Suppr超能文献

Cyclic summation versus m-sequence technique in the multifocal ERG.

作者信息

Lindenberg Thomas, Horn Folkert K, Korth Matthias

机构信息

Augenklinik mit Poliklinik der Friedrich-Alexander-Universität Erlangen-Nürnberg, Schwabachanlage 6, 91054 Erlangen, Germany.

出版信息

Graefes Arch Clin Exp Ophthalmol. 2003 Jun;241(6):505-10. doi: 10.1007/s00417-002-0608-2. Epub 2003 May 17.

Abstract

BACKGROUND

The m-sequence technique is a typical tool for the multifocal ERG. The use of LEDs instead of a computer monitor enables a new technique that merits closer investigation: The cyclic summation technique. The aim of this study was to compare the two methods.

METHODS

Six normal right eyes were examined with the RETIscan system using DTL electrodes. With an LED array (display diameter 52 degrees, 103 segments, 1 foveal + 102 arranged in six concentric rings) we studied: (1). first order kernels (m-sequence); (2). 30-Hz flicker responses (m-sequence); (3). 30-Hz flicker responses (cyclic summation). The three methods were tested with a pattern of concentric rings generated by selective deactivation of LEDs (the central LED and rings 2, 4 and 6; rings 1, 3 and 5 remained active). In each case six cumulative measurements (40 s each) were made and stored separately. To determine the signal-to-noise ratio, the average mf ERG response to all active LEDs was divided by the average response to the inactive ones.

RESULTS

  1. Using cyclic summation the signal-to-noise ratio exceeds the signal-to-noise ratio of both m-sequence-controlled stimuli about twofold. This implies also better spatial resolution with the cyclic summation technique 2. Since the signal-to-noise ratio increases faster with the cyclic summation technique than with the m-sequence technique, the gain of time in mf ERG can reach 80%.

CONCLUSION

As far as the signal-to-noise ratio and measuring time is concerned, the cyclic summation technique outmatches the m-sequence technique in mf ERG.

摘要

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验