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https://www.readbyqxmd.com/read/28723960/a-validation-of-11-body-condition-indices-in-a-giant-snake-species-that-exhibits-positive-allometry
#1
Bryan G Falk, Ray W Snow, Robert N Reed
Body condition is a gauge of the energy stores of an animal, and though it has important implications for fitness, survival, competition, and disease, it is difficult to measure directly. Instead, body condition is frequently estimated as a body condition index (BCI) using length and mass measurements. A desirable BCI should accurately reflect true body condition and be unbiased with respect to size (i.e., mean BCI estimates should not change across different length or mass ranges), and choosing the most-appropriate BCI is not straightforward...
2017: PloS One
https://www.readbyqxmd.com/read/28722127/contrasting-outcomes-of-species-and-community-level-analyses-of-the-temporal-consistency-of-functional-composition
#2
Masatoshi Katabuchi, S Joseph Wright, Nathan G Swenson, Kenneth J Feeley, Richard Condit, Stephen P Hubbell, Stuart J Davies
Multiple anthropogenic drivers affect every natural community, and there is broad interest in using functional traits to understand and predict the consequences for future biodiversity. There is, however, no consensus regarding the choice of analytical methods. We contrast species- and community-level analyses of change in the functional composition for four traits related to drought tolerance using three decades of repeat censuses of trees in the 50-ha Forest Dynamics Plot on Barro Colorado Island (BCI), Panama...
July 19, 2017: Ecology
https://www.readbyqxmd.com/read/28718781/latent-variable-method-for-automatic-adaptation-to-background-states-in-motor-imagery-bci
#3
Nikolay Dagaev, Ksenia Volkova, Alexei Ossadtchi
<i>Objective</i>. Brain-computer interface (BCI) systems are known to be vulnerable to variabilities in background states of a user. Usually, no detailed information on these states is available even during the training stage. Thus there is a need in a method which is capable of taking background states into account in an unsupervised way. <i>Approach</i>. We propose a latent variable method that is based on a probabilistic model with a discrete latent variable. In order to estimate the model's parameters, we suggest to use the expectation maximization (EM) algorithm...
July 18, 2017: Journal of Neural Engineering
https://www.readbyqxmd.com/read/28713233/the-role-of-the-interplay-between-stimulus-type-and-timing-in-explaining-bci-illiteracy-for-visual-p300-based-brain-computer-interfaces
#4
Roberta Carabalona
Visual P300-based Brain-Computer Interface (BCI) spellers enable communication or interaction with the environment by flashing elements in a matrix and exploiting consequent changes in end-user's brain activity. Despite research efforts, performance variability and BCI-illiteracy still are critical issues for real world applications. Moreover, there is a quite unaddressed kind of BCI-illiteracy, which becomes apparent when the same end-user operates BCI-spellers intended for different applications: our aim is to understand why some well performers can become BCI-illiterate depending on speller type...
2017: Frontiers in Neuroscience
https://www.readbyqxmd.com/read/28713232/detection-of-movement-related-cortical-potentials-from-eeg-using-constrained-ica-for-brain-computer-interface-applications
#5
Fatemeh Karimi, Jonathan Kofman, Natalie Mrachacz-Kersting, Dario Farina, Ning Jiang
The movement related cortical potential (MRCP), a slow cortical potential from the scalp electroencephalogram (EEG), has been used in real-time brain-computer-interface (BCI) systems designed for neurorehabilitation. Detecting MPCPs in real time with high accuracy and low latency is essential in these applications. In this study, we propose a new MRCP detection method based on constrained independent component analysis (cICA). The method was tested for MRCP detection during executed and imagined ankle dorsiflexion of 24 healthy participants, and compared with four commonly used spatial filters for MRCP detection in an offline experiment...
2017: Frontiers in Neuroscience
https://www.readbyqxmd.com/read/28711988/emotion-recognition-based-on-eeg-features-in-movie-clips-with-channel-selection
#6
Mehmet Siraç Özerdem, Hasan Polat
Emotion plays an important role in human interaction. People can explain their emotions in terms of word, voice intonation, facial expression, and body language. However, brain-computer interface (BCI) systems have not reached the desired level to interpret emotions. Automatic emotion recognition based on BCI systems has been a topic of great research in the last few decades. Electroencephalogram (EEG) signals are one of the most crucial resources for these systems. The main advantage of using EEG signals is that it reflects real emotion and can easily be processed by computer systems...
July 15, 2017: Brain Informatics
https://www.readbyqxmd.com/read/28709110/a-full-bayesian-approach-to-appraise-the-safety-effects-of-pedestrian-countdown-signals-to-drivers
#7
Angela E Kitali, P E Thobias Sando
Although they are meant for pedestrians, pedestrian countdown signals (PCSs) give cues to drivers about the length of the remaining green phase, hence affecting drivers' behavior at intersections. This study focuses on the evaluation of the safety effectiveness of PCSs to drivers, in the cities of Jacksonville and Gainesville, Florida, using crash modification factors (CMFs) and crash modification functions (CMFunctions). A full Bayes (FB) before-and-after with comparison group method was used to quantify the safety impacts of PCSs to drivers...
July 11, 2017: Accident; Analysis and Prevention
https://www.readbyqxmd.com/read/28708963/a-qualitative-study-adopting-a-user-centered-approach-to-design-and-validate-a-brain-computer-interface-for-cognitive-rehabilitation-for-people-with-brain-injury
#8
Suzanne Martin, Elaine Armstrong, Eileen Thomson, Eloisa Vargiu, Marc Solà, Stefan Dauwalder, Felip Miralles, Jean Daly Lynn
Cognitive rehabilitation is established as a core intervention within rehabilitation programs following a traumatic brain injury (TBI). Digitally enabled assistive technologies offer opportunities for clinicians to increase remote access to rehabilitation supporting transition into home. Brain Computer Interface (BCI) systems can harness the residual abilities of individuals with limited function to gain control over computers through their brain waves. This paper presents an online cognitive rehabilitation application developed with therapists, to work remotely with people who have TBI, who will use BCI at home to engage in the therapy...
July 14, 2017: Assistive Technology: the Official Journal of RESNA
https://www.readbyqxmd.com/read/28705577/comparative-evaluation-of-bladder-specific-health-related-quality-of-life-hrqol-instruments-for-bladder-cancer
#9
T J Moncrief, P Balaji, B Lindgren, C J Weight, B R Konety
OBJECTIVE: To compare two bladder cancer specific health related quality of life instruments (HRQOL) in the same patient population. Previous HRQOL studies in cystectomy patients have yielded conflicting results. Using a cross sectional study design we examined the only two validated Bladder Cancer Specific (HRQOL) measures. METHODS: Of the 256 patients who had undergone (RC) from 2009-2014, 131 met both inclusion and exclusion criteria. The Functional Assessment Cancer Therapy-Vanderbilt Cystectomy Index (FACT-VCI) and Bladder Cancer Index (BCI) were mailed to these patients...
July 10, 2017: Urology
https://www.readbyqxmd.com/read/28701939/behavioral-and-cortical-effects-during-attention-driven-brain-computer-interface-operations-in-spatial-neglect-a-feasibility-case-study
#10
Luca Tonin, Marco Pitteri, Robert Leeb, Huaijian Zhang, Emanuele Menegatti, Francesco Piccione, José Del R Millán
During the last years, several studies have suggested that Brain-Computer Interface (BCI) can play a critical role in the field of motor rehabilitation. In this case report, we aim to investigate the feasibility of a covert visuospatial attention (CVSA) driven BCI in three patients with left spatial neglect (SN). We hypothesize that such a BCI is able to detect attention task-specific brain patterns in SN patients and can induce significant changes in their abnormal cortical activity (α-power modulation, feature recruitment, and connectivity)...
2017: Frontiers in Human Neuroscience
https://www.readbyqxmd.com/read/28696536/an-emergency-call-system-for-patients-in-locked-in-state-using-an-ssvep-based-brain-switch
#11
Jeong-Hwan Lim, Yong-Wook Kim, Jun-Hak Lee, Kwang-Ok An, Han-Jeong Hwang, Ho-Seung Cha, Chang-Hee Han, Chang-Hwan Im
Patients in a locked-in state (LIS) due to severe neurological disorders such as amyotrophic lateral sclerosis (ALS) require seamless emergency care by their caregivers or guardians. However, it is a difficult job for the guardians to continuously monitor the patients' state, especially when direct communication is not possible. In the present study, we developed an emergency call system for such patients using a steady-state visual evoked potential (SSVEP)-based brain switch. Although there have been previous studies to implement SSVEP-based brain switch system, they have not been applied to patients in LIS, and thus their clinical value has not been validated...
July 11, 2017: Psychophysiology
https://www.readbyqxmd.com/read/28693110/potential-effects-of-brevetoxins-and-toxic-elements-on-various-health-variables-in-kemp-s-ridley-lepidochelys-kempii-and-green-chelonia-mydas-sea-turtles-after-a-red-tide-bloom-event
#12
Justin R Perrault, Nicole I Stacy, Andreas F Lehner, Cody R Mott, Sarah Hirsch, Jonathan C Gorham, John P Buchweitz, Michael J Bresette, Catherine J Walsh
Natural biotoxins and anthropogenic toxicants pose a significant risk to sea turtle health. Documented effects of contaminants include potential disease progression and adverse impacts on development, immune function, and survival in these imperiled species. The shallow seagrass habitats of Florida's northwest coast (Big Bend) serve as an important developmental habitat for Kemp's ridley (Lepidochelys kempii) and green (Chelonia mydas) sea turtles; however, few studies have been conducted in this area. Our objectives were (1) to evaluate plasma analytes (mass, minimum straight carapace length, body condition index [BCI], fibropapilloma tumor score, lysozyme, superoxide dismutase, reactive oxygen/nitrogen species, plasma protein electrophoresis, cholesterol, and total solids) in Kemp's ridleys and green turtles and their correlation to brevetoxins that were released from a red tide bloom event from July-October 2014 in the Gulf of Mexico near Florida's Big Bend, and (2) to analyze red blood cells in Kemp's ridleys and green turtles for toxic elements (arsenic, cadmium, lead, mercury, selenium, thallium) with correlation to the measured plasma analytes...
July 6, 2017: Science of the Total Environment
https://www.readbyqxmd.com/read/28692997/automated-classification-and-removal-of-eeg-artifacts-with-svm-and-wavelet-ica
#13
Chong Yeh Sai, Norrima Mokhtar, Hamzah Arof, Paul Cumming, Masahiro Iwahashi
Brain electrical activity recordings by electroencephalography (EEG) are often contaminated with signal artifacts. Procedures for automated removal of EEG artifacts are frequently sought for clinical diagnostics and brain computer interface (BCI) applications. In recent years, a combination of independent component analysis (ICA) and discrete wavelet transform (DWT) has been introduced as standard technique for EEG artifact removal. However, in performing the wavelet-ICA procedure, visual inspection or arbitrary thresholding may be required for identifying artifactual components in the EEG signal...
July 4, 2017: IEEE Journal of Biomedical and Health Informatics
https://www.readbyqxmd.com/read/28692996/effectiveness-evaluation-of-real-time-scalp-signal-separating-algorithm-on-near-infrared-spectroscopy-neurofeedback
#14
Wei Chun Ung, Tsukasa Funane, Takushige Katura, Hiroki Sato, Tong Boon Tang, Ahmad Fadzil Mohammad Hani, Masashi Kiguchi
Near-infrared spectroscopy (NIRS), one of the candidates to be used in a neurofeedback system or brain-computer interface (BCI), measures the brain activity by monitoring the changes in cerebral hemoglobin concentration. However, hemodynamic changes in the scalp may affect the NIRS signals. In order to remove the superficial signals when NIRS is used in a neurofeedback system or BCI, real-time processing is necessary. Real-time scalp signal separating (RT-SSS) algorithm, which is capable of separating the scalp-blood signals from NIRS signals obtained in real-time, may thus be applied...
July 4, 2017: IEEE Journal of Biomedical and Health Informatics
https://www.readbyqxmd.com/read/28690497/high-amplitude-eeg-motor-potential-during-repetitive-foot-movement-possible-use-and-challenges-for-futuristic-bcis-that-restore-mobility-after-spinal-cord-injury
#15
Aljoscha Thomschewski, Yvonne Höller, Peter Höller, Stefan Leis, Eugen Trinka
Recent advances in neuroprostheses provide us with promising ideas of how to improve the quality of life in people suffering from impaired motor functioning of upper and lower limbs. Especially for patients after spinal cord injury (SCI), futuristic devices that are controlled by thought via brain-computer interfaces (BCIs) might be of tremendous help in managing daily tasks and restoring at least some mobility. However, there are certain problems arising when trying to implement BCI technology especially in such a heterogenous patient group...
2017: Frontiers in Neuroscience
https://www.readbyqxmd.com/read/28688489/a-pca-aided-cross-covariance-scheme-for-discriminative-feature-extraction-from-eeg-signals
#16
Roozbeh Zarei, Jing He, Siuly Siuly, Yanchun Zhang
BACKGROUND AND OBJECTIVES: Feature extraction of EEG signals plays a significant role in Brain-computer interface (BCI) as it can significantly affect the performance and the computational time of the system. The main aim of the current work is to introduce an innovative algorithm for acquiring reliable discriminating features from EEG signals to improve classification performances and to reduce the time complexity. METHODS: This study develops a robust feature extraction method combining the principal component analysis (PCA) and the cross-covariance technique (CCOV) for the extraction of discriminatory information from the mental states based on EEG signals in BCI applications...
July 2017: Computer Methods and Programs in Biomedicine
https://www.readbyqxmd.com/read/28685918/a-long-term-bci-study-with-ecog-recordings-in-freely-moving-rats
#17
Thomas Costecalde, Tetiana Aksenova, Napoleon Torres-Martinez, Andriy Eliseyev, Corinne Mestais, Cecile Moro, Alim Louis Benabid
BACKGROUND: Brain Computer Interface (BCI) studies are performed in an increasing number of applications. Questions are raised about electrodes, data processing and effectors. Experiments are needed to solve these issues. OBJECTIVE: To develop a simple BCI set-up to easier studies for improving the mathematical tools to process the ECoG to control an effector. METHOD: We designed a simple BCI using transcranial electrodes (17 screws, three mechanically linked to create a common reference, 14 used as recording electrodes) to record Electro-Cortico-Graphic (ECoG) neuronal activities in rodents...
July 6, 2017: Neuromodulation: Journal of the International Neuromodulation Society
https://www.readbyqxmd.com/read/28683745/topographical-measures-of-functional-connectivity-as-biomarkers-for-post-stroke-motor-recovery
#18
Gavin R Philips, Janis J Daly, José C Príncipe
BACKGROUND: Biomarkers derived from neural activity of the brain present a vital tool for the prediction and evaluation of post-stroke motor recovery, as well as for real-time biofeedback opportunities. METHODS: In order to encapsulate recovery-related reorganization of brain networks into such biomarkers, we have utilized the generalized measure of association (GMA) and graph analyses, which include global and local efficiency, as well as hemispheric interdensity and intradensity...
July 6, 2017: Journal of Neuroengineering and Rehabilitation
https://www.readbyqxmd.com/read/28682260/is-implicit-motor-imagery-a-reliable-strategy-for-a-brain-computer-interface
#19
Bethel A Osuagwu, Magdalena Zych, Aleksandra Vuckovic
Explicit motor imagery (eMI) is a widely used brain computer interface (BCI) paradigm, but not everybody can accomplish this task. Here we propose a BCI based on implicit motor imagery (iMI). We compared classification accuracy between eMI and iMI of hands. Fifteen able bodied people were asked to judge the laterality of hand images presented on a computer screen in a lateral or medial orientation. This judgement task is known to require mental rotation of a person's own hands which in turn is thought to involve iMI...
June 29, 2017: IEEE Transactions on Neural Systems and Rehabilitation Engineering
https://www.readbyqxmd.com/read/28676734/fuzzy-decision-making-fuser-fdmf-for-integrating-human-machine-autonomous-hma-systems-with-adaptive-evidence-sources
#20
Yu-Ting Liu, Nikhil R Pal, Amar R Marathe, Yu-Kai Wang, Chin-Teng Lin
A brain-computer interface (BCI) creates a direct communication pathway between the human brain and an external device or system. In contrast to patient-oriented BCIs, which are intended to restore inoperative or malfunctioning aspects of the nervous system, a growing number of BCI studies focus on designing auxiliary systems that are intended for everyday use. The goal of building these BCIs is to provide capabilities that augment existing intact physical and mental capabilities. However, a key challenge to BCI research is human variability; factors such as fatigue, inattention, and stress vary both across different individuals and for the same individual over time...
2017: Frontiers in Neuroscience
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