{"title":"Adaptive trajectory control based robotic rehabilitation device","authors":"T. Anwar, Adel Al-Jumaily","doi":"10.1109/MECBME.2014.6783256","DOIUrl":"https://doi.org/10.1109/MECBME.2014.6783256","url":null,"abstract":"One of the main objectives of a successful lower limb robotic rehabilitation device is to obtain a smooth human machine interaction in different phase of gait cycle. The new concept in robotics rehabilitation is a “cooperative patient strategy” meaning patient's voluntary efforts are taken into account rather than imposing any predefined movements or inflexible strategies. The term cooperative is defined to include compliance of robot as it behaves soft and gentle. It only reacts to muscular effort, interactive because there is a bidirectional exchange of energy and information between robot and patient. The control of trajectory is shared by robot and patient to complete gait cycle. In this paper an effort has been made to establish a control law to tune the inertia, damping and stiffness which in turn produce the desired trajectory impedance for smooth human machine interaction. The gain margin and phase margin in bode plot of our system is positive and hence a stable system.","PeriodicalId":384055,"journal":{"name":"2nd Middle East Conference on Biomedical Engineering","volume":"74 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134159617","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Detection of coupling with linear and nonlinear synchronization measures for EEG","authors":"Hanieh Bakhshayesh, S. Fitzgibbon, K. Pope","doi":"10.1109/MECBME.2014.6783249","DOIUrl":"https://doi.org/10.1109/MECBME.2014.6783249","url":null,"abstract":"There has been extensive research aimed at measuring synchronization to study the relationships between complex time series, such as electroencephalography (EEG). We compare six synchronization measures: the linear measures of cross-correlation, coherence and partial coherence, and three nonlinear similarity measures, namely correntropy, phase index and mutual information. We apply these measures to simulated data (unidirectionally coupled Henon maps) to test the detection of nonlinear and nonstationary interdependence, including in the presence of noise, and to simulated EEG. No measure fails, none is the clear winner, all measures have advantages and disadvantages. “Best measure” depends on the research aims and data. The tests selected here for EEG research recommend correntropy as the preferred measure.","PeriodicalId":384055,"journal":{"name":"2nd Middle East Conference on Biomedical Engineering","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134601060","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}