This dataset presents the measurements corresponding to the article "Validation of a Velostat-Based Pressure Sensitive Mat for Center of Pressure Measurements". You will find the data corresponding to an affordable commercial mat, a Velostat-based mat prototype, and a commercial force platform. The results obtained in the above-mentioned article can be reproduced with them.
This dataset contains cardiovascular data recorded during progressive exsanguination in a porcine model of hemorrhage. Both wearable and catheter-based sensors were used to capture cardiovascular function; the wearable system contained a fusion of ECG, SCG, and PPG sensors while the catheter-based system was comprised of pressure catheters in the aortic arch, femoral artery, and right and left atria via a Swan-Ganz catheter.
This repository introduces a novel dataset for the classification of Chronic Obstructive Pulmonary Disease (COPD) patients and Healthy Controls. The Exasens dataset includes demographic information on 4 groups of saliva samples (COPD-HC-Asthma-Infected) collected in the frame of a joint research project, Exasens (https://www.leibniz-healthtech.de/en/research/projects/bmbf-project-exasens/), at the Research Center Borstel, BioMaterialBank Nord (Borstel, Germany).
The data set is collected from MyNeuroHealth Application developed for the detection of Seizures and Falls. Data is gathered using tri-axial accelerometer placed at the upper left arm of an individual in an unconstraint environment.
Reddit is one of the largest social media websites in the world and it contains valuable data about its users and their perspectives organized into virtual communities or subreddits, based on common areas of interest. Substance use issues are particularly salient within this online community due to the burgeoning substance use (opioid) crisis within the United States among other countries. A particularly important location for understanding user perceptions of opioids is the Philadelphia, Pennsylvania, USA region, due to the prevalence associated with overdose deaths. To collect user sen
This data set includes Covid-19 related Tweet messages written in Turkish that contain at least one of four keywords (Covid, Kovid, Corona, Korona). These keywords are used to express Covid-19 virus in Turkey. Tweets collection was started from 11th March 2020, the first Covid-19 case seen in Turkey.
Currently dataset contain 4,8 million tweets with 6 different attribute of each tweets that were sent from 9 March 2020 until 6 May 2020.
The data file contains comma separated values (CSV). It contains the following information (6 Column) for each tweet in the data file:
Internet of Things (IoT) make the world easy, with healthcare applications being the most important. In general, IoT is used to interconnect advanced medical resources and provide smart and effective healthcare services to people. Advanced sensors can either be worn or embedded in patients' bodies, so that their health can be monitored remotely. Information collected in this way can be analyzed, collected, and mined to make an early prediction of diseases. Processing algorithms help physicians to personalize treatment and it helps to make healthcare affordable, with better results.
