Unintended complication of intracranial subdural hematoma after percutaneous epidural neuroplasty.

Percutaneous epidural neuroplasty (PEN) is a known interventional technique for the management of spinal pain. As with any procedures, PEN is associated with complications ranging from mild to more serious ones. We present a case of intracranial subdural hematoma after PEN requiring surgical evacuation. We review the relevant literature and discuss possible complications of PEN and patholophysiology of intracranial subdural hematoma after PEN

Online home appliance control using EEG-Based brain-computer interfaces

Brain???computer interfaces (BCIs) allow patients with paralysis to control external devices by mental commands. Recent advances in home automation and the Internet of things may extend the horizon of BCI applications into daily living environments at home. In this study, we developed an online BCI based on scalp electroencephalography (EEG) to control home appliances. The BCI users controlled TV channels, a digital door-lock system, and an electric light system in an unshielded environment. The BCI was designed to harness P300 andN200 components of event-related potentials (ERPs). On average, the BCI users could control TV channels with an accuracy of 83.0% ?? 17.9%, the digital door-lock with 78.7% ?? 16.2% accuracy, and the light with 80.0% ?? 15.6% accuracy, respectively. Our study demonstrates a feasibility to control multiple home appliances using EEG-based BCIs

A monolithic and flexible fluoropolymer film microreactor for organic synthesis applications

A photocurable and viscous fluoropolymer with chemical stability is a highly desirable material for fabrication of microchemical devices. Lack of a reliable fabrication method, however, limits actual applications for organic reactions. Herein, we report fabrication of a monolithic and flexible fluoropolymer film microreactor and its use as a new microfluidic platform. The fabrication involves facile soft lithography techniques that enable partial curing of thin laminates, which can be readily bonded by conformal contact without any external forces. We demonstrate fabrication of various functional channels (similar to 300 mu m thick) such as those embedded with either a herringbone micromixer pattern or a droplet generator. Organic reactions under strongly acidic and basic conditions can be carried out in this film microreactor even at elevated temperature with excellent reproducibility. In particular, the transparent film microreactor with good deformability could be wrapped around a light-emitting lamp for close contact with the light source for efficient photochemical reactions with visible light, which demonstrates easy integration with optical components for functional miniaturized systems.open1112Ysciescopu

MPPI-IPDDP: Hybrid Method of Collision-Free Smooth Trajectory Generation for Autonomous Robots

This study presents a hybrid trajectory optimization method that generates a collision-free smooth trajectory for autonomous mobile robots. The hybrid method combines sampling-based model predictive path integral (MPPI) control and gradient-based interior-point differential dynamic programming (IPDDP) exploiting their advantages of exploration and smoothing. The proposed method, called MPPI-IPDDP, consists of three steps. The first step generates a coarse trajectory by MPPI control, the second step constructs a collision-free convex corridor, and the third step smooths the coarse trajectory by IPDDP using the collision-free convex corridor computed in the second step. For demonstration, the proposed algorithm was applied to trajectory optimization for differential-driving wheeled mobile robots and point-mass quadrotors. A supplementary video of the simulations can be found at https://youtu.be/-oUAt5sd9Bk

The usefulness of the Korean version of modified Mini-Mental State Examination (K-mMMSE) for dementia screening in community dwelling elderly people

BACKGROUND: We assessed whether the Korean version of modified Mini-Mental State Examination (K-mMMSE) has improved performance as a screening test for cognitive impairment or dementia in a general population compared with the Korean Mini-Mental State Examination (K-MMSE). METHODS: Screening interviews were conducted with people aged 65 and over in Noam-dong, Namwon-city, Jeonbuk province. There were 522 community participants, of whom 235 underwent clinical and neuropsychological examination for diagnosis of dementia and Cognitive Impairment No Dementia (CIND). Sensitivity, specificity and areas under the receiver operating characteristic (ROC) curves for the K-mMMSE and the K-MMSE were the main outcome measures. RESULTS: Cronbach's alpha for the K-mMMSE was 0.91, compared with 0.84 for the K-MMSE. The areas under the ROC curves in identifying all levels of CIND or dementia were 0.91 for the K-mMMSE and 0.89 for the K-MMSE (P < 0.05). For the K-mMMSE, the optimal cut-off score for a diagnosis of CIND was 69/70, which had a sensitivity of 0.86 and a specificity of 0.79, while, for a diagnosis of dementia, the optimal cut-off score of 59/60 had a sensitivity of 0.91 and a specificity of 0.78. The K-mMMSE also had a high test-retest reliability (r = 0.89). CONCLUSION: Our findings indicate that the K-mMMSE is more reliable and valid than the K-MMSE as a cognitive screen in a population based study of dementia. Considering the test characteristics, the K-MMSE and modified version are expected to be optimally used in clinical and epidemiologic fields

A Review on the Computational Methods for Emotional State Estimation from the Human EEG

A growing number of affective computing researches recently developed a computer system that can recognize an emotional state of the human user to establish affective human-computer interactions. Various measures have been used to estimate emotional states, including self-report, startle response, behavioral response, autonomic measurement, and neurophysiologic measurement. Among them, inferring emotional states from electroencephalography (EEG) has received considerable attention as EEG could directly reflect emotional states with relatively low costs and simplicity. Yet, EEG-based emotional state estimation requires well-designed computational methods to extract information from complex and noisy multichannel EEG data. In this paper, we review the computational methods that have been developed to deduct EEG indices of emotion, to extract emotion-related features, or to classify EEG signals into one of many emotional states. We also propose using sequential Bayesian inference to estimate the continuous emotional state in real time. We present current challenges for building an EEG-based emotion recognition system and suggest some future directions.open