In this work, we present a Long Short-Term Memory Model (LSTMM) for gait phase classification based on sEMG signals to control the lower limb exoskeleton robot which can recognize 2 phases (Stand and Swing) of leg pha...
In this work, we present a Long Short-Term Memory Model (LSTMM) for gait phase classification based on sEMG signals to control the lower limb exoskeleton robot which can recognize 2 phases (Stand and Swing) of leg phases between the foot and ground. This model only needs four sEMG signals to control the lower limb exoskeleton robot helping the hemiplegia patient walking. Compared with the existing methods, the proposed model not only avoids the complex sensor systems but also enhances the accuracy of gait phase classification. The experimental results first verify the availability of sEMG data acquisition system on the lower limb exoskeleton robot made by the Shenzhen Institutes of Advanced Technologies (SIAT) by quantify the system with gold standard optoelectronic system Vicon, then show that the proposed LSTMM is significantly higher on prediction accuracy and has better robustness for gait phase classification to control the lower limb exoskeleton robot with different speeds. Finally, the maximum accuracy of LSTMM on the gait phase classification is 97.89%.
The micro-expression spotting has recently attracted increasing attention from psychology and computer vision community, since embraced in the second facial Micro-Expression Grand Challenge (MEGC 2019). Different from...
The micro-expression spotting has recently attracted increasing attention from psychology and computer vision community, since embraced in the second facial Micro-Expression Grand Challenge (MEGC 2019). Different from the original feature difference (FD) analysis, in this paper, we proposed a novel temporal and spatial domain weight analysis of feature difference (TSW-FD) to achieve micro-expression spotting. The experimental results showed that TSW-FD improved 17.86% and 24.21% in F1-Score comparing to the FD in CASME II and SMIC-E-HS.
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