Mechanical Sensing
The dataset 'sensitivityThreshold(haptic feedback).zip' contains the results of a haptic feedback sensitivity study comparing a novel laparoscopic grasper with 2 conventional graspers. Also grip preference of each participant was stored.The instrument sensitivity was validated by measuring the level at which participants could discriminate force differences applied at the grasper tip with an increasing force level, while the subjects were holding the new instrument and a conventional grasper at the handle grip.
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Recently, there has been a notable shift to increasingly more sedentary lifestyles, yet it remains unclear whether inexpensive accelerometers, such as those contained in Actigraph devices, can provide consistent measurements of low magnitude accelerations. This study sought to explore the ability of two Actigraph models to differentiate low frequency oscillations, in reference to higher-end accelerometers with the idle sleep mode disabled (ISM) (Part 1) and enabled (Part 2) in a controlled environment.
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The measurement and diagnosis of the severity of failures in rotating machines allow the execution of predictive maintenance actions on equipment. These actions make it possible to monitor the operating parameters of the machine and to perform the prediction of failures, thus avoiding production losses, severe damage to the equipment, and safeguarding the integrity of the equipment operators. This paper describes the construction of a dataset composed of vibration signals of a rotating machine.
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This dataset is in support of my research paper '9-DoF Personal Robot Servant'.
Preprint :
On this robot servant, my first work was done in the year 2011.
Image Source: https://www.dreamstime.com/robot-tray-d-rendering-mini-holding-serving-i...
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The dataset includes the sweep scanning paths and measured points in two experiments.
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Please cite the following paper when using this dataset:
N. Thakur, "Twitter Big Data as a Resource for Exoskeleton Research: A Large-Scale Dataset of about 140,000 Tweets from 2017–2022 and 100 Research Questions", Journal of Analytics, Volume 1, Issue 2, 2022, pp. 72-97, DOI: https://doi.org/10.3390/analytics1020007
Abstract
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Delta 3D printers can significantly increase throughput in additive manufacturing by enabling faster and more precise motion compared to traditional serial-axis 3D printers. Further improvements in motion speed and part quality can be realized through model-based feedforward vibration control, as demonstrated on several serial-axis 3D printers. However, delta 3D printers have not benefited from model-based controllers because their position-varying, coupled nonlinear dynamics are difficult to model accurately.
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The PHM Data Challenge is a competition open to all potential conference attendees. This dataset is from the challenge and focused on RUL estimation for a high-speed CNC milling machine cutters using dynamometer, accelerometer, and acoustic emission data.
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This is a dataset of 32 five-second-long vibration recordings. One human used a metal tool to perform one of two tool-mediated surface interactions (tapping or dragging) on the following four different surfaces: sandpaper (hard and rough), acrylic plastic (hard and smooth), rough paper (soft and rough), and rubber (soft and smooth). Each of the eight combinations of interaction and surface were recorded four times.
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<p>The technique of electrical impedance tomography (EIT) has been recognized as a promising method to design tactile sensors with continuous sensing capability over a large area. The mechanism of electrical impedance tomography allows reconstructing tactile information within the sensing area based on measurements made only at the boundary. However, spatial performance of EIT-based tactile sensors has demonstrated location dependency in previous reports, which severely affects correct interpretation of tactile stimuli.
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