Electroencephalograph (EEG) signal processing techniques for motor imagery Brain Computer interface systems

Brain-Computer Interface (BCI) system provides a channel for the brain to control external devices using electrical activities of the brain without using the peripheral nervous system. These BCI systems are being used in various medical applications, for example controlling a wheelchair and neuroprosthesis devices for the disabled, thereby assisting them in activities of daily living. People suffering from Amyotrophic Lateral Sclerosis (ALS), Multiple Sclerosis and completely locked in are unable to perform any body movements because of the damage of the peripheral nervous system, but their cognitive function is still intact. BCIs operate external devices by acquiring brain signals and converting them to control commands to operate external devices. Motor-imagery (MI) based BCI systems, in particular, are based on the sensory-motor rhythms which are generated by the imagination of body limbs. These signals can be decoded as control commands in BCI application. Electroencephalogram (EEG) is commonly used for BCI applications because it is non-invasive. The main challenges of decoding the EEG signal are because it is non-stationary and has a low spatial resolution. The common spatial pattern algorithm is considered to be the most effective technique for discrimination of spatial filter but is easily affected by the presence of outliers. Therefore, a robust algorithm is required for extraction of discriminative features from the motor imagery EEG signals. This thesis mainly aims in developing robust spatial filtering criteria which are effective for classification of MI movements. We have proposed two approaches for the robust classification of MI movements. The first approach is for the classification of multiclass MI movements based on the thinICA (Independent Component Analysis) and mCSP (multiclass Common Spatial Pattern Filter) method. The observed results indicate that these approaches can be a step towards the development of robust feature extraction for MI-based BCI system. The main contribution of the thesis is the second criterion, which is based on Alpha- Beta logarithmic-determinant divergence for the classification of two class MI movements. A detailed study has been done by obtaining a link between the AB log det divergence and CSP criterion. We propose a scaling parameter to enable a similar way for selecting the respective filters like the CSP algorithm. Additionally, the optimization of the gradient of AB log-det divergence for this application was also performed. The Sub-ABLD (Subspace Alpha-Beta Log-Det divergence) algorithm is proposed for the discrimination of two class MI movements. The robustness of this algorithm is tested with both the simulated and real data from BCI competition dataset. Finally, the resulting performances of the proposed algorithms have been favorably compared with other existing algorithms

Use of Dreams in Girish Karnad’s The Dreams of Tipu Sultan

Girish karnad s in his play the The Dreams of Tipu Sultan use the concept of dreams to indicate the downfall of Tipu Sultan through his dreams The dreams of Tipu Sultan can be interpreted as symbol or an indication which focuses on his downfall in the future The dreams book Khwab-nama was looted from Seringapatam along with other books The book was not in library or the royal library in Seringapatam It was discovered hidden in the bed chamber of Tipu Sultan palace Lal Mahal the ruin of which can be seen today in front of the Sri Ranganatha Swamy Temple Tipu sultan one of the most politically perceptive and tragic figures in modern Indian history In the play he had four dreams but in history has 37 dream

Non-Perturbative Theory for Dispersion Self-Energy of Atoms

We go beyond the approximate series-expansions used in the dispersion theory of finite size atoms. We demonstrate that a correct, and non-perturbative, theory dramatically alters the dispersion selfenergies of atoms. The non-perturbed theory gives as much as 100% corrections compared to the traditional series expanded theory for the smaller noble gas atoms.Comment: 3 pages, no figures, 1 tabl

Burden and Marital Satisfaction among the Spouses of Persons with Depression

Background: Depression is a very common psychiatric disorder. The burden on the spouse of a depressed individual is considered to be a multi-dimensional problem and is seen in the context of its emotional, psychological, physical and economic consequences. The depressed individual’s aversive interpersonal behaviours may lead spouses to experience depression and problems in marital adjustment. Aim: To study and compare the burden and marital satisfaction among male and female spouses of patients suffering from depression. Materials & Methods: Spouses of patients were inducted from those attending the Department of Psychiatry of Government Medical College and Hospital (GMCH), Chandigarh, India with their partners. A total of 60 spouses of patients with ICD-10 diagnosis of depression fulfilling inclusion and exclusion criteria were recruited for the study. Consecutive sampling was used for data collection. Participants were divided into two groups i.e. Male and Female. Zarit Burden Interview and Marital Satisfaction Scale were used to assess the burden and marital satisfaction respectively. Results: There was no significant difference in burden and marital satisfaction between the two genders which means both the groups are equally vulnerable and prone to develop psychiatric problems like stress, anxiety, depression. Conclusion: Considering the findings, both groups have an equal need to cater to care giving and related responsibilities. The study can be useful in implementing programs to help the spouses and cater the needs of care giving, to handle the burden productively associated with the care giving of their depressed partners, to strengthen their coping and to have a better marital life. Keywords: Depression, burden, marital satisfactio

Non-Perturbative Theory of Dispersion Interactions

Some open questions exist with fluctuation-induced forces between extended dipoles. Conventional intuition derives from large-separation perturbative approximations to dispersion force theory. Here we present a full non-perturbative theory. In addition we discuss how one can take into account finite dipole size corrections. It is of fundamental value to investigate the limits of validity of the perturbative dispersion force theory.Comment: 9 pages, no figure

Machine Learning-Based Classification of Hybrid BCI Signals using Mayfly-Optimized Multiclass Weighted Random Forest

The Brain-Computer Interface (BCI) technologies have excellent clinical and non-clinical uses. Among the most popular imaging methods adopted in BCI technologies is electroencephalography (EEG). But EEG signals are typically quite complicated, so analyzing them necessitates a significant amount of effort. With the help of machine learning (ML), this research investigates the feasibility of a BCI platform based on the motor imagery (MI) concept. The steps of pre-processing, feature extraction and classification are the underpinning of any conventional ML model. To train such a model, however, a large amount of data is needed. To address this gap, this work introduces a new mayfly-optimized multiclass weighted random forest (MFO-MWRF) technique that uses retrieved features as input to mitigate the need for this supplementary data. In this study, we gather a dataset of hybrid EEG and fNIRS motor imagery that can be pre-processed using a Wiener filter (WF) to filter out noisier signals without affecting the high-quality images. The characteristics are extracted using the discrete wavelet transform (DWT). The research results indicate that the proposed approach achieves the best performance compared to existing approaches for classifying motor movement images

Effective Polarisability Models

Theories for the effective polarisability of a small particle in a medium are presented using different levels of approximation: we consider the virtual cavity, real cavity and the hard-sphere models as well as a continuous interpolation of the latter two. We present the respective hard-sphere and cavity radii as obtained from density-functional simulations as well as the resulting effective polarisabilities at discrete Matsubara frequencies. This enables us to account for macroscopic media in van der Waals interactions between molecules in water and their Casimir-Polder interaction with an interface

Increased porosity turns desorption to adsorption for gas bubbles near water-SiO2 interface

We consider theoretically the retarded van der Waals interaction of a small gas bubble in water with a porous SiO2 surface. We predict a possible transition from repulsion to attraction as the surface is made more porous. It highlights that bubbles will interact differently with surface regions with different porosity (i.e., with different optical properties)

Determination of Sinapic Acid Derivatives in Canola Extracts Using High-Performance Liquid Chromatography

A high-performance liquid chromatographic (HPLC) method with diode array detection (DAD) was used to determine the total phenolics, including sinapic acid derivatives in canola. Ten Western Canadian canola seeds, six other commodity canola seeds, their corresponding press cakes and meals were analyzed. Seeds of European 00 rapeseed and Brassica Juncea (Indian mustard) were included for comparison. Phenolic compounds were separated using a gradient elution system of water–methanol-ο-phosphoric acid solution with a flow rate of 0.8 ml/min. In addition to sinapine (SP) and sinapic acid (SA), sinapoyl glucose (SG) is reported in the methanolic extracts. The detection and quantification limits of these compounds were 0.20–0.40 and 0.50–0.80 μg/ml, respectively with recovery values over 98.0%. The content of total phenolics, SP, SA and SG in canola extracts ranged from 9.16 to 16.13, 6.39 to 12.28, 0.11 to 0.59 and 1.36 to 7.50 mg/g, respectively with significant differences among varieties