2012 Annual International Conference of the IEEE Engineering in Medicine and Biology Society 2012
DOI: 10.1109/embc.2012.6346955
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Using spatio-temporal interest points (STIP) for myoclonic jerk detection in nocturnal video

Abstract: In this study we introduce a method for detecting myoclonic jerks during the night with video. Using video instead of the traditional method of using EEG-electrodes, permits patients to sleep without any attached sensors. This improves the comfort during sleep and it makes long term home monitoring possible. The algorithm for the detection of the seizures is based on spatio-temporal interest points (STIPs), proposed by Ivan Laptev, which is the state-of-the-art in action recognition.We applied this algorithm o… Show more

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Cited by 26 publications
(39 citation statements)
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References 15 publications
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“…A c c e p t e d M a n u s c r i p t evidence confirms that patient specific algorithms are crucial for achieving accurate detection devices [54,64,69,71,74,94,95,102,119]. Different sensors have been used for detecting GTCS, including mattress sensors, EDA, sEMG, ACM, cerebral oxygen saturation sensors and seizure-alert dogs with promising results [55,57,58,60,61,65,83,84,90,102,103,105,132].…”
Section: Page 24 Of 48mentioning
confidence: 88%
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“…A c c e p t e d M a n u s c r i p t evidence confirms that patient specific algorithms are crucial for achieving accurate detection devices [54,64,69,71,74,94,95,102,119]. Different sensors have been used for detecting GTCS, including mattress sensors, EDA, sEMG, ACM, cerebral oxygen saturation sensors and seizure-alert dogs with promising results [55,57,58,60,61,65,83,84,90,102,103,105,132].…”
Section: Page 24 Of 48mentioning
confidence: 88%
“…This was done with frontal and temporal lobe seizures to evaluate for the lateralizing value of ictal head turning [99,100]. The overall sensitivity varies from 75-100%, positive predictive value over 85%, and specificity of 53-93% [93][94][95][96]. Reported latencies range from 4.6 to 21.4 seconds [94].…”
Section: Video Detection Systemsmentioning
confidence: 99%
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