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Purpose: An important challenge for eye care practitioners is meeting the needs of an ever-increasing elderly population. Standard vision tests are inadequate for determining performance in real life situations. One test that was developed to address this issue is the Attended Field of View (AFOV) test (Coeckelbergh et al, 2004). This test was designed to assess the functional field of view when people are allowed to make habitual head and eye movements. The original AFOV test is no longer available. This research seeks to develop a replacement AFOV test and to demonstrate its reliability as an assessment tool. Methods: Two groups of participants were recruited. The first group consisted of seven participants between the ages of 15-41 years. The second group consisted of seven participants between the ages of 59–79 years. All subjects had visual acuities equal or better than 20/25 and no history of visual field loss. A computer-generated display was observed from a 60cm distance. The display consisted of 24 white circles on a gray background and one open circle (target). The circles were organized with one circle in the centre and eight located radially at three eccentricities (4, 8, and 12 degrees). Participants were required to locate the target circle and identify the gap direction. A response was considered correct when both the location and gap direction were accurate. Using a weighted staircase method based on presentation time each location was evaluated independently. Viewing efficiency [log (1/threshold presentation time)] was obtained for each location. The data was analyzed using repeated measures ANOVA. Results: A comparison of viewing efficiency for the two age groups demonstrates that viewing efficiency is consistently lower for the older group at all three visits. The main effect of age was observed (F1,12=25.842;p=0.000). In the older group, a significant difference was found between the second and third visits. This difference was not found in the younger group. A main effect of eccentricity was found in both groups (F2,36=30.84;p<0.000), but no interaction was observed between eccentricity and group (F2,36=0.42;p=0.662). Viewing efficiency values in the older group were lower in all directions (main effect of age) (F1,96=150.36;p<0.000). Directional variations in viewing efficiency were observed showing higher values in the horizontal axes (directions Right and Left) than along the vertical axes (directions Up and Down) in both groups. A comparison of superior and inferior hemifield data shows consistent differences for both age groups. The superior hemifield (average of directions located superiorly to the horizontal axis) demonstrate higher viewing efficiency values (better performance) than the inferior hemifield. Conclusions: The use of the new AFOV test requires a practice time before its use in order to avoid the confound of a learning effect, but subsequent data is reliable in young people. The learning effect was more significant in older people and for this reason the use of the test should be preceded by a longer practice session in this population. When interpreting the results of this test one must account for eccentricity, direction, and age.

Purpose: An important challenge for eye care practitioners is meeting the needs of an ever-increasing elderly population. Standard vision tests are inadequate for determining performance in real life situations. One test that was developed to address this issue is the Attended Field of View (AFOV) test (Coeckelbergh et al, 2004). This test was designed to assess the functional field of view when people are allowed to make habitual head and eye movements. The original AFOV test is no longer available. This research seeks to develop a replacement AFOV test and to demonstrate its reliability as an assessment tool. Methods: Two groups of participants were recruited. The first group consisted of seven participants between the ages of 15-41 years. The second group consisted of seven participants between the ages of 59–79 years. All subjects had visual acuities equal or better than 20/25 and no history of visual field loss. A computer-generated display was observed from a 60cm distance. The display consisted of 24 white circles on a gray background and one open circle (target). The circles were organized with one circle in the centre and eight located radially at three eccentricities (4, 8, and 12 degrees). Participants were required to locate the target circle and identify the gap direction. A response was considered correct when both the location and gap direction were accurate. Using a weighted staircase method based on presentation time each location was evaluated independently. Viewing efficiency [log (1/threshold presentation time)] was obtained for each location. The data was analyzed using repeated measures ANOVA. Results: A comparison of viewing efficiency for the two age groups demonstrates that viewing efficiency is consistently lower for the older group at all three visits. The main effect of age was observed (F1,12=25.842;p=0.000). In the older group, a significant difference was found between the second and third visits. This difference was not found in the younger group. A main effect of eccentricity was found in both groups (F2,36=30.84;p<0.000), but no interaction was observed between eccentricity and group (F2,36=0.42;p=0.662). Viewing efficiency values in the older group were lower in all directions (main effect of age) (F1,96=150.36;p<0.000). Directional variations in viewing efficiency were observed showing higher values in the horizontal axes (directions Right and Left) than along the vertical axes (directions Up and Down) in both groups. A comparison of superior and inferior hemifield data shows consistent differences for both age groups. The superior hemifield (average of directions located superiorly to the horizontal axis) demonstrate higher viewing efficiency values (better performance) than the inferior hemifield. Conclusions: The use of the new AFOV test requires a practice time before its use in order to avoid the confound of a learning effect, but subsequent data is reliable in young people. The learning effect was more significant in older people and for this reason the use of the test should be preceded by a longer practice session in this population. When interpreting the results of this test one must account for eccentricity, direction, and age.

京都大学 / 0048 / 新制・課程博士 / 博士(医学) / 甲第19608号 / 医博第4115号 / 新制||医||1015(附属図書館) / 32644 / 京都大学大学院医学研究科医学専攻 / (主査)教授 大森 孝一, 教授 鈴木 茂彦, 教授 影山 龍一郎 / 学位規則第4条第1項該当 / Doctor of Medical Science / Kyoto University / DFAM

Yes / Microperimetry, also referred to as fundus perimetry or fundus-driven perimetry, enables simultaneous acquisition of visual sensitivity and eye movement data. We present sensitivity data collected from 60 participants with normal vision using gaze-contingent perimetry. A custom designed spatially dense test grid was used to collect data across the visual field within 13° of fixation. These data are supplemental to a study in which we demonstrated a spatial interpolation method that facilitates comparison of acquired data from any set of spatial locations to normative data and thus screening of individuals with both normal and non-foveal fixation (Denniss and Astle, 2016)[1].

No / To present a computational model mapping visual field (VF) locations to optic nerve head (ONH) sectors accounting for individual ocular anatomy, and to describe the effects of anatomical variability on maps produced. A previous model that related retinal locations to ONH sectors was adapted to model eyes with varying axial length, ONH position and ONH dimensions. Maps (n = 11,550) relating VF locations (24-2 pattern, n = 52 non–blind-spot locations) to 1° ONH sectors were generated for a range of clinically plausible anatomical parameters. Infrequently mapped ONH sectors (5%) were discarded for all locations. The influence of anatomical variables on the maps was explored by multiple linear regression. Across all anatomical variants, for individual VF locations (24-2), total number of mapped 1° ONH sectors ranged from 12 to 90. Forty-one locations varied more than 30°. In five nasal-step locations, mapped ONH sectors were bimodally distributed, mapping to vertically opposite ONH sectors depending on vertical ONH position. Mapped ONH sectors were significantly influenced (P < 0.0002) by axial length, ONH position, and ONH dimensions for 39, 52, and 30 VF locations, respectively. On average across all VF locations, vertical ONH position explained the most variance in mapped ONH sector, followed by horizontal ONH position, axial length, and ONH dimensions. Relations between ONH sectors and many VF locations are strongly anatomy-dependent. Our model may be used to produce customized maps from VF locations to the ONH in individual eyes where some simple biometric parameters are known. / ustralian Research Council Linkage Project LP100100250 (with Heidelberg Engineering GmbH, Germany); Australian Research Council Future Fellowship FT0990930 (AMM); Australian Research Council Future Fellowship FT0991326 (AT)