This paper presents a new method for the analysis of newborn infant cry to detect hypothyroidism. Hypothyroidism is a condition caused by insufficient production of thyroid hormone by the thyroid gland. The proposed technique is robust as it automatically extracts and analyzes features of infant cry signal. In preprocessing of the signals, separation of voice or unvoiced sections is implemented with automatic segmentation that integrates zero rate crossing and short time energy methods. For feature extraction, the Mel frequency cepstrum coefficient analysis is used to extract main features from the infant cry signal. Then, similarities between the two types of signals and significant information are studied using the F-Ratio analysis. Results show that the F-Ratio analysis was able to discriminate between essential and non-essential features for classification.
Surface Enhanced Raman spectroscopy (SERS) is an enhanced technique of Raman spectroscopy, which amplifies the intensity of Raman scattering to a practical range with adsorption of analyte onto nano-size plasmonic material such as gold, silver or copper. This feature of SERS has given it a niche in tracing molecular structure, especially useful for marking diseases specific biomarker. NS1 protein has been clinically accepted as an alternative biomarker for diseases caused by flavivirus. Detection of Nonstructural Protein 1 (NS1) will allow early diagnosis of the diseases. Its presence in the blood serum has been reported as early as first day of infection. With gold substrate, our work here intends to explore if SERS is suitable to detect NS1 from saliva, with saliva becoming the most favored alternative to blood as diagnostic fluid due to its advantages in sample collection. Our experimental results find both gold coated slide (GS) and saliva being Raman inactive, but the molecular fingerprint of NS1 protein at Raman shift 1012 cm(-1), which has never been reported before. The distinct peak is discovered to be attributed by breathing vibration of the benzene ring structure of NS1 side chain molecule. The characteristic peak is also found to vary in direct proportion to concentration of the NS1-saliva mixture, with a correlation coefficient of +0.96118 and a standard error estimation of 0.11382.
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