Brain
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 and design related to ß-machines- Non-Medical, ß-Biomedical machines, processed ECG, sensors, heart and breathing patterns, sounds, finite element analysis, mathematics and BioEngineering.
As all only want free download and I used to get emails to share data freely ; with IEEE DataPort I had began journey of Data, so I will do update data as long as IEEE DataPort allows it or as long as I can or . I might also upload same data externally to other site.
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This dataset is in support of my following Research papers
Preprint (Make sure you have read Caution) :
- Novel ß Transtibial Prosthetic 9-DoF Artificial Leg Adaptive Controller - Part I*
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This is a two-part open-access page -'Data:B-Bio Models-1 and 'Data:B-Bio Models-2'. This webpage contains datasets and models, with clinical investigation in simulation, proposed by me which are Self-Claimed advancements. All the content can be freely downloaded after sign-up.
I. Novel B-Bio Models
To freely download, pls. click on title. Make sure you have read My ORCid, Disclaimer and Legal Disclosure Statement.
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Ten volunteers were trained through a series of twelve daily lessons to type in a computer using the Colemak keyboard layout. During the fourth-, eight-, and eleventh-session, electroencephalography (EEG) measurements were acquired for the five trials each subject performed in the corresponding lesson. Electrocardiography (ECG) data at each of those trials were acquired as well. The purpose of this experiment is to aim in the development of different methods to assess the process of learning a new task.
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EEG signals of various subjects in text files are uploaded. It can be useful for various EEG signal processing algorithms- filtering, linear prediction, abnormality detection, PCA, ICA etc.
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Participants were 61 children with ADHD and 60 healthy controls (boys and girls, ages 7-12). The ADHD children were diagnosed by an experienced psychiatrist to DSM-IV criteria, and have taken Ritalin for up to 6 months. None of the children in the control group had a history of psychiatric disorders, epilepsy, or any report of high-risk behaviors.
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Dataset asscociated with a paper in IEEE Transactions on Pattern Analysis and Machine Intelligence
"The perils and pitfalls of block design for EEG classification experiments"
DOI: 10.1109/TPAMI.2020.2973153
If you use this code or data, please cite the above paper.
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