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https://www.readbyqxmd.com/read/28227979/dispersion-entropy-for-the-analysis-of-resting-state-meg-regularity-in-alzheimer-s-disease
#1
Hamed Azami, Mostafa Rostaghi, Alberto Fernandez, Javier Escudero, Hamed Azami, Mostafa Rostaghi, Alberto Fernandez, Javier Escudero, Alberto Fernandez, Javier Escudero, Mostafa Rostaghi, Hamed Azami
Alzheimer's disease (AD) is a progressive degenerative brain disorder affecting memory, thinking, behaviour and emotion. It is the most common form of dementia and a big social problem in western societies. The analysis of brain activity may help to diagnose this disease. Changes in entropy methods have been reported useful in research studies to characterize AD. We have recently proposed dispersion entropy (DisEn) as a very fast and powerful tool to quantify the irregularity of time series. The aim of this paper is to evaluate the ability of DisEn, in comparison with fuzzy entropy (FuzEn), sample entropy (SampEn), and permutation entropy (PerEn), to discriminate 36 AD patients from 26 elderly control subjects using resting-state magnetoencephalogram (MEG) signals...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28227788/lessons-learnt-from-a-mooc-about-social-media-for-digital-health-literacy
#2
Suleman Atique, Mowafa Hosueh, Luis Fernandez-Luque, Elia Gabarron, Marian Wan, Onkar Singh, Vicente Traver Salcedo, Yu-Chuan Jack Li, Syed-Abdul Shabbir, Suleman Atique, Mowafa Hosueh, Luis Fernandez-Luque, Elia Gabarron, Marian Wan, Onkar Singh, Vicente Traver Salcedo, Yu-Chuan Jack Li, Syed-Abdul Shabbir, Elia Gabarron, Marian Wan, Mowafa Hosueh, Luis Fernandez-Luque, Onkar Singh, Syed-Abdul Shabbir, Yu-Chuan Jack Li, Vicente Traver Salcedo, Suleman Atique
Nowadays, the Internet and social media represent prime channels for health information seeking and peer support. However, benefits of health social media can be reduced by low digital health literacy. We designed a massive open online course (MOOC) course about health social media to increase the students' digital health literacy. In this course, we wanted to explore the difficulties confronted by the MOOC users in relation to accessing quality online health information and to propose methods to overcome the issues...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28227693/using-bioimpedance-spectroscopy-parameters-as-real-time-feedback-during-tdcs
#3
Isar Nejadgholi, Herschel Caytak, Miodrag Bolic, Isar Nejadgholi, Herschel Caytak, Miodrag Bolic, Isar Nejadgholi, Miodrag Bolic, Herschel Caytak
An exploratory analysis is carried out to investigate the feasibility of using BioImpedance Spectroscopy (BIS) parameters, measured on scalp, as real-time feedback during Transcranial Direct Current Stimulation (tDCS). TDCS is shown to be a potential treatment for neurological disorders. However, this technique is not considered as a reliable clinical treatment, due to the lack of a measurable indicator of treatment efficacy. Although the voltage that is applied on the head is very simple to measure during a tDCS session, changes of voltage are difficult to interpret in terms of variables that affect clinical outcome...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28227640/hardness-map-of-human-meta-tarsals-and-phalanges-of-toes
#4
Irfan Manarvi, Irfan Manarvi, Irfan Manarvi
Predicting location of fracture in human bones has been a keen area of research for the past few decades. A variety of tests for hardness, deformation and strain field measurement have been conducted in the past; but considered insufficient due to various limitations. Researchers therefore have proposed further studies due to inaccuracies in measurement methods, testing machines and experimental errors. Advancement and availability of hardware, measuring instrumentation and testing machines can now provide remedies to these limitations...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28227624/relationship-between-gait-variables-and-domains-of-neurologic-dysfunction-in-multiple-sclerosis-using-six-minute-walk-test
#5
Asma Qureshi, Maite Brandt-Pearce, Myla D Goldman, Asma Qureshi, Maite Brandt-Pearce, Myla D Goldman, Asma Qureshi, Myla D Goldman, Maite Brandt-Pearce
Most multiple sclerosis (MS) patients eventually suffer from mobility impairment, and thus it is critical that walking disability in MS be accurately assessed. The six-minute walk test (6MWT), a reliable MS measure, is traditionally used to determine the distance covered in six minutes using a standard protocol. With the availability of body sensor networks (BSNs), researchers are interested in leveraging BSN data for finding new gait assessment anchors for improved separability performance. Further, current methods for gait assessments are insufficient since assessments are absolute, performed by comparing outcomes to the statistical norms established from diverse patient data despite natural inter-patient variability...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28227565/a-simulation-analysis-of-the-variability-of-the-roving-level-hearing-test
#6
Greg D Watkins, Brett A Swanson, Gregg J Suaning, Greg D Watkins, Brett A Swanson, Gregg J Suaning, Greg D Watkins, Brett A Swanson, Gregg J Suaning
In the study of auditory prostheses, the Speech Recognition Threshold (SRT) is the Signal to Noise Ratio (SNR) at which 50% of words are correctly identified. SRT is typically measured using an adaptive procedure wherein speech is presented at a fixed sound pressure level (SPL) and the noise level is varied according to the subject's responses. A roving level SRT test has been used by researchers with the goal of including the effectiveness of Automatic Gain Control (AGC) systems in SRT measurements. The roving method presents speech at three different SPLs with the level for each sentence chosen pseudo-randomly, while adaptively varying the SNR...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28227551/detecting-slow-eye-movement-for-recognizing-driver-s-sleep-onset-period-with-eeg-features
#7
Yingying Jiao, Bao-Liang Lu, Yingying Jiao, Bao-Liang Lu, Baa-Liang Lu, Yingying Jiao
Slow eye movement (SEM) is reported as a reliable indicator of sleep onset period (SOP) in sleep researches, but its characteristics and functions for detecting driving fatigue have not been fully studied. Through visual observations on ten subjects' experimental data, we found that SEMs tend to occur during eye closure events (ECEs). SEMs accompanied with alpha wave's attenuation during simulated driving was observed in our study. We used box plots to analyze the distribution of durations of different ECEs to measure sleepiness level...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28227408/structural-brain-network-analysis-in-schizophrenia-using-minimum-spanning-tree
#8
Ali Anjomshoa, Mahsa Dolatshahi, Fatemeh Amirkhani, Farzaneh Rahmani, Mehdi M Mirbagheri, Mohammad Hadi Aarabi, Ali Anjomshoa, Mahsa Dolatshahi, Fatemeh Amirkhani, Farzaneh Rahmani, Mehdi M Mirbagheri, Mohammad Hadi Aarabi, Mehdi M Mirbagheri, Mahsa Dolatshahi, Ali Anjomshoa, Farzaneh Rahmani, Fatemeh Amirkhani, Mohammad Hadi Aarabi
Schizophrenia is a mental disorder in which functional and structural brain networks are disrupted. Classical network analysis has been used by many researchers to quantify brain networks and to study the network changes in schizophrenia, but unfortunately metrics used in this classical method highly depend on the networks' density and weight; the comparisons made by this method are biased. The minimum spanning tree (MST) is an alternative method to solve this problem, but its usefulness in studying the schizophrenic brain network has not been examined yet...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28227396/supervised-multimodal-fusion-and-its-application-in-searching-joint-neuromarkers-of-working-memory-deficits-in-schizophrenia
#9
Shile Qi, Vince D Calhoun, Theo G M van Erp, Eswar Damaraju, Juan Bustillo, Yuhui Du, Jessica A Turner, Daniel H Mathalon, Judith M Ford, James Voyvodic, Bryon A Mueller, Aysenil Belger, Sarah Mc Ewen, Steven G Potkin, Adrian Preda, F Birn, Tianzi Jiang, Jing Sui, Shile Qi, Vince D Calhoun, Theo G M van Erp, Eswar Damaraju, Juan Bustillo, Yuhui Du, Jessica A Turner, Daniel H Mathalon, Judith M Ford, James Voyvodic, Bryon A Mueller, Aysenil Belger, Sarah McEwen, Steven G Potkin, Adrian Preda, F Birn, Tianzi Jiang, Jing Sui
Multimodal fusion is an effective approach to better understand brain disease. To date, most current fusion approaches are unsupervised; there is need for a multivariate method that can adopt prior information to guide multimodal fusion. Here we proposed a novel supervised fusion model, called "MCCAR+jICA", which enables both identification of multimodal co-alterations and linking the covarying brain regions with a specific reference signal, e.g., cognitive scores. The proposed method has been validated on both simulated and real human brain data...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28227353/low-resolution-tool-tracking-for-microsurgical-training-in-a-simulated-environment
#10
Antonio Carlos Furtado, Irene Cheng, Eric Fung, Bin Zheng, Anup Basu, Antonio Carlos Furtado, Irene Cheng, Eric Fung, Bin Zheng, Anup Basu, Anup Basu, Eric Fung, Antonio Carlos Furtado, Irene Cheng, Bin Zheng
In this work, we propose a method that detects and tracks the tip of tools used in microsurgical training. This method can be used to provide valuable metrics regarding the surgeon's hand movement. It can benefit the training of surgeons, given the steep learning curve in microsurgery. Unlike past research, our tool tracking algorithm does not rely on color based measurements. Thus, it can be used in a broader domain. Also, our approach is robust to surrounding environments with non-static background, where background subtraction techniques are not suitable...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28227351/video-based-depression-detection-using-local-curvelet-binary-patterns-in-pairwise-orthogonal-planes
#11
Anastasia Pampouchidou, Kostas Marias, Manolis Tsiknakis, Panagiotis Simos, Fan Yang, Guillaume Lemaitre, Fabrice Meriaudeau, Anastasia Pampouchidou, Kostas Marias, Manolis Tsiknakis, Panagiotis Simos, Fan Yang, Guillaume Lemaitre, Fabrice Meriaudeau, Fabrice Meriaudeau, Guillaume Lemaitre, Manolis Tsiknakis, Kostas Marias, Anastasia Pampouchidou, Panagiotis Simos, Fan Yang
Depression is an increasingly prevalent mood disorder. This is the reason why the field of computer-based depression assessment has been gaining the attention of the research community during the past couple of years. The present work proposes two algorithms for depression detection, one Frame-based and the second Video-based, both employing Curvelet transform and Local Binary Patterns. The main advantage of these methods is that they have significantly lower computational requirements, as the extracted features are of very low dimensionality...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28227343/application-of-a-new-robust-ecg-t-wave-delineation-algorithm-for-the-evaluation-of-the-autonomic-innervation-of-the-myocardium
#12
Matteo Cesari, Jesper Mehlsen, Anne-Birgitte Mehlsen, Helge Bjarup Dissing Sorensen, Matteo Cesari, Jesper Mehlsen, Anne-Birgitte Mehlsen, Helge Bjarup Dissing Sorensen, Jesper Mehlsen, Helge Bjarup Dissing Sorensen, Matteo Cesari, Anne-Birgitte Mehlsen
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/28227341/applicability-of-multiresolution-wavelet-analysis-for-qrs-waves-detection
#13
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/28227335/a-noise-assisted-data-analysis-method-for-automatic-eog-based-sleep-stage-classification-using-ensemble-learning
#14
Alexander Neergaard Olesen, Julie A E Christensen, Helge B D Sorensen, Poul J Jennum, Alexander Neergaard Olesen, Julie A E Christensen, Helge B D Sorensen, Poul J Jennum, Julie A E Christensen, Helge B D Sorensen, Alexander Neergaard Olesen, Poul J Jennum
Reducing the number of recording modalities for sleep staging research can benefit both researchers and patients, under the condition that they provide as accurate results as conventional systems. This paper investigates the possibility of exploiting the multisource nature of the electrooculography (EOG) signals by presenting a method for automatic sleep staging using the complete ensemble empirical mode decomposition with adaptive noise algorithm, and a random forest classifier. It achieves a high overall accuracy of 82% and a Cohen's kappa of 0...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28227203/real-time-ultrasound-based-control-of-a-virtual-hand-by-a-trans-radial-amputee
#15
Clayton A Baker, Nima Akhlaghi, Huzefa Rangwala, Jana Kosecka, Siddhartha Sikdar, Clayton A Baker, Nima Akhlaghi, Huzefa Rangwala, Jana Kosecka, Siddhartha Sikdar, Nima Akhlaghi, Siddhartha Sikdar, Clayton A Baker, Jana Kosecka, Huzefa Rangwala
Advancements in multiarticulate upper-limb prosthetics have outpaced the development of intuitive, non-invasive control mechanisms for implementing them. Surface electromyography is currently the most popular non-invasive control method, but presents a number of drawbacks including poor deep-muscle specificity. Previous research established the viability of ultrasound imaging as an alternative means of decoding movement intent, and demonstrated the ability to distinguish between complex grasps in able-bodied subjects via imaging of the anterior forearm musculature...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28227107/a-comparison-of-the-cluster-span-threshold-and-the-union-of-shortest-paths-as-objective-thresholds-of-eeg-functional-connectivity-networks-from-beta-activity-in-alzheimer-s-disease
#16
Keith Smith, Daniel Abasolo, Javier Escudero, Keith Smith, Daniel Abasolo, Javier Escudero, Javier Escudero, Keith Smith, Daniel Abasolo
The Cluster-Span Threshold (CST) is a recently introduced unbiased threshold for functional connectivity networks. This binarisation technique offers a natural trade-off of sparsity and density of information by balancing the ratio of closed to open triples in the network topology. Here we present findings comparing it with the Union of Shortest Paths (USP), another recently proposed objective method. We analyse standard network metrics of binarised networks for sensitivity to clinical Alzheimer's disease in the Beta band of Electroencephalogram activity...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28227089/low-energy-defibrillation-research-using-a-rabbit-ventricular-model-optimizing-the-potential-gradient-distribution-using-multiple-epicardial-electrodes
#17
Jianfei Wang, Lian Jin, Xiaomei Wu, Biao Song, Li Qian, Weiqi Wang, Jianfei Wang, Lian Jin, Xiaomei Wu, Biao Song, Li Qian, Weiqi Wang, Xiaomei Wu, Li Qian, Biao Song, Jianfei Wang, Weiqi Wang, Lian Jin
Cardiac potential gradient distribution directly affects defibrillation efficacy, and the electrode configuration that ensures optimal distribution is yet to be determined. In this study, a rabbit ventricular finite element conductor model containing blood perfusion in ventricular cavities was developed. The electric field was solved on the model by using 95% myocardial volume potential gradient higher than 5 V/cm as the successful defibrillation threshold (DFT). Multiple epicardial electrodes (MEE) protocols and a SCAN protocol were used to identify the optimum defibrillation method...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28227018/using-constrained-information-entropy-to-detect-rare-adverse-drug-reactions-from-medical-forums
#18
Yi Zheng, Chaowang Lan, Hui Peng, Jinyan Li, Yi Zheng, Chaowang Lan, Hui Peng, Jinyan Li, Jinyan Li, Hui Peng, Chaowang Lan, Yi Zheng
Adverse drug reactions (ADRs) detection is critical to avoid malpractices yet challenging due to its uncertainty in pre-marketing review and the underreporting in post-marketing surveillance. To conquer this predicament, social media based ADRs detection methods have been proposed recently. However, existing researches are mostly co-occurrence based methods and face several issues, in particularly, leaving out the rare ADRs and unable to distinguish irrelevant ADRs. In this work, we introduce a constrained information entropy (CIE) method to solve these problems...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28226984/analysis-of-causal-cardio-postural-interaction-under-orthostatic-stress-using-convergent-cross-mapping
#19
Ajay K Verma, Amanmeet Garg, Andrew Blaber, Reza Fazel-Rezai, Kouhyar Tavakolian, Ajay K Verma, Amanmeet Garg, Andrew Blaber, Reza Fazel-Rezai, Kouhyar Tavakolian, Ajay K Verma, Amanmeet Garg, Kouhyar Tavakolian, Reza Fazel-Rezai, Andrew Blaber
Knowledge of a cause-and-effect relationship between different physiological systems is helpful in predicting their performance under perturbations, such as orthostatic challenge. The causal coupling between representative signals of the cardiovascular and postural systems under orthostatic challenge remains unknown. Understanding the causal relationship between these two systems is critical, as their interplay is vital to maintain stable upright posture of the human body during quiet standing. In this research, convergent cross mapping (CCM) method was applied to study the causal relationship between the cardiovascular and postural systems previously shown to have coherent activity during quiet standing...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28226905/passthoughts-authentication-with-low-cost-eareeg
#20
Max T Curran, Jong-Kai Yang, Nick Merrill, John Chuang, Max T Curran, Jong-Kai Yang, Nick Merrill, John Chuang, Jong-Kai Yang, Max T Curran, John Chuang, Nick Merrill
Personal and wearable computing are moving toward smaller and more seamless devices. We explore how this trend could be mirrored in an authentication scheme based on electroencephalography (EEG) signals collected from the ear. We evaluate this model using a low cost, single-channel, consumer grade device for data collection. Using data from 12 study participants who performed a set of 5 mental tasks, we achieve a 44% reduction in half total error rate (HTER) compared with a random classifier, corresponding to a 72% authentication accuracy in within-participants analyses and a 60% reduction and 80% accuracy in between-participant analyses...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
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