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(BCI)
4,443 results
  • C-reactive protein and ART outcomes: a systematic review. [Journal Article]
    Hum Reprod Update. 2020 May 29 [Online ahead of print]Brouillet S, Boursier G, … Hamamah S
  • A dynamic balance between pro- and anti-inflammatory factors contributes to regulating human female reproduction. Chronic low-grade inflammation has been detected in several female reproductive conditions, from anovulation to embryo implantation failure. C-reactive protein (CRP) is a reliable marker of inflammation that is extensively used in clinical practice. Recent studies quantified CRP in th…
  • Extended endocrine therapy in premenopausal breast cancer patients: Where are we now? [Journal Article]
    Breast J. 2020 May 29 [Online ahead of print]Villasco A, D'Alonzo M
  • Approximately 25% of new breast cancers are diagnosed in premenopausal patients, 50%-70% presenting as estrogen receptor-positive (ER+) breast tumors. Five-year adjuvant endocrine therapy (ET) with Tamoxifen is the cornerstone treatment for those patients but the evidence that up to 50% of ER + breast cancer distant recurrences develop after this time has now raised some questions. ATLAS and aTTo…
  • Cognitive Enhancement and Brain-Computer Interfaces: Potential Boundaries and Risks. [Journal Article]
    Adv Exp Med Biol. 2020; 1194:275-283.Kaimara P, Plerou A, Deliyannis I
  • Electroencephalography (EEG) systems and brain-computer interfaces (BCIs) are terms frequently involved in the field of neurological research. Under a technological point of view, BCI is considered to be a significant achievement within the frame of learning disabilities rehabilitation. Nevertheless, the specifications for efficient use for cognitive enhancement and its potential boundaries are u…
  • The performance of a low-cost bio-amplifier on 3D human arm movement reconstruction. [Journal Article]
    Biomed Tech (Berl). 2020 May 28 [Online ahead of print]Ayodele KP, Akinboboye EA, Komolafe MA
  • Objectives In this study, the performance of OpenBCI, a low-cost bio-amplifier, is assessed when used for 3D motion reconstruction. Methods Eleven scalp electrode locations from three subjects were used, with sampling rate of 125 Hz, subsequently band-pass filtered from 0.5 to 40 Hz. After segmentation into epochs, information-rich frequency ranges were determined using filter bank common spatial…
  • Predictive regression modeling with MEG/EEG: from source power to signals and cognitive states. [Journal Article]
    Neuroimage. 2020 May 18 [Online ahead of print]Sabbagh D, Ablin P, … Engemann DA
  • Predicting biomedical outcomes from Magnetoencephalography and Electroencephalography (M/EEG) is central to applications like decoding, brain-computer-interfaces (BCI) or biomarker development and is facilitated by supervised machine learning. Yet most of the literature is concerned with classification of outcomes defined at the event-level. Here, we focus on predicting continuous outcomes from M…
  • Development of a Combined, Sequential Real-Time fMRI and fNIRS Neurofeedback System Enhance Motor Learning After Stroke. [Journal Article]
    J Neurosci Methods. 2020 May 18 [Online ahead of print]Rieke JD, Matarasso AK, … Daly JJ
  • CONCLUSIONS: . The system functioned well during user testing. Methods are detailed for others' use. The system user successfully engaged rt-fMRI and rt-fNIRS neurofeedback systems, modulated brain signal during rt-fMRI and rt-fNIRS training, according to volume of brain activation and intensity of signal, respectively, and clinically significant improved limb coordination and active wrist extension. fNIRS use in this case demonstrates a feasible/practical BCI system for further study with regard to use in chronic stroke rehab, and fMRI worked in concept, but cost and patient-friendly issues make it less feasible for clinical practice.
  • Multiclass covert speech classification using extreme learning machine. [Journal Article]
    Biomed Eng Lett. 2020 May; 10(2):217-226.Pawar D, Dhage S
  • The objective of the proposed research is to classify electroencephalography (EEG) data of covert speech words. Six subjects were asked to perform covert speech tasks i.e mental repetition of four different words i.e 'left', 'right', 'up' and 'down'. Fifty trials for each word recorded for every subject. Kernel-based Extreme Learning Machine (kernel ELM) was used for multiclass and binary classif…
  • EEG Headset Evaluation for Detection of Single-Trial Movement Intention for Brain-Computer Interfaces. [Journal Article]
    Sensors (Basel). 2020 May 14; 20(10)Jochumsen M, Knoche H, … Kidmose P
  • Brain-computer interfaces (BCIs) can be used in neurorehabilitation; however, the literature about transferring the technology to rehabilitation clinics is limited. A key component of a BCI is the headset, for which several options are available. The aim of this study was to test four commercially available headsets' ability to record and classify movement intentions (movement-related cortical po…
  • Decoding covert visual attention based on phase transfer entropy. [Journal Article]
    Physiol Behav. 2020 May 13; 222:112932.Ahmadi A, Davoudi S, … Daliri MR
  • Covert attention to spatial and color features in the visual field is a relatively new control signal for brain-computer interfaces (BCI). To guide the processing resources to the related visual scene aspects, covert attention should be decoded from human brain. Here, a novel expert system is designed to decode covert visual attention based on the EEG signal provided from 15 subjects during a new…
  • An Augmented-Reality fNIRS-Based Brain-Computer Interface: A Proof-of-Concept Study. [Journal Article]
    Front Neurosci. 2020; 14:346.Benitez-Andonegui A, Burden R, … Sorger B
  • Augmented reality (AR) enhances the user's environment by projecting virtual objects into the real world in real-time. Brain-computer interfaces (BCIs) are systems that enable users to control external devices with their brain signals. BCIs can exploit AR technology to interact with the physical and virtual world and to explore new ways of displaying feedback. This is important for users to perce…
  • Impact of very high-frequency sound and low-frequency ultrasound on people - the current state of the art. [Review]
    Int J Occup Med Environ Health. 2020 May 12 [Online ahead of print]Pawlaczyk-Łuszczyńska M, Dudarewicz A
  • For several decades, low-frequency ultrasound (<100 kHz) has been widely used in industry, medicine, commerce, military service and the home. The objective of the study was to present the current state of the art on the harmful effects of low-frequency airborne ultrasound on people, especially in occupational settings. The scientific literature search was performed using accessible medical and ot…
  • EEG-Controlled Wall-Crawling Cleaning Robot Using SSVEP-Based Brain-Computer Interface. [Journal Article]
    J Healthc Eng. 2020; 2020:6968713.Shao L, Zhang L, … Liu H
  • The assistive, adaptive, and rehabilitative applications of EEG-based robot control and navigation are undergoing a major transformation in dimension as well as scope. Under the background of artificial intelligence, medical and nonmedical robots have rapidly developed and have gradually been applied to enhance the quality of people's lives. We focus on connecting the brain with a mobile home rob…
  • Blunt Cardiac Injury: A Single-Center 15-Year Experience. [Journal Article]
    Am Surg. 2020 Apr 01; 86(4):354-361.Gao JM, Li H, … Yang Q
  • In recent years, the incidence of blunt cardiac injury (BCI) has increased rapidly and is an important cause of death in trauma patients. This study aimed to explore early diagnosis and therapy to increase survival. All patients with BCI during the past 15 years were analyzed retrospectively regarding the mechanism of injury, diagnostic and therapeutic methods, and outcome. The patients were divi…
  • Reduce brain computer interface inefficiency by combining sensory motor rhythm and movement-related cortical potential features. [Journal Article]
    J Neural Eng. 2020 May 07 [Online ahead of print]Liu T, Huang G, … Zhang Z
  • CONCLUSIONS: The feature combination of SMR and MRCP is not new in BCI decoding, but the large scale and repeatable study on BCI inefficiency assessment by using SMR and MRCP features is novel. MRCP feature provides the similar classification accuracies on the two subject groups with poor (< 70%) and good (>90%) accuracies by SMR feature. These results suggest that the combination of SMR and MRCP features may be a practical approach to reduce BCI inefficiency. While, "BCI inefficiency" might be more aptly called "SMR inefficiency" after this study.
  • Learning graph in graph convolutional neural networks for robust seizure prediction. [Journal Article]
    J Neural Eng. 2020 May 06 [Online ahead of print]Lian Q, Qi Y, … Wang Y
  • Brain-computer interface (BCI) has demonstrated its effectiveness in epilepsy treatment and control. In a BCI-aided epilepsy treatment system, therapic electrical stimulus is delivered in response to the prediction of upcoming seizure onsets, therefore timely and accurate seizure prediction algorithm plays an important role. However, unlike typical signatures such as slow or sharp waves in ictal …
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