10 results found
Eftekhar A, Juffali W, El-Imad J, et al., 2014, Ngram-derived Pattern Recognition for the Detection and Prediction of Epileptic Seizures, PLOS One, Vol: 9, Pages: 1-15
This work presents a new method that combines symbol dynamics methodologies with an Ngram algorithm for the detection and prediction of epileptic seizures. The presented approach specifically applies Ngram-based pattern recognition, after data pre-processing, with similarity metrics, including the Hamming distance and Needlman-Wunsch algorithm, for identifying unique patterns within epochs of time. Pattern counts within each epoch are used as measures to determine seizure detection and prediction markers. Using 623 hours of intracranial electrocorticogram recordings from 21 patients containing a total of 87 seizures, the sensitivity and false prediction/detection rates of this method are quantified. Results are quantified using individual seizures within each case for training of thresholds and prediction time windows. The statistical significance of the predictive power is further investigated. We show that the method presented herein, has significant predictive power in up to 100% of temporal lobe cases, with sensitivities of up to 70–100% and low false predictions (dependant on training procedure). The cases of highest false predictions are found in the frontal origin with 0.31–0.61 false predictions per hour and with significance in 18 out of 21 cases. On average, a prediction sensitivity of 93.81% and false prediction rate of approximately 0.06 false predictions per hour are achieved in the best case scenario. This compares to previous work utilising the same data set that has shown sensitivities of up to 40–50% for a false prediction rate of less than 0.15/hour.
Rezaei Haddad ALI, 2014, Imagining The Future of Medicine, Imagining The Future of Medicine
El-Imad J, Juffali W, 2013, A system and method of detecting or predicting the onset of a neurological episode, GB20130021124 20131129
Detecting or predicting the onset of a neurological episode, e.g. a seizure, comprising: receiving a neurological electrical input, e.g. EEG, ECoG, comprising a digital signal of a neurologically derived signal over a recording length (L, fig 31); converting the digital signal into a digital data string of characters, preferably using a pre-processing module 3; deriving a layer of digital data from the signal, the layer comprising multiple intervals; identifying recurring patterns and/or anomalies in the digital string of characters, preferably provided by pattern search module 4; and measuring a pattern-derived parameter for intervals in the layer. Patterns and/or anomalies may be analysed from at least two different layers. Different weights, preferably provided by weighting module 100 may be applied to respective layers.; Weighted outputs may be provided from analysis of multiple layers. Interval start points may be offset from one another. The pattern-derived parameter may be one or more of: a count/rate of change of count rate of said recurring patterns or anomalies or a proportion/rate of change of proportion/statistical spread of the distribution of the recurring patterns in the digital data string.
El-Imad J, et A, 2013, A headset, GB2516275
An electroencephalography (EEG) headset comprising a semi-rigid bow element 2 adapted to locate at least partially around a user's head, wherein the bow element provides an attachment site 6 for an EEG electrode and the position on the bow element of the attachment site is adjustable. The adjustable attachment site for an electrode allows for the user to comfortably position an EEG electrode accurately, regardless of their head size and geometry. Embodiments include an elastic extension element attached to the semi-rigid bow element which can loop around a users head. Other embodiments include an electrode locator mesh which provides positionally adjustable attachment sites for electrodes on the head of the user.
El-Imad J, 2013, WO2013160706
(EN)A method of gathering data to detect or predict the onset of a neurological episode comprising: receiving a neurological electrical input comprising a digital representation of a neurologically derived signal; and selecting at least one optimising parameter derived from analysis of data collected during an inter-ictal period.(FR)L'invention concerne un procédé de collecte de données pour détecter ou prédire l'apparition d'un épisode neurologique, comprenant : la réception d'une entrée électrique neurologique comprenant une représentation numérique d'un signal d'origine neurologique ; et la sélection d'au moins un paramètre d'optimisation déduit d'une analyse de données collectées pendant une période interictale.
El-Imad J, Juffali W, 2011, Monitoring neurological electrical signals to detect the onset of a neurological episode, BR20131104642 20110826
A monitoring or predicting system to detect the onset of a neurological episode, such as an epileptic seizure, the system comprising: a neurological electrical input, the input being a digital representation of a neurologically derived signal; a converter to convert the digital signal into a digital data string; a pattern analyser to identify recurring patterns in the digital data string; and a monitor to measure a pattern-derived parameter, wherein an output from the monitor gives an indication of the onset or occasion of a neuronal activity in dependence on the pattern-derived parameter.
Juffali W, El-Imad J, Eftekhar A, et al., 2010, The WiNAM project: Neural data analysis with applications to epilespy, Biomedical Circuits and Systems Conference (BioCAS)
El-Imad J, Hormigo J, 2009, A media system and method, WO2009GB50222 20090305
An interactive media system configured to present a substantially real-time simulation of an actual live event involving a moveable object in an arena, the system comprising: a tag attachable to a moveable object involved in an actual live event in an arena; one or more base stations located relative to the arena and operable to receive a signal from the tag; a location platform configured to determine the location of the tag in the arena based on the signal received from the tag by the or each base station, and to output location data representing a location of the tag in the arena; a virtual world environment unit to simulate the actual live event including the arena, the object, and movement of the object in the arena using the location data for the tag; and an access interface in communication with the virtual world environment unit, the access interface being arranged to provide a user with access to the simulated arena and to permit the user to observe the simulated event in substantially real-time.
El-Imad J, Tang N, 2001, Generic Strategies for the Efficient and EffectiveUse of Information Systems in Business, American Conference on Information Systems
El-Imad J, 2001, Technology In Business, Publisher: 4E Business Solutions Inc
This book looks into the areas that constitute information technology management and attempts to identify the various generic approaches that can be applied to improve the efficiency and effectiveness of the decision making.
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