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Electroencephalogram (EEG) signal classification plays an important role to facilitate physically impaired patients by providing brain-computer interface (BCI)-controlled devices. However, practical applications of BCI make it difficult to decode motor imagery-based brain signals for multiclass classification due to their non-stationary nature. In this study, we aim to improve multiclass classification accuracy for motor imagery movement using sub-band common spatial patterns with sequential feature selection (SBCSP-SBFS) method. Filter bank having bandpass filters of different overlapped frequency cutoffs is applied to suppress the noise signals from raw EEG signals. The output of these sub-band filters is sent for feature extraction by applying common spatial pattern (CSP) and linear discriminant analysis (LDA). As all of the extracted features are not necessary for classification therefore, selection of optimal features is done by passing the extracted features to sequential backward floating selection (SBFS) technique. Three different classifiers were then trained on these optimal features, i.e., support vector machine (SVM), Naïve-Bayesian Parzen-Window (NBPW), and k-Nearest Neighbor (KNN). Results are evaluated on two datasets, i.e., Emotiv Epoc and wet gel electrodes for three classes, i.e., right-hand motor imagery, left hand motor imagery, and rest state. The proposed model yields a maximum accuracy of 60.61% in case of Emotiv Epoc headset and 86.50% for wet gel electrodes. The computed accuracy shows an increase of 7% as compared to previously implemented multiclass EEG classification.

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-This paper presents design and specific absorption rate analysis of a 2.4 GHz wearable patch antenna on a conventional and electromagnetic bandgap (EBG) ground planes, under normal and bent conditions. Wearable materials are used in the design of the antenna and EBG surfaces. A woven fabric (Zelt) is used as a conductive material and a 3 mm thicker Wash Cotton is used as a substrate. The dielectric constant and tangent loss of the substrate are 1.51 and 0.02 respectively. The volume of the proposed antenna is 113×96.4×3 mm 3 . The metamaterial surface is used as a high impedance surface which shields the body from the hazards of electromagnetic radiations to reduce the Specific Absorption Rate (SAR). For on-body analysis a three layer model (containing skin, fats and muscles) of human arm is used. Antenna employing the EBG ground plane gives safe value of SAR (i.e. 1.77W/kg<2W/kg), when worn on human arm. This value is obtained using the safe limit of 2 W/kg, averaged over 10g of tissue, specified by the International Commission of Non Ionization Radiation Protection (ICNIRP). The SAR is reduced by 83.82 % as compare to the conventional antenna (8.16 W/kg>2W/kg). The efficiency of the EBG based antenna is improved from 52 to 74 %, relative to the conventional counterpart. The proposed antenna can be used in wearable electronics and smart clothing.

In this paper, a rotated Y-shaped antenna is designed and compared in terms of performance using a conventional and EBG ground planes for future Fifth Generation (5G) cellular communication system. The rotated Y-shaped antenna is designed to transmit at 38 GHz which is one of the most prominent candidate bands for future 5G communication systems. In the design of conventional antenna and metamaterial surfaces (mushroom, slotted), Rogers-5880 substrate having relative permittivity, thickness and loss tangent of 2.2, 0.254 mm, and 0.0009 respectively have been used. The conventional rotated Y-shaped antenna offers a satisfactory wider bandwidth (0.87 GHz) at 38.06 GHz frequency band, which gets further improved using the EBG surfaces (mushroom, slotted) as a ground plane by 1.23 GHz and 0.97 GHz respectively. Similarly, the conventional 5G antenna radiates efficiently with an efficiency of 88% and is increased by using the EBG surfaces (slotted, mushroom-like) to 90% and 94% respectively at the desired resonant frequency band. The conventional antenna yields a bore side gain of 6.59 dB which is further enhanced up to 8.91dB and 7.50 dB by using mushroom-like and slotted EBG surfaces respectively as a ground plane. The proposed rotated Y-shaped antenna and EBG surfaces (mushroom, slotted) are analyzed using the Finite Integration Technique (FIT) employed in Computer Simulation Technology (CST) software. The designed antenna is applicable for future 5G applications.