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A novel few-channel strategy for removing muscle artifacts from multichannel EEG data.

, , and . GlobalSIP, page 976-980. IEEE, (2017)

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A Computationally Efficient, Exploratory Approach to Brain Connectivity Incorporating False Discovery Rate Control, A Priori Knowledge, and Group Inference., , , and . Comput. Math. Methods Medicine, (2012)The Use of Multivariate EMD and CCA for Denoising Muscle Artifacts From Few-Channel EEG Recordings., , , , and . IEEE Trans. Instrum. Meas., 67 (2): 359-370 (2018)MSAIF-Net: A Multistage Spatial Attention-Based Invertible Fusion Network for MR Images., , , , , and . IEEE Trans. Instrum. Meas., (2023)MGDUN: An interpretable network for multi-contrast MRI image super-resolution reconstruction., , , , , and . Comput. Biol. Medicine, (December 2023)Image De-Raining Transformer., , , , and . IEEE Trans. Pattern Anal. Mach. Intell., 45 (11): 12978-12995 (November 2023)Decoding muscle force from individual motor unit activities using a twitch force model and hybrid neural networks., , , , , , and . Biomed. Signal Process. Control., 72 (Part): 103297 (2022)Signal Processing for Brain-Computer Interfaces: A review and current perspectives., , , , and . IEEE Signal Process. Mag., 40 (5): 80-91 (July 2023)A Novel Phonology- and Radical-Coded Chinese Sign Language Recognition Framework Using Accelerometer and Surface Electromyography Sensors., , , and . Sensors, 15 (9): 23303-23324 (2015)Learning Dual Transformation Networks for Image Contrast Enhancement., , and . IEEE Signal Process. Lett., (2020)Remove Diverse Artifacts Simultaneously From a Single-Channel EEG Based on SSA and ICA: A Semi-Simulated Study., , , , , , and . IEEE Access, (2019)