Mental state estimation for brain-computer interfaces

Mental state estimation is potentially useful for the development of asynchronous brain-computer interfaces. In this study, four mental states have been identified and decoded from the electrocorticograms (ECoGs) of six epileptic patients, engaged in a memory reach task. A novel signal analysis technique has been applied to high-dimensional, statistically sparse ECoGs recorded by a large number of electrodes. The strength of the proposed technique lies in its ability to jointly extract spatial and temporal patterns, responsible for encoding mental state differences. As such, the technique offers a systematic way of analyzing the spatiotemporal aspects of brain information processing and may be applicable to a wide range of spatiotemporal neurophysiological signals

Age-related Variations in Anthropometry, Body Composition and Nutritional Status among the Adult Kheria Sabar Males of Purulia, West Bengal, India

Undernutrition and ageing may have a significant effect on body composition. A cross sectional study was conducted to explore the age-related variations among different anthropometric and body composition characteristics amongst the adult Kheria Sabar males of Purulia district of West Bengal. From fifteen villages, 304 apparently healthy adult males aged 18–60 years were selected at random. Subjects were categorized into four age groups and standard anthropometric measurements were used like height (HT), weight (WT), mid-upper-arm circumference (MUAC) and skinfolds of biceps (BSF), triceps (TSF) and sub-scapular (SSSF) region. Derived variables of body mass index (BMI), per cent body fat (PBF), fat mass (FM), fat-free mass (FFM), fat mass index (FMI) and fat-free mass index (FFMI) were also calculated. Majority of the variables were found to be inversely correlated with age. Positive (HT, WT, MUAC, BMI, FFM and FFMI) and negative (FM and FMI) significant differences were observed across different age groups. It was also observed that the frequency of undernutrition (62.6%) was the highest among the elderly people with 47.6% overall prevalence. This study clearly indicates that among the undernourished individuals, older people were more vulnerable to malnutrition and thus immediate nutritional intervention is required

Sample size calculation: Basic principles

Addressing a sample size is a practical issue that has to be solved during planning and designing stage of the study. The aim of any clinical research is to detect the actual difference between two groups (power) and to provide an estimate of the difference with a reasonable accuracy (precision). Hence, researchers should do a priori estimate of sample size well ahead, before conducting the study. Post hoc sample size computation is not encouraged conventionally. Adequate sample size minimizes the random error or in other words, lessens something happening by chance. Too small a sample may fail to answer the research question and can be of questionable validity or provide an imprecise answer while too large a sample may answer the question but is resource-intensive and also may be unethical. More transparency in the calculation of sample size is required so that it can be justified and replicated while reporting

Curvature Minimizing Depth Interpolation for Intuitive and Interactive Space Curve Sketching

Space curve sketching using 2D user interface is a challenging task and forms the foundation for almost all sketch based modeling systems. Since the inverse projection from 2D to 3D is a one to many function, there is no unique solution. In this paper, we propose to interpret the given 2D curve to be the projection of the 3D curve that has minimum curvature among all the candidates in 3D. We present an elegant algorithm to efficiently find a close approximation of this minimum curvature 3D space curve. We also compare with many other 2D to 3D curve generation techniques to show that the curve generated by our method is the one of the most “intuitive ” and easy to compute. Fixing the space curve to be the minimum curvature curve does not restrict the user from getting high-curvature space curve, if desired. We analyze the complete behavior of our space curve generation algorithm in order to provide simple sketching rules to achieve the curve that the user wants, even the high-curvature space curve, with no change in our algorithm. 1

Classification accuracy between preexposure and postexposure for all participant categories.

A. The orange, green and brown bars represent mean classification accuracies for DFE, LFE and NEC respectively. The horizontal dashed line represents the chance classification. B. Frontal (F1, F2, F3, F4, Fz, AF3, AF4), centro-parietal (CP1, CP2, CP3, CP4, CPz) and parietal (P1, P2, P3, P4, Pz, PO3, PO4) electrodes on a 64-channel EEG cap. There seems to be an above chance classification accuracy for the DFE only. *p p p < 0.001.</p