A PCA/ICA based Fetal ECG Extraction from Mother Abdominal Recordings by Means of a Novel Data-driven Approach to Fetal ECG Quality Assessment.

BACKGROUND: Fetal electrocardiography is a developing field that provides valuable information on the fetal health during pregnancy. By early diagnosis and treatment of fetal heart problems, more survival chance is given to the infant. MATERIALS AND METHODS: Here, we extract fetal ECG from maternal abdominal recordings and detect R-peaks in order to recognize fetal heart rate. On the next step, we find a better and more qualified extracted fetal ECG by using a novel approach. RESULTS: In this paper, a PCA/ICA-based algorithm is proposed for extracting fetal ECG, and fetal R-peaks are detected as well. The method validates the quality of extracted ECGs and selects the best candidate fetal ECG to provide the required morphological ECG features such as fetal heart rate and RR interval for more clinical examinations. The method was evaluated using the dataset which was provided by PhysioNet/Computing in Cardiology Challenge 2013. The dataset consists of 75 recordings of 4-channel ECGs each containing 1-minute length for training and 100 similar recordings for testing. CONCLUSION: When the proposed algorithm was applied to the test set, the scores of 85.853 bpm2 for fetal heart rate and an error of 9.725 ms RMS for fetal RR-interval estimation were obtained.

A string matching computer-assisted system for dolphin photoidentification.

This paper presents a syntactic/semantic string representation scheme as well as a string matching method as part of a computer-assisted system to identify dolphins from photographs of their dorsal fins. A low-level string representation is constructed from the curvature function of a dolphin's fin trailing edge, consisting of positive and negative curvature primitives. A high-level string representation is then built over the low-level string via merging appropriate groupings of primitives in order to have a less sensitive representation to curvature fluctuations or noise. A family of syntactic/semantic distance measures between two strings is introduced. A composite distance measure is then defined and used as a dissimilarity measure for database search, highlighting both the syntax (structure or sequence) and semantic (attribute or feature) differences. The syntax consists of an ordered sequence of significant protrusions and intrusions on the edge, while the semantics consist of seven attributes extracted from the edge and its curvature function. The matching results are reported for a database of 624 images corresponding to 164 individual dolphins. The identification results indicate that the developed string matching method performs better than the previous matching methods including dorsal ratio, curvature, and curve matching. The developed computer-assisted system can help marine mammalogists in their identification of dolphins, since it allows them to examine only a handful of candidate images instead of the currently used manual searching of the entire database.