artefacts than the red PPG signal. In this case, the
recorded signals in the conditions of eye vertical
oscillations have a lower SNR ratio than for signals
that were recorded under the conditions of eye
horizontal oscillations. This can be explained by a
change in the thickness of the eyelid layers in which
the PPG signal is recorded.
Even higher SNR ratios can be achieved using the
vPPG method. This method demonstrates the spectral
component of the signal, similar to the previous PPG
method. When the signal vPPG is decomposed into
components, it is characterized similarly to the signal
recorded from the eyelid skin surface.
4 CONCLUSIONS
As a result of the studies, it was shown that using the
proposed method, it is possible to carry out a
quantitative assessment of blood flow both in the
eyelid skin and in deeper tissues. This allows
supplementing the non-invasive diagnostic method
with a new research algorithm. In this case, the doctor
receives additional diagnostic information about the
blood flow both in the eyelid and in eye structures. It
also becomes possible to calculate blood flow
parameters in each structure of the study area, which
increases the diagnostic value of such studies.
The conducted researches confirm possibility of
using PPG sensor on the closed eyelid. Authors note
a possibility of simultaneous research TP ROG and
PPG signals for the control of individual eyelid
features and for the rising accuracy of ocular blood
filling determining during transpalpebral diagnostics
in the future.
CONFLICT OF INTEREST
The authors declare that they have no conflict of
interest. The paper was supported by a grant from
RFBR (No.18-08-01192).
REFERENCES
Allen, J., 2007. Photoplethysmography and its application
in clinical physiological measurement. Physiol. Meas.
28(3): R1–R39.
Kurysheva, N.I., Parshunina, O.A., Shatalova, E.O., et al.,
2017. Value of structural and hemodynamic parameters
for the early detection of primary open-angle glaucoma.
Curr. Eye Res. 42(3): 411–417.
Lazarenko, V.I., Kornilovsky, I.M., Ilenkov, S.S. et al.,
1999. Our method of functional rheography of eye.
Vestnik oftalmologii 115(4): 33–37.
Liu, J., Ping-Yen Yan, B., Wen-Xuan Dai, et al., 2016.
Multi-wavelength photoplethysmography method for
skin arterial pulse extraction. Biomedical optic express
7(10): 4326. DOI: 10.1364/BOE.7.004313
Luzhnov, P.V., Shamaev, D.M., Iomdina, E.N. et al., 2015.
Transpalpebral tetrapolar rheoophtalmography in the
assessment of parameters of the eye blood circulatory
system. Vestn Ross Akad Med Nauk 70(3): 372–377.
DOI: 10.15690/vramn.v70i3.1336
Luzhnov, P.V., Shamaev, D.M., Iomdina, E.N., et al., 2017.
Using quantitative parameters of ocular blood filling
with transpalpebral rheoophthalmography. IFMBE
Proceedings 65: 37–40. DOI:10.1007/978-981-10-
5122-7_10
Rubins, U., Erts, R., and Nikiforovs, V., 2010. The blood
perfusion mapping in the human skin by
photoplethysmography imaging. IFMBE Proceedings
29: 304–306.
Rubins, U., Spigulis, J., Miscuks, A., 2016.
Photoplethysmography imaging algorithm for
continuous monitoring of regional anesthesia. Proc. of
14th ACM/IEEE Symposium on Embedded Systems for
Real-Time Multimedia : 67-71.
Shamaev, D. M., Luzhnov, P. V., Iomdina, E. N., 2018.
Mathematical modeling of ocular pulse blood filling in
rheoophthalmography. IFMBE Proceedings 68(1):
495–498. DOI: 10.1007/978-981-10-9035-6_91
Shamaev, D.M., Luzhnov, P.V., Iomdina, E.N., 2017.
Modeling of ocular and eyelid pulse blood filling in
diagnosing using transpalpebral rheoophthalmography.
IFMBE Proceedings 65: 1000–1003. DOI:10.1007/9
78-981-10-5122-7_250
Tamura, T., Maeda, Y., Sekine, M., and Yoshida, M., 2014.
Wearable photoplethysmographic sensors – past and
present. Electronics 3(2): 282–302.