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Classifying Normal and Abnormal Status Based on Video Recordings of Epileptic Patients

Identifieur interne : 002467 ( Pmc/Corpus ); précédent : 002466; suivant : 002468

Classifying Normal and Abnormal Status Based on Video Recordings of Epileptic Patients

Auteurs : Jing Li ; Xiantong Zhen ; Xianzeng Liu ; Gaoxiang Ouyang

Source :

RBID : PMC:4000972

Abstract

Based on video recordings of the movement of the patients with epilepsy, this paper proposed a human action recognition scheme to detect distinct motion patterns and to distinguish the normal status from the abnormal status of epileptic patients. The scheme first extracts local features and holistic features, which are complementary to each other. Afterwards, a support vector machine is applied to classification. Based on the experimental results, this scheme obtains a satisfactory classification result and provides a fundamental analysis towards the human-robot interaction with socially assistive robots in caring the patients with epilepsy (or other patients with brain disorders) in order to protect them from injury.


Url:
DOI: 10.1155/2014/459636
PubMed: 24977196
PubMed Central: 4000972

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   |texte=   Classifying Normal and Abnormal Status Based on Video Recordings of Epileptic Patients
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