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Title: Using spatio-temporal interest points (STIP) for myoclonic jerk detection in nocturnal video
Authors: Cuppens, Kris ×
Chen, Chih-Wei
Wong, Kevin Bing-Yung
Van de Vel, Anouk
Lagae, Lieven
Ceulemans, Berten
Tuytelaars, Tinne
Van Huffel, Sabine
Vanrumste, Bart
Aghajan, Hamid #
Issue Date: Aug-2012
Publisher: IEEE
Series Title: IEEE Engineering in Medicine and Biology Society. Conference Proceedings vol:2012 pages:4454-4457
Article number: 10.1109/EMBC.2012.6346955
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 [8].We applied this algorithm on a group of patients suffering from myoclonic jerks. With an optimal parameter setting this resulted in a sensitivity of over 75% and a PPV of over 85%, on the patients' combined data.
Description: Cuppens K., Chen C., Wong K.B., Van de Vel A., Lagae L., Ceulemans B., Tuytelaars T., Van Huffel S., Vanrumste B., Aghajan H., ''Using spatio-temporal interest points (STIP) for myoclonic jerk detection in nocturnal video'', Proceedings 34th annual international conference of the IEEE Engineering in Medicine and Biology Society, vol. 2012, pp. 4454-4457, August 28 - September 1, 2012, San Diego, California, USA.
URI: 
ISSN: 1557-170X
Publication status: published
KU Leuven publication type: IC
Appears in Collections:ESAT - STADIUS, Stadius Centre for Dynamical Systems, Signal Processing and Data Analytics
Neuro-musculo-skeletal Research (-)
ESAT - PSI, Processing Speech and Images
Technologiecluster ESAT Elektrotechnische Engineering
Electrical Engineering (ESAT) TC, Technology Campus Geel
× corresponding author
# (joint) last author

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