This database contains the results of an experiment were healthy subjects played 5 trials of a rehabilitation-based VR game, to experience either difficulty variations or presence variations.
Colected results are demogrpahic information, emotional emotions after each trial and electrophysiological signals during all 5 trials.
One of the materials that is commonly being used in electronics applications is paper. It is flexible, cheap, highly available, and allows for simple manufacturing when paired with methods such as screen printing or inkjet printing. Proposed below is an optogenetic device that uses paper as the sole substrate, with a screenprinted PCB with Ag/AgCl wires. This device was quick and easy to manufacture, unlike the state of the art optoelectronic devices that use polymers and rely on complex fabrication methods such as photolithography.
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
* GSR signals of each participant:The files whose names begin with letter A correspond to the GSR registers extracted from the participants. These files have a single column which correspond to the values of the GSR signal sampled at Fs=1Hz.* Labels of each signal:The files whose names begin with LABEL correspond to the labels of the RResp of each subject.These files have two columns. The first column corresponds to the label of the register and the second column corresponds to the timestamp for that given label. The registers have been labeled using 20s windows (sliding every 5s) and being the labels positioned in the center of the window. For example:-1 12.5 --> In the time window going from 2.5s to 22.5s, the RResp label corresponds to RResp=-1, being the center of the window at 12.5s.There are four RResp intensity levels: 0 stands for the absence of any RResp, -1 for a Low intensity RResp, -2 for a Medium intensity RResp and -3 for a High intensity RResp.
Motor point identification is pivotal to elicit comfortable and sustained muscle contraction through functional electrical stimulation. To this purpose, anatomical charts and manual search techniques are used to extract subject-specific stimulation profile. Such information being heterogenous they lack standardization and reproducibility. To address these limitations; we aim to identify, localize, and characterize the motor points of forearm muscles across nine healthy subjects.
Hyperspectral (HS) imaging presents itself as a non-contact, non-ionizing and non-invasive technique, proven to be suitable for medical diagnosis. However, the volume of information contained in these images makes difficult providing the surgeon with information about the boundaries in real-time. To that end, High-Performance-Computing (HPC) platforms become necessary. This paper presents a comparison between the performances provided by five different HPC platforms while processing a spatial-spectral approach to classify HS images, assessing their main benefits and drawbacks.
1) Size of the images
- PD1C1: 1000 samples x 1000 lines x 100 bands
- PD1C2: 1000 samples x 1000 lines x 100 bands
- PD1C3: 1000 samples x 1000 lines x 100 bands
2) Image composition
- The information is stored band by band
- Within each band, the information is stored line by line
- The data type is float
3) Important information
This database only contains the dermatological images. The three brain images, obtained within the context of HELICoiD EU project, are already available in the following repository:
For downloading the brain images used in this research:
- PB1C1: Op12C1
- PB2C1: Op15C1
- PB3C1: Op20C1
Magnetic resonance spectroscopy (MRS) data for a series of GABA phantoms specifically designed to provide ground truth data for GABA quantification based on MRS data. The spectra were obtained using the WIP Siemens implementation svs-edit of the common edited spectroscopy MEGAPRESS sequence on a 3T Siemens Magnetom Skyra system installed in the Clinical Imaging Unit at Swansea University (UK).
The dataset consists of MRS data for four different phantoms.
* E1 - pH-calibrated solutions of NAA, CRE and varying amounts of GABA scanned at room temperature.
* E2 - non-pH calibrated solutions of NAA, CRE and varying amounts of GABA scanned at room temperature.
* E3 - pH calibrated solutions of NAA, CRE, GLU, GLN and varying amounts of GABA scanned at room temperature.
* E4 - pH calibrated gel phantoms containing NAA, CRE, GLU, GLU and various amounts of GABA.
The preparation of the phantoms is detailed in readme-phantoms.md and the composition of the phantoms for each experiment is detailed in the spreadsheet phantoms.ods. The gel phantoms (E4) were scanned 4 times on two different dates with two different acquisition bandwidths leading to four datasets E4a, E4b, E4c, E4d.
Each of the top-level directory has multiple sub-directories, e.g., for E1:
* MEGA_Combi_WS_ON: averaged MEGAPRESS spectra in Siemens spectroscopy dicom (.IMA) format;
* MEGA_SingleAve_WS_ON: single average MEGAPRESS spectra in Siemens spectroscopy dicom (.IMA) format;
* PRESS_WS_OFF: water-unsuppressed spectra (in this case PRESS spectra);
* RAW: raw spectroscopy data in Siemens .dat format.
Each of these subdirectories in turn contains several subdirectories for each experiment performed, e.g., ls E1/MEGA_Combi_WS_ON gives
For the combined spectra, each of these subdirectories contains 3 IMA files
* MP_EDIT_DIFF.IMA: MEGAPRESS EDIT DIFF spectrum;
* MP_EDIT_OFF.IMA: MEGAPRESS EDIT OFF spectrum;
* MP_EDIT_ON.IMA: MEGAPRESS EDIT ON spectrum.
The full scan protocols are embedded in the IMA files.
For the single average MEGAPRESS spectra, each subdirectory contains 320 IMA files named 0001.IMA to 0320.IMA where the odd numbered spectra are MP EDIT ON spectra and the even numbered spectra are EDIT OFF.
Each subdirectory in the RAW directory will usually contain two .dat files, one corresponding to water suppressed and one water unsuppressed. Which is which is clear from the file names where svs_edit indicates MEGAPRESS scans and svs_se corresponds to the standard PRESS sequence. The spreadsheet calibration.ods also links the scan numbers and the corresponding measurements ID and acquisition times. WS_OFF indicates that the scan was performed with water suppression turned OFF. The default is WS ON. In some cases additional information is provided, e.g., a warning if any auto-adjustments between the two scans were detected.
A new wearable sensing system of respiration rate based on a piezoresistive FlexiForce sensor has been developed. The 3D casing of the system has been designed and printed with a 3D printer. The design of the casing has a direct impact on sensor accuracy. The casing was designed to house all elements of the sensing system in a compact way: microcontroller, battery, conditioning circuit, Bluetooth module and battery charger. The sensing system was validated with twenty-one subjects using a metronome as a reference.
Monitoring cell viability and proliferation in real-time provides a more comprehensive picture of the changes cells undergo during their lifecycle than can be achieved using traditional end-point assays. Our lab has developed a CMOS biosensor that monitors cell viability through high-resolution capacitance measurements of cell adhesion quality. The system consists of a 3 × 3 mm2 chip with an array of 16 sensors, on-chip digitization, and serial data output that can be interfaced with inexpensive off-the-shelf components.
The dataset file (cap_sensor_data.zip) contains capacitance measurements and images. CSV data is provided in the "capData_csv" folder. Images are provided in the "images" folder. The data in MATLAB format is found in "capData.mat". The MATLAB script file, "script_plot_data.m", contains code to parse and plot the data. It can be used as an example to perform data analysis. The spatial locations of the 16 channels can be found in "channel_numbers.jpg".
Please see the attached documentation file for more details.
The data is obtained from electrocardiography, using flexible electrode, Ag/AgCl electrode and Metal Clamp electrode of a femal subject, age 22 years old.
This dataset is associated with the paper, Giovanni Dimauro et al. 2017, which is open source, and can be found here: https://ieeexplore.ieee.org/document/8070308
The DataPort Repository contains the data used primarily for generating Figure 2,3,4,5
The paper associated with the dataset describes in great detail how the dataset was created, what it contains and how it can be used. In any case, the content can be easily understood by comparing the .xlsx files with the wav files, both included in the zip file. However, the authors are available to provide further details to anyone.