Evaluation of time-domain features for motor imagery movements using FCM and SVM

Brain–Machine Interface is a direct communication pathway between brain and an external electronic device. BMIs aim to translate brain activities into control commands. To design a system that translates brain waves and its activities to desired commands, motor imagery tasks classification is the core part. Classification accuracy not only depends on how capable the classifier is but also it is about the input data. Feature extraction is to highlight the properties of signal that make it distinct from the signal of the other mental tasks. Performance of BMIs directly depends on the effectiveness of the feature extraction and classification algorithms. If a feature provides large interclass difference for different classes, the applied classifier exhibits a better performance. In order to attain less computational complexity, five timedomain procedure, namely: Mean Absolute Value, Maximum peak value, Simple Square Integral, Willison Amplitude, and Waveform Length are used for feature extraction of EEG signals. Two classifiers are applied to assess the performance of each feature-subject. SVM with polynomial kernel is one of the applied nonlinear classifier and supervised FCM is the other one. The performance of each feature for input data are evaluated with both classifiers and classification accuracy is the considered common comparison parameter

Evaluating the effectiveness of time-domain features for motor imagery movements using SVM

Motor imagery electroencephalogram signals are the only bio-signals that enable locked-in patients, who have lost control over every motor output, to communicate with and control their surroundings. Brain Machine Interface is collaboration between a human and machines, which translates brain waves to desired, understandable commands for a machine. Classification of motor imagery tasks for BMIs is the crucial part. Classification accuracy not only depends on how accurate and robust the classifier is; it is also about data. For well separated data, classifiers such as kernel SVM can handle classification and deliver acceptable results. If a feature provides large interclass difference for different classes, immunity to random noise and chaotic behavior of EEG signal is rationally conformed, which means the applied feature is suitable for classifying EEG signals. In this work, in order to have less computational complexity, time-domain algorithms are employed to motor imagery signals. Extracted features are: Mean Absolute Value, Maximum peak value, Simple Square Integral, Willison Amplitude, and Waveform Length. Support Vector Machine with polynomial kernel is applied for classification of four different classes of data. The obtained results show that these features have acceptable, distinct values for different these four motor imagery tasks. Maximum classification accuracy belongs to contribution of Willison amplitude as feature and SVM as classifier, with 95.1 percentages accuracy. Where, the lowest is the contribution of Waveform Length and SVM with 31.67 percentages classification accuracy

Health-related quality of life and medication adherence in elderly patients with epilepsy

© 2019 Polish Neurological Society. Objective. Considering the high prevalence of epilepsy in the elderly and the importance of maximising their quality of life (QoL), this study aimed to investigate the relationship between medication adherence and QoL, and the mediating effects of medication adherence on the association between serum antiepileptic drug (AED) level and seizure severity with QoL in elderly epileptics. Methods. In a longitudinal study, 766 elderly patients with epilepsy who were prescribed a minimum of one antiepileptic drug were selected by convenience sampling method. A Medication Adherence Report Scale (MARS-5) questionnaire was completed at the baseline. Seizure severity and QoL were assessed after six months using the Liverpool Seizure Severity Scale (LSSS) and the QoL in Epilepsy (QOLIE-31) questionnaires respectively. Serum level of AED was also measured at six-month follow-up. Results. Medication adherence was significantly correlated with both seizure severity (β = -0.33, p < 0.0001) and serum AED level (β = 0.29, p < 0.0001) after adjusting for demographic and clinical characteristics. Neither QoL nor its sub-classes were correlated with seizure severity. In addition, a significant correlation was not observed between serum AED level and QoL. However, medication adherence was significantly correlated with QoL (β = 0.30, p < 0.0001). The mediating effects of medication adherence on the association between serum AED level (Z = 3.39, p < 0.001) and seizure severity (Z = -3.47, p < 0.001) with QoL were supported by the Sobel test. Conclusion. This study demonstrates that medication adherence has a beneficial impact on QoL in elderly epileptics. Therefore, adherence to treatment should be monitored to improve their QoL

A Novel Method (T-Junction with a Tilted Slat) for Controlling Breakup Volume Ratio of Droplets in Micro and Nanofluidic T-Junctions

We propose a novel method for producing unequal sized droplets using a titled slat in the center of a T-junctions. In the available methods for generating unequal-sized droplets such as T-junction with valve and T-junction with a heater, the minimum breakup volume ratio that is accessible is approximately 0.3 while the system of this paper can generate droplets with the volume ratio 0.05. Therefore, the manufacturing cost of the system decreases considerably because it does not need to the consecutive breakup systems for generation of small droplets. The employed method was investigated through a numerical simulation using the volume of fluid (VOF) algorithm. The simulation results are reported for micro and nano-scaled T-junctions in various tilted slat sizes, capillary numbers (a dimensionless group describes the ratio of the inertial forces to the surface tension forces) and slat angles. Our method decreases (increases) considerably the breakup time (speed of the breakup process). For example in the case Ca=0.1 and volume ratio 0.4, dimensionless breakup time of our method and the method of T-junction with valve are 0.25 and 3.6, respectively. The results revealed that the breakup length of the nanoscale T-junction is smaller than microscale and increases by increasing the slat angle in both scales. The results demonstrated the breakup volume ratio decreases by increasing the tilted slat length. Also the breakup volume ratio minimizes in a specific slat angle. The results showed the breakup time is reduced by decreasing the slat angle. We also found that the pressure drop of the system is almost independent of the system geometry

Using Facial Gestures to Drive Narrative in VR

We developed an exploratory VR environment, where spatial features and narratives can be manipulated in real time by the facial and head gestures of the user. We are using the Faceteq prototype, exhibited in 2017, as the interactive interface. Faceteq consists of a wearable technology that can be adjusted on commercial HMDs for measuring facial expressions and biometric responses. Faceteq project was founded with the aim to provide a human-centred additional tool for affective human-computer interaction. The proposed demo will exhibit the hardware and the functionality of the demo in real time

FACETEQ interface demo for emotion expression in VR

© 2017 IEEE.Faceteq prototype v.05 is a wearable technology for measuring facial expressions and biometric responses for experimental studies in Virtual Reality. Developed by Emteq Ltd laboratory, Faceteq can enable new avenues for virtual reality research through combination of high performance patented dry sensor technologies, proprietary algorithms and real-time data acquisition and streaming. Emteq founded the Faceteq project with the aim to provide a human-centered additional tool for emotion expression, affective human-computer interaction and social virtual environments. The proposed demonstration will exhibit the hardware and its functionality by allowing attendees to experience three of the showcasing applications we developed this year

FACETEQ; A novel platform for measuring emotion in VR

FaceTeq prototype v.05 is a wearable technology for measuring facial expressions and biometric responses for experimental studies in Virtual Reality. Developed by Emteq Ltd laboratory, FaceTeq can enable new avenues for virtual reality research through combination of high performance patented dry sensor technologies, proprietary algorithms and real-time data acquisition and streaming. FaceTeq project was founded with the aim to provide a human-centred additional tool for emotion expression, affective human-computer interaction and social virtual environments. The proposed poster will exhibit the hardware and its functionality

How prepared are pharmacists to support atrial fibrillation patients in adhering to newly prescribed oral anticoagulants?

BACKGROUND: The New Medicines Service (NMS) was implemented in the United Kingdom in 2011 and first evaluated in 2014, showing 10% increase on adherence. OBJECTIVE: To assess community pharmacists' current practice, knowledge and confidence in supporting patients' adherence as part of the NMS for patients on Oral Anti-Coagulants (OACs) for stroke prevention in Atrial Fibrillation. SETTING: Community pharmacists in London. METHOD: An online cross-sectional survey was sent to pharmacists from their Local Pharmaceutical Committees and advertised by the Royal Pharmaceutical Society. Analysis was undertaken in SPSs v23 considering a confidence level of 95%. MAIN OUTCOME MEASURES: pharmacists reported confidence of providing the NMS on OACs; training needs and skills for supporting adherence. RESULTS: A total of 257 valid responses were analysed (6.8% response rate; {Cronbach's α = 0.676-0.892}). Data indicates that over a 2-month period, 25% of pharmacists had completed ≥6 NMS consultations for all OACs, of which 11% for new oral anticoagulants (NOACs). The key priorities in counselling items during the NMS consultation were to discuss actions to take when bleeding occurs, followed by supporting adherence. Pharmacists were more confident in their knowledge, skills and access to resources for Vitamin-K Antagonists (VKAs) than for NOACs (p < 0.005). Results also highlight pharmacists' unfamiliarity with alert cards, lower for NOACs than VKAs (p < 0.001), albeit perceived as critically important. Half the sample mentioned to use the British National Formulary as information resource. CONCLUSION: Results suggest the provision of NMS for NOACs is low. Supporting pharmacists with tailored education and adherence support might foster dissemination