Analisis Photoplethysmography Jarak Jauh dalam berbagai Kondisi Pencahayaan

https://doi.org/10.22146/ijeis.78715

Atar Fuady Babgei(1*), Muhammad Wikan Sasongko(2), Tri Arief Sardjono(3)

(1) Department of Computer Engineering, Institut Teknologi Sepuluh Nopember, Surabaya
(2) Department of Biomedical Engineering, Institut Teknologi Sepuluh Nopember, Surabaya
(3) Department of Biomedical Engineering, Institut Teknologi Sepuluh Nopember, Surabaya
(*) Corresponding Author

Abstract


One of the limitations of photoplethysmography (PPG) using a contact sensor to estimate the heart rate is that the sensor must be attached directly to the patient's body. rPPG (remote-Photoplethysmography) can remotely monitor a patient's heart ratebased on an image. However, rPPG  has  limitations  in  instances  where  this  technology  is  directly  affected  by  the  lighting conditions  and  direction  of  the  observed  subject. This  study  used  rPPG  based  on  the  Green Channel and HSV (Hue, Saturation, and Value) color model to estimate heart rate under different lighting  conditions. Analysis,  computational  methods,and  image  transformation  functions  are used for data selection, denoising, colormodel conversion, spectral analysis, and visualization to  extract  biomedical  signals from  inputs. The  estimatedheart  rate was then derivedusing spectral  analysis  on videostaken  from  an  area  of  interest  on  the  forehead. Compared  to  the ground truth, theaverage percentage error from the facial lighting tests conducted at 260 lux, 19 lux, and 11 lux for the Green Channel color modelis 0.038, 0.118, and 0.229, which is less than the HSV's error of 0.095, 0.212, and 0.247.


Keywords


RemotePhotoplethysmography; Hearth Rate Estimation; Spectral Analysis

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References

[1] L. Xi, X. Wu, W. Chen, J. Wang, and C. Zhao, “Weighted combination and singular spectrum analysis based remote photoplethysmography pulse extraction in low-light environments,” Med. Eng. Phys., vol. 105, p. 103822, Jul. 2022, doi: 10.1016/j.medengphy.2022.103822.

[2] J. Chen, K. Sun, Y. Sun, and X. Li, “Signal Quality Assessment of PPG Signals using STFT Time-Frequency Spectra and Deep Learning Approaches,” in 2021 43rd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC), Nov. 2021, pp. 1153–1156. doi: 10.1109/EMBC46164.2021.9630758.

[3] L. Xi, W. Chen, C. Zhao, X. Wu, and J. Wang, “Image Enhancement for Remote Photoplethysmography in a Low-Light Environment,” in 2020 15th IEEE International Conference on Automatic Face and Gesture Recognition (FG 2020), Nov. 2020, pp. 1–7. doi: 10.1109/FG47880.2020.00076.

[4] B.-F. Wu, P.-W. Huang, C.-H. Lin, M.-L. Chung, T.-Y. Tsou, and Y.-L. Wu, “Motion Resistant Image-Photoplethysmography Based on Spectral Peak Tracking Algorithm,” IEEE Access, vol. 6, pp. 21621–21634, 2018, doi: 10.1109/ACCESS.2018.2828133.

[5] W. Wang, A. C. den Brinker, S. Stuijk, and G. de Haan, “Algorithmic Principles of Remote PPG,” IEEE Trans. Biomed. Eng., vol. 64, no. 7, pp. 1479–1491, Jul. 2017, doi: 10.1109/TBME.2016.2609282.

[6] S. Tulyakov, X. Alameda-Pineda, E. Ricci, L. Yin, J. F. Cohn, and N. Sebe, “Self-Adaptive Matrix Completion for Heart Rate Estimation from Face Videos under Realistic Conditions,” in 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Jun. 2016, pp. 2396–2404. doi: 10.1109/CVPR.2016.263.

[7] A. Procházka, M. Schätz, O. Vyšata, and M. Vališ, “Microsoft Kinect Visual and Depth Sensors for Breathing and Heart Rate Analysis,” Sensors, vol. 16, no. 7, Art. no. 7, Jul. 2016, doi: 10.3390/s16070996.

[8] W. Verkruysse, L. O. Svaasand, and J. S. Nelson, “Remote plethysmographic imaging using ambient light,” Opt. Express, vol. 16, no. 26, pp. 21434–21445, Dec. 2008.

[9] M. A. Hassan, G. S. Malik, N. Saad, B. Karasfi, Y. S. Ali, and D. Fofi, “Optimal source selection for image photoplethysmography,” in 2016 IEEE International Instrumentation and Measurement Technology Conference Proceedings, May 2016, pp. 1–5. doi: 10.1109/I2MTC.2016.7520406.

[10] G. de Haan and V. Jeanne, “Robust Pulse Rate From Chrominance-Based rPPG,” IEEE Trans. Biomed. Eng., vol. 60, no. 10, pp. 2878–2886, Oct. 2013, doi: 10.1109/TBME.2013.2266196.

[11] L. Xi, W. Chen, C. Zhao, X. Wu, and J. Wang, “Image Enhancement for Remote Photoplethysmography in a Low-Light Environment,” in 2020 15th IEEE International Conference on Automatic Face and Gesture Recognition (FG 2020), Nov. 2020, pp. 1–7. doi: 10.1109/FG47880.2020.00076.

[12] H. Liu, Y. Wang, and L. Wang, “The Effect of Light Conditions on Photoplethysmographic Image Acquisition Using a Commercial Camera,” IEEE J. Transl. Eng. Health Med., vol. 2, pp. 1–11, 2014, doi: 10.1109/JTEHM.2014.2360200.

[13] P. Viola and M. Jones, “Robust real-time face detection,” in Proceedings Eighth IEEE International Conference on Computer Vision. ICCV 2001, Jul. 2001, vol. 2, pp. 747–747. doi: 10.1109/ICCV.2001.937709.

[14] “Motion Resistant Image-Photoplethysmography Based on Spectral Peak Tracking Algorithm | IEEE Journals & Magazine | IEEE Xplore.” https://ieeexplore.ieee.org/document/8340779 (accessed Oct. 22, 2022).

[15] N. Spicher, S. Maderwald, M. E. Ladd, and M. Kukuk, “Heart rate monitoring in ultra-high-field MRI using frequency information obtained from video signals of the human skin compared to electrocardiography and pulse oximetry,” Curr. Dir. Biomed. Eng., vol. 1, no. 1, pp. 69–72, Sep. 2015, doi: 10.1515/cdbme-2015-0018.



DOI: https://doi.org/10.22146/ijeis.78715

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