July 2019
Volume 60, Issue 9
Free
ARVO Annual Meeting Abstract  |   July 2019
Evaluation of HFA3 gaze monitoring feature using lens-based head tracking
Author Affiliations & Notes
  • Ashwini Tamhankar
    Carl Zeiss Meditec, Inc., Dublin, California, United States
  • Gary C Lee
    Carl Zeiss Meditec, Inc., Dublin, California, United States
  • Thomas Callan
    Carl Zeiss Meditec, Inc., Dublin, California, United States
  • Charles Wu
    Carl Zeiss Meditec, Inc., Dublin, California, United States
  • Mary K Durbin
    Carl Zeiss Meditec, Inc., Dublin, California, United States
  • Footnotes
    Commercial Relationships   Ashwini Tamhankar, Carl Zeiss Meditec, Inc. (E); Gary Lee, Carl Zeiss Meditec, Inc. (E); Thomas Callan, Carl Zeiss Meditec, Inc. (E); Charles Wu, Carl Zeiss Meditec, Inc. (C); Mary Durbin, Carl Zeiss Meditec, Inc. (E)
  • Footnotes
    Support  None
Investigative Ophthalmology & Visual Science July 2019, Vol.60, 2453. doi:
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    • Get Citation

      Ashwini Tamhankar, Gary C Lee, Thomas Callan, Charles Wu, Mary K Durbin; Evaluation of HFA3 gaze monitoring feature using lens-based head tracking. Invest. Ophthalmol. Vis. Sci. 2019;60(9):2453.

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      © ARVO (1962-2015); The Authors (2016-present)

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Abstract

Purpose : A new lens-based head tracking feature for the HFA3 perimeter (ZEISS, Dublin, CA) can now automatically align the center of the patient’s pupil to the center of the lens (Figure 1) and continually reposition throughout the exam. The purpose of this study was to compare this prototype design to the original manual alignment and gaze monitoring method.

Methods :
Two HFA3 (Model 860, SW versions 1.4 and 1.5) systems, with the liquid trial lens, were used to test one eye of 18 healthy volunteers by taking three SITA Faster 24-2 exams in a randomized test order. On version 1.4 SW, the pupil was manually aligned to “+” camera center (CC) mark and manually estimated lens center (LC) while with the version 1.5 SW, pupil was automatically aligned (AA) to lens “+” mark during gaze initialization. Patient alignment time (Ta) was recorded from patient being comfortable at the instrument to successful gaze initialization during all exams. Fixation loss (FL) and blind spot location threshold (BS) data were recorded. Ta, FL and BSdata were analyzed and compared using ANOVA and Friedman’s tests.

Results : Mean age for subjects was 41.5 years (SD: 9.9, range: 23-57). Average time with standard deviation for CC, LC and AA was 17.2 ± 3.7, 20.4 ± 4.7, and 12.8 ± 2.5 seconds respectively ( p<0.001). AA significantly reduced the average time by 25.6 % and 37% compared to CC and LC, respectively. Differences in FL and BS were determined not to be statistically significant among the methods (p>0.05). Visual inspection of individual gaze graphs showed minimal differences (Figure 2).

Conclusions :
In this preliminary study, patient alignment and gaze initialization time were significantly reduced using the lens-based head tracking method. Performance of gaze monitoring was comparable to the current commercial software based upon qualitative observations and the analysis of FL and BS results. The lens-based head tracking provides automated alignment and improved user interface with indicators for the lens center and the pupil center.

This abstract was presented at the 2019 ARVO Annual Meeting, held in Vancouver, Canada, April 28 - May 2, 2019.

 

Figure 1: Gaze monitoring software comparison

Figure 1: Gaze monitoring software comparison

 

Figure 2: Gaze graph examples for one subject

Figure 2: Gaze graph examples for one subject

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