Suitability of an inter-burst detection method for grading hypoxic-ischemic encephalopathy in newborn EEG.

Electroencephalography (EEG) is an important clinical tool for grading injury caused by lack of oxygen or blood to the brain during birth. Characteristics of low-voltage waveforms, known as inter-bursts, are related to different grades of injury. This study assesses the suitability of an existing inter-burst detection method, developed from preterm infants born <; 30 weeks of gestational age, to detect inter-bursts in term infants.

Feature selection and classification methodology for the detection of knee-joint disorders.

Vibroarthographic (VAG) signals emitted from the knee joint disorder provides an early diagnostic tool. The nonstationary and nonlinear nature of VAG signal makes an important aspect for feature extraction. In this work, we investigate VAG signals by proposing a wavelet based decomposition.