Using spatio-temporal interest points (STIP) for myoclonic jerk detection in nocturnal video

• Published in: 2012 Annual International Conference of the IEEE Engineering in Medicine and Biology Society
• Main 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
• Format: Article in Journal/Newspaper
• Language: English
• Published: IEEE 2012
• Subjects: SISTA; PSI_VISICS; laptev
• Online Access: https://lirias.kuleuven.be/handle/123456789/388450; https://doi.org/10.1109/EMBC.2012.6346955; https://lirias.kuleuven.be/bitstream/123456789/388450/2//3664_final.pdf

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. 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. status: published