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Home / programming language / Online Java Projects / Evaluation of Video Magnification for Nonintrusive Heart Rate Measurement
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Evaluation of Video Magnification for Nonintrusive Heart Rate Measurement

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SKU: PROJ7724 Categories: 2017 Projects, Datamining Projects, Online Java Projects Tags: Android Project, Asp.Net Project, C# Project, Computer Engineering Final Year Projects, Computer Science Final Year Projects, Electronics Projects Engineering Students Final Year, Engineering Student Project Ideas, Final Semester Projects, Final Year Project Center, Final Year Projects, ieee ECE Projects, ieee EEE Projects, ieee Final Year Projects, IEEE Projects, ieee Projects Networking, Image Processing Projects, J2EE Project, Java Project, Java Project Code, Matlab Project, PHP Project, Students Projects
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Evaluation of Video Magnification for Nonintrusive Heart Rate Measurement

Abstract—Measurements of physiological signals have been used in many areas, including medical, sports, and automotive applications. Cardiac signals such as electrocardiogram (ECG) and heart rate variability (HRV) are particularly important, but conventional measurement techniques require wired devices and static subjects. These limitations preclude application of these devices from various dynamic scenarios. Recently, however, developments in computer vision have shown that some physiological variables related to the heart can be measured in a non intrusive way. “Video magnification” (VidMag) is one such technique, and it has been used to measure blood volume pulse (BVP) from face video data in laboratory settings. This paper discusses the readiness of VidMag for psychophysiological assessment more generally. The approach is to assess beat-by-beat comparison of VidMag with BVP signals extracted from medical devices. In addition, a novel skin detection algorithm, which does not use color cues, has been proposed in this paper as a preprocessing step to support VidMag. The paper also presents a systematic post-processing strategy using Savitzky-Golay filtering to improve the accuracy of the raw output from the video magnification algorithm< final year rojects >

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