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The brain computer interface (BCI) speller system can be classified into synchronous and asynchronous type. In synchronous type, one of the target characters is selected with specific interval periodically even if the user is making or not making attention on the target, whereas, in asynchronous case, the target character will not be selected until a confirmation signal is received from the user. In this proposed study a novel oddball stimulus paradigm is introduced on the hybrid steady state visual evoked potential (SSVEP) and electrooculogram (EOG) speller system to achieve an asynchronous control and high performance. The proposed system consists of forty characters grouped and indexed into five flickering unique frequency visual stimuli. Each visual stimulus is assigned with eight unique characters. The characters in each group are randomly highlighted by the oddball paradigm and the user performs blink eye movement in synchrony with the desired target character highlight. An asynchronous control is achieved by EOG signal and oddball paradigm because the target character will not be selected until the user performs blink eye movement. The stimulus paradigm helps the user to select the target group and desired target character, concurrently by SSVEP and EOG signal which increases the performance of the system. The proposed asynchronous speller system is tested and validated on ten subjects. The online classification accuracy and information transfer rate (ITR) of the proposed hybrid speller system are 99.38% and 116.58 bits/min respectively. Performance metrics of the proposed system are compared with the conventional speller systems and is found to be much superior to existing systems.

This study aims to design a high performance communication system using steady state visual evoked potential (SSVEP) and electro-oculogram (EOG) signal. The proposed keyboard system consists of twenty three randomly chosen characters and they were indexed into different flickering visual stimuli designed using three SSVEP stimulus frequencies. The same frequency valued visual stimuli were used many times (more than once) in the keyboard layout. In this approach an oddball paradigm is introduced and it randomly highlights three/two unique frequency valued visual stimuli at a time. The system identifies a desired target by user eye blink in accordance to the oddball paradigm and recognized SSVEP frequency value. The signal to noise ratio (SNR) of the real time SSVEP electroencephalogram signal gets increased by the introduction of oddball paradigm in the SSVEP based keyboard system. The paradigm will increase the subject’s attention and concentration on the flickering target stimulus. The real time SSVEP data were classified using extended multivariate synchronization index (EMSI) method. The thresholding method is used for single blink detection. The offline and online experiments were performed by all the subjects for evaluating the proposed communication system. The average classification accuracy and information transfer rate of the system are 96.73 % and 76.02 bits/min respectively.

Recently, deep learning and convolutional neural networks (CNNs) have reported several promising results in the classification of Motor Imagery (MI) using Electroencephalography (EEG). With the gaining popularity of CNN-based BCI, the challenges in deploying it in a real-world mobile and embedded device with limited computational and memory resources need to be explored. Towards this objective, we investigate the impact of the magnitude-based weight pruning technique to reduce the number of parameters of the pre-trained CNN-based classifier while maintaining its performance. We evaluated the proposed method on an open-source Korea University dataset which consists of 54 healthy subjects' EEG, recorded while performing right-and left-hand MI. Experimental results demonstrate that the subject-independent model can be maximumly pruned to 90% sparsity, with a compression ratio of 4.77× while retaining classification accuracy at 84.44% with minimal loss of 0.02% when compared to the baseline model's performance. Therefore, the proposed method can be used to design more compact deep CNN- based BCIs without compromising on their performance.

The focus of this paper is to increase the number of targets and classification rate in the SSVEP-BCI visual keyboard system. The dual frequency steady state visual evoked potential (SSVEP) and video-oculography (VOG) based hybrid system has been developed in this study. The visual stimuli (targets) were designed using dual frequency SSVEP method. This method could create more targets through a suitable combination of limited number of frequencies. The keyboard screen was divided into three sections (left, middle and right), and each section visual stimuli/keys were designed with a unique set of frequencies. The webcam based video-oculography was used to detect the direction of the eye gaze. This selection reduces the issue of misclassification of SSVEP frequencies. Extended multivariate synchronization index (EMSI) method is used for SSVEP frequency recognition. Both online and offline experiments were conducted on 10 subjects and an average online detection accuracy of 94.987% was obtained with the information transfer rate (ITR) of 82.786 bits/minutes.

This paper aims to design a new stimulus paradigm for SSVEP based keyboard system. The proposed paradigm was implemented using black and white checkerboard flickering visual stimuli along with the integration of videooculography (VOG). The on-screen speller was designed using three frequencies. The goal of this study is how to increase more number of targets using less number of stimulus frequencies. It is achieved by the use of VOG data. The study was carried out using 36 selected characters. A webcam is integrated along with the system to obtain VOG data. The webcam captures the images of the eyes, which in turn is used to detect the eye gaze direction. This additional information from VOG overcomes the limitations of SSVEP based spelling system. The extended multivariate synchronization index (EMSI) method is used for SSVEP frequency recognition. Offline and online analysis of the experiment were conducted and the duration of recognition of each character required by the participant was calculated based on the classification accuracy. Online experiment was conducted on 10 subjects to validate the accuracy and information transfer rate (ITR) of the system. An average online detection accuracy of 90.46 % was obtained with the ITR of 65.98 bits/minutes.

BACKGROUND : Orthopaedic surgeons have long maintained that all children who have sustained a diaphyseal fracture of femur recover with c onservative treatment, given the excellent remodeling ability of immature bone in children. Angulations, shortenings and malrotations are not always corrected by conservative treatment. Of many surgical options, titanium elastic nailing has been the newer implant which is being used regularly. Although good results have been reported with elastic intramedullary nails, plate fixation continues to be a viable alternative in surgical treatment of femoral shaft fractures. However there are not many studies comp aring the efficiency of titanium elastic nailing and plating for femoral diaphyseal fractures in pediatric age group. AIM : The present study aims to compare the surgical management of diaphyseal fractures of femur in children with Dynamic Compression Plati ng versus Titanium Elastic Nailing. DESIGN : This is a prospective study . MATERIALS AND METHODS : This prospective study was conducted in a tertiary hospital. Patients who presented to the out - patient department and casualty of the hospital with femoral diap hyseal fractures during April 2012 to June 2014 were considered for the study. Subjects fulfilling the predetermined inclusion and exclusion criteria were included in the study. STATISTICAL METHODS : Fisher Exact test, Chi - Square Test, Student t test (Two t ailed, independent) . RESULTS : Patients in the age group of 6 - 14 years were considered for the study, Patients were divided into two groups and treated with DCP/TENS. The duration of surgery, hospital stay, and, amount of blood loss was minimal in TENS grou p. Callus was seen early in TENS group. Radiological union was early in TENS group by 2 - 3 weeks. Outcome was better in patients treated with TENS (Excellent - 70%; Satisfactory – 30%; Poor - 0%) in comparison to DCP (Excellent - 70%; Satisfactory - 25%; Poor - 5%). CO NCLUSION : TENS is more versatile and can achieve biological fixation, with minimal complications compared to DCP hence it is concluded that TENS is better procedure for fracture shaft femur in children than DCP