128 citations · 137 across the 4 of their papers we have counts for
4 papers
Improving Rehabilitative Assessment with Statistical and Shape Preserving Surrogate Data and Singular Spectrum Analysis
T. K. M. Lee, H. W. Chan, K. H. Leo +3
Time series data are collected in temporal order and are widely used to train systems for prediction, modeling and classification to name a few. These systems require large amounts…
Fidelitous Augmentation of Human Accelerometric Data for Deep Learning
Tracey K. M. Lee, H. W. Chan, K. H. Leo +3
Time series (TS) data have consistently been in short supply, yet their demand remains high for training systems in prediction, modeling, classification, and various other applicat…
FBCNet: A Multi-view Convolutional Neural Network for Brain-Computer Interface
Ravikiran Mane, Effie Chew, Karen Chua +5
Lack of adequate training samples and noisy high-dimensional features are key challenges faced by Motor Imagery (MI) decoding algorithms for electroencephalogram (EEG) based Brain-…
How transcranial direct current stimulation facilitates post-stroke rehabilitation
Feng Qi, Xin Hong, ZhongKang Lu +7
Whether transcranial direct current stimulation (tDCS) benefits stroke rehabilitation remains unclear. To investigate how tDCS reorganizes brain circuitry, nineteen post-stroke pat…