Zheng Tai1, Richard W Hertle, Richard A Bilonick, Dongsheng Yang. 1. The Laboratory of Visual and Ocular Motor Neurophysiology, The UPMC and Children’s Eye Center, Department of Ophthalmology, Pediatric Ophthalmology, The Children’s Hospital of Pittsburgh, University of Pittsburgh, USA.
Abstract
AIMS: We developed a new data analysis algorithm called the automated nystagmus acuity function (ANAF) to automatically assess nystagmus acuity function. We compared results from the ANAF with those of the well-known expanded nystagmus acuity function (NAFX). METHODS: Using the ANAF and NAFX, we analysed 60 segments of nystagmus data collected with a video-based eye tracking system (EyeLink 1000) from 30 patients with infantile or mal-development fusional nystagmus. The ANAF algorithm used the best-foveation positions (not true foveation positions) and all data points in each nystagmus cycle to calculate a nystagmus acuity function. RESULTS: The ANAF automatically produced a nystagmus acuity function in a few seconds because manual identification of foveation eye positions is not required. A structural equation model was used to compare the ANAF and NAFX. Both ANAF and NAFX have similar measurement imprecision and relatively little bias. The estimated bias was not statistically significant for either methods or replicates. CONCLUSIONS: We conclude that the ANAF is a valid and efficient algorithm for determining a nystagmus acuity function.
AIMS: We developed a new data analysis algorithm called the automated nystagmus acuity function (ANAF) to automatically assess nystagmus acuity function. We compared results from the ANAF with those of the well-known expanded nystagmus acuity function (NAFX). METHODS: Using the ANAF and NAFX, we analysed 60 segments of nystagmus data collected with a video-based eye tracking system (EyeLink 1000) from 30 patients with infantile or mal-development fusional nystagmus. The ANAF algorithm used the best-foveation positions (not true foveation positions) and all data points in each nystagmus cycle to calculate a nystagmus acuity function. RESULTS: The ANAF automatically produced a nystagmus acuity function in a few seconds because manual identification of foveation eye positions is not required. A structural equation model was used to compare the ANAF and NAFX. Both ANAF and NAFX have similar measurement imprecision and relatively little bias. The estimated bias was not statistically significant for either methods or replicates. CONCLUSIONS: We conclude that the ANAF is a valid and efficient algorithm for determining a nystagmus acuity function.