Hilbert-Huang transform in detecting and analyzing the uterine contraction activities.

Objective: The diagnosis of labor is currently one of the most difficult problems encountered by obstetrical healthcare providers. A major health problem is the increase in the rate of preterm delivery, which is responsible for 75% of all deaths in newborns. In addition, preterm delivery is associated with several cognitive and health problems in later life and enormous costs for the health system.

Electroencephalography Spectral Power Density in First-Episode Mania: A Comparative Study with Subsequent Remission Period.

Introduction: Our aim in this study was to investigate spectral power density (PSD) in first-episode mania and subsequent remission period and to evaluate their difference.

Methods: Sixty-nine consecutive cases referring to our hospital within the previous 1 year, who were evaluated as bipolar disorder manic episode according to The Diagnostic and Statistical Manual of Mental Disorders-IV (DSM-IV) at the first episode and had the informed consent form signed by first degree relatives, were included in this study. Exclusion criteria included having previous depressive episode, using drugs which could influence electroencephalographic activity before electroencephalography (EEG), and having previous neurological disease, particularly epilepsy, head trauma, and/or loss of consciousness.

Determination of ECoG information flow activity based on Granger causality and Hilbert transformation.

Analysis of directional information flow patterns among different regions of the brain is important for investigating the relation between ECoG (electrocorticographic) and mental activity. The objective is to study and evaluate the information flow activity at different frequencies in the primary motor cortex. We employed Granger causality for capturing the future state of the propagation path and direction between recording electrode sites on the cerebral cortex.

Sub-similarity matching based on data mining with dihedral angles.

Protein sub-similarity matching remains largely unknown even though it is becoming one of the most important open problems in bioinformatics for drug and vaccine design. Variations in human immune responses to vaccines are, and thus responses, fail. We propose a new matching and protein alignment method based on clustering and Longest Common Subsequence (LCS) techniques.

A radar-enabled collaborative sensor network integrating COTS technology for surveillance and tracking.

The feasibility of using Commercial Off-The-Shelf (COTS) sensor nodes is studied in a distributed network, aiming at dynamic surveillance and tracking of ground targets. Data acquisition by low-cost (<$50 US) miniature low-power radar through a wireless mote is described. We demonstrate the detection, ranging and velocity estimation, classification and tracking capabilities of the mini-radar, and compare results to simulations and manual measurements.

Classification of imaginary movements in ECoG with a hybrid approach based on multi-dimensional Hilbert-SVM solution.

The study presented in this paper shows that electrocorticographic (ECoG) signals can be classified for making use of a human brain-computer interface (BCI) field. The results show that certain invariant phase transition features can be reliably used to classify two types of imagined movements accurately. Those are the left small-finger and tongue movements.