Visual Acuity “Cheat Sheet” for high and low vision

Visual acuity (VA) is arguably the most important measure of our visual performance. Further essential aspects like visual field, contrast sensitivity, color vision, motion perception, etc., are not covered here.

There exist (too) many measures to quantify visual acuity. Luckily, they can be converted into each other. Which is best? Most people prefer the one they were brought up with… See next section and this historical review: Colenbrander (2008).

All acuity measures relate to the visual angle of the smallest perceived (or discriminated) structure. Whichever way we define “smallest perceived structure”, let’s call it “MAR” for “minimum angle of resolution”, and let its dimension be minutes of arc. Then:

The “20” resp. “6” in the Snellen columns correspond to a testing distance of 20 ft resp. 6 m.   For the “illogicalopposite direction” of LogMAR versus the other acuity measures: think of LogMAR in terms of “visual loss”.

So which one is best?

• Snellen ratio and decimal acuity notation are identical after you simply calculate the fraction.
• Decimal notation and Snellen ratio are not useful for calculations; for instance, you must never calculate the mean!
• LogMAR is approximately normally distributed. That means you can calculate means, SDs, t-tests, etc. to your heart’s desire.
• As the first analysis step, convert everything to LogMAR. After analysis, one can convert back to Snellen or decimal notation to reach the pertinent audience. I suggest plotting LogMAR on an inverted axis, so “good” acuity is up and/or right.
• Lines. This is not an ISO Standard term. Acuity charts are typically arranged in lines, with equal optotype grade along a line. Following ISO, the lines should have equidistant progressive acuity grades with 0.1 LogMAR increments. One Line is equivalent to 0.1 LogMAR.
• Letters / Letter Score. This is not an ISO Standard term, it’s basically equivalent to a step of 0.02 LogMAR. I understand the attraction of “Letters”: Saying “vision improved by 15 letters” sounds more intuitive than “vision improved by –(minus!)0.3 LogMAR”. It is just so obnoxious that LogMAR “runs the wrong way round”.
  • The “Letter Score” refers to the count of letters read from the top of an ETDRS chart. [For me, this confounds lapse errors with threshold errors, but it seems to work well].
  • To convert from Letter Score to LogMAR with a standard ETDRS chart at a distance of 4 m this formula applies (Ferris et al. 1982, p96):
           LogMAR = 1.1 – 0.02 · (number of letters correctly identified).
  • Now (2026) the most commonly used Letter Formula seems the one for 1 m distance (Beck et al. 2003, Table 1; or “ETDRS#7”):
           LogMAR = 1.7 – 0.02 · (number of letters correctly identified).
    That adds 30 letters to the 4-m result above, see also footnote⁷ in the table below.
• “ETDRS”? This is not a unit for visual acuity; ETDRS charts use LogMAR.
• “EDTRS”? A frequent misspelling of ETDRS, guilty myself 😎.
  

For studies, visual acuity data often requires quantitative processing, such as averaging. For example, if you measure everything twice (my recommendation), or for treatment group comparisons, you’d like to average. As Holladay (1997) clearly explains, there are wrong ways to average. So, how can you average correctly?

• LogMAR values can be averaged in the normal arithmetic way [e.g. (value1+value2)/2] because LogMAR follows an (approximate) interval scale
• Decimal acuity notation MUST NOT be averaged arithmetically (its “scale of measurement” is only ordinal). You could calculate the geometric mean, but best: Convert to LogMAR, then average. If desired, you can then convert back to decimal notation.
• Snellen Fraction: convert to LogMAR, then average. If desired, you can then convert back to Snellen Fraction.
  

For very low vision, we routinely use categories rather than numbers, namely counting fingers (CF), hand motion/movement (HM), light perception (LP) and no light perception (NLP). Based on finger size, Holladay (2004) suggested that CF is equivalent to ≈2.3 LogMAR at 1 foot (my conversion); he considers HM as having 10× worse Snellen acuity, resulting in ≈3.3 LogMAR for HM at 1 foot. [Fun fact: “hand movement” is 5× more often used than “hand motion” (2024).]

With the help of the FrACT Vision test, which can present very large optotypes, we were able to measure reproducible values for CF and HM (Schulze-Bonsel et al. 2006, Bach et al. 2007, Lange et al. 2009); given in the table above. The values for light perception (LP) and no light perception (NLP) are imputations (Bach et al. 2007, footnote³ below).

CF: counting fingers, HM: hand movement, LP: light perception, NLP: no LP.
¹WHO definitions of distance vision impairment.
²Based on data from Schulze-Bonsel et al. 2006 and Lange et al. 2009.
³Imputations / suggestions. I agree with Holladay (2004) “[these] are not actually visual acuity measurements, but simply the detection of a stimulus … should be excluded.” Still, numbers here are useful, e.g. to quantitatively document intervention success, aggregate data, etc. Note: these values are not on an interval scale.
⁴The “simple” Letter Score, where errors before the last line are not considered.
⁵Values in parentheses represent plausible extensions of ISO 8596.
⁶Beck et al. (2003), page 197, Table 1; or “ETDRS#7”.
⁷To maintain acuity across distance, adding 30 to the 4-m results equates to 1-m results.

• Bach M, Schulze-Bonsel K, Feltgen N, Burau H, Hansen LL (2007) Author Response: Numerical Imputation for Low Vision States. Invest Ophthalmol Vis Sci. eLetter, Aug 2007 [PDF] [on CF & HM equivalents]
• Beck RW, Moke PS, Turpin AH, et al (2003) A computerized method of visual acuity testing: adaptation of the early treatment of diabetic retinopathy study testing protocol. Am J Ophthalmol 135:194–205
• Colenbrander A (2008) The Historical Evolution of Visual Acuity Measurement. Visual Impairment Research 10:57–66
• “ETDRS#7” • Early Treatment Diabetic Retinopathy Study design and baseline patient characteristics. ETDRS report number 7 (1991) Ophthalmology 98:741–756
• Frisén & Frisén 1981 How good is normal visual acuity? Albrecht von Graefes Arch Klin Ophthalmol 215:149–157 [Normal acuity in the age range 20–65 is ≈–0.2 LogMAR = 1.6 decimal]
• Holladay JT (1997) Proper Method for Calculating Average Visual Acuity. J Refract Surg 13(4):388–391
• Holladay JT (2004) Visual acuity measurements. J Cataract Refract Surg 30:287–90.
• Lange, Feltgen, Junker, Schulze-Bonsel, Bach (2009) Resolving the clinical acuity categories “hand motion” and “counting fingers” using the Freiburg Visual Acuity Test (FrACT). Graefe’s Arch Clin Exp Ophthalmol 247:137–142 read→here, [PDF] [on CF & HM equivalents]
• Schulze-Bonsel K, Feltgen N, Burau H, Hansen LL, Bach M (2006) Visual acuities “Hand Motion” and “Counting Fingers” can be quantified using the Freiburg Visual Acuity Test. Invest Ophthalmol Vis Sci 47:1236–1240 [PDF] [on CF & HM equivalents]
• Karanjia et al. (2016) Correcting Finger Counting to Snellen Acuity. Neuro Ophthalmol 40:219-221 [CF depending on distance (not based on acuity data)]

1. Bach, Treutwein & Heinrich (2026)] Visual acuity: single-run confidence interval obtained via bootstrapping, implemented in the Freiburg Vision Test. Graefes Arch [PDF]
2. Ketz, Bach & Heinrich (2026) Landolt C acuity follows Bloch’s Law for short-duration flashes. Front. Neurosci. 20
3. Anderson, Bach & Hogg (2026) Assessing Visual Function in Retinal Gene Therapy. Methods Mol Biol 3023:225–236 (book chapter)
4. Quanz, Al-Nosairy, Stolle, Kusk, Heinrich, Bach & Hoffmann (2026) Impact of pulsed stimulation on objective and subjective visual acuity measurements in nystagmus. Doc Ophthalmol 152:85–90
5. Bach (2025) Freiburg Vision Test (FrACT): Optimal number of trials? Graefes Arch [PDF]
6. Farassat, Jehle, Heinrich, Lagrèze & Bach (2024) The Freiburg Acuity Test in preschool children: Testability, test–retest variability, and comparison with LEA symbols. Translational Vision Science & Technology 13:14]
7. Korn, Al-Nosairy, Gopiswaminathan, João, Scanferla, Bach & Hoffmann (2024) Scotopic and Photopic Conventional Visual Acuity and Hyperacuity – Binocular Summation. Transl Vis Sci Technol 13:25
8. Bailey, Bach, Ferris, Johnson, Bittner, Colenbrander & Keeffe (2020) Visual acuity. In: [PDF]
9. Freundlieb, Kramer, Herbik, Bach & Hoffmann (2020) Scotopic and photopic conventional visual acuity and hyperacuity. Graefes Archives 258(1):129–135   [→read]
10. Wesemann, Schiefer, Heinrich, Jägle & Bach (2020) Neue DIN- und ISO-Normen zur Sehschärfebestimmung. Der Ophthalmologe 117(1):19–26
11. Rohrschneider, Spittler & Bach (2019) Vergleich der Sehschärfenbestimmung mit Landolt-Ringen versus Zahlen. Der Ophthalmologe 116(11):1058–1063
12. Reiniger, Lobecke, Sabesan, Bach, Verbakel, Brabander, Holz, Berendschot & Harmening (2019) Visual hyperacuity and acuity in the presence of ocular aberrations. JOV 1;19(5):11
13. Bach (2016) Dichoptisches Training bei Amblyopie. Der Ophthalmologe 113(4):304–308
14. Bach, Reuter & Lagrèze (2016) Vergleich zweier Visustests in der Einschulungsuntersuchung – E-Haken-Einblickgerät versus Freiburger Visustest. Der Ophthalmologe 113:684–689
15. Bach M, Schäfer K (2016) Visual acuity testing: feedback affects neither outcome nor reproducibility, but leaves participants happier. PLOS ONE 11(1):e0147803
16. Bartholomew AJ, Lad EM, Cao D, Bach M, Cirulli ET (2016) Individual differences in scotopic visual acuity and contrast sensitivity: genetic and non-genetic influences. PLOS ONE 11(2):e0148192
17. Tebartz van Elst L, Bach M, Blessing J, Riedel A, Bubl E (2015) Normal visual acuity and electrophysiological contrast gain in adults with high functioning autism spectrum disorder. Front Hum Neurosci 9:460
18. König S, Tonagel F, Schiefer U, Bach M, Heinrich SP (2014) Assessing visual acuity across five disease types: ETDRS charts are faster with clinical outcome comparable to Landolt Cs. Graefe’s Arch Clin Exp Ophthalmol 252:1093–1099
19. Heinrich SP, Bach M (2013) Resolution Acuity versus Recognition Acuity with Landolt-style Optotypes. Graef Arch Clin Exp 251:2235–2241
20. Dehnert A, Bach M, Heinrich SP (2011) Subjective visual acuity with simulated defocus. Ophthalmic Physiol Optics 31:625–631
21. Heinrich SP, Krüger K, Bach M (2011) The dynamics of practice effects in an optotype acuity task. Graefe’s Arch Clin Exp Ophthalmol 249:1319–1326
22. Tavassoli T, Latham K, Bach M, Dakin SC, Baron-Cohen S (2011) Psychophysical Measures of Visual Acuity in Autism Spectrum Conditions. Vision Res 51:1778–1780
23. Heinrich SP, Krüger K, Bach M (2010) The effect of optotype presentation duration on acuity estimates revisited. Graefe’s Arch Clin Exp Ophthalmol 248:389–394
24. Wesemann W, Schiefer U, Bach M (2010) Neue DIN-Normen zur Sehschärfebestimmung. Der Ophthalmologe 107:821–826 [→Visustafeln zum Ausdrucken ]
25. Bach M, Dakin SC (2009) Regarding “Eagle-Eyed Visual Acuity: An Experimental Investigation of Enhanced Perception in Autism” Biol Psychiat 66:e19–e20
26. Lange C, Feltgen N, Junker B, Schulze-Bonsel K, Bach M (2009) Resolving the clinical acuity categories “hand motion” and “counting fingers” using the Freiburg Visual Acuity Test (FrACT). Graefe’s Arch Clin Exp Ophthalmol 247:137–142 [→PDF]
27. Bach M (2007) The Freiburg Visual Acuity Test – Variability unchanged by post-hoc re-analysis. Graefe’s Arch Clin Exp Ophthalmol 245:965–971
28. Schulze-Bonsel K, Feltgen N, Burau H, Hansen L, Bach M (2006) Visual acuities “hand motion” and “counting fingers” can be quantified with the Freiburg visual acuity test. Invest Ophth Vis Sci 47: 1236–1240
29. Jägle H, de Luca E, Serey L, Bach M, Sharpe LT (2006) Visual acuity and X-linked color blindness. Graefe’s Arch Clin Exp Ophthalmol 244:447–453
30. Bach M, Kommerell G (1998) Sehschärfebestimmung nach Europäischer Norm – wissenschaftliche Grundlagen und Möglichkeiten der automatischen Messung. Klin Mbl Augenheilk 212:190–195 (→HTML)
31. Bach M (1997) Anti-aliasing and dithering in the “Freiburg Visual Acuity Test”. Spatial Vision 11:85–89
32. Bach M (1996) The “Freiburg Visual Acuity Test” – Automatic measurement of visual acuity. Optometry and Vision Science 73:49–53

1. Haldina, Bach, Duval, Hoffmann & Heinrich SP (2026) A concise overview of using the P300 component of the event-related potential for objective estimation of visual acuity. Front Ophthalmol 6:1846725
2. Heinrich SP, Strübin I, Bach M (2021) VEP-based acuity estimation: unaffected by translucency of contralateral occlusion. Doc Ophthalmol 143:249–257
3. Hamilton R, Bach M, Heinrich SP, Hoffmann MB, Odom JV, McCulloch DL, Thompson DA (2021) VEP estimation of visual acuity: a systematic review. Doc Ophthalmol 142:17–24 [→PDF]
4. Hamilton R, Bach M, Heinrich SP, Hoffmann MB, Odom JV, McCulloch DL, Thompson DA (2021) ISCEV extended protocol for estimating visual acuity using VEP spatial frequency thresholds. Doc Ophthalmol 142:25–74 [→PDF]
5. Bach M, Farmer JD (2020) Evaluation of the “Freiburg Acuity VEP” on commercial equipment. Doc Ophthalmol 140:139–145   [→PDF]
6. Bach M, Heinrich SP (2019) Acuity VEP: Improved with machine learning. Doc Ophthalmol 139(2):113–122. read→here
7. Hoffmann MB, Brands J, Behrens-Baumann W, Bach M (2017) VEP-based acuity assessment in low vision. Doc Ophthalmol 135(3):209–218 read→here
8. Heinrich SP, Bock CM, Bach M (2016) Imitating the effect of amblyopia on VEP-based acuity estimates. Doc Ophthalmol 133:183–187
9. Heinrich SP, Lüth I, Bach M (2015) Event-related potentials allow for optotype-based objective acuity estimation. IOVS 56:2184–2191
10. Marhöfer DJ, Bach M, Heinrich SP (2015) Objective acuity assessment with self-face P300 responses. Doc Ophthalmol 131(2):137–148
11. Wenner Y, Heinrich SP, Beisse C, Fuchs A, Bach M (2014) Visual evoked potential-based acuity assessment: overestimation in amblyopia. Doc Ophthalmol 128:191–200
12. Heinrich SP, Marhöfer D, Bach M (2010) “Cognitive” visual acuity estimation based on the event-related potential P300 component. Clin Neurophysiol 121:1464–1472
13. Bach M, Maurer JP, Wolf ME (2008) Visual evoked potential-based acuity assessment in normal vision, artificially degraded vision, and in patients. Br J Ophthalmol 92:396–403