":"J. Meng , S. Zhang , A. Bekyo , J. Olsoe , B. Baxter , and B. He , \" Noninvasive Electroencephalogram Based Control of a Robotic Arm for Reach and Grasp Tasks,\" Sci . Rep. , 2016 , doi: 10.1038\/srep38565. 10.1038\/srep38565 J. Meng, S. Zhang, A. Bekyo, J. Olsoe, B. Baxter, and B. He, \"Noninvasive Electroencephalogram Based Control of a Robotic Arm for Reach and Grasp Tasks,\" Sci. Rep., 2016, doi: 10.1038\/srep38565."},{"key":"e_1_3_2_1_9_1","volume":"2008","author":"Cvetkovic D.","unstructured":"D. Cvetkovic , E. D. \u00dcbeyli , and I. Cosic , \"Wavelet transform feature extraction from human PPG, ECG, and EEG signal responses to ELF PEMF exposures: A pilot study,\" Digit. Signal Process. A Rev. J. , 2008 , doi: 10.1016\/j.dsp.2007.05.009. 10.1016\/j.dsp.2007.05.009 D. Cvetkovic, E. D. \u00dcbeyli, and I. Cosic, \"Wavelet transform feature extraction from human PPG, ECG, and EEG signal responses to ELF PEMF exposures: A pilot study,\" Digit. Signal Process. A Rev. J., 2008, doi: 10.1016\/j.dsp.2007.05.009.","journal-title":"Signal Process. A Rev. J."},{"key":"e_1_3_2_1_10_1","volume":"2008","author":"Blankertz B.","unstructured":"B. Blankertz , R. Tomioka , S. Lemm , M. Kawanabe , and K. R. M\u00fcller , \"Optimizing spatial filters for robust EEG single-trial analysis,\" IEEE Signal Process. Mag. , 2008 , doi: 10.1109\/MSP.2008.4408441. 10.1109\/MSP.2008.4408441 B. Blankertz, R. Tomioka, S. Lemm, M. Kawanabe, and K. R. M\u00fcller, \"Optimizing spatial filters for robust EEG single-trial analysis,\" IEEE Signal Process. Mag., 2008, doi: 10.1109\/MSP.2008.4408441.","journal-title":"Mag."},{"key":"e_1_3_2_1_11_1","volume-title":"Rehabil. Eng.","author":"Ramoser H.","year":"2000","unstructured":"H. Ramoser , J. M\u00fcller-Gerking , and G. Pfurtscheller , \" Optimal spatial filtering of single trial EEG during imagined hand movement,\" IEEE Trans . Rehabil. Eng. , 2000 , doi: 10.1109\/86.895946. 10.1109\/86.895946 H. Ramoser, J. M\u00fcller-Gerking, and G. Pfurtscheller, \"Optimal spatial filtering of single trial EEG during imagined hand movement,\" IEEE Trans. Rehabil. Eng., 2000, doi: 10.1109\/86.895946."},{"key":"e_1_3_2_1_12_1","volume-title":"A review of classification algorithms for EEG-based brain-computer interfaces: A 10 year update,\" Journal of Neural Engineering","author":"Lotte F.","year":"2018","unstructured":"F. Lotte , \" A review of classification algorithms for EEG-based brain-computer interfaces: A 10 year update,\" Journal of Neural Engineering . 2018 , doi: 10.1088\/1741-2552\/aab2f2. 10.1088\/1741-2552 F. Lotte et al., \"A review of classification algorithms for EEG-based brain-computer interfaces: A 10 year update,\" Journal of Neural Engineering. 2018, doi: 10.1088\/1741-2552\/aab2f2."},{"key":"e_1_3_2_1_13_1","volume-title":"Neurosci.","author":"Ang K. K.","year":"2012","unstructured":"K. K. Ang , Z. Y. Chin , C. Wang , C. Guan , and H. Zhang , \" Filter bank common spatial pattern algorithm on BCI competition IV datasets 2a and 2b,\" Front . Neurosci. , 2012 , doi: 10.3389\/fnins.2012.00039. 10.3389\/fnins.2012.00039 K. K. Ang, Z. Y. Chin, C. Wang, C. Guan, and H. Zhang, \"Filter bank common spatial pattern algorithm on BCI competition IV datasets 2a and 2b,\" Front. Neurosci., 2012, doi: 10.3389\/fnins.2012.00039."},{"key":"e_1_3_2_1_14_1","unstructured":"C.-J. L. Chih-Wei Hsu Chih-Chung Chang \"A Practical Guide to Support Vector Classification \" BJU Int. 2008.  C.-J. L. Chih-Wei Hsu Chih-Chung Chang \"A Practical Guide to Support Vector Classification \" BJU Int. 2008."},{"key":"#cr-split#-e_1_3_2_1_15_1.1","doi-asserted-by":"crossref","unstructured":"L. Peterson \"K-nearest neighbor \" Scholarpedia 2009 doi: 10.4249\/scholarpedia.1883. 10.4249\/scholarpedia.1883","DOI":"10.4249\/scholarpedia.1883"},{"key":"#cr-split#-e_1_3_2_1_15_1.2","doi-asserted-by":"crossref","unstructured":"L. Peterson \"K-nearest neighbor \" Scholarpedia 2009 doi: 10.4249\/scholarpedia.1883.","DOI":"10.4249\/scholarpedia.1883"},{"key":"e_1_3_2_1_16_1","volume":"2001","author":"Martinez A. M.","unstructured":"A. M. Martinez and A. C. Kak , \"PCA versus LDA,\" IEEE Trans. Pattern Anal. Mach. Intell. , 2001 , doi: 10.1109\/34.908974. 10.1109\/34.908974 A. M. Martinez and A. C. Kak, \"PCA versus LDA,\" IEEE Trans. Pattern Anal. Mach. Intell., 2001, doi: 10.1109\/34.908974.","journal-title":"\"PCA versus LDA,\" IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"e_1_3_2_1_17_1","volume-title":"Going deeper with convolutions,\" in Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition","author":"Szegedy C.","year":"2015","unstructured":"C. Szegedy , \" Going deeper with convolutions,\" in Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition , 2015 , doi: 10.1109\/CVPR.2015.7298594. 10.1109\/CVPR.2015.7298594 C. Szegedy et al., \"Going deeper with convolutions,\" in Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2015, doi: 10.1109\/CVPR.2015.7298594."},{"key":"e_1_3_2_1_18_1","volume-title":"Deep learning,\" Nature","author":"Lecun Y.","year":"2015","unstructured":"Y. Lecun , Y. Bengio , and G. Hinton , \" Deep learning,\" Nature . 2015 , doi: 10.1038\/nature14539. 10.1038\/nature14539 Y. Lecun, Y. Bengio, and G. Hinton, \"Deep learning,\" Nature. 2015, doi: 10.1038\/nature14539."},{"key":"e_1_3_2_1_19_1","volume-title":"Reducing the dimensionality of data with neural networks,\" Science (80-.)","author":"Hinton G. E.","year":"2006","unstructured":"G. E. Hinton and R. R. Salakhutdinov , \" Reducing the dimensionality of data with neural networks,\" Science (80-.) ., 2006 , doi: 10.1126\/science. 1127647. 10.1126\/science G. E. Hinton and R. R. Salakhutdinov, \"Reducing the dimensionality of data with neural networks,\" Science (80-.)., 2006, doi: 10.1126\/science. 1127647."},{"key":"e_1_3_2_1_20_1","volume-title":"Upper limb movements can be decoded from the time-domain of low-frequency EEG,\" PLoS One","author":"Ofner P.","year":"2017","unstructured":"P. Ofner , A. Schwarz , J. Pereira , and G. R. M\u00fcller-Putz , \" Upper limb movements can be decoded from the time-domain of low-frequency EEG,\" PLoS One , 2017 , doi: 10.1371\/journal.pone.0182578. 10.1371\/journal.pone.0182578 P. Ofner, A. Schwarz, J. Pereira, and G. R. M\u00fcller-Putz, \"Upper limb movements can be decoded from the time-domain of low-frequency EEG,\" PLoS One, 2017, doi: 10.1371\/journal.pone.0182578."},{"key":"e_1_3_2_1_21_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.jneumeth.2003.10.009"},{"key":"e_1_3_2_1_22_1","volume-title":"ACPR 2015","author":"Liu S.","year":"2016","unstructured":"S. Liu and W. Deng , \" Very deep convolutional neural network based image classification using small training sample size,\" in Proceedings - 3rd IAPR Asian Conference on Pattern Recognition , ACPR 2015 , 2016 , doi: 10.1109\/ACPR.2015.7486599. 10.1109\/ACPR.2015.7486599 S. Liu and W. Deng, \"Very deep convolutional neural network based image classification using small training sample size,\" in Proceedings - 3rd IAPR Asian Conference on Pattern Recognition, ACPR 2015, 2016, doi: 10.1109\/ACPR.2015.7486599."},{"key":"e_1_3_2_1_23_1","first-page":"2009","author":"Cortes C.","year":"2009","unstructured":"C. Cortes , M. Mohri , and A. Rostamizadeh , \"L2 regularization for learning kernels,\" in Proceedings of the 25th Conference on Uncertainty in Artificial Intelligence, UAI 2009 , 2009 . C. Cortes, M. Mohri, and A. Rostamizadeh, \"L2 regularization for learning kernels,\" in Proceedings of the 25th Conference on Uncertainty in Artificial Intelligence, UAI 2009, 2009.","journal-title":"\"L2 regularization for learning kernels,\" in Proceedings of the 25th Conference on Uncertainty in Artificial Intelligence, UAI"},{"key":"e_1_3_2_1_24_1","volume-title":"Mach. Learn. Res.","author":"Srivastava N.","year":"2014","unstructured":"N. Srivastava , G. Hinton , A. Krizhevsky , I. Sutskever , and R. Salakhutdinov , \" Dropout: A simple way to prevent neural networks from overfitting,\" J . Mach. Learn. Res. , 2014 . N. Srivastava, G. Hinton, A. Krizhevsky, I. Sutskever, and R. Salakhutdinov, \"Dropout: A simple way to prevent neural networks from overfitting,\" J. Mach. Learn. Res., 2014."},{"key":"e_1_3_2_1_25_1","volume-title":"ICML 2015","author":"Ioffe S.","year":"2015","unstructured":"S. Ioffe and C. Szegedy , \" Batch normalization: Accelerating deep network training by reducing internal covariate shift,\" in 32nd International Conference on Machine Learning , ICML 2015 , 2015 . S. Ioffe and C. Szegedy, \"Batch normalization: Accelerating deep network training by reducing internal covariate shift,\" in 32nd International Conference on Machine Learning, ICML 2015, 2015."},{"key":"e_1_3_2_1_26_1","volume-title":"ICLR 2015 - Conference Track Proceedings","author":"Kingma D. P.","year":"2015","unstructured":"D. P. Kingma and J. L. Ba , \" Adam: A method for stochastic optimization,\" in 3rd International Conference on Learning Representations , ICLR 2015 - Conference Track Proceedings , 2015 . D. P. Kingma and J. L. Ba, \"Adam: A method for stochastic optimization,\" in 3rd International Conference on Learning Representations, ICLR 2015 - Conference Track Proceedings, 2015."},{"key":"e_1_3_2_1_27_1","volume-title":"OSDI 2016","author":"Abadi M.","year":"2016","unstructured":"M. Abadi : A system for large-scale machine learning,\" in Proceedings of the 12th USENIX Symposium on Operating Systems Design and Implementation , OSDI 2016 , 2016 . M. Abadi et al., \"TensorFlow: A system for large-scale machine learning,\" in Proceedings of the 12th USENIX Symposium on Operating Systems Design and Implementation, OSDI 2016, 2016."},{"key":"#cr-split#-e_1_3_2_1_28_1.1","doi-asserted-by":"crossref","unstructured":"J. Xu \"An extended one-versus-rest support vector machine for multi-label classification \" Neurocomputing 2011 doi: 10.1016\/j.neucom.2011.04.024. 10.1016\/j.neucom.2011.04.024","DOI":"10.1016\/j.neucom.2011.04.024"},{"key":"#cr-split#-e_1_3_2_1_28_1.2","doi-asserted-by":"crossref","unstructured":"J. Xu \"An extended one-versus-rest support vector machine for multi-label classification \" Neurocomputing 2011 doi: 10.1016\/j.neucom.2011.04.024.","DOI":"10.1016\/j.neucom.2011.04.024"}],"event":{"name":"ICCPR 2020: 2020 9th International Conference on Computing and Pattern Recognition","sponsor":["Beijing University of Technology"],"location":"Xiamen China","acronym":"ICCPR 2020"},"container-title":["Proceedings of the 2020 9th International Conference on Computing and Pattern Recognition"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3436369.3437433","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3436369.3437433","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,17]],"date-time":"2025-06-17T22:02:53Z","timestamp":1750197773000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3436369.3437433"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,10,30]]},"references-count":30,"alternative-id":["10.1145\/3436369.3437433","10.1145\/3436369"],"URL":"https:\/\/doi.org\/10.1145\/3436369.3437433","relation":{},"subject":[],"published":{"date-parts":[[2020,10,30]]},"assertion":[{"value":"2021-01-11","order":2,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}