Biophysiological Signals
The UBFC-Phys dataset is a public multimodal dataset dedicated to psychophysiological studies. 56 participants followed a three-step experience where they lived social stress through a rest task T1, a speech task T2 and an arithmetic task T3. During the experience, the participants were filmed and were wearing a wristband that measured their Blood Volume Pulse (BVP) and ElectroDermal Activity (EDA) signals. Before the experience started and once it finished, the participants filled a form allowing to compute their self-reported anxiety scores.
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We develop a potential biomarker to subdivide the stress groups into eustress and distress groups using hemodynamic responses of functional near-infrared spectroscopy (fNIRS). We stimulate two stress groups divided by saliva alpha-amylase (sAA) with an international affective picture system (IAPS) inducing positive or negative emotions and measure hemodynamic responses at the same time. As a result, we have developed a newly designed biomarker using fNIRS.
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This open access webpage has all miscellaneous data related to Medical, BioEngineering. This page has data of processed X-Rays, CT Scans, MRI, ECG, heart and breathing patterns, sounds, data and design of ß-Biomedical machines.
This is an open access, so everything can be downloaded freely after login (free signup). You have to click on 'Title'. Datasets are helpful to doctors in diagnosing and to pharmacologists in making medicine or machine/therapy.
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This open- access page is especially for 'Female' ß-Bio models of Self-Claimed advancements, Research papers and computer models proposed by me.
I have shown in video and in papers, these giving results as per clinical textbooks & expect these to be useful, particularly when computer has to diagnose or to make medicine or machine/therapy.
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Models shared only for humanitarian purposes, Can be used by Clinical Doctors or Pharmacologists or Researchers under License CC-BY. Make sure you have read Caution.
I have shown in video and in papers, these giving results as per clinical textbooks & expect these to be useful, particularly when computer has to diagnose or to make medicine or machine/therapy.
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2179 Views
This dataset is in support of my 3 Research papers-'Geometrical Insight on Sinusoidal Waveform: Part-I','Geometrical Insight on Sinusoidal Waveform: Part-II' and 'Geometrical Insight on Sinusoidal Waveform: Part-III'
PrePrint :
- Part I :
- Part II :
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Image : Image was made by me for other International Contest (held by some Medical Institute,USA in the year 2021), 'An intuitive of electromagnetic radiation flowing over epithelial tissue'.
Related Research paper and book* - 'Electro-Magnetic Radiations and Human Body : Magnetism Either Flows And Can Heal or Disable or Annihilate' and 'Observational Analysis of Common & Abnormal Electromagnetic Fields'.
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Electroretinography (ERG) has great potential in visual health detection in early diagnosis and intervention. To date, optical coherence tomography and other diagnostic tests are mainly used. Clinically used ERG is an important diagnostic assessment for various retinal diseases, such as hereditary diseases (retinitis pigmentosa, choroideremia, cone dystrophy, etc), diabetic retinopathies, glaucoma, macular degeneration, toxic retinopathies etc. A database of five types of adult and pediatric biomedical electroretinography signals is presented in this study.
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This dataset is associated with an IEEE journal submission titled: "Prediction of larynx function using multichannel surface EMG classification" by the associated authors. The dataset consists of surface electromyography (sEMG) signals recorded from 10 study participants (5 control, 5 laryngectomees), each undertaking 3 recording sessions.
During each session the following were recorded:
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Data consists of an EMG registry obtained with a hybrid electrostimulation and electromyography device. Electrodes were placed to record activity from the extensor muscle of the fingers while the subject was squeezing a hand gripper for 10 seconds and resting for another 10.
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