Abstract

We introduce a novel, noninvasive retinal eye-tracking system capable of detecting eye displacements with an angular resolution of 0.039 arcmin and a maximum velocity of 300°/s across an 8° span. Our system is designed based on a confocal retinal imaging module similar to a scanning laser ophthalmoscope. It utilizes a 2D MEMS scanner ensuring high image frame acquisition frequencies up to 1.24 kHz. In contrast with leading eye-tracking technology, we measure the eye displacements via the collection of the observed spatial excursions for all the times corresponding a full acquisition cycle, thus obviating the need for both a baseline reference frame and absolute spatial calibration. Using this approach, we demonstrate the precise measurement of eye movements with magnitudes exceeding the spatial extent of a single frame, which is not possible using existing image-based retinal trackers. We describe our retinal tracker, tracking algorithms and assess the performance of our system by using programmed artificial eye movements. We also demonstrate the clinical capabilities of our system with in vivo subjects by detecting microsaccades with angular extents as small as 0.028°. The rich kinematic ocular data provided by our system with its exquisite degree of accuracy and extended dynamic range opens new and exciting avenues in retinal imaging and clinical neuroscience. Several subtle features of ocular motion such as saccadic dysfunction, fixation instability and abnormal smooth pursuit can be readily extracted and inferred from the measured retinal trajectories thus offering a promising tool for identifying biomarkers of neurodegenerative diseases associated with these ocular symptoms.

© 2020 Optical Society of America under the terms of the OSA Open Access Publishing Agreement

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2019 (3)

J. Kerr-Gaffney, A. Harrison, and K. Tchanturia, “Eye-tracking research in eating disorders: A systematic review,” Int. J. Eat. Disord. 52(1), 3–27 (2019).
[Crossref]

C. Viviane, K. Peter, and K. Sabine, “Eye tracking in virtual reality,” J. Eye Mov. Res. 12(1), 1–8 (2019).
[Crossref]

J. A. Bijvank, L. J. Van Rijn, L. J. Balk, H. S. Tan, B. M. J. Uitdehaag, and A. Petzold, “Diagnosing and quantifying a common deficit in multiple sclerosis: Internuclear ophthalmoplegia,” Neurology 92(20), e2299–e2308 (2019).
[Crossref]

2018 (5)

C. C. Wu, B. Cao, V. Dali, C. Gagliardi, O. J. Barthelemy, R. D. Salazar, M. Pomplun, A. Cronin-Golomb, and A. Yazdanbakhsh, “Eye movement control during visual pursuit in Parkinson’s disease,” PeerJ 6, e5442 (2018).
[Crossref]

R. M. Mallery, P. Poolman, M. J. Thurtell, J. M. Full, J. Ledolter, D. Kimbrough, E. M. Frohman, T. C. Frohman, and R. H. Kardon, “Visual fixation instability in multiple sclerosis measured using SLO-OCT,” Invest. Ophthalmol. Visual Sci. 59(1), 196–201 (2018).
[Crossref]

F. Lengwiler, D. Rappoport, G. P. Jaggi, K. Landau, and G. L. Traber, “Reliability of Cyclotorsion measurements using Scanning Laser Ophthalmoscopy imaging in healthy subjects: The CySLO study,” Br. J. Ophthalmol. 102(4), 535–538 (2018).
[Crossref]

K. V. Vienola, M. Damodaran, B. Braaf, K. A. Vermeer, and J. F. de Boer, “In vivo retinal imaging for fixational eye motion detection using a high-speed digital micromirror device (DMD)-based ophthalmoscope,” Biomed. Opt. Express 9(2), 591–602 (2018).
[Crossref]

M. Azimipour, R. J. Zawadzki, I. Gorczynska, J. Migacz, J. S. Werner, and R. S. Jonnal, “Intraframe motion correction for raster-scanned adaptive optics images using strip-based cross-correlation lag biases,” PLoS One 13(10), e0206052–24 (2018).
[Crossref]

2017 (2)

A. E. Salmon, R. F. Cooper, C. S. Langlo, A. Baghaie, A. Dubra, and J. Carroll, “An automated reference frame selection (ARFS) algorithm for cone imaging with adaptive optics scanning light ophthalmoscopy,” Trans. Vis. Sci. Tech. 6(2), 9–15 (2017).
[Crossref]

M. Damodaran, K. V. Vienola, B. Braaf, K. A. Vermeer, and J. F. de Boer, “Digital micromirror device based ophthalmoscope with concentric circle scanning,” Biomed. Opt. Express 8(5), 2766–2780 (2017).
[Crossref]

2016 (2)

S. B. Stevenson, C. K. Sheehy, and A. Roorda, “Binocular eye tracking with the tracking scanning laser ophthalmoscope,” Vision Res. 118, 98–104 (2016).
[Crossref]

M. R. MacAskill and T. J. Anderson, “Eye movements in neurodegenerative diseases,” Curr. Opin. Neurol. 29(1), 61–68 (2016).
[Crossref]

2015 (2)

2014 (2)

2013 (5)

B. Braaf, K. V. Vienola, C. K. Sheehy, Q. Yang, K. A. Vermeer, P. Tiruveedhula, D. W. Arathorn, A. Roorda, and J. F. de Boer, “Real-time eye motion correction in phase-resolved OCT angiography with tracking SLO,” Biomed. Opt. Express 4(1), 51–65 (2013).
[Crossref]

S. Martinez-Conde, J. Otero-Millan, and S. L. Macknik, “The impact of microsaccades on vision: towards a unified theory of saccadic function,” Nat. Rev. Neurosci. 14(2), 83–96 (2013).
[Crossref]

F. LaRocca, A.-H. Dhalla, M. P. Kelly, S. Farsiu, and J. A. Izatt, “Optimization of confocal scanning laser ophthalmoscope design,” J. Biomed. Opt. 18(7), 076015 (2013).
[Crossref]

J. Otero-Millan, R. Schneider, R. J. Leigh, S. L. Macknik, and S. Martinez-Conde, “Saccades during attempted fixation in Parkinsonian disorders and recessive ataxia: from microsaccades to square-wave jerks,” PLoS One 8(3), e58535 (2013).
[Crossref]

L. Thaler, A. C. Schütz, M. A. Goodale, and K. R. Gegenfurtner, “What is the best fixation target? The effect of target shape on stability of fixational eye movements,” Vision Res. 76, 31–42 (2013).
[Crossref]

2012 (6)

A. B. Watson and J. I. Yellott, “A unified formula for light-adapted pupil size,” J. Vis. 12(10), 12 (2012).
[Crossref]

P. J. Benson, S. A. Beedie, E. Shephard, I. Giegling, D. Rujescu, and D. St. Clair, “Simple viewing tests can detect eye movement abnormalities that distinguish schizophrenia cases from controls with exceptional accuracy,” Biol. Psychiatry 72(9), 716–724 (2012).
[Crossref]

G. T. Gitchel, P. A. Wetzel, and M. S. Baron, “Pervasive ocular tremor in patients with Parkinson disease,” Arch. Neurol. 69(8), 1011–1017 (2012).
[Crossref]

M. Nowakowski, M. Sheehan, D. Neal, and A. V. Goncharov, “Investigation of the isoplanatic patch and wavefront aberration along the pupillary axis compared to the line of sight in the eye,” Biomed. Opt. Express 3(2), 240–258 (2012).
[Crossref]

C. K. Sheehy, Q. Yang, D. W. Arathorn, P. Tiruveedhula, J. F. de Boer, and A. Roorda, “High-speed, image-based eye tracking with a scanning laser ophthalmoscope,” Biomed. Opt. Express 3(10), 2611–2622 (2012).
[Crossref]

K. V. Vienola, B. Braaf, C. K. Sheehy, Q. Yang, P. Tiruveedhula, D. W. Arathorn, J. F. de Boer, and A. Roorda, “Real-time eye motion compensation for OCT imaging with tracking SLO,” Biomed. Opt. Express 3(11), 2950–2963 (2012).
[Crossref]

2011 (2)

J. Otero-Millan, A. Serra, R. J. Leigh, X. G. Troncoso, S. L. Macknik, and S. Martinez-Conde, “Distinctive features of saccadic intrusions and microsaccades in progressive supranuclear palsy,” J. Neurosci. 31(12), 4379–4387 (2011).
[Crossref]

R. Engbert, K. Mergenthaler, P. Sinn, and A. Pikovsky, “An integrated model of fixational eye movements and microsaccades,” Proc. Natl. Acad. Sci. 108(39), E765–E770 (2011).
[Crossref]

2009 (2)

M. Rolfs, “Microsaccades: small steps on a long way,” Vision Res. 49(20), 2415–2441 (2009).
[Crossref]

N. J. Wade and B. W. Tatler, “Did Javal measure eye movements during reading,” J. Eye Mov. Res. 2, 1–7 (2009).
[Crossref]

2008 (1)

G. D. Evangelidis and E. Z. Psarakis, “Parametric Image Alignment Using Enhanced Correlation Coefficient Maximization,” IEEE Trans. Pattern Anal. Mach. Intell. 30(10), 1858–1865 (2008).
[Crossref]

2007 (3)

2006 (1)

2005 (2)

D. X. Hammer, R. D. Ferguson, J. C. Magill, L. A. Paunescu, S. Beaton, H. Ishikawa, G. Wollstein, and J. S. Schuman, “Active retinal tracker for clinical optical coherence tomography systems,” J. Biomed. Opt. 10(2), 024038 (2005).
[Crossref]

D. A. Atchison, S. W. Fisher, C. A. Pedersen, and P. G. Ridall, “Noticeable, troublesome and objectionable limits of blur,” Vision Res. 45(15), 1967–1974 (2005).
[Crossref]

2004 (2)

R. D. Ferguson, D. X. Hammer, L. A. Paunescu, S. Beaton, and J. S. Schuman, “Tracking optical coherence tomography,” Opt. Lett. 29(18), 2139–2141 (2004).
[Crossref]

S. Martinez-Conde, S. L. Macknik, and D. H. Hubel, “The role of fixational eye movements in visual perception,” Nat. Rev. Neurosci. 5(3), 229–240 (2004).
[Crossref]

2003 (3)

2002 (2)

D. X. Hammer, R. D. Ferguson, J. C. Magill, M. A. White, A. E. Elsner, and R. H. Webb, “Image stabilization for scanning laser ophthalmoscopy,” Opt. Express 10(26), 1542–1549 (2002).
[Crossref]

A. T. Duchowski, “A breadth-first survey of eye-tracking applications,” Behav. Res. Methods, Instruments. Comput. 34(4), 455–470 (2002).
[Crossref]

1996 (1)

M. Stetter, R. A. Sendtner, and G. T. Timberlake, “A novel method for measuring saccade profiles using the scanning laser ophthalmoscope,” Vision Res. 36(13), 1987–1994 (1996).
[Crossref]

1988 (1)

W. N. Charman and G. Heron, “Fluctuations in accommodation: a review,” Oph Phys Optics 8(2), 153–164 (1988).
[Crossref]

1987 (1)

1986 (1)

W. A. Fletcher and J. A. Sharpe, “Saccadic eye movement dysfunction in Alzheimer’s disease,” Ann. Neurol. 20(4), 464–471 (1986).
[Crossref]

1981 (1)

R. H. Webb and G. W. Hughes, “Scanning laser ophthalmoscope,” IEEE Trans. Biomed. Eng. BME-28(7), 488–492 (1981).
[Crossref]

1975 (2)

A. T. Bahill, M. R. Clark, and L. Stark, “The main sequence, a tool for studying human eye movements,” Math. Biosci. 24(3-4), 191–204 (1975).
[Crossref]

R. W. Baloh, A. W. Sills, W. E. Kumley, and V. Honrubia, “Quantitative measurement of saccade amplitude, duration, and velocity,” Neurology 25(11), 1065 (1975).
[Crossref]

1973 (1)

1963 (1)

D. A. Robinson, “Movement Using a Scleral Search in a Magnetic Field,” IEEE Trans. Bio-Med. Electron. 10(4), 137–145 (1963).
[Crossref]

1958 (1)

a White, M.

Anderson, T. J.

M. R. MacAskill and T. J. Anderson, “Eye movements in neurodegenerative diseases,” Curr. Opin. Neurol. 29(1), 61–68 (2016).
[Crossref]

Arathorn, D. W.

Atchison, D. A.

D. A. Atchison, S. W. Fisher, C. A. Pedersen, and P. G. Ridall, “Noticeable, troublesome and objectionable limits of blur,” Vision Res. 45(15), 1967–1974 (2005).
[Crossref]

Azimipour, M.

M. Azimipour, R. J. Zawadzki, I. Gorczynska, J. Migacz, J. S. Werner, and R. S. Jonnal, “Intraframe motion correction for raster-scanned adaptive optics images using strip-based cross-correlation lag biases,” PLoS One 13(10), e0206052–24 (2018).
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B. Braaf, K. V. Vienola, C. K. Sheehy, Q. Yang, K. A. Vermeer, P. Tiruveedhula, D. W. Arathorn, A. Roorda, and J. F. de Boer, “Real-time eye motion correction in phase-resolved OCT angiography with tracking SLO,” Biomed. Opt. Express 4(1), 51–65 (2013).
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Supplementary Material (12)

NameDescription
» Visualization 1       Video showing the retinal trajectory reconstruction. Subject 1 performing 2 degree saccades during 20 seconds with the first 5 seconds shown in slow motion.
» Visualization 2       Video showing the retinal trajectory reconstruction. Subject 2 performing 2 degree saccades during 20 seconds with the first 5 seconds shown in slow motion.
» Visualization 3       Video showing the retinal trajectory reconstruction. Subject 1 performing 4 degree saccades during 20 seconds with the first 5 seconds shown in slow motion.
» Visualization 4       Video showing the retinal trajectory reconstruction. Subject 2 performing 4 degree saccades during 20 seconds with the first 5 seconds shown in slow motion.
» Visualization 5       Video showing the retinal trajectory reconstruction. Subject 3 performing 6 degree saccades during 20 seconds with the first 5 seconds shown in slow motion.
» Visualization 6       Video showing the retinal trajectory reconstruction. Subject 2 performing 6 degree saccades during 20 seconds with the first 5 seconds shown in slow motion.
» Visualization 7       Video showing the retinal trajectory reconstruction. Subject 1 performing 8 degree saccades during 20 seconds with the first 5 seconds shown in slow motion.
» Visualization 8       Video showing the retinal trajectory reconstruction. Subject 3 performing 8 degree saccades during 20 seconds with the first 5 seconds shown in slow motion.
» Visualization 9       Video showing the retinal trajectory reconstruction. Subject 1 fixating on a target during 20 seconds with the first 5 seconds shown in slow motion. Imaging retinal vessels.
» Visualization 10       Video showing the retinal trajectory reconstruction. Subject 3 fixating on a target during 20 seconds with the first 5 seconds shown in slow motion. Imaging the optics nerve.
» Visualization 11       Video showing the retinal trajectory reconstruction. Subject 2 fixating on a target during 20 seconds with the first 5 seconds shown in slow motion. Imaging retinal vessels close to the optic nerve.
» Visualization 12       Video showing the retinal trajectory reconstruction. Subject 1 fixating on a target during 20 seconds with the first 5 seconds shown in slow motion. Imaging the fovea.

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Figures (10)

Fig. 1.
Fig. 1. Schematic diagram of the optical design of the FET. LD—laser diode, CL—collimating lens, BS—pellicle beam splitter, L1-L9 achromatic doublet lenses, MEMS 2D—two-axis resonant MEMS scanning mirror, FET PS—positioning galvanometric mirrors, D—variable iris aperture, PH—pinhole, APD—avalanche photodiode, HIL—halogen lamp, BST—Badal stage, AES—artificial eye scanner set, AEO—artificial eye objective, AET—artificial eye test target. Stars and circles denote conjugated plane pairs. Inset A: FT1, FT2—targets for static fixation and saccadic measurements, respectively. The diameter of FT1 subtends 1.5°. The diameters of individual targets in FT2 subtend 0.6° and their variable baseline separation range is 1–8°. Inset B: artificial eye for system testing and calibration, described in subsection 2.3.
Fig. 2.
Fig. 2. Examples of different tracking features in the human retina in vivo (1-15) and in the artificial eye (I-III). Images 1–2: part of an optic nerve, images 3–4: fovea; images 5–15: retinal vasculature with different sizes. Images I–III in the red frame were acquired using an artificial eye (see description in subsection 2.3) and are shown here for visual comparison with images of the living eye. Angular extent of scale bars is 1°.
Fig. 3.
Fig. 3. Retinal trajectory reconstruction algorithm and saccade extraction. See text for details. a) Raw data acquired along the Lissajous scanning pattern distorted by retinal motion. b) Image frame created by re-sampling the data to a rectangular grid with equidistant pixels without motion compensation. c) Image frame corrected for motion artifacts. d) Calculation of displacement between consecutive frames using image correlation. e) Displacement calculated for a number of previously acquired frames. f) Trajectory recovery using N-back algorithm. g) Trajectory correction using Key Frames. h) Saccade detection using eye motion velocity and calculation of saccade magnitude.
Fig. 4.
Fig. 4. Root square error (RSE) time series for N-back (blue) and Key Frames (green) trajectories. These error values derive from the 4° saccade experiment. Only the first 3.25 s are shown for clearness.
Fig. 5.
Fig. 5. Typical saccade magnitude plot. Solid blue circles and their numbers correspond to the acquired FET images representing moving vascular features in the retina during the saccade. The yellow arrows show direction of motion. The green and red solid circles correspond to beginning and end of saccade respectively. The depicted saccade comes from a series of saccades shown in Fig. 6 shaded in blue.
Fig. 6.
Fig. 6. Typical example of the x- and y- retinal coordinates during a 20-s series of back-and-forth horizontal saccades and fixation targets with angular separation of 4° for subject 1. The region shaded in blue indicates the saccade presented in Fig. 5. Green/red solid circles mark the starts/ends of saccades. The green-shaded area marks a gap in the trajectory points due to a blink. The area shaded in grey corresponds to the position and angular size of fixation targets.
Fig. 7.
Fig. 7. Angular magnitude, velocity, and acceleration plots of all 42 detected saccades for both measurements from subject 1 for a fixation target separation of 4°. Orange lines correspond to temporal-nasal saccades, while blue lines correspond to nasal-temporal saccades.
Fig. 8.
Fig. 8. Example of a retinal trajectory obtained during a 20-s voluntary saccades experiment. Panels (a) and (d) show the y- and x-trajectories of the retina over time, respectively. Panel (c) shows the entire x–y trajectory. Panel (b) is the retinal position density map with up-to-scale contour of the fixation target. The region shaded in green indicates a blink. For further visualizations and examples, please refer to Visualization 1, Visualization 2, Visualization 3, Visualization 4, Visualization 5, Visualization 6, Visualization 7, and Visualization 8.
Fig. 9.
Fig. 9. Example of a retinal trajectory obtained during a 20-s fixation experiment. (a) and (d) show the y- and x-trajectories of the retina, respectively. (c) shows the whole x-y trajectory. (d) retinal position density map. The regions shaded in green indicate blinks. See Visualization 9, Visualization 10, Visualization 11, and Visualization 12 in Supplementary Materials.
Fig. 10.
Fig. 10. A main sequence of 5,159 saccades and microsaccades detected from 57 measurements performed in vivo during a period of 1,140 s. The inset shows the magnitude of the smallest microsaccade detected in this study with an angular magnitude of 0.028°. Dashed line rectangle shows the range of detected saccades reported in [35].

Equations (4)

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f = M f L
t m = t m 1 + p m , m 1
t m = n B w m , n ( t m n + p m , m n ) / n B w m , n ( t m n + p m , m n ) n B w m , n n B w m , n
σ ( T ^ K F ) = a < b w a , b ( P a , b K F | t ^ a K F t ^ b K F | ) 2