pith. sign in

arxiv: 2605.19816 · v1 · pith:LVGCUCXHnew · submitted 2026-05-19 · 🧬 q-bio.NC

Performance of low vision individuals when selecting a target with head-pointing in virtual reality

Pith reviewed 2026-05-20 01:38 UTC · model grok-4.3

classification 🧬 q-bio.NC
keywords central visual field losshead-pointingvirtual realitylow visiontarget selectionaccessibilityhuman-machine interfaces
0
0 comments X

The pith

Patients with central visual field loss can select a 2-degree target using head-pointing in virtual reality, approaching normal performance with larger activation zones.

A machine-rendered reading of the paper's core claim, the machinery that carries it, and where it could break.

The paper tests whether people who have lost central vision can still guide a cursor with head movements to select a small target shown in virtual reality. Participants had to keep the target inside an invisible activation zone around the cursor for 1.5 seconds to register a selection. Increasing the zone diameter sped up both groups, but patients needed zones roughly three times larger than controls to reach their fastest times, after which both groups performed similarly.

Core claim

Patients with CFL are able to point at a 2° target thanks to head-pointing. Their performance can get close to controls' best performance by increasing PAZ size.

What carries the argument

The pointer activation zone (PAZ), an invisible circular region centered on the head-tracked reticle whose diameter sets how closely the cursor must align with the target before the 1.5-second dwell timer begins.

If this is right

  • Selection time falls steadily as PAZ diameter grows from 0.5° to 8° for both patients and controls.
  • Patients reach their shortest selection times at an average PAZ of 3.48°, while controls do so at 1.32°.
  • When three cursors appear at once, both groups tend to use the one nearest the target.
  • Head-pointing can therefore serve as a workable input method for visually guided tasks in VR once the activation zone is sized appropriately.

Where Pith is reading between the lines

These are editorial extensions of the paper, not claims the author makes directly.

  • Interface designers could offer an easy toggle for larger default PAZ sizes when a low-vision profile is detected.
  • The same head-pointing logic might transfer to augmented-reality glasses that overlay targets on the real world.
  • Varying dwell time or adding sound cues could be tested next to see whether even smaller PAZ sizes become usable for some patients.

Load-bearing premise

The 1.5-second dwell time and the specific virtual-reality head-tracking setup produce performance patterns that will hold in everyday real-world pointing tasks.

What would settle it

Running the identical target-selection task outside the headset, with a physical head-tracking pointer and real objects at the same visual angles, would show whether the same PAZ sizes and time improvements appear.

read the original abstract

Purpose: To investigate psychophysically the ability of low vision individuals with central visual field loss (CFL) to perform a visually-guided pointing task in a virtual reality environment. Methods: Patients with CFL (n=25, ages = 67-90 years) and normally-sighted controls (n=26, ages = 67-85 years) had to select a target (2{\textdegree} diameter dot) with a head-contingent cursor (6{\textdegree} diameter reticle). Target selection occurred when target was validly pointed at for 1.5 seconds. Pointing was valid when target was inside an invisible pointer activation zone (PAZ) centered on reticle. Task difficulty was decreased by increasing PAZ diameter from 0.5{\textdegree} to 8{\textdegree}. Performance was assessed by measuring the time needed to select the target. The task was also performed with an array of three simultaneously-displayed cursors. Results: Selection times decreased (from 14.1 and 8.4 seconds for patients and controls respectively) with increasing PAZ diameter and reached a similar asymptote for both groups (1.4 seconds). The rate of this decrease was smaller for patients so that PAZ diameter needed for their best performance was much larger than PAZ diameter needed for controls' best performance (average: 3.48{\textdegree} vs 1.32{\textdegree}). In the three-reticle condition, both groups tended to use the cursor closer to the target. Conclusions: Patients with CFL are able to point at a 2{\textdegree} target thanks to head-pointing. Their performance can get close to controls' best performance by increasing PAZ size. Translational relevance: This research suggests guidelines to improve the accessibility of visually-guided pointing tools for human-machine interfaces designed for low vision individuals.

Editorial analysis

A structured set of objections, weighed in public.

Desk editor's note, referee report, simulated authors' rebuttal, and a circularity audit. Tearing a paper down is the easy half of reading it; the pith above is the substance, this is the friction.

Referee Report

2 major / 2 minor

Summary. The manuscript reports a behavioral experiment comparing head-pointing target selection in VR between 25 patients with central visual field loss (CFL, ages 67-90) and 26 normally sighted controls (ages 67-85). Participants selected a 2° target using a 6° head-contingent reticle, with selection requiring a 1.5 s dwell time inside an invisible pointer activation zone (PAZ) whose diameter was parametrically increased from 0.5° to 8° to reduce task difficulty. Selection times decreased monotonically from 14.1 s (patients) / 8.4 s (controls) to a shared 1.4 s asymptote; patients required larger average PAZ (3.48° vs 1.32°) to reach best performance. A secondary condition with three simultaneous cursors showed both groups preferring the cursor nearest the target. The central claim is that CFL patients can acquire the target via head-pointing and that increasing PAZ size allows their performance to approach that of controls, with translational implications for accessible interfaces.

Significance. If the reported parametric results hold after statistical verification, the work supplies direct empirical evidence that head-pointing combined with adjustable activation zones can enable low-vision users to perform precise visually guided pointing tasks in VR at levels approaching normal performance. The monotonic improvement and convergence at larger PAZ sizes constitute a clear demonstration of a practical compensatory strategy. The study is strengthened by its within-subject parametric design and the inclusion of a multi-cursor condition, but its current impact is tempered by the absence of inferential statistics and variability measures needed to confirm the reliability of the group differences and asymptotes.

major comments (2)
  1. [Abstract/Results] Abstract/Results: The key quantitative claims—selection times of 14.1 s (patients) and 8.4 s (controls) at the smallest PAZ, convergence to a 1.4 s asymptote, and average PAZ thresholds of 3.48° versus 1.32°—are presented as point estimates without statistical tests, confidence intervals, standard deviations, or participant-level distributions. This omission prevents verification of the reported monotonic decrease and between-group convergence that underpin the central claim.
  2. [Methods] Methods: No information is provided on participant recruitment, inclusion/exclusion criteria, visual acuity or field-loss quantification for the CFL group, or how the 1.5 s dwell time and specific VR head-tracking hardware were chosen. These details are load-bearing for assessing whether the observed performance differences and PAZ requirements generalize beyond the laboratory setup.
minor comments (2)
  1. [Abstract] The abstract states that 'both groups tended to use the cursor closer to the target' in the three-reticle condition but supplies no quantitative measure (e.g., proportion of selections or distance statistics) to support this observation.
  2. [Abstract/Methods] Age ranges are reported but no means, standard deviations, or other demographic matching statistics are given, which would help evaluate the comparability of the two cohorts.

Simulated Author's Rebuttal

2 responses · 0 unresolved

We thank the referee for their constructive and detailed comments, which have helped us identify areas where the manuscript can be strengthened. We address each major comment below and indicate the revisions made to the manuscript.

read point-by-point responses
  1. Referee: [Abstract/Results] Abstract/Results: The key quantitative claims—selection times of 14.1 s (patients) and 8.4 s (controls) at the smallest PAZ, convergence to a 1.4 s asymptote, and average PAZ thresholds of 3.48° versus 1.32°—are presented as point estimates without statistical tests, confidence intervals, standard deviations, or participant-level distributions. This omission prevents verification of the reported monotonic decrease and between-group convergence that underpin the central claim.

    Authors: We agree that presenting these key results solely as point estimates without accompanying statistical support or variability measures reduces the ability to fully assess the reliability of the observed trends and group differences. In the revised manuscript, we have added inferential statistics (including appropriate repeated-measures analyses to confirm the monotonic decrease with PAZ size and the interaction with group), standard deviations or standard errors, confidence intervals for the reported means and thresholds, and participant-level data visualizations or summaries where space permits. These additions directly support the central claim of performance convergence at larger PAZ sizes. revision: yes

  2. Referee: [Methods] Methods: No information is provided on participant recruitment, inclusion/exclusion criteria, visual acuity or field-loss quantification for the CFL group, or how the 1.5 s dwell time and specific VR head-tracking hardware were chosen. These details are load-bearing for assessing whether the observed performance differences and PAZ requirements generalize beyond the laboratory setup.

    Authors: We acknowledge that these methodological details are necessary for readers to evaluate the generalizability and replicability of the findings. The original submission emphasized the experimental paradigm but did not fully elaborate on these aspects. In the revised Methods section, we now include: the recruitment strategy and screening process; explicit inclusion and exclusion criteria; quantitative characterization of visual acuity and central field loss in the CFL participants (e.g., via acuity testing and perimetry summaries); the rationale for the 1.5 s dwell time (drawn from pilot data and prior accessibility literature); and the specific VR hardware, head-tracking system, and calibration procedures used. revision: yes

Circularity Check

0 steps flagged

No circularity: purely empirical behavioral study

full rationale

This paper reports direct experimental measurements of target selection times in a VR head-pointing task for CFL patients and controls across parametrically varied PAZ diameters. No equations, models, derivations, or first-principles predictions are present; performance metrics (e.g., time to asymptote, required PAZ size) are observed outcomes from the task protocol itself. The central claims follow immediately from the reported data without any reduction to fitted inputs, self-definitions, or self-citation chains. The study is self-contained as a straightforward comparison of behavioral results.

Axiom & Free-Parameter Ledger

0 free parameters · 1 axioms · 0 invented entities

Empirical psychophysical study with no mathematical derivations, new theoretical entities, or fitted model parameters; relies on standard experimental design and group comparison assumptions.

axioms (1)
  • standard math Standard assumptions for comparing means between independent groups (e.g., approximate normality or use of appropriate non-parametric tests)
    Implicit when reporting average selection times and differences between the patient and control groups.

pith-pipeline@v0.9.0 · 5966 in / 1144 out tokens · 50553 ms · 2026-05-20T01:38:05.380154+00:00 · methodology

discussion (0)

Sign in with ORCID, Apple, or X to comment. Anyone can read and Pith papers without signing in.

Lean theorems connected to this paper

Citations machine-checked in the Pith Canon. Every link opens the source theorem in the public Lean library.

What do these tags mean?
matches
The paper's claim is directly supported by a theorem in the formal canon.
supports
The theorem supports part of the paper's argument, but the paper may add assumptions or extra steps.
extends
The paper goes beyond the formal theorem; the theorem is a base layer rather than the whole result.
uses
The paper appears to rely on the theorem as machinery.
contradicts
The paper's claim conflicts with a theorem or certificate in the canon.
unclear
Pith found a possible connection, but the passage is too broad, indirect, or ambiguous to say the theorem truly supports the claim.

Reference graph

Works this paper leans on

87 extracted references · 87 canonical work pages

  1. [1]

    visually-guided pointing at an object

    Introduction Central visual Field Loss (CFL) is one of the major causes of low vision, with Age-related Macular Degeneration (AMD) being the most frequent cause. Approximately 200 million of individuals were affected by AMD around the world in 2020, leading to moderate or severe low vision for more than 6 million of them1. This area of lost vision in the ...

  2. [2]

    Experiment codes

    Method 2.1. Participants Twenty five patients with CFL (patients group, 10 women, age: Mean = 79.0; SD = 6.3, Range [67, 90]) and twenty six age-matched normally-sighted control individuals (control group, 20 women, age: Mean = 73.9; SD = 4.3, Range [67, 85]) participated in the study. Two patients were excluded from the study after their experimental ses...

  3. [3]

    Selection times Average selection times of patients and controls are respectively 3682 ms ± 4864 (standard deviation) and 2692 ms ± 3294 (standard deviation)

    Results 22 / 51 3.1. Selection times Average selection times of patients and controls are respectively 3682 ms ± 4864 (standard deviation) and 2692 ms ± 3294 (standard deviation). Minimal selection times of patients and controls are respectively 555 ms and 522 ms. The difficulty of the task was manipulated by varying the PAZ diameter in separate experimen...

  4. [4]

    area cursor

    Discussion The general context of the present work is that low vision individuals face serious issues when interacting with complex digital interfaces, for instance to select items in a menu39,40. In this context, our general goal is to improve visually-guided pointing when low vision individuals with CFL, or more generally with visual impairments, are en...

  5. [5]

    Select and Augment Segmented Items

    Apart from optimizing pointing performance, extracting individual CPAZ values has the advantage of characterizing each individual’s performance with a single value. This is similar for instance to the use of the Critical Print Size used in many reading studies especially to characterize and compare reading performance of low vision persons64. In our work,...

  6. [6]

    Steinmetz JD, Bourne RRA, Briant PS, Flaxman SR, Taylor HRB, Jonas JB, et al. Causes of blindness and vision impairment in 2020 and trends over 30 years, and prevalence of avoidable blindness in relation to VISION 2020: the Right to Sight: an analysis for the Global Burden of Disease Study. Lancet Glob Health. févr 2021;9(2):e144-60. doi:10.1016/S2214-109...

  7. [7]

    Precision of position signals for letters

    Chung STL, Legge GE. Precision of position signals for letters. Vision Res. 2009;49(15):1948-60. doi:10.1016/j.visres.2009.05.004

  8. [8]

    Crowding in central and eccentric vision: the effects of contour interaction and attention

    Leat SJ, Li W, Epp K. Crowding in central and eccentric vision: the effects of contour interaction and attention. Investig Opthalmology Vis Sci. 1999;40(2):504-12

  9. [9]

    Positional uncertainty in peripheral and amblyopic vision

    Levi DM, Klein SA, Yen Lee Yap. Positional uncertainty in peripheral and amblyopic vision. Vision Res. 1987;27(4):581-97. doi:10.1016/0042-6989(87)90044-7

  10. [10]

    Visual crowding: a fundamental limit on conscious perception and object recognition

    Whitney D, Levi DM. Visual crowding: a fundamental limit on conscious perception and object recognition. Trends Cogn Sci. 2011;15(4):160-8. doi:10.1016/j.tics.2011.02.005

  11. [11]

    Psychophysics of reading—II

    Legge GE, Rubin GS, Pelli DG, Schleske MM. Psychophysics of reading—II. Low vision. Vision Res. 1985;25(2):253-65. doi:10.1016/0042-6989(85)90118-X

  12. [12]

    Psychophysical Function in Age-related Maculopathy

    Neelam K, Nolan J, Chakravarthy U, Beatty S. Psychophysical Function in Age-related Maculopathy. Surv Ophthalmol. 2009;54(2):167-210. doi:10.1016/j.survophthal.2008.12.003

  13. [14]

    Low Vision and Plasticity: Implications for Rehabilitation

    Legge GE, Chung STL. Low Vision and Plasticity: Implications for Rehabilitation. Annu Rev Vis Sci. 2016;2(1):321-43. doi:10.1146/annurev-vision-111815-114344

  14. [15]

    Quantifying Eye Stability During a Fixation Task: A Review of Definitions and Methods

    Castet E, Crossland M. Quantifying Eye Stability During a Fixation Task: A Review of Definitions and Methods. Seeing Perceiving. 2012;25(5):449-69. doi:10.1163/187847611X620955

  15. [16]

    Preferred Retinal Locus Development in Patients with Macular Disease

    Crossland MD, Culham LE, Kabanarou SA, Rubin GS. Preferred Retinal Locus Development in Patients with Macular Disease. Ophthalmology. 2005;112(9):1579-85. doi:10.1016/j.ophtha.2005.03.027

  16. [17]

    Combined use of several preferred retinal loci in patients with macular disorders when reading single words

    Duret F, Issenhuth M, Safran AB. Combined use of several preferred retinal loci in patients with macular disorders when reading single words. Vision Res. 1999;39(4):873-9. doi:10.1016/S0042- 6989(98)00179-5

  17. [18]

    Comparing the fixational and functional preferred retinal location in a pointing task

    Sullivan B, Walker L. Comparing the fixational and functional preferred retinal location in a pointing task. Vision Res. 2015;116:68-79. doi:10.1016/j.visres.2015.07.007

  18. [19]

    THE PREFERRED RETINAL LOCUS IN MACULAR DISEASE: Toward A Consensus Definition

    Crossland MD, Engel SA, Legge GE. THE PREFERRED RETINAL LOCUS IN MACULAR DISEASE: Toward A Consensus Definition. Retina. 2011;31(10):2109-14. doi:10.1097/IAE.0b013e31820d3fba

  19. [20]

    The Effect of Age-Related Macular Degeneration on Components of Face Perception

    Logan AJ, Gordon GE, Loffler G. The Effect of Age-Related Macular Degeneration on Components of Face Perception. Investig Opthalmology Vis Sci. 2020;61(6):38. doi:10.1167/iovs.61.6.38

  20. [21]

    Scene Perception in Age-Related Macular Degeneration

    Tran THC, Rambaud C, Despretz P, Boucart M. Scene Perception in Age-Related Macular Degeneration. Investig Opthalmology Vis Sci. 2010;51(12):6868. doi:10.1167/iovs.10-5517 41 / 51

  21. [22]

    Driving Habits and Health-Related Quality of Life in Patients with Age-Related Maculopathy: Optom Vis Sci

    Decarlo DK, Scilley K, Wells J, Owsley C. Driving Habits and Health-Related Quality of Life in Patients with Age-Related Maculopathy: Optom Vis Sci. 2003;80(3):207-13. doi:10.1097/00006324-200303000-00010

  22. [23]

    Low vision: the role of visual acuity in the efficiency of cursor movement

    Jacko JA, Barreto AB, Marmet GJ, Chu JYM, Bautsch HS, Scott IU, et al. Low vision: the role of visual acuity in the efficiency of cursor movement. In: Proceedings of the fourth international ACM conference on Assistive technologies. Arlington Virginia USA: ACM; 2000. p. 1-8. doi:10.1145/354324.354327

  23. [24]

    Impact of graphical user interface screen features on computer task accuracy and speed in a cohort of patients with age-related macular degeneration

    Scott IU, Feuer WJ, Jacko JA. Impact of graphical user interface screen features on computer task accuracy and speed in a cohort of patients with age-related macular degeneration. Am J Ophthalmol. 2002;134(6):857-62. doi:10.1016/S0002-9394(02)01795-6

  24. [25]

    Impact of visual function on computer task accuracy and reaction time in a cohort of patients with age-related macular degeneration

    Scott IU, Feuer WJ, Jacko JA. Impact of visual function on computer task accuracy and reaction time in a cohort of patients with age-related macular degeneration. Am J Ophthalmol. 2002;133(3):350-7. doi:10.1016/S0002-9394(01)01406-4

  25. [26]

    Impact of Wet Macular Degeneration on the Execution of Natural Actions

    Boucart M, Delerue C, Thibaut M, Szaffarczyk S, Hayhoe M, Tran THC. Impact of Wet Macular Degeneration on the Execution of Natural Actions. Investig Opthalmology Vis Sci. 2015;56(11):6832. doi:10.1167/iovs.15-16758

  26. [27]

    Preferred Retinal Locus—Hand Coordination in a Maze-Tracing Task

    Timberlake GT, Omoscharka E, Grose SA, Bothwell R. Preferred Retinal Locus—Hand Coordination in a Maze-Tracing Task. Investig Opthalmology Vis Sci. 2012;53(4):1810. doi:10.1167/iovs.11-9282

  27. [28]

    What Is the Nature of the Reach and Grasp Deficit in Wet Age-related Macular Degeneration? Optom Vis Sci

    Corveleyn X, Lenoble Q, Szaffarczyk S, Tran THC, Boucart M. What Is the Nature of the Reach and Grasp Deficit in Wet Age-related Macular Degeneration? Optom Vis Sci. 2018;95(3):171-82. doi:10.1097/OPX.0000000000001189 42 / 51

  28. [29]

    Can I reach it? A study in age- related macular degeneration and glaucoma patients

    Lenoble Q, Corveleyn X, Tran THC, Rouland JF, Boucart M. Can I reach it? A study in age- related macular degeneration and glaucoma patients. Vis Cogn. 2019;27(9-10):732-9. doi:10.1080/13506285.2019.1661319

  29. [30]

    Categorization Task over a Touch Screen in Age-Related Macular Degeneration

    Lenoble Q, Tran THC, Szaffarczyk S, Boucart M. Categorization Task over a Touch Screen in Age-Related Macular Degeneration. Optom Vis Sci. 2015;92(10):986-94. doi:10.1097/OPX.0000000000000694

  30. [31]

    Target Contrast Affects Reaching and Grasping in the Visually Impaired Subjects

    Pardhan S, Gonzalez-Alvarez C, Subramanian A. Target Contrast Affects Reaching and Grasping in the Visually Impaired Subjects. Optom Vis Sci. 2012;89(4):426-34. doi:10.1097/OPX.0b013e31824c1b89

  31. [32]

    A Comparison of Reach-to-Grasp and Transport-to- Place Performance in Participants With Age-Related Macular Degeneration and Glaucoma

    Pardhan S, Scarfe A, Bourne R, Timmis M. A Comparison of Reach-to-Grasp and Transport-to- Place Performance in Participants With Age-Related Macular Degeneration and Glaucoma. Investig Opthalmology Vis Sci. 2017;58(3):1560. doi:10.1167/iovs.16-20273

  32. [33]

    The Effect of Central Visual Impairment on Manual Prehension When Tasked with Transporting-to-Place an Object Accurately to a New Location

    Timmis MA, Pardhan S. The Effect of Central Visual Impairment on Manual Prehension When Tasked with Transporting-to-Place an Object Accurately to a New Location. Investig Opthalmology Vis Sci. 2012;53(6):2812. doi:10.1167/iovs.11-8860

  33. [34]

    Effect of Bilateral Macular Scotomas from Age-Related Macular Degeneration on Reach-to-Grasp Hand Movement

    Timberlake GT, Omoscharka E, Quaney BM, Grose SA, Maino JH. Effect of Bilateral Macular Scotomas from Age-Related Macular Degeneration on Reach-to-Grasp Hand Movement. Investig Opthalmology Vis Sci. 2011;52(5):2540. doi:10.1167/iovs.10-6062

  34. [35]

    How does age-related macular degeneration affect real-world visual ability and quality of life? A systematic review

    Taylor DJ, Hobby AE, Binns AM, Crabb DP. How does age-related macular degeneration affect real-world visual ability and quality of life? A systematic review. BMJ Open. 2016;6(12):e011504. doi:10.1136/bmjopen-2016-011504 43 / 51

  35. [36]

    The neural and behavioural organization of goal-directed movements

    Jeannerod M. The neural and behavioural organization of goal-directed movements. Oxford [England]ௗ: New York: Clarendon Pressௗ; Oxford University Press; 1988. 283 p. (Oxford psychology series; no. 15)

  36. [37]

    The Roles of Vision and Eye Movements in the Control of Activities of Daily Living

    Land M, Mennie N, Rusted J. The Roles of Vision and Eye Movements in the Control of Activities of Daily Living. Perception. 1999;28(11):1311-28. doi:10.1068/p2935

  37. [38]

    Eye-head-hand coordination in pointing at visual targets: spatial and temporal analysis

    V ercher JL, Magenes G, Prablanc C, Gauthier GM. Eye-head-hand coordination in pointing at visual targets: spatial and temporal analysis. Exp Brain Res. 1994;99(3). doi:10.1007/BF00228987

  38. [39]

    Human-computer interaction: input devices

    Jacob RJK. Human-computer interaction: input devices. ACM Comput Surv. 1996;28(1):177-9. doi:10.1145/234313.234387

  39. [40]

    The bubble cursor: enhancing target acquisition by dynamic resizing of the cursor’s activation area

    Po BA, Fisher BD, Booth KS. Comparing cursor orientations for mouse, pointer, and pen interaction. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems. Portland Oregon USA: ACM; 2005. p. 291-300. doi:10.1145/1054972.1055013

  40. [41]

    Low vision devices for age-related macular degeneration: a systematic review

    Macnamara A, Chen CS, Davies A, Sloan C, Loetscher T. Low vision devices for age-related macular degeneration: a systematic review. Disabil Rehabil Assist Technol. 2023;18(7):998-1010. doi:10.1080/17483107.2021.1966523

  41. [42]

    Silva R, Macedo AF

    Crossland MD, S. Silva R, Macedo AF. Smartphone, tablet computer and e‐reader use by people with vision impairment. Ophthalmic Physiol Opt. 2014;34(5):552-7. doi:10.1111/opo.12136

  42. [43]

    Computer and World Wide Web Accessibility by Visually Disabled Patients: Problems and Solutions

    Chiang MF, Cole RG, Gupta S, Kaiser GE, Starren JB. Computer and World Wide Web Accessibility by Visually Disabled Patients: Problems and Solutions. Surv Ophthalmol. 2005;50(4):394-405. doi:10.1016/j.survophthal.2005.04.004 44 / 51

  43. [44]

    An Equitable Experience? How HCI Research Conceptualizes Accessibility of Virtual Reality in the Context of Disability

    Gerling K, Meiners AL, Schumm L, Rixen J, Wolf M, Yildiz Z, et al. An Equitable Experience? How HCI Research Conceptualizes Accessibility of Virtual Reality in the Context of Disability. ACM Trans Access Comput. 2025;3770755. doi:10.1145/3770755

  44. [45]

    A framework of assistive pointers for low vision users

    Fraser J, Gutwin C. A framework of assistive pointers for low vision users. In: Proceedings of the fourth international ACM conference on Assistive technologies. Arlington Virginia USA: ACM; 2000. p. 9-16. doi:10.1145/354324.354329

  45. [46]

    A survey of 3D object selection techniques for virtual environments

    Argelaguet F, Andujar C. A survey of 3D object selection techniques for virtual environments. Comput Graph. 2013;37(3):121-36. doi:10.1016/j.cag.2012.12.003

  46. [47]

    The Effects of Selection Technique on Target Acquisition Movements Made with a Mouse

    Bohan M, Chaparro A, Scarlett D. The Effects of Selection Technique on Target Acquisition Movements Made with a Mouse. Proc Hum Factors Ergon Soc Annu Meet. 1998;42(5):473-5. doi:10.1177/154193129804200506

  47. [48]

    Enhanced area cursors: reducing fine pointing demands for people with motor impairments

    Findlater L, Jansen A, Shinohara K, Dixon M, Kamb P, Rakita J, et al. Enhanced area cursors: reducing fine pointing demands for people with motor impairments. In: Proceedings of the 23nd annual ACM symposium on User interface software and technology. New York New York USA: ACM; 2010. p. 153-62. doi:10.1145/1866029.1866055

  48. [49]

    The bubble cursor: enhancing target acquisition by dynamic resizing of the cursor’s activation area

    Grossman T, Balakrishnan R. The bubble cursor: enhancing target acquisition by dynamic resizing of the cursor’s activation area. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems. Portland Oregon USA: ACM; 2005. p. 281-90. doi:10.1145/1054972.1055012

  49. [50]

    Fitts’ Law in Two Dimensions with Hand and Head Movements Movements

    Jagacinski RJ, Monk DL. Fitts’ Law in Two Dimensions with Hand and Head Movements Movements. J Mot Behav. 1985;17(1):77-95. doi:10.1080/00222895.1985.10735338 45 / 51

  50. [51]

    The “prince” technique: Fitts’ law and selection using area cursors

    Kabbash P, Buxton WAS. The “prince” technique: Fitts’ law and selection using area cursors. In: Proceedings of the SIGCHI conference on Human factors in computing systems - CHI ’95. Denver, Colorado, United States: ACM Press; 1995. p. 273-9. doi:10.1145/223904.223939

  51. [52]

    Acquisition of expanding targets

    McGuffin M, Balakrishnan R. Acquisition of expanding targets. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems. Minneapolis Minnesota USA: ACM

  52. [53]

    p. 57-64. doi:10.1145/503376.503388

  53. [54]

    Dwell-Based Pointing in Applications of Human Computer Interaction

    Müller-Tomfelde C. Dwell-Based Pointing in Applications of Human Computer Interaction. In: Baranauskas C, Palanque P, Abascal J, Barbosa SDJ, éditeurs. Human-Computer Interaction – INTERACT 2007. Berlin, Heidelberg: Springer Berlin Heidelberg; 2007. p. 560-73. (Lecture Notes in Computer Science). doi:10.1007/978-3-540-74796-3_56

  54. [55]

    Making computers easier for older adults to use: area cursors and sticky icons

    Worden A, Walker N, Bharat K, Hudson S. Making computers easier for older adults to use: area cursors and sticky icons. In: Proceedings of the ACM SIGCHI Conference on Human factors in computing systems. Atlanta Georgia USA: ACM; 1997. p. 266-71. doi:10.1145/258549.258724

  55. [56]

    Target Selection in Head-Mounted Display Virtual Reality Environments

    Y u D, Liang HN, Lu F, Nanjappan V , Papangelis K, Wang W. Target Selection in Head-Mounted Display Virtual Reality Environments. J Univers Comput Sci. 2018;24(9):1217-43. doi:10.3217/jucs-024-09-1217

  56. [57]

    Silk Cursor

    Zhai S, Buxton W, Milgram P. The “Silk Cursor”: investigating transparency for 3D target acquisition. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems. Boston Massachusetts USA: ACM; 1994. p. 459-64. doi:10.1145/191666.191822

  57. [58]

    PTVR – A software in Python to make virtual reality experiments easier to build and more reproducible

    Castet E, Termoz-Masson J, Vizcay S, Delachambre J, Myrodia V , Aguilar C, et al. PTVR – A software in Python to make virtual reality experiments easier to build and more reproducible. J Vis. 2024;24(4):19. doi:10.1167/jov.24.4.19 46 / 51

  58. [59]

    Evaluation of a gaze-controlled vision enhancement system for reading in visually impaired people

    Aguilar C, Castet E. Evaluation of a gaze-controlled vision enhancement system for reading in visually impaired people. González-Méijome JM, éditeur. PLOS ONE. 2017;12(4):e0174910. doi:10.1371/journal.pone.0174910

  59. [60]

    A Vision Enhancement System to Improve Face Recognition with Central Vision Loss

    Calabrèse A, Aguilar C, Faure G, Matonti F, Hoffart L, Castet E. A Vision Enhancement System to Improve Face Recognition with Central Vision Loss. Optom Vis Sci. 2018;95(9):738-46. doi:10.1097/OPX.0000000000001263

  60. [61]

    An asymmetric VR system to configure and practice low-vision aids for social interactions in clinical settings

    Delachambre J, Wu HY , Kornprobst P, Meo MD, Lagniez F, Morfin-Bourlat C, et al. An asymmetric VR system to configure and practice low-vision aids for social interactions in clinical settings. In: 2025 IEEE Conference on Virtual Reality and 3D User Interfaces Abstracts and Workshops (VRW). Saint Malo, France: IEEE; 2025. p. 1190-1. doi:10.1109/VRW66409.2025.00241

  61. [62]

    WatchCap: Improving Scanning Efficiency in People with Low Vision through Compensatory Head Movement Stimulation

    Jo T, Yeo D, Kim G, Hwang S, Kim S. WatchCap: Improving Scanning Efficiency in People with Low Vision through Compensatory Head Movement Stimulation. Proc ACM Interact Mob Wearable Ubiquitous Technol. 2024;8(2):1-32. doi:10.1145/3659592

  62. [63]

    Eye Movements and Reading Speed in Macular Disease: The Shrinking Perceptual Span Hypothesis Requires and Is Supported by a Mediation Analysis

    Calabrèse A, Bernard JB, Faure G, Hoffart L, Castet E. Eye Movements and Reading Speed in Macular Disease: The Shrinking Perceptual Span Hypothesis Requires and Is Supported by a Mediation Analysis. Investig Opthalmology Vis Sci. 2014;55(6):3638. doi:10.1167/iovs.13- 13408

  63. [64]

    Visual, vestibular and voluntary contributions to human head stabilization

    Guitton D, Kearney RE, Wereley N, Peterson BW. Visual, vestibular and voluntary contributions to human head stabilization. Exp Brain Res. 1986;64(1). doi:10.1007/BF00238201

  64. [65]

    Does print size matter for reading? A review of findings from vision science and typography

    Legge GE, Bigelow CA. Does print size matter for reading? A review of findings from vision science and typography. J Vis. 2011;11(5):8-8. doi:10.1167/11.5.8 47 / 51

  65. [66]

    The Mini-Mental State Examination

    Folstein MF. The Mini-Mental State Examination. Arch Gen Psychiatry. 1983;40(7):812. doi:10.1001/archpsyc.1983.01790060110016

  66. [67]

    Adaptation of dementia screening for vision-impaired older persons Administration of the Mini-Mental State Examination (MMSE)

    Busse A, Sonntag A, Bischkopf J, Matschinger H, Angermeyer MC. Adaptation of dementia screening for vision-impaired older persons Administration of the Mini-Mental State Examination (MMSE). J Clin Epidemiol. 2002

  67. [68]

    Towards FAIR principles for research software

    Lamprecht AL, Garcia L, Kuzak M, Martinez C, Arcila R, Martin Del Pico E, et al. Towards FAIR principles for research software. Data Sci. 2020;3(1):37-59. doi:10.3233/DS-190026

  68. [69]

    How to measure distance visual acuity

    Marsden J, Stevens S, Ebri A. How to measure distance visual acuity. Community Eye Health. 2014;27(85):16. PubMed PMID: 24966459; PubMed Central PMCID: PMC4069781

  69. [70]

    Psychophysics of reading

    Chung STL, Mansfield JS, Legge GE. Psychophysics of reading. XVIII. The effect of print size on reading speed in normal peripheral vision. Vision Res. 1998;38(19):2949-62. doi:10.1016/S0042-6989(98)00072-8

  70. [71]

    R: a language and environment for statistical computing

    R Core Team. R: a language and environment for statistical computing. Vienna, Austria: R Foundation for Statistical Computing; 2020. http://www.R-project.org/

  71. [72]

    Mixed-Effects Models in S and S-PLUS

    Pinheiro M, Bates D. Mixed-Effects Models in S and S-PLUS . New York: Springer-Verlag

  72. [73]

    doi:10.1007/b98882

    (Statistics and Computing). doi:10.1007/b98882

  73. [74]

    Bates, M

    Bates D, Mächler M, Bolker B, Walker S. Fitting Linear Mixed-Effects Models Using lme4. J Stat Softw. 2015;67(1). doi:10.18637/jss.v067.i01

  74. [75]

    Least-Squares Means: The R Package lsmeans

    Lenth RV . Least-Squares Means: The R Package lsmeans. J Stat Softw. 2016;69(1). doi:10.18637/jss.v069.i01 48 / 51

  75. [76]

    Pointing by gaze, head, and foot in a head-mounted display

    Minakata K, Hansen JP, MacKenzie IS, Bækgaard P, Rajanna V . Pointing by gaze, head, and foot in a head-mounted display. In: Proceedings of the 11th ACM Symposium on Eye Tracking Research & Applications. Denver Colorado: ACM; 2019. p. 1-9. doi:10.1145/3317956.3318150

  76. [77]

    Selecting Menu Items in Mobile Head-Mounted Displays: Effects of Selection Technique and Active Area

    Chittaro L, Sioni R. Selecting Menu Items in Mobile Head-Mounted Displays: Effects of Selection Technique and Active Area. Int J Human–Computer Interact. 2019;35(16):1501-16. doi:10.1080/10447318.2018.1541546

  77. [78]

    What you look at is what you get: eye movement-based interaction techniques

    Jacob RJK. What you look at is what you get: eye movement-based interaction techniques. In: Proceedings of the SIGCHI conference on Human factors in computing systems Empowering people - CHI ’90. Seattle, Washington, United States: ACM Press; 1990. p. 11-8. doi:10.1145/97243.97246

  78. [79]

    Flicker Observer Effect: Guiding Attention Through High Frequency Flicker in Images

    Waldin N, Waldner M, Viola I. Flicker Observer Effect: Guiding Attention Through High Frequency Flicker in Images. Comput Graph Forum. 2017;36(2):467-76. doi:10.1111/cgf.13141

  79. [80]

    GazePrompt: Enhancing Low Vision People’s Reading Experience with Gaze-Aware Augmentations

    Wang R, Potter Z, Ho Y , Killough D, Zeng L, Mondal S, et al. GazePrompt: Enhancing Low Vision People’s Reading Experience with Gaze-Aware Augmentations. In: Proceedings of the CHI Conference on Human Factors in Computing Systems. Honolulu HI USA: ACM; 2024. p. 1-17. doi:10.1145/3613904.3642878

  80. [81]

    Towards making videos accessible for low vision screen magnifier users

    Aydin AS, Feiz S, Ashok V , Ramakrishnan I. Towards making videos accessible for low vision screen magnifier users. In: Proceedings of the 25th International Conference on Intelligent User Interfaces. Cagliari Italy: ACM; 2020. p. 10-21. doi:10.1145/3377325.3377494

Showing first 80 references.