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Visualization process assisted by the Eulerian video magnification algorithm for a heart rate monitoring system: mobile applications

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Abstract

Medical technology employs a range of different computational methods for analyzing noninvasive heart rate monitoring processes. During the heart rate monitoring process, accurate heart rate detection is difficult which is overcome by applying the effective image processing techniques. Thus, the present study offers a mobile application framework that uses video frames captured from mobile camera. These video frames are analyzed by Eulerian video magnification (EVM) with a region extraction technique for efficiently detecting and monitoring heart rates. Initially, EVM captures the feelings of the subject from a face visualization process. Then, temporal filtering and spatial decomposition methods are applied to reconstruct the video frames. Subtle changes in the face image are extracted from the video frames by applying an enhanced multi-scale segmentation technique. The segmented region from the face helps to identify the intensity level of the green channel feature, which differs from the normal red and blue channel features. This process identifies the hidden heart rate from the region extracted by the EVM visualization process. Finally, system efficiency is evaluated in terms of the estimated heart rate, actual heart rate, and heart rate accuracy. The mobile based video magnification analyzing process reduces mortality rate, and accurately examines heart rates.

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References

  1. Abuzaghleh O et al. (2015) Noninvasive Real-Time Automated Skin Lesion Analysis System for Melanoma Early Detection and Prevention. IEEE J Transl Eng Health Med 3

    Article  Google Scholar 

  2. Altameem T, Alfarraj O, Zanaty EA, Tolba A, Ibrahim SM (2016) Performance analysis of medical image compression using various wavelet techniques. Journal of Medical Imaging and Health Informatics 6(6):1451–1461

    Article  Google Scholar 

  3. Altameem T, Zanaty EA, Tolba A (2015) A new fuzzy C-means method for magnetic resonance image brain segmentation. Connect Sci 27(4):305–321

    Article  Google Scholar 

  4. Altameem T, Zanaty EA, Tolba A, Asaad A (2016) Surface–surface tissue reconstruction and visualization for the magnetic resonance imaging or tomography imaging engineering design. Journal of Medical Imaging and Health Informatics 6(6):1462–1468

    Article  Google Scholar 

  5. Alzahrani A, Whitehead A (2015) Preprocessing Realistic Video for Contactless Heart Rate Monitoring Using Video Magnification. International conference on Computer and Robot Vision (CRV) in IEEE

  6. Balakrishnan G, Durand F, Gutta J, (2013) Detecting Pulse from Head Motions in Video. IEEE Computer Society Washington, Proceedings of the 2013 IEEE Conference on Computer Vision and Pattern Recognition, pp. 3430–3437

  7. Belkouch S, Bahtat M (2010) An Enhanced Algorithm of the Statistical Training method in boosting-based face detection. IJCSI International Journal of Computer Sciences 7(6)

  8. Shafqat S, Kishwer S, Rasool RU, Qadir J, Amjad T, Ahmad HF (2018) Big data analytics enhanced healthcare systems: a review. J Supercomput 1–46. https://doi.org/10.1007/s11227-017-2222-4

  9. Chandak et al (2016) An application of Haar wavelet decomposition in video frames preservation in association with visual cryptography. International Journal on Recent and Innovation Trends in Computing and Communication 4(12):57–62

    Google Scholar 

  10. Cheng Y, Cheung G, Stankovic V (2015) Estimating Heart Rate Via Depth Video Motion Tracking. International conference on Multimedia and Expo (ICME) in IEEE

  11. Hao-Yu W, Rubinstein M, Shih E, Guttag J, Durand F, Freeman W (2012) Eulerian video magnification for revealing subtle changes in the world. Journal ACM Transactions on Graphics (TOG) TOG Homepage archive, (31) 4

  12. Wadhwa N, Wu HY, Davis A, Rubinstein M, Shih E, Mysore GJ, Durand F (2016) Eulerian video magnification and analysis. Commun ACM 60(1):87–95

    Article  Google Scholar 

  13. Kamble K, Jagtap N, Patil RA, Bhurane A (2015) A Review: Eulerian Video Motion Magnification. International Journal of Innovative Research in Computer and Communication Engineering 3(3)

  14. Koolen N, Decroupet O, Dereymaeker A, Jansen K, Vervisch J, Matic V, Vanrumste B, Naulaers G, Van Huffel S, De Vos M (2015) Automated respiration detection from neonatal video data. ICPRAM 2015 Proceedings of the International Conference on Pattern Recognition Applications and Methods 2:164–169

    Google Scholar 

  15. Ming-Zher P, McDuff DJ, Picard RW (2010) Noncontact, automated cardiac pulse measurements using video imaging and blind source separation. Opt Express 10:10762–10774

    Google Scholar 

  16. Osman A, Turcot J, El Kaliouby R (2015) Supervised learning approach to remote heart rate estimation from facial videos. 11th IEEE International Conference and Workshops on Automatic Face and Gesture Recognition (FG), 1:1–6

  17. Pursche T, Krajewski J, Moeller R (2012) Video base Heart Rate Measurement from Human Faces. IEEE International Conference on Consumer Electronics

  18. Qayyum H et al. (2017) Facial Expression Recognition Using Stationary Wavelet Transform Features. Mathematical Problems in Engineering pp-1-9

  19. Verkruysse W, Svaasand LO, Nelson JS (2008) Remote plethysmographic imaging using ambient light. Opt Express 16(26):21434–21445. https://doi.org/10.1364/OE.16.021434

    Article  Google Scholar 

  20. Yandan Wang et.al (2017) Effective recognition of facial micro-expressions with video motion magnification. International Journal of Multimedia Tools and Applications 76(20):21665–21690

  21. Xiaochuan H, Goubran RA, Liu XP (2016) Wrist pulse measurement and analysis using Eulerian video magnification. IEEE-EMBS International Conference on Biomedical and Health Informatics (BHI), pp. 41–44

  22. Yong-Poh Y, Raveendran P, Chern-Loon L (2015) Dynamic heart rate measurements from video sequences. Biomed Opt Express 6(7):2466–2480. https://doi.org/10.1364/BOE.6.002466

    Article  Google Scholar 

  23. Yuan Fang L, Vuong C, Walker PC, Peterson NR, Inman JC, Filho PAA, and Lee S C-S (2016) Noninvasive Free Flap Monitoring Using Eulerian Video Magnification. Case Rep Otolaryngol 9471696

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Acknowledgments

“This research was supported by King Saud University, Deanship of Scientific Research, Community College Research Unit. “.

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Correspondence to Azza S. Hassanein.

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Alarifi, A., Tolba, A. & Hassanein, A.S. Visualization process assisted by the Eulerian video magnification algorithm for a heart rate monitoring system: mobile applications. Multimed Tools Appl 79, 5149–5160 (2020). https://doi.org/10.1007/s11042-018-6313-x

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  • DOI: https://doi.org/10.1007/s11042-018-6313-x

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