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Erkan Zeki Engin

Publications and source records attributed to Erkan Zeki Engin.

2 recordsLinked to original sources

Laryngeal findings and voice quality in Sjögren's syndrome.

OBJECTIVE: The effect of Sjögren syndrome (SS) on perceptual ratings of the laryngeal findings using the Reflux Finding Score (RFS) and the Reflux Symptom Index (RSI) and the objective voice quality using Jitter (JITT), Pitch Period Perturbation Quotient (PPQ), Shimmer (Shim), Amplitude Perturbation Quotient (APQ) and Noise-to-Harmonic Ratio (NHR) was examined. METHODS: Seventy-seven patients with SS and seventy-seven healthy individuals for the control group were studied. The Reflux Symptom Index (RSI); nine-item outcomes instrument for assessment of symptoms in patients and the Reflux Finding Score (RFS), eight-item laryngoscopic-based scale for evaluation of laryngeal findings in patients were realised. The Multi Dimensional Voice Program (MDVP) was used for capturing and analysis of the voice samples. For comparison of all parameters of patients and control group subjects, the independent sample t-test was used. RESULTS: The difference of RSI and RFS between patients with SS and control subjects was statistically significant. The difference of voice quality parameters between patients with SS and control subjects expect NHR were statistically significant. CONCLUSION: There is a significant association between SS and a variety of laryngeal pathologies. The SS patients with reflux symptoms and voice problems must be examined by an ENT specialist and local laryngeal manifestations of SS can be treated symptomatically.

Adult↗

Wavelet transformation based watermarking technique for human electrocardiogram (ECG).

Nowadays, watermarking has become a technology of choice for a broad range of multimedia copyright protection applications. Watermarks have also been used to embed prespecified data in biomedical signals. Thus, the watermarked biomedical signals being transmitted through communication are resistant to some attacks. This paper investigates discrete wavelet transform based watermarking technique for signal integrity verification in an Electrocardiogram (ECG) coming from four ECG classes for monitoring application of cardiovascular diseases. The proposed technique is evaluated under different noisy conditions for different wavelet functions. Daubechies (db2) wavelet function based technique performs better than those of Biorthogonal (bior5.5) wavelet function. For the beat-to-beat applications, all performance results belonging to four ECG classes are highly moderate.

Algorithms↗