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Purpose-To investigate whether combining optic disc topography and short-wavelength automated perimetry (SWAP) data improves the diagnostic accuracy of relevance vector machine (RVM) classifiers for detecting glaucomatous eyes compared to using each test alone.Methods-One eye of 144 glaucoma patients and 68 healthy controls from the Diagnostic Innovations in Glaucoma Study were included. RVM were trained and tested with cross-validation on optimized (backward elimination) SWAP features (thresholds plus age; pattern deviation (PD); total deviation (TD)) and on Heidelberg Retina Tomograph II (HRT) optic disc topography features, independently and in combination. RVM performance was also compared to two HRT linear discriminant functions (LDF) and to SWAP mean deviation (MD) and pattern standard deviation (PSD). Classifier performance was measured by the area under the receiver operating characteristic curves (AUROCs) generated for each feature set and by the sensitivities at set specificities of 75%, 90% and 96%.Results-RVM trained on combined HRT and SWAP thresholds plus age had significantly higher AUROC (0.93) than RVM trained on HRT (0.88) and SWAP (0.76) alone. AUROCs for the SWAP global indices (MD: 0.68; PSD: 0.72) offered no advantage over SWAP thresholds plus age, while the LDF AUROCs were significantly lower than RVM trained on the combined SWAP and HRT feature set and on HRT alone feature set.Conclusions-Training RVM on combined optimized HRT and SWAP data improved diagnostic accuracy compared to training on SWAP and HRT parameters alone. Future research may identify other combinations of tests and classifiers that can also improve diagnostic accuracy. NIH-PA Author ManuscriptNIH-PA Author Manuscript NIH-PA Author ManuscriptDiagnosis and staging of glaucoma rely on both structural evaluation of the optic nerve and functional assessment of the visual field1. Several studies have documented the ability of confocal scanning laser ophthalmoscopy optic disc topographic measurements to discriminate between healthy and glaucomatous eyes2 -4. Function-specific tests of visual function have been shown to be more sensitive to glaucomatous damage than standard automated perimetry (SAP)5 -7. Short-wavelength automated perimetry (SWAP), for example, targets the blueyellow pathway and may detect glaucomatous damage up to five years earlier than SAP8. A recent study has shown that the sensitivity to detect glaucoma can be improved by combining data from structural and function-specific tests9.In efforts to summarize the large amount of data produced by structural and functional tests, various types of pattern-recognition algorithms known as machine learning classifiers have been applied to optic disc imaging results and visual field data. Machine learning classifiers (MLCs) are well suited for evaluating these large data sets, because they are able to detect complex patterns and trends. Several types of MLCs have been applied to glaucoma, including the mixture of Gaussian (MoG), sub-space mixture of Gaussian (...

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An important factor affecting the performance of EA modulators is their tone behavior. A recent approach to alleviate the tone problem consists of moving the open loop poles outside the unit circle. In this paper, we determine the frequency location of two dominant tones as a function of pole location and obtain a partial characterization of the spectral shape. Audio testing along with a series of simulations are then performed to compare the efficacy of pole placement with that of the more traditional tone removal technique of dithering.

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