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Identifying the technology trends, key patents to be aware of, the key players active in the field, the product areas that are heavily patented or scarcely addressed, and the focus of a company's competitors represent crucial aspects of developing a successful strategic plan, determining a company's freedom to make and sell their product, and focusing future research & product development efforts...
Pesticides are chemicals used to eliminate and/or protect crops from pest infestations. Carbamates and organophosphorus are two of the most common classes of pesticides used worldwide. Although these compounds increase the quantity and quality of the foods, their excessive use could cause health problems for animals and humans. In this work were extracted electrochemical information from seven pesticides,...
Chemical characterization of illicit drugs, like cocaine, is important to provide chemical and physical information to assist police agencies to understand drug trafficking and identify drug origin. In this context, the present work shows the use of an electrochemical sensor containing two working electrodes (pt and GC) to extract voltammetric information about cutting agents added to cocaine (procaine,...
The precondition of productive data mining is having an efficient database to work on. The BioVid Emo DB is a multimodal database recorded for the purpose of analyzing human affective states and data mining related to emotion. Psychophysiological signals such as Skin Conductance Level, Electrocardiogram, Trapezius Electromyogram and also 4 video signals were recorded. 5 discrete emotions (amusement,...
Emotion classification using electroencephalogram (EEG) has been actively researched in many Human-Computer Interaction (HCI) applications such as healthcare, recreation and education. In the last decade, studies in affective Brain-Computer Interfaces (aBCI) have increased especially in the discipline of affective computing. One of the topics is fuzzy classification of human emotions. Fuzzy set theory...
In this paper, a polar coordinate-based touch data extraction (PCTDE) algorithm is proposed to enhance the linearity and accuracy of touch coordinates for large-sized capacitive touch screen panels (TSPs) with a wide electrode pitch. The proposed PCTDE algorithm accurately extracts the touch coordinates by calculating the distance and directional angle between the touch point and the intersection...
In this paper the variability of the Cole-impedance parameters, extracted from magnitude-only measurements using a two-electrode setup are examined. Eight electrodes placed around the centre latitudinal line of an apple are used to collect magnitude measurements from 200 Hz to 1 MHz. Parameters are extracted in MATLAB using a non-linear least squares fitting (NLSF) algorithm, with simulations showing...
After long time cognitive work, most of people confronted with the mental fatigue, which can decrease the classification accuracy of cognitive, or even cause the traffic accidents for drivers. Therefore, the detection of the fatigue state is very essential. The study aims to explore an effective and novel approach based on electroencephalogram. All participants were instructed to implement the spelling...
In the present study a feature selection algorithm based on mutual information (MI) was applied to electro-encephalographic (EEG) data acquired during three different motor imagery tasks from two dataset: Dataset I from BCI Competition IV including full scalp recordings from four subjects, and new data recorded from three subjects using the popular low-cost Emotiv EPOC EEG headset. The aim was to...
Discretization of data has generally been proven to improve the classification accuracy in various data sets. Eye state classification of EEG data holds a lot of importance in the performance of prospective machines like Brain Computer Interfaces that work on EEG data. In this paper we have taken two sample data sets and seen the impact of discretization on classification does not always improve classification...
This paper describes an methodology to detect the end of a triggered horizontal saccade and beginning of gaze fixation in a database of Electrooculography (EOG) data; captured during a target tracking task, designed to generate full horizontal saccades followed by a random interval fixation. This methodology results in generation of accurate assessment of the Saccadic duration, and as such, helps...
This paper proposes a methodology for identifying hot topics and tracking technology trends from the patent domain. The methodology uses frequency information in combination with the International Patent Classification (IPC) to capture semantic information on word categorization, doing so in a way that heretofore has not been employed for topic detection and trend tracking. Term Frequency and Proportional...
This paper describes the secondary research on feature extraction and selection for decoding the brain electroencephalograph (EEG) signals in designing a prosthetic arm, a Brain Computer Interface (BCI) system. It considers EEG pattern recognition using Principal Component Analysis (PCA) for Feature Extraction. The data used for this research is the EEG signal that is recorded during the imagination...
This paper describes the secondary research on feature extraction and selection for decoding the brain electroencephalograph (EEG) signals in designing a prosthetic arm, a Brain Computer Interface (BCI) system. It considers EEG pattern recognition using Principal Component Analysis (PCA) for Feature Extraction. The data used for this research is the EEG signal that is recorded during the imagination...
In our research, classification of music preference based on brain-wave is studied. We assume that there is a clear difference between brain-wave when hearing favorite music and it when hearing disgusting music, and we collect the brain-wave of human while hearing the music. And, there are two methods of collecting: one is separation of favorite/disgusting music clips, and the other is mixing of them...
Alzheimer's Disease (AD) and its preliminary stage - Mild Cognitive Impairment (MCI) - are the most widespread neurodegenerative disorders, and their investigation remains an open challenge. ElectroEncephalography (EEG) appears as a non-invasive and repeatable technique to diagnose brain abnormalities. Despite technical advances, the analysis of EEG spectra is usually carried out by experts that must...
A 65nm CMOS 4.78mm2 integrated neuromodulation SoC consumes 417µW from a 1.2V supply while operating 64 acquisition channels with epoch compression at an average firing rate of 50Hz and engaging two stimulators with a pulse width of 250µs/phase, differential current of 150µA, and a pulse frequency of 100Hz. Compared to the state of the art, this represents the lowest area and power for the highest...
The proposed research focuses on designing a low-cost electromyogram (EMG) data acquisition system (DAQ). The developed system acquires EMG signals from the sub-vocal region and suitable features are extracted using time-frequency transform such as Wavelet Transform. Once the features are extracted, the final classification is carried out using ensemble decision trees called Random Forests (RF). Giving...
Fetal electrocardiogram (fECG) provides clinically important information concerning the electrophysiological state of a fetus. The fECG contains activity of electrical depolarization and repolarization of fetal heart. In this paper a technique is proposed called Fast Independent Component Analysis (Fast ICA) to extract the fECG signals from the 20 sets of abdominal ECG signals. Using Fast ICA, 91...
EEG-fMRI research to study brain function became popular because of the complementarity of the modalities. Through the use of data-driven approaches such as jointICA, sources extracted from EEG can be linked to regions in fMRI. Joint-ICA in its standard formulation however does not allow for the inclusion of multiple EEG electrodes, so it is a rather arbitrary choice which electrode is used in the...
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