This dataset is for the performance verification of sEMG-based intention recognition algorithm with upper-limb position effect.
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This database contains the 166 Galvanic Skin Response (GSR) signal registers collected from the subjects participating in the first experiment (EXP 1) presented in:
R. Martinez, A. Salazar-Ramirez, A. Arruti, E. Irigoyen, J. I. Martin and J. Muguerza, "A Self-Paced Relaxation Response Detection System Based on Galvanic Skin Response Analysis," in IEEE Access, vol. 7, pp. 43730-43741, 2019. doi: 10.1109/ACCESS.2019.2908445
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The dataset is used to test the performance of encryption model
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The data that we used to test the performance of different encryption methods
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Two files are provided. In the first one, there are the power signals obtained from the current and voltage measurements made with our own acquisition system (with a sampling frequency of 5 kHz). They correspond to the switching on and off of 12 home electrical appliances randomly switched on and off during 1 hour by using relay modules and resulting in 1200 events.
In the second file, the time instants of these events are all reported.
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The dataset comprises motion sensor data of 19 daily and sports activities each performed by 8 subjects in their own style for 5 minutes. Five Xsens MTx units are used on the torso, arms, and legs.
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The data is a truth table of a 21-variable 1-resilient Boolean function with nonlinearity 1047680. You may also see the truth table at
http://web.xidian.edu.cn/wgzhang/files/20180821_093235.txt
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