Photoplethysmographic analysis of retinal videodata based on the Fourier domain approach

Kolář, Radim; Odstrčilík, Jan; Tornow, Ralf P.

doi:10.1364/boe.441451

Cited by 3 publications

(11 citation statements)

References 40 publications

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“…However, the light intensity also changed as a result of eye/head movements and pupil dilation. To compensate for these changes that do not occur in the cardiac cycle, the relative intensity I′(n) is calculated [10, 20]:

I^{'} ((), n) goodbreak= \frac{I ((), n)}{I_{avg} ((), n)},

where I avg (n) is the trend signal. This equation can also be interpreted as a relative light transmission, which can be turned into a relative light absorption A(n) as [10, 20]:

A ((), n) goodbreak= 100 . ((), 1 goodbreak- \frac{I ((), n)}{I_{avg} ((), n)}) .

…”

Section: Methodsmentioning

confidence: 99%

“…Detailed descriptions of the underlying principles and calculations were already published [10]. Furthermore, the PAA can be computed in the frequency domain with the Fourier transform as [20]

italicPAA ((), x, y) goodbreak= 100 . ((), \frac{2 . {Amp}_{1}}{1 + {Amp}_{1}} goodbreak+ \frac{2 . {Amp}_{2}}{1 + {Amp}_{2}}),

where Amp 1 and Amp 2 represent the amplitude of the fundamental and second harmonic frequency of the pulsation signal, respectively. The fundamental frequency is determined by the heart rate, and it is estimated from the pulsation signals.…”

Section: Methodsmentioning

confidence: 99%

“…In our previous papers [10,19,20], we introduced the concept of retinal photoplethysmography applied to retinal video sequences. The main idea was based on the cardiac cycle-induced temporal changes of light intensity in a specific retinal region.…”

Section: Retinal Photoplethysmographychanges In Light Intensitymentioning

confidence: 99%

Section: Retinal Photoplethysmographychanges In Light Intensitymentioning

confidence: 99%

“…where I avg (n) is the trend signal. This equation can also be interpreted as a relative light transmission, which can be turned into a relative light absorption A(n) as [10,20]:…”

Section: Retinal Photoplethysmographychanges In Light Intensitymentioning

confidence: 99%

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Multispectral retinal video‐ophthalmoscope with fiber optic illumination

Kolář

Vičar

Odstrčilík

et al. 2022

Journal of Biophotonics

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Multispectral imaging is used in various applications including astronomy, industry and agriculture. In retinal imaging, the single-shot multispectral image stack is typically acquired and analyzed. This multispectral analysis can provide information on various structural or metabolic properties. This paper describes the multispectral improvement of a videoophthalmoscope, which can acquire retinal video sequences of the optic nerve head and peripapillary area using various spectral light illumination. The description of the multispectral video imaging is provided and several applications are described. These applications include multispectral retinal photoplethysmography, visualization of spontaneous vein pulsation and multispectral RGB image generation.

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I^{'} ((), n) goodbreak= \frac{I ((), n)}{I_{avg} ((), n)},

where I avg (n) is the trend signal. This equation can also be interpreted as a relative light transmission, which can be turned into a relative light absorption A(n) as [10, 20]:

A ((), n) goodbreak= 100 . ((), 1 goodbreak- \frac{I ((), n)}{I_{avg} ((), n)}) .

…”

Section: Methodsmentioning

confidence: 99%

“…Detailed descriptions of the underlying principles and calculations were already published [10]. Furthermore, the PAA can be computed in the frequency domain with the Fourier transform as [20]

italicPAA ((), x, y) goodbreak= 100 . ((), \frac{2 . {Amp}_{1}}{1 + {Amp}_{1}} goodbreak+ \frac{2 . {Amp}_{2}}{1 + {Amp}_{2}}),

Section: Methodsmentioning

confidence: 99%

Section: Retinal Photoplethysmographychanges In Light Intensitymentioning

confidence: 99%

Section: Retinal Photoplethysmographychanges In Light Intensitymentioning

confidence: 99%

“…where I avg (n) is the trend signal. This equation can also be interpreted as a relative light transmission, which can be turned into a relative light absorption A(n) as [10,20]:…”

Section: Retinal Photoplethysmographychanges In Light Intensitymentioning

confidence: 99%

See 3 more Smart Citations

Multispectral retinal video‐ophthalmoscope with fiber optic illumination

Kolář

Vičar

Odstrčilík

et al. 2022

Journal of Biophotonics

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Assessment of retinal vein pulsation through video-ophthalmoscopy and simultaneous biosignals acquisition

Kolář¹,

Vičar²,

Chmelík³

et al. 2023

Biomed. Opt. Express

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The phenomenon of retinal vein pulsation is still not a deeply understood topic in retinal hemodynamics. In this paper, we present a novel hardware solution for recording retinal video sequences and physiological signals using synchronized acquisition, we apply the photoplethysmographic principle for the semi-automatic processing of retinal video sequences and we analyse the timing of the vein collapse within the cardiac cycle using of an electrocardiographic signal (ECG). We measured the left eyes of healthy subjects and determined the phases of vein collapse within the cardiac cycle using a principle of photoplethysmography and a semi-automatic image processing approach. We found that the time to vein collapse (Tvc) is between 60 ms and 220 ms after the R-wave of the ECG signal, which corresponds to 6% to 28% of the cardiac cycle. We found no correlation between Tvc and the duration of the cardiac cycle and only a weak correlation between Tvc and age (0.37, p = 0.20), and Tvc and systolic blood pressure (-0.33, p = 0.25). The Tvc values are comparable to those of previously published papers and can contribute to the studies that analyze vein pulsations.

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Comparative analysis of retinal photoplethysmographic spatial maps and thickness of retinal nerve fiber layer

et al. 2023

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The paper presents a comparative study of the pulsatile attenuation amplitude (PAA) within the optic nerve head (ONH) at four different areas calculated from retinal video sequences and its relevance to the retinal nerve fiber layer thickness (RNFL) changes in normal subjects and patients with different stages of glaucoma. The proposed methodology utilizes processing of retinal video sequences acquired by a novel video ophthalmoscope. The PAA parameter measures the amplitude of heartbeat-modulated light attenuation in retinal tissue. Correlation analysis between PAA and RNFL is performed in vessel-free locations of the peripapillary region with the proposed evaluating patterns: 360° circular area, temporal semi-circle, nasal semi-circle. For comparison, the full ONH area is also included. Various positions and sizes of evaluating patterns in peripapillary region were tested which resulted in different outputs of correlation analysis. The results show significant correlation between PAA and RNFL thickness calculated in proposed areas. The highest correlation coefficient Rtemp = 0.557 (p<0.001) reflects the highest PAA-RNFL correspondence in the temporal semi-circular area, compared to the lowest value in the nasal semi-circular area (Rnasal = 0.332, p<0.001). Furthermore, the results indicate the most relevant approach to calculate PAA from the acquired video sequences is using a thin annulus near the ONH center. Finally, the paper shows the proposed photoplethysmographic principle based on innovative video ophthalmoscope can be used to analyze changes in retinal perfusion in peripapillary area and can be potentially used to assess progression of the RNFL deterioration.

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Photoplethysmographic analysis of retinal videodata based on the Fourier domain approach

Cited by 3 publications

References 40 publications

Multispectral retinal video‐ophthalmoscope with fiber optic illumination

Multispectral retinal video‐ophthalmoscope with fiber optic illumination

Assessment of retinal vein pulsation through video-ophthalmoscopy and simultaneous biosignals acquisition

Comparative analysis of retinal photoplethysmographic spatial maps and thickness of retinal nerve fiber layer

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