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For research and application of functional near-infrared spectroscopy in neuroscience, appropriate signal analysis method of functional near-infrared spectroscopy is significant. Most of researchers have applied traditional statistical features for feature extraction, and classic machine learning method like support vector machine for further analysis. In this paper, a new feature extraction method...
Passive brain computer interface has provided an efficient method to conduct research about cerebral function and brain neuron activity measurement. And functional near-infrared spectroscopy-based passive brain computer interface research is a developing technique, appropriate pattern classification method may lead further development. In this paper, a new classification method is proposed based on...
Acupoints are the positions that the Qi and blood inject in the bodies. The changes in Qi and Blood of the human body would be shown in the changes of corresponding acupoint, with the changes of electric properties of these acupoints. This paper designs a hardware system based on the acquisition card PCI8335B, Which is mainly composed of AD9833, AD620 and AD8302. To measure the acupoints impedance,...
A novel method is proposed in this paper for the feature extraction of electrocardiogram (ECG). The shape characteristic of the QRS complex has been a diagnostic criterion of cardiac arrhythmia. In other words, geometric property of the QRS complex is a very important kind of feature. Different with other feature extraction algorithms, the proposed method utilizes geometric algebra (GA) to extract...
As an active topic in pattern recognition, the graph spectral is applied in clustering and segmentation. But issues in the analysis to image, especially the texture image, could not been retrieved till now. In this paper, we present a novel texture analysis method, which introduces graph spectral theory into the field of texture image analysis. At first, the image is partitioned into several sub images...
A novel visual combining classifier (VCC), which integrates two-dimensional graphical representation of the attribute data, image processing and pattern recognition techniques together, has been proposed. The basic principle of the VCC is mapping attribute data of a data matrix to the two-dimensional graphs, transforming these graphs to sub classifiers by pixel graphs, and combining the sub classifiers...
A novel feature extraction method based on parallel coordinate plots was presented. Observing the parallel coordinate plots, discovered that using the distance of one point to others on one dimensionality to measurement the classify performance of the variable, can express the fact classify performance more impersonally. The Euclidean distance or module matrix and the relative distance matrix were...
A novel method is proposed in this paper for the feature extraction of electrocardiogram (ECG). Different with other algorithms, the proposed method utilizes independent component analysis (ICA) and wavelet transform to get an ensemble feature composed of ICA-based features and the QRS complex width feature. The QRS complex is the most characteristic waveform of an ECG signal and its width has been...
A novel method for non-statistical PR/dimensionality reduction technology of multivariate information is proposed, which based on graphical techniques, quantitative non-statistical technique, grey system theory, fuzzy system theory, Information entropy theory, neronet technique et al. In nowadays pattern recognition field, statistical pattern recognition techniques are exercising dominion over. But...
A novel method for optimizing the principal component analysis in feature extraction is proposed, which making use of parallel coordinate plot for graphical presentation of multivariate information. In supervised multivariate information classification, before feature extraction on principal component analysis, filtering the variable that has bigger variance and has little effect on classification...
A novel method for optimising the principal component analysis in feature extraction is proposed, which makes use of parallel coordinate plot for graphical presentation of multivariate information. The objectivity and automatization of above manual observation and filtering process is realized by algorithm. In supervised multivariate information classification, before feature extraction on principal...
Moxibustion has been one of the most important therapeutic methods in traditional Chinese medicine for thousands of years. It is meaningful to research on the mechanism of moxibustion and the techniques about how to realize the perfect efficacy with modern engineering technology. In this paper, the authors presented a series of research works on this, including: experiments on the indirect and direct...
This thesis puts forward an intelligent electroacupuncture(EA) technique that imitates traditional chinese medical (TCM) acupuncture technique. In order to solute the difficulty of the fusion between TCM acupuncture technique and engineering technology instruments, the symbolized measurement theory proposed by author has been applied in the imitated approach, which make use of the problem mapping...
We endeavor to provide a novel tool to evaluate environmental comfort level in health smart home (HSH). HSH is regarded a good alternative for the independent life of elders and people with disability. Numerous intelligent devices, installed within a home environment, can provide the resident with continuous monitoring and comfortable environment. In this paper, a novel method of evaluating environmental...
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