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https://www.readbyqxmd.com/read/28324996/analysis-of-the-non-stationarity-of-neural-activity-during-an-auditory-oddball-task-in-schizophrenia
#1
P Nunez, J Poza, J Gomez-Pilar, A Bachiller, C Gomez, A Lubeiro, V Molina, R Hornero
The aim of this study was to characterize brain dynamics during an auditory oddball task. For this purpose, a measure of the non-stationarity of a given time-frequency representation (TFR) was applied to electroencephalographic (EEG) signals. EEG activity was acquired from 20 schizophrenic (SCH) patients and 20 healthy controls while they underwent a three-stimulus auditory oddball task. The Degree of Stationarity (DS), a measure of the non-stationarity of the TFR, was computed using the continuous wavelet transform...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28316861/complexity-analysis-of-electroencephalogram-dynamics-in-patients-with-parkinson-s-disease
#2
Guotao Liu, Yanping Zhang, Zhenghui Hu, Xiuquan Du, Wanqing Wu, Chenchu Xu, Xiangyang Wang, Shuo Li
In this study, a new combination scheme has been proposed for detecting Parkinson's disease (PD) from electroencephalogram (EEG) signal recorded from normal subjects and PD patients. The scheme is based on discrete wavelet transform (DWT), sample entropy (SampEn), and the three-way decision model in analysis of EEG signal. The EEG signal is noisy and nonstationary, and, as a consequence, it becomes difficult to distinguish it visually. However, the scheme is a well-established methodology in analysis of EEG signal in three stages...
2017: Parkinson's Disease
https://www.readbyqxmd.com/read/28303099/meet-spinky-an-open-source-spindle-and-k-complex-detection-toolbox-validated-on-the-open-access-montreal-archive-of-sleep-studies-mass
#3
Tarek Lajnef, Christian O'Reilly, Etienne Combrisson, Sahbi Chaibi, Jean-Baptiste Eichenlaub, Perrine M Ruby, Pierre-Emmanuel Aguera, Mounir Samet, Abdennaceur Kachouri, Sonia Frenette, Julie Carrier, Karim Jerbi
Sleep spindles and K-complexes are among the most prominent micro-events observed in electroencephalographic (EEG) recordings during sleep. These EEG microstructures are thought to be hallmarks of sleep-related cognitive processes. Although tedious and time-consuming, their identification and quantification is important for sleep studies in both healthy subjects and patients with sleep disorders. Therefore, procedures for automatic detection of spindles and K-complexes could provide valuable assistance to researchers and clinicians in the field...
2017: Frontiers in Neuroinformatics
https://www.readbyqxmd.com/read/28301356/local-heating-test-for-detection-of-microcirculation-abnormalities-in-patients-with-diabetes-related-foot-complications
#4
Aleksey Parshakov, Nadezhda Zubareva, Sergey Podtaev, Peter Frick
OBJECTIVE: In this study, authors used a wavelet analysis of skin temperature (WAST) to assess the mechanisms of microvascular tone regulation during the local heating test in patients with diabetic foot syndrome (DFS). PARTICIPANTS: The participants included control subjects and 36 hospitalized patients with DFS between 52 and 79 years old (68 ± 8 years old). They were distributed among 5 groups: 15 control subjects, 8 patients with DFS who did not develop ulcerative or necrotic disorders, 10 patients who developed the neuroischemic form of DFS complicated by foot ulceration, 12 patients with DFS complicated by toe necrosis, and 6 patients with DFS and foot gangrene...
April 2017: Advances in Skin & Wound Care
https://www.readbyqxmd.com/read/28298702/fixed-versus-mixed-rsa-%C3%A2-explaining-visual-representations-by-fixed-and-mixed-feature-sets-from-shallow-and-deep-computational-models
#5
Seyed-Mahdi Khaligh-Razavi, Linda Henriksson, Kendrick Kay, Nikolaus Kriegeskorte
Studies of the primate visual system have begun to test a wide range of complex computational object-vision models. Realistic models have many parameters, which in practice cannot be fitted using the limited amounts of brain-activity data typically available. Task performance optimization (e.g. using backpropagation to train neural networks) provides major constraints for fitting parameters and discovering nonlinear representational features appropriate for the task (e.g. object classification). Model representations can be compared to brain representations in terms of the representational dissimilarities they predict for an image set...
February 2017: Journal of Mathematical Psychology
https://www.readbyqxmd.com/read/28298182/electrocardiogram-his-bundle-potentials-can-be-recorded-noninvasively-beat-by-beat-on-surface-electrocardiogram
#6
Gaopin Wang, Renguang Liu, Qinghua Chang, Zhaolong Xu, Yingjie Zhang, Dianzhu Pan
BACKGROUND: The micro waveform of His bundle potential can't be recorded beat-to-beat on surface electrocardiogram yet. We have found that the micro-wavelets before QRS complex may be related to atrioventricular conduction system potentials. This study is to explore the possibility of His bundle potential can be noninvasively recorded on surface electrocardiogram. METHODS: We randomized 65 patients undergoing radiofrequency catheter ablation of paroxysmal superventricular tachycardia (exclude overt Wolff-Parkinson-White syndrome) to receive "conventional electrocardiogram" and "new electrocardiogram" before the procedure...
March 15, 2017: BMC Cardiovascular Disorders
https://www.readbyqxmd.com/read/28284000/a-method-for-microcalcifications-detection-in-breast-mammograms
#7
Abbas H Hassin Alasadi, Ahmed Kadem Hamed Al-Saedi
Breast cancer is the most cause of death for women above age 40 around the world. In this paper, we propose a method to detect microcalcifications in digital mammography images using two-dimensional Discrete Wavelets Transform and image enhancement techniques for removing noise as well as to get a better contrast. The initial step is applying a preprocessing techniques to improve the edge of the breast and then segmentation process (Region of interest) for eliminating some regions in the image, which are not useful for the mammography interpretation...
April 2017: Journal of Medical Systems
https://www.readbyqxmd.com/read/28278203/a-high-performance-seizure-detection-algorithm-based-on-discrete-wavelet-transform-dwt-and-eeg
#8
Duo Chen, Suiren Wan, Jing Xiang, Forrest Sheng Bao
In the past decade, Discrete Wavelet Transform (DWT), a powerful time-frequency tool, has been widely used in computer-aided signal analysis of epileptic electroencephalography (EEG), such as the detection of seizures. One of the important hurdles in the applications of DWT is the settings of DWT, which are chosen empirically or arbitrarily in previous works. The objective of this study aimed to develop a framework for automatically searching the optimal DWT settings to improve accuracy and to reduce computational cost of seizure detection...
2017: PloS One
https://www.readbyqxmd.com/read/28278031/forecasting-of-pm10-time-series-using-wavelet-analysis-and-wavelet-arma-model-in-taiyuan-china
#9
Hong Zhang, Sheng Zhang, Ping Wang, Yuzhe Qin, Huifeng Wang
PM10 forecasting is difficult because of the uncertainties in describing the emission and meteorological fields. This paper proposed a wavelet-ARMA/ARIMA model to forecast the short-time series of the PM10 concentrations. It was evaluated by experiments using a 10-year dataset of daily PM10 concentrations from 4 stations located in Taiyuan, China. The results indicated the following: 1) PM10 concentrations of Taiyuan had a decreasing trend during 2005 to 2012 but it was increased in 2013. PM10 concentrations had an obvious seasonal fluctuation related with coal fired heating in winter and early spring...
February 23, 2017: Journal of the Air & Waste Management Association
https://www.readbyqxmd.com/read/28273079/climate-variability-animal-reservoir-and-transmission-of-scrub-typhus-in-southern-china
#10
Yuehong Wei, Yong Huang, Xiaoning Li, Yu Ma, Xia Tao, Xinwei Wu, Zhicong Yang
OBJECTIVES: We aimed to evaluate the relationships between climate variability, animal reservoirs and scrub typhus incidence in Southern China. METHODS: We obtained data on scrub typhus cases in Guangzhou every month from 2006 to 2014 from the Chinese communicable disease network. Time-series Poisson regression models and distributed lag nonlinear models (DLNM) were used to evaluate the relationship between risk factors and scrub typhus. RESULTS: Wavelet analysis found the incidence of scrub typhus cycled with a period of approximately 8-12 months and long-term trends with a period of approximately 24-36 months...
March 2017: PLoS Neglected Tropical Diseases
https://www.readbyqxmd.com/read/28272020/a-stationary-wavelet-transform-and-a-time-frequency-based-spike-detection-algorithm-for-extracellular-recorded-data
#11
Florian Lieb, Hans-Georg Stark, Christiane Thielemann
OBJECTIVE Spike detection from extracellular recordings is a crucial preprocessing step when analyzing neuronal activity. The decision whether a specific part of the signal is a spike or not is important for any kind of other subsequent preprocessing steps, like spike sorting or burst detection in order to reduce the classification of erroneously identified spikes. Many spike detection algorithms have already been suggested, all working reasonably well whenever the signal-to-noise ratio is large enough. When the noise level is high, however, these algorithms have a poor performance...
March 8, 2017: Journal of Neural Engineering
https://www.readbyqxmd.com/read/28269816/automatic-epileptic-seizure-detection-in-eegs-using-mf-dfa-svm-based-on-cloud-computing
#12
Zhongnan Zhang, Tingxi Wen, Wei Huang, Meihong Wang, Chunfeng Li
BACKGROUND: Epilepsy is a chronic disease with transient brain dysfunction that results from the sudden abnormal discharge of neurons in the brain. Since electroencephalogram (EEG) is a harmless and noninvasive detection method, it plays an important role in the detection of neurological diseases. However, the process of analyzing EEG to detect neurological diseases is often difficult because the brain electrical signals are random, non-stationary and nonlinear. OBJECTIVE: In order to overcome such difficulty, this study aims to develop a new computer-aided scheme for automatic epileptic seizure detection in EEGs based on multi-fractal detrended fluctuation analysis (MF-DFA) and support vector machine (SVM)...
March 3, 2017: Journal of X-ray Science and Technology
https://www.readbyqxmd.com/read/28269284/cross-frequency-information-transfer-from-eeg-to-emg-in-grasping
#13
Winnie K Y So, Lingling Yang, Beth Jelfs, Qi She, Savio W H Wong, Joseph N Mak, Rosa H M Chan
This paper presents an investigation into the cortico-muscular relationship during a grasping task by evaluating the information transfer between EEG and EMG signals. Information transfer was computed via a non-linear model-free measure, transfer entropy (TE). To examine the cross-frequency interaction, TEs were computed after the times series were decomposed into various frequency ranges via wavelet transform. Our results demonstrate the capability of TE to capture the direct interaction between EEG and EMG...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28269134/3d-gabor-wavelet-based-vessel-filtering-of-photoacoustic-images
#14
Israr Ul Haq, Ryo Nagoaka, Takahiro Makino, Takuya Tabata, Yoshifumi Saijo
Filtering and segmentation of vasculature is an important issue in medical imaging. The visualization of vasculature is crucial for the early diagnosis and therapy in numerous medical applications. This paper investigates the use of Gabor wavelet to enhance the effect of vasculature while eliminating the noise due to size, sensitivity and aperture of the detector in 3D Optical Resolution Photoacoustic Microscopy (OR-PAM). A detailed multi-scale analysis of wavelet filtering and Hessian based method is analyzed for extracting vessels of different sizes since the blood vessels usually vary with in a range of radii...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28269119/analysis-of-embolic-signals-with-directional-dual-tree-rational-dilation-wavelet-transform
#15
Gorkem Serbes, Nizamettin Aydin
The dyadic discrete wavelet transform (dyadic-DWT), which is based on fixed integer sampling factor, has been used before for processing piecewise smooth biomedical signals. However, the dyadic-DWT has poor frequency resolution due to the low-oscillatory nature of its wavelet bases and therefore, it is less effective in processing embolic signals (ESs). To process ESs more effectively, a wavelet transform having better frequency resolution than the dyadic-DWT is needed. Therefore, in this study two ESs, containing micro-emboli and artifact waveforms, are analyzed with the Directional Dual Tree Rational-Dilation Wavelet Transform (DDT-RADWT)...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28269114/application-of-a-new-robust-ecg-t-wave-delineation-algorithm-for-the-evaluation-of-the-autonomic-innervation-of-the-myocardium
#16
Matteo Cesari, Jesper Mehlsen, Anne-Birgitte Mehlsen, Helge Bjarup Dissing Sorensen
T-wave amplitude (TWA) is a well know index of the autonomic innervation of the myocardium. However, until now it has been evaluated only manually or with simple and inefficient algorithms. In this paper, we developed a new robust single-lead electrocardiogram (ECG) T-wave delineation algorithm that is able to detect the T-wave with a wavelet based method and automatically calculate the TWA. We evaluated the algorithm on the QT database, achieving a sensitivity of 99.92% for the T wave peak and 99.38% for the T wave end...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28269112/applicability-of-multiresolution-wavelet-analysis-for-qrs-waves-detection
#17
Aleksandr A Fedotov, Anna S Akulova, Sergey A Akulov
The aim of this study is to create highly effective QRS-detector of electrocardiographic (ECG) signal based on the multiresolution wavelet analysis, set of nonlinear transforms and adaptive thresholding. The efficiency of various QRS-waves detectors for processing model ECG signals contaminated by artificially simulated intensive noise and artifacts was researched. The performance of the proposed method as well as some other well-known algorithms for QRS-waves detection was further verified for clinical ECG recordings from the Physionet MIT-BIH Arrhythmia database...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28269104/a-lung-sound-classification-system-based-on-the-rational-dilation-wavelet-transform
#18
Sezer Ulukaya, Gorkem Serbes, Ipek Sen, Yasemin P Kahya
In this work, a wavelet based classification system that aims to discriminate crackle, normal and wheeze lung sounds is presented. While the previous works related with this problem use constant low Q-factor wavelets, which have limited frequency resolution and can not cope with oscillatory signals, in the proposed system, the Rational Dilation Wavelet Transform, whose Q-factors can be tuned, is employed. Proposed system yields an accuracy of 95 % for crackle, 97 % for wheeze, 93.50 % for normal and 95.17 % for total sound signal types using energy feature subset and proposed approach is superior to conventional low Q-factor wavelet analysis...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28269101/detection-of-binaural-interaction-in-free-field-evoked-auditory-brainstem-responses-by-time-scale-representations
#19
Erik Schebsdat, Horst Hessel, Harald Seidler, Daniel J Strauss
The so called β-wave of the binaural interaction component (BIC) in auditory brainstem responses (ABR) has been shown to be an objective measure for binaural interaction (BI). This component is the arithmetical difference between the sum of the monaurally evoked ABRs and the binaurally evoked ABR. Unfortunately, these neural responses are known to be very fragile and as a result the calculated BIC. An additional issue is, that the findings of this measurement are predominantly needed in people with hearing loss who may use hearing devices like hearing aids (HA) or cochlear implants (CI), thus they are not able to use headphones (like in conventional ABR measurements) during the detection of possible BI...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28268495/seizure-detection-using-dynamic-warping-for-patients-with-intellectual-disability
#20
Lei Wang, Johan B A M Arends, Xi Long, Yan Wu, Pierre J M Cluitmans
Electroencephalography (EEG) is paramount for both retrospective analysis and real-time monitoring of epileptic seizures. Studies have shown that EEG-based seizure detection is very difficult for a specific epileptic population with intellectual disability due to the cerebral development disorders. In this work, a seizure detection method based on dynamic warping (DW) is proposed for patients with intellectual disability. It uses an EEG template of an individual subject's dominant seizure type, to extract the morphological features from EEG signals...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
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