Chendi Wang

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In this paper, we propose a method to evaluate human's emotion and stress based on heart rate variability (HRV). Firstly, experiment scheme has been designed to induce 4 kinds of emotions and the corresponding electrocardiogram (ECG) changes have been measured in a laboratory setting; Secondly, an improved fast denoising method based on wavelet transform(More)
Cortical parcellation of the human brain typically serves as a basis for higher-level analyses such as connectivity analysis and investigation of brain network properties. Inferences drawn from such analyses can be significantly confounded if the brain parcels are inaccurate. In this paper, we propose a novel affinity matrix structure based on multiple(More)
Functional subnetwork extraction is commonly employed to study the brain’s modular structure. However, reliable extraction from functional magnetic resonance imaging (fMRI) data remains challenging. As representations of brain networks, brain graph estimates are typically noisy due to the pronounced noise in fMRI data. Also, confounds, such as region size(More)
Community detection methods have been widely used for studying the modular structure of the brain. However, few of these methods exploit the intrinsic properties of brain networks other than modularity to tackle the pronounced noise in neuroimaging data. We propose a random walker (RW) based approach that reflects how regions of a brain subnetwork tend to(More)
Bighead carp (Aristichthys nobilis) is one of the most economically and ecologically important fish species widely stocked in lakes or cultured in ponds throughout China. The natural populations are facing the stringent challenges of germplasm resources reduction because of pollution and culture. Thus, developing sufficient molecular markers for the(More)
The biomedical signals are often corrupted by noise in their acquisition or transmission resulting in lower Signal to Noise Ratio (SNR), which brings problematic obstacles to successive biomedical signal processing. So suppressing noise and improving SNR effectively is an essential procedure and key issue in the research on biomedical signal processing. In(More)
Reliable cortical parcellation is a crucial step in human brain network analysis since incorrect definition of nodes may invalidate the inferences drawn from the network. Cortical parcellation is typically cast as an unsupervised clustering problem on functional magnetic resonance imaging (fMRI) data, which is particularly challenging given the pronounced(More)
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