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

Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS

Volumn , Issue , 2012, Pages 4454-4457

  Cuppens, Kris ^a   Chen, Chih Wei ^b   Wong, Kevin Bing Yung ^b   Van De Vel, Anouk ^c   Lagae, Lieven ^d   Ceulemans, Berten ^c   Tuytelaars, Tinne ^d   Van Huffel, Sabine ^e   Vanrumste, Bart ^a   Aghajan, Hamid ^b,f  

^a Thomas More University College   (Belgium)

^b Stanford University   (United States)

^c ANTWERP UNIVERSITY HOSPITAL   (Belgium)

^d UNIVERSITY OF LEUVEN   (Belgium)

^e IBBT Future Health Department   (Belgium)

^f GHENT UNIVERSITY   (Belgium)

Author keywords

[No Author keywords available]

Indexed keywords

ACTION RECOGNITION; ATTACHED SENSOR; HOME MONITORING; OPTIMAL PARAMETER SETTINGS; SPATIO-TEMPORAL;

ENGINEERING; INDUSTRIAL ENGINEERING;

ALGORITHMS;

AMBULATORY MONITORING; ANATOMIC LANDMARK; ARTICLE; AUTOMATED PATTERN RECOGNITION; CHILD; FEMALE; HUMAN; MALE; METHODOLOGY; MYOCLONUS; MYOCLONUS EPILEPSY; PATHOLOGY; PATHOPHYSIOLOGY; PHOTOGRAPHY; POLYSOMNOGRAPHY; PRESCHOOL CHILD; REPRODUCIBILITY; SENSITIVITY AND SPECIFICITY; THREE DIMENSIONAL IMAGING; VIDEORECORDING;

ANATOMIC LANDMARKS; CHILD; CHILD, PRESCHOOL; EPILEPSIES, MYOCLONIC; FEMALE; HUMANS; IMAGING, THREE-DIMENSIONAL; MALE; MONITORING, AMBULATORY; MYOCLONUS; PATTERN RECOGNITION, AUTOMATED; PHOTOGRAPHY; POLYSOMNOGRAPHY; REPRODUCIBILITY OF RESULTS; SENSITIVITY AND SPECIFICITY; VIDEO RECORDING;

EID: 84870821789     PISSN: 1557170X     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/EMBC.2012.6346955     Document Type: Conference Paper

References (14)

1. Chen L, Yang X, Liu Y, Zeng D, Tang Y, Yan B, Lin X, Liu L, Xu H, Zhou D (2009) Quantitative and trajectory analysis of movement trajectories in supplementary motor area seizures of frontal lobe epilepsy. Epilepsy & Behavior 14(2):344-353
2. Conradsen I, Beniczky S, Wolf P, Henriksen J, Sams T, Sorensen HBD (2010) Seizure onset detection based on a uni- or multi-modal intelligent seizure acquisition (uisa/misa) system. 2010 32nd Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC 2010) pp 3269-72
3. Cuppens K, Lagae L, Ceulemans B, Van Huffel S, Vanrumste B (2009) Detection of nocturnal frontal lobe seizures in pediatric patients by means of accelerometers: a first study. EMBC: 2009 Annual International Conference of the Ieee Engineering in Medicine and Biology Society, Vols 1-20 pp 6608-6611
4. Haiping L, How-Lung E, Mandal B, Chan DWS, Yen-Ling N (2011) Markerless video analysis for movement quantification in pediatric epilepsy monitoring. 2011 33rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society
5. Jallon P (2010) A bayesian approach for epileptic seizures detection with 3d accelerometers sensors. 2010 32nd Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC 2010) pp 6325-8
6. Karayiannis NB, Tao GZ, Frost JD, Wise MS, Hrachovy RA, Mizrahi EM (2006) Automated detection of videotaped neonatal seizures based on motion segmentation methods. Clinical Neurophysiology 117(7):1585-1594
7. Kramer U, Kipervasser S, Shlitner A, Kuzniecky R (2011) A novel portable seizure detection alarm system: Preliminary results. Journal of Clinical Neurophysiology 28(1):36-38
8. Laptev I (2005) On space-time interest points. International Journal of Computer Vision 64(2-3):107-123
9. Laptev I, Marszalek M, Schmid C, Rozenfeld B (2008) Learning realistic human actions from movies. 2008 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)
10. Li ZJ, da Silva AM, Cunha JPS (2002) Movement quantification in epileptic seizures: A new approach to video-eeg analysis. IEEE Transactions on Biomedical Engineering 49(6):565-573
11. Lockman J, Fisher RS, Olson DM (2011) Detection of seizurelike movements using a wrist accelerometer. Epilepsy & Behavior 20(4):638-641
12. Nijsen TME, Aarts RM, Cluitmans PJM, Griep PAM (2010) Time-frequency analysis of accelerometry data for detection of my-oclonic seizures. IEEE Transactions on Information Technology in Biomedicine 14(5):1197-1203
13. Poppe R (2010) A survey on vision-based human action recognition. Image and Vision Computing 28(6):976-990
14. Schuldt C, Laptev I, Caputo B (2004) Recognizing human actions: A local svm approach. In: 17th International Conference on Pattern Recognition (ICPR), pp 32-36