Vision-based absence seizure detection
Autor: | S. Voutoufianakis, Lefteris Koumakis, Manolis Tsiknakis, Pelagia Vorgia, M. Pediaditis, M. Karachaliou |
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Rok vydání: | 2012 |
Předmět: |
Male
Background subtraction Contextual image classification medicine.diagnostic_test Computer science Speech recognition Feature extraction Video Recording Signal Processing Computer-Assisted Electroencephalography medicine.disease Sensitivity and Specificity Facial recognition system Epilepsy Absence seizure Seizures Child Preschool Image Interpretation Computer-Assisted medicine Humans Female Child Face detection |
Zdroj: | EMBC |
DOI: | 10.1109/embc.2012.6345872 |
Popis: | In order to diagnose epilepsy, neurologists rely on their experience, performing an equal assessment of the electroencephalogram and the clinical image. Since misdiagnosis reaches a rate of 30% and more than one-third of all epilepsies are poorly understood, a need for leveraging diagnostic precision is obvious. With the aim at enhancing the clinical image assessment procedure, this paper evaluates the suitability of certain facial expression features for detecting and quantifying absence seizures. These features are extracted by means of time-varying signal analysis from signals that are gained by applying computer vision techniques, such as face detection, dense optical flow computation and averaging background subtraction. For the evaluation, video sequences of four patients with absence seizures are used. The classification performance of a C4.5 decision tree shows accuracies of up to 99.96% with a worst percentage of incorrectly classified instances of 0.14%. |
Databáze: | OpenAIRE |
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