Cervical Diastematomyelia: A Case Presentation and Systematic Review.

Diastematomyelia is a rare congenital disorder characterized by the separation of the spinal cord by an osseocartilaginous or fibrous septum. While diastematomyelia has been reported to be more common in the thoracic and lumbar regions, the true incidence of cervical diastematomyelia is currently unknown. In this study, we conducted the most comprehensive systematic review to date of all other case reports of diastematomyelia to better characterize the incidence of cervical diastematomyelia and provide comprehensive statistics on the clinical characteristics of diastematomyelia generally.

Eyeblink recognition improves fatigue prediction from single-channel forehead EEG in a realistic sustained attention task.

Objective: A passive brain-computer interface recognizes its operator's cognitive state without an explicitly performed control task. This technique is commonly used in conjunction with consumer-grade EEG devices for detecting the conditions of fatigue, attention, emotional arousal, or motion sickness. While it is easy to mount the sensors in the forehead area, which is not covered with hair, the recorded signals become greatly contaminated with eyeblink and movement artifacts, which makes it a challenge to acquire the data of suitable for analysis quality, particularly in few channel systems where a lack of spatial information limits the applicability of sophisticated signal cleaning algorithms.

Associations Among Emotional State, Sleep Quality, and Resting-State EEG Spectra: A Longitudinal Study in Graduate Students.

University students are routinely influenced by a variety of natural stressors and experience irregular sleep-wake cycles caused by the necessity to trade sleep for studying while dealing with academic assignments. Often these factors result in long-term issues with daytime sleepiness, emotional instability, and mental exhaustion, which may lead to difficulties in the educational process. This study introduces the Daily Sampling System (DSS) implemented as a smartphone application, which combines a set of self-assessment scales for evaluating variations in the emotional state and sleep quality throughout a full academic term.

Enhancing the Hybrid BCI Performance With the Common Frequency Pattern in Dual-Channel EEG.

The brain-computer interface establishes a direct communication pathway between the human brain and an external device by recognizing specific patterns in cortical activities. The principle of hybridization stands for combining at least two different BCI modalities into a single interface with the aim of improving the information transfer rate by increasing the recognition accuracy and number of choices available for the user. This study proposes a simultaneous hybrid BCI system that recognizes the motor imagery (MI) and the steady-state visually evoked potentials (SSVEP) using the EEG signals from a dual-channel EEG setting with sensors placed over the central area (C3 and C4 channels).

Development of Single-Channel Hybrid BCI System Using Motor Imagery and SSVEP.

Numerous EEG-based brain-computer interface (BCI) systems that are being developed focus on novel feature extraction algorithms, classification methods and combining existing approaches to create hybrid BCIs. Several recent studies demonstrated various advantages of hybrid BCI systems in terms of an improved accuracy or number of commands available for the user. But still, BCI systems are far from realization for daily use.