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https://www.readbyqxmd.com/read/28227980/motor-imagery-based-brain-computer-interface-using-transform-domain-features
#1
Ahmed M Elbaz, Ahmed T Ahmed, Ayman M Mohamed, Mohamed A Oransa, Khaled S Sayed, Ayman M Eldeib, Ahmed M Elbaz, Ahmed T Ahmed, Ayman M Mohamed, Mohamed A Oransa, Khaled S Sayed, Ayman M Eldeib, Mohamed A Oransa, Khaled S Sayed, Ayman M Mohamed, Ahmed T Ahmed, Ahmed M Elbaz, Ayman M Eldeib
Brain Computer Interface (BCI) is a channel of communication between the human brain and an external device through brain electrical activity. In this paper, we extracted different features to boost the classification accuracy as well as the mutual information of BCI systems. The extracted features include the magnitude of the discrete Fourier transform and the wavelet coefficients for the EEG signals in addition to distance series values and invariant moments calculated for the reconstructed phase space of the EEG measurements...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28227520/cross-frequency-information-transfer-from-eeg-to-emg-in-grasping
#2
Winnie K Y So, Lingling Yang, Beth Jelfs, Qi She, Savio W H Wong, Joseph N Mak, Rosa H M Chan, Winnie K Y So, Lingling Yang, Beth Jelfs, Qi She, Savio W H Wong, Joseph N Mak, Rosa H M Chan, Rosa H M Chan, Beth Jelfs, Savio W H Wong, Lingling Yang, Qi She, Joseph N Mak, Winnie K Y So
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/28227422/a-probabilistic-framework-based-on-slic-superpixel-and-gaussian-processes-for-segmenting-nerves-in-ultrasound-images
#3
Julian Gil Gonzalez, Mauricio A Alvarez, Alvaro A Orozco, Julian Gil Gonzalez, Mauricio A Alvarez, Alvaro A Orozco, Mauricio A Alvarez, Julian Gil Gonzalez, Alvaro A Orozco
We deal with an important problem in the field of anesthesiology known as automatic segmentation of nerve structures depicted in ultrasound images. This is important to aid the experts in anesthesiology, in order to carry out Peripheral Nerve Blocking (PNB). Ultrasound imaging has gained recent interest for performing PNB procedures since it offers a non-invasive visualization of the nerve and the anatomical structures around it. However, the location of these nerves in ultrasound images is a difficult task for the specialist due to the artifacts (i...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28227349/automated-embolic-signal-detection-using-adaptive-gain-control-and-classification-using-anfis
#4
Praotasna Sombune, Phongphan Phienphanich, Sombat Muengtaweepongsa, Anuchit Ruamthanthong, Charturong Tantibundhit, Praotasna Sombune, Phongphan Phienphanich, Sombat Muengtaweepongsa, Anuchit Ruamthanthong, Charturong Tantibundhit, Praotasna Sombune, Charturong Tantibundhit, Phongphan Phienphanich, Sombat Muengtaweepongsa, Anuchit Ruamthanthong
This work proposes an automated system for real-time high-accuracy detection of cerebral embolic signals (ES) to couple with transcranial Doppler ultrasound (TCD) devices in diagnosing a risk of stroke. The algorithm employs Adaptive Gain Control (AGC) approach to capture suspected ESs in real-time. Then, Adaptive Wavelet Packet Transform (AWPT) and Fast Fourier Transform (FFT) are used to extract from them features most efficiently representing ES, which determined by Sequential Feature Selection technique...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28227348/analysis-of-embolic-signals-with-directional-dual-tree-rational-dilation-wavelet-transform
#5
Gorkem Serbes, Nizamettin Aydin, Gorkem Serbes, Nizamettin Aydin, Nizamettin Aydin, Gorkem Serbes
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/28227345/wolff-parkinson-white-wpw-syndrome-the-detection-of-delta-wave-in-an-electrocardiogram-ecg
#6
Hassan Adam Mahamat, Sabir Jacquir, Cliff Khalil, Gabriel Laurent, Stephane Binczak, Hassan Adam Mahamat, Sabir Jacquir, Cliff Khalil, Gabriel Laurent, Stephane Binczak, Stephane Binczak, Sabir Jacquir, Gabriel Laurent, Cliff Khalil
The delta wave remains an important indicator to diagnose the WPW syndrome. In this paper, a new method of detection of delta wave in an ECG signal is proposed. Firstly, using the continuous wavelet transform, the P wave, the QRS complex and the T wave are detected, then their durations are computed after determination of the boundary location (onsets and offsets of the P, QRS and T waves). Secondly, the PR duration, the QRS duration and the upstroke of the QRS complex are used to determine the presence or absence of the delta wave...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28227341/applicability-of-multiresolution-wavelet-analysis-for-qrs-waves-detection
#7
Aleksandr A Fedotov, Anna S Akulova, Sergey A Akulov, Aleksandr A Fedotov, Anna S Akulova, Sergey A Akulov, 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/28227337/prediction-of-the-outcome-in-cardiac-arrest-patients-undergoing-hypothermia-using-eeg-wavelet-entropy
#8
Hana Moshirvaziri, Nima Ramezan-Arab, Shadnaz Asgari, Hana Moshirvaziri, Nima Ramezan-Arab, Shadnaz Asgari, Hana Moshirvaziri, Nima Ramezan-Arab, Shadnaz Asgari
Cardiac arrest (CA) is the leading cause of death in the United States. Induction of hypothermia has been found to improve the functional recovery of CA patients after resuscitation. However, there is no clear guideline for the clinicians yet to determine the prognosis of the CA when patients are treated with hypothermia. The present work aimed at the development of a prognostic marker for the CA patients undergoing hypothermia. A quantitative measure of the complexity of Electroencephalogram (EEG) signals, called wavelet sub-band entropy, was employed to predict the patients' outcomes...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28227329/a-lung-sound-classification-system-based-on-the-rational-dilation-wavelet-transform
#9
Sezer Ulukaya, Gorkem Serbes, Ipek Sen, Yasemin P Kahya, Sezer Ulukaya, Gorkem Serbes, Ipek Sen, Yasemin P Kahya, 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/28227324/analysis-of-the-non-stationarity-of-neural-activity-during-an-auditory-oddball-task-in-schizophrenia
#10
P Nunez, J Poza, J Gomez-Pilar, A Bachiller, C Gomez, A Lubeiro, V Molina, R Hornero, P Nunez, J Poza, J Gomez-Pilar, A Bachiller, C Gomez, A Lubeiro, V Molina, R Hornero, J Gomez-Pilar, A Bachiller, C Gomez, J Poza, P Nunez, 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/28227319/detecting-postural-transitions-a-robust-wavelet-based-approach
#11
Sadra Hemmati, Eric Wade, Sadra Hemmati, Eric Wade, Sadra Hemmati, Eric Wade
The ability to perform postural transitions such as sit-to-stand is an accepted metric for functional independence. The number of transitions performed in real-life situations provides clinically useful information for individuals recovering from lower extremity injury or surgery. Performance deficits during these transitions are well correlated to negative outcomes in numerous populations. Thus, continuous monitoring and detection of transitions in individuals outside of the clinical setting may provide important, clinically relevant information regarding the progression of physical impairments...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28226716/robust-watermarking-in-non-roi-of-medical-images-based-on-dct-dwt
#12
M Jamali, S Samavi, N Karimi, S M R Soroushmehr, K Ward, K Najarian, M Jamali, S Samavi, N Karimi, S M R Soroushmehr, K Ward, K Najarian, K Ward, S M R Soroushmehr, M Jamali, S Samavi, K Najarian, N Karimi
Increasing demand and utilization of telemedicine require transmission of medical information and images over internet. Since authenticity of received images is crucial and patient's information should be included with minimum changes in images, robust watermarking schemes are needed. In this paper, we propose a robust watermark method that embeds patient's information outside the region of interest (ROI) in medical image. In order to find appropriate regions for embedding, we use saliency as a means of measuring importance of regions and find blocks having minimum overlap with the ROI...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28226669/seizure-detection-using-dynamic-warping-for-patients-with-intellectual-disability
#13
Lei Wang, Johan B A M Arends, Xi Long, Yan Wu, Pierre J M Cluitmans, Lei Wang, Johan B A M Arends, Xi Long, Yan Wu, Pierre J M Cluitmans, Yan Wu, Johan B A M Arends, Lei Wang, Pierre J M Cluitmans, Xi Long
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
https://www.readbyqxmd.com/read/28226629/emotion-classification-using-single-channel-scalp-eeg-recording
#14
Amir Jalilifard, Ednaldo Brigante Pizzolato, Md Kafiul Islam, Amir Jalilifard, Ednaldo Brigante Pizzolato, Md Kafiul Islam, Ednaldo Brigante Pizzolato, Amir Jalilifard, Md Kafiul Islam
Several studies have found evidence for corticolimbic Theta electroencephalographic (EEG) oscillation in the neural processing of visual stimuli perceived as fear or threatening scene. Recent studies showed that neural oscillations' patterns in Theta, Alpha, Beta and Gamma sub-bands play a main role in brain's emotional processing. The main goal of this study is to classify two different emotional states by means of EEG data recorded through a single-electrode EEG headset. Nineteen young subjects participated in an EEG experiment while watching a video clip that evoked three emotional states: neutral, relaxation and scary...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28226610/data-driven-estimation-of-blood-pressure-using-photoplethysmographic-signals
#15
Shi Chao Gao, Peter Wittek, Li Zhao, Wen Jun Jiang, Shi Chao Gao, Peter Wittek, Li Zhao, Wen Jun Jiang, Shi Chao Gao, Peter Wittek, Li Zhao, Wen Jun Jiang
Noninvasive measurement of blood pressure by optical methods receives considerable interest, but the complexity of the measurement and the difficulty of adjusting parameters restrict applications. We develop a method for estimating the systolic and diastolic blood pressure using a single-point optical recording of a photoplethysmographic (PPG) signal. The estimation is data-driven, we use automated machine learning algorithms instead of mathematical models. Combining supervised learning with a discrete wavelet transform, the method is insensitive to minor irregularities in the PPG waveform, hence both pulse oximeters and smartphone cameras can record the signal...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28226587/combined-accelerometer-and-emg-analysis-to-differentiate-essential-tremor-from-parkinson-s-disease
#16
Nooshin Haji Ghassemi, Franz Marxreiter, Cristian F Pasluosta, Patrick Kugler, Johannes Schlachetzki, Axel Schramm, Bjoern M Eskofier, Jochen Klucken, Nooshin Haji Ghassemi, Franz Marxreiter, Cristian F Pasluosta, Patrick Kugler, Johannes Schlachetzki, Axel Schramm, Bjoern M Eskofier, Jochen Klucken, Johannes Schlachetzki, Nooshin Haji Ghassemi, Cristian F Pasluosta, Patrick Kugler, Franz Marxreiter, Axel Schramm, Bjoern M Eskofier, Jochen Klucken
In this study, we intended to differentiate patients with essential tremor (ET) from tremor dominant Parkinson disease (PD). Accelerometer and electromyographic signals of hand movement from standardized upper extremity movement tests (resting, holding, carrying weight) were extracted from 13 PD and 11 ET patients. The signals were filtered to remove noise and non-tremor high frequency components. A set of statistical features was then extracted from the discrete wavelet transformation of the signals. Principal component analysis was utilized to reduce dimensionality of the feature space...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28226532/sampling-and-recovery-of-mri-data-using-low-rank-tensor-models
#17
Daniel Banco, Shuchin Aeron, W Scott Hoge, Daniel Banco, Shuchin Aeron, W Scott Hoge, Shuchin Aeron, Daniel Banco, W Scott Hoge
In this paper we investigate the utility of several low-rank models for recovery of Magnetic Resonance Imaging (MRI) data from limited sampling in the k - t space for dynamic imaging. In particular, for 3D temporal (2D space + time) MRI data we employ several tensor factorization techniques and assess the degree of dimensionality reduction, or compressibility, that can be obtained. This algebraic approach is more data adaptive, in contrast to existing compressed sensing (CS) based methods that exploit sparsity in a transform domain, such as wavelets or total variation...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28226529/shearlet-transform-a-good-candidate-for-compressed-sensing-in-optical-coherence-tomography
#18
Lesley-Ann Duflot, Alexandre Krupa, Brahim Tamadazte, Nicolas Andreff, Lesley-Ann Duflot, Alexandre Krupa, Brahim Tamadazte, Nicolas Andreff, Alexandre Krupa, Lesley-Ann Duflot, Brahim Tamadazte, Nicolas Andreff
This paper deals with the development of a fast and smart acquisition technique of Optical Coherence Tomography (OCT) data that has the capability to reconstruct missing data of OCT image. The main objective is to reduce the acquisition time (i.e., increase the frame rate) of an OCT-scan system by choosing a trajectory that covers entirely the image but that does not take all the measurements. The reconstruction of the missing data is achieved by applying an updated Fast Iterative Soft-Thresholding Algorithm (FISTA) on a sparse representation of the image...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28217811/-quantitative-evaluation-of-inhibitory-effects-of-epileptic-spikes-on-theta-rhythms-in-the-network-of-hippocampal-ca3-and-entorhinal-cortex-in-patients-with-temporal-lobe-epilepsy
#19
Man-Ling Ge, Jun-Dan Guo, Sheng-Hua Chen, Ji-Chang Zhang, Xiao-Xuan Fu, Yu-Min Chen
Epileptic spike is an indicator of hyper-excitability and hyper-synchrony in the neural networks. The inhibitory effects of spikes on theta rhythms (4-8 Hz) might be helpful to understand the mechanism of epileptic damage on the cognitive functions. To quantitatively evaluate the inhibitory effects of spikes on theta rhythms, intracerebral electroencephalogram (EEG) recordings with both sporadic spikes (SSs) and spike-free transient period between adjacent spikes were selected in 4 patients in the status of rapid eyes movement (REM) sleep with temporal lobe epilepsy (TLE) under the pre-surgical monitoring...
February 25, 2017: Sheng Li Xue Bao: [Acta Physiologica Sinica]
https://www.readbyqxmd.com/read/28216590/initial-results-from-squid-sensor-analysis-and-modeling-for-the-elf-vlf-atmospheric-noise
#20
Huan Hao, Huali Wang, Liang Chen, Jun Wu, Longqing Qiu, Liangliang Rong
In this paper, the amplitude probability density (APD) of the wideband extremely low frequency (ELF) and very low frequency (VLF) atmospheric noise is studied. The electromagnetic signals from the atmosphere, referred to herein as atmospheric noise, was recorded by a mobile low-temperature superconducting quantum interference device (SQUID) receiver under magnetically unshielded conditions. In order to eliminate the adverse effect brought by the geomagnetic activities and powerline, the measured field data was preprocessed to suppress the baseline wandering and harmonics by symmetric wavelet transform and least square methods firstly...
February 14, 2017: Sensors
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