cvpr cvpr2013 cvpr2013-118 cvpr2013-118-reference knowledge-graph by maker-knowledge-mining
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Author: Guha Balakrishnan, Fredo Durand, John Guttag
Abstract: We extract heart rate and beat lengths from videos by measuring subtle head motion caused by the Newtonian reaction to the influx of blood at each beat. Our method tracks features on the head and performs principal component analysis (PCA) to decompose their trajectories into a set of component motions. It then chooses the component that best corresponds to heartbeats based on its temporal frequency spectrum. Finally, we analyze the motion projected to this component and identify peaks of the trajectories, which correspond to heartbeats. When evaluated on 18 subjects, our approach reported heart rates nearly identical to an electrocardiogram device. Additionally we were able to capture clinically relevant information about heart rate variability.
[1] L. Adde et al. Early prediction of cerebral palsy by computer-based video analysis of general movements: a feasibility study. Developmental Medicine & Child Neurology, 52:773–778, 2010.
[2] G. Bonmassar et al. Motion and ballistocardiogram artifact removal for interleaved recording of eeg and eps during mri. NeuroImage, 16: 1127–1 141, 2001.
[3] G. Bradski. The OpenCV Library. Dr. Dobb’s Journal of Software Tools, 2000.
[4] S. Chen et al. Quantification and recognition of parkinsonian gait from monocular video imaging using kernelbased principal component analysis. BioMedical Engineering OnLine, 10, 2011.
[5] M. Delano. A long term wearable electrocardiogram (ecg) measurement system. Master’s Thesis, Massachusetts Institute of Technology, 2012.
[6] M. Garbey et al. Contact-free measurement of cardiac pulse based on the analysis of thermal imagery. IEEE Trnas Biomed Eng, 54(8):1418–1426, 2007.
[7] D. He. A continuous, wearable, and wireless heart monitor using head ballistocardiogram (bcg) and head electrocardio-
[8]
[9]
[10]
[11]
[12]
[13]
[14]
[15]
[16]
[17]
[18] gram (ecg). Conf Proc IEEE Eng Med Biol Soc. 2011, 2011, 2011. O. Inan et al. Robust ballistocardiogram acquisition for home monitoring. Physiological Measurement, 30: 169–185, 2009. K. Kim et al. A new method for unconstrained pulse arrival time measurement on a chair. J. Biomed. Eng. Res., 27:83– 88, 2006. C. Liu et al. Motion magnification. ACM Trans. Graph. , 24:519. P. Lynch. Human head anatomy with external and internal carotid arteries. http : / /www . fli ckr . com/phot o s / pat rlynch/ 4 5 0 14 2 0 19, 2007. M. Pediaditis et al. Vision-based human motion analysis in epilepsy - methods and challenges. Proceedings of IEEE ITAB, pages 1–5, 2010. Philips. Philips vitals signs camera. http : / /www . vit al s igns camera . com, 2011. M. Poh et al. Non-contact, automated cardiac pulse measurements using video imaging and blind source separation. Optics Express, 18(10): 10762–10774, 2010. I. Starr et al. Studies on the estimation of cardiac output in man, and of abnormalities in cardiac function, from the hearts recoil and the bloods impacts; the ballistocardiogram. The American Journal of Physiology, 127: 1–28, 1939. Z. Syed et al. Computationally generated cardiac biomarkers for risk stratification after acute coronary syndrome. Sci Transl Med, 3(102): 102ra95, 2011. K. Tan et al. Real-time vision based respiration monitoring system. Proceedings of CSNDSP, pages 770–774, 2010. W. Verkruysse et al. Remote plethysmographic imaging using ambient light. Optics Express, 16(26):21434–21445,
[19]
[20]
[21]
[22] 2008. P. Viola and M. Jones. Rapid object detection using a boosted cascade of simple features. Proceedings of IEEE Conference on Computer Vision and Patern Recognition, pages 511–5 18, 2001. C. Wang et al. Vision analysis in detecting abnormal breathing activity in application to diagnosis of obstructive sleep apnoea. Proceedings of IEEE Eng Med Biol Soc, pages 4469–4473, 2006. F. Wieringa et al. Contactless multiple wavelength photoplethysmographic imaging: a first step toward spo2 camera technology. Ann. Biomed. Eng., 33(8): 1034–1041, 2005. H. Wu et al. Eulerian video magnification for revealing subtle changes in the world. ACM Trans. Graph. (Proceedings SIGGRAPH 2012), 31(4), 2012. 333444333755