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This study uses a dataset from 5 subjects, including 4 with Parkinson's Disease (PD) and 1 with Essential Tremor (ET). The data includes Inertial Measurement Unit (IMU) and surface electromyography (sEMG) signals. The dataset supports conclusions in the article "An OpenSim-based closed-loop biomechanical wrist model for pathological tremor simulation."
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533 Views
Human biomechanics is still an active topic of research that requires more technological advancements and data collection of various human body movements. There is a need for methodologies to identify daily activities in various scenarios, such as one while carrying a school bag. Deakin university has developed an Internet of Things (IoT) enabled smart school bag consisting of motion analysis sensors that would recognize the activities performed while carrying the school bag.
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110 Views
Progress toward the use of S-band SoOp in sea surface remote sensing was demonstrated in a 2012-2013 experiment based at the Harvest Oil Platform located at 34.469° N and 120.682° W, roughly 11 km from Point Conception, Santa Barbara, CA. Satellite transmissions from the XM-radio service were observed, using one channel each from the “Rhythm” (located above 85°W) and the “Blues” (115°W) satellites. Each downlink channel had a bandwidth of 1.886 MHz with a symbol rate of 1.64 Msps in Quadrature Phase Shift Key (QPSK) modulation.
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127 Views
We present a sEMG signal database corresponding to the Indian population named “ElectroMyography Analysis of Human Activities - DataBase -2 (EMAHA-DB2).” This data set consists of two different weight training activities which involve isotonic and isometric contractions. Weight training activities are effective for improving muscle strength, overall health, and regaining limb functionality for people undergoing rehabilitation post stroke-related episodes. The EMG signals acquired during weight training can be used for muscle recruitment analysis.
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894 Views
Over 34,000 frames from 60 commercial-off-the-shelf ZigBee devices were collected in various scenarios including indoor/outdoor and line-of-sight/non-line-of-sight (LOS/NLOS). The ZigBee devices are hybrid, with 36 equipped with power amplifiers and the other 24 not. The ZigBee device uses the CC2530 chip, while the power amplifier is the RFX2401C chip. The signal frames in each scenario are placed in a separate folder, where all device numbers are fixed. Each frame reaches its maximum length, which includes 266 symbols.
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664 Views
This dataset is associated with the manuscript entitled "Data-efficient Human Walking Speed Intent Inference". The data represent the measurements taken from 15 able-bodied human subjects as the made speed changes while walking on a treadmill. Each subject is associated with a .mat file that contains 8 variables. Four variables are associated with the training dataset while four are associated with the experimental testing protocol.
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123 Views
Dataset: IQ samples of LTE, 5G NR, WiFi, ITS-G5, and C-V2X PC5
Thes dataset comprises IQ samples captured from ITSG-5, C-V2X PC5, WiFi, LTE, 5G NR and Noise. Six different dataset bunches are collected at sampling rates of 1, 5, 10, 15 , 20, and 25 Msps. In each dataset cluster, 7500 examples are collected from each considered technology. The dataset size at each considered sampling rate is 7500 X M, where M can be 44, 220, 440, 660, 880, and 1100 for a sampling rate of 1, 5, 10, 15 , 20, and 25 Msps,respectively.
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3693 Views