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- Alcohol (1)
- Calibration (1)
- Classification (1)
- Electroencephalography (1)
- Epilepsy (1)
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- Epileptic focus (1)
- Epileptogenic zone (1)
- Functional Connectivity (1)
- Graph theory (1)
- Interictal Spike (1)
- Isoflurane (1)
- Multivariate (1)
- Nonlinear Recurrence-based method (1)
- Principal component regression (PCR) (1)
- Proton exchange membrane fuel cell (PEMFC) (1)
- Sensor (1)
- Temporal Lobe Epilepsy (1)
- Volatile organic compound (VOC) (1)
Articles 1 - 2 of 2
Full-Text Articles in Biomedical
Multivariate Analysis For The Quantification Of Transdermal Volatile Organic Compounds In Humans By Proton Exchange Membrane Fuel Cell System, Ahmed Hasnain Jalal
Multivariate Analysis For The Quantification Of Transdermal Volatile Organic Compounds In Humans By Proton Exchange Membrane Fuel Cell System, Ahmed Hasnain Jalal
FIU Electronic Theses and Dissertations
In this research, a proton exchange membrane fuel cell (PEMFC) sensor was investigated for specific detection of volatile organic compounds (VOCs) for point-of-care (POC) diagnosis of the physiological conditions of humans. A PEMFC is an electrochemical transducer that converts chemical energy into electrical energy. A Redox reaction takes place at its electrodes whereas the volatile biomolecules (e.g. ethanol) are oxidized at the anode and ambient oxygen is reduced at the cathode. The compounds which were the focus of this investigation were ethanol (C2H5OH) and isoflurane (C3H2ClF5O), but theoretically, the sensor …
Brain Connectivity Networks For The Study Of Nonlinear Dynamics And Phase Synchrony In Epilepsy, Hoda Rajaei
Brain Connectivity Networks For The Study Of Nonlinear Dynamics And Phase Synchrony In Epilepsy, Hoda Rajaei
FIU Electronic Theses and Dissertations
Assessing complex brain activity as a function of the type of epilepsy and in the context of the 3D source of seizure onset remains a critical and challenging endeavor. In this dissertation, we tried to extract the attributes of the epileptic brain by looking at the modular interactions from scalp electroencephalography (EEG). A classification algorithm is proposed for the connectivity-based separation of interictal epileptic EEG from normal. Connectivity patterns of interictal epileptic discharges were investigated in different types of epilepsy, and the relation between patterns and the epileptogenic zone are also explored in focal epilepsy.
A nonlinear recurrence-based method is …