RESUMEN
BACKGROUND: Electromyographic (EMG) signal decomposition is the process by which an EMG signal is decomposed into its constituent motor unit potential trains (MUPTs). A major step in EMG decomposition is feature extraction in which each detected motor unit potential (MUP) is represented by a feature vector. As with any other pattern recognition system, feature extraction has a significant impact on the performance of a decomposition system. EMG decomposition has been studied well and several systems were proposed, but feature extraction step has not been investigated in detail. OBJECTIVE: Several EMG signals were generated using a physiologically-based EMG signal simulation algorithm. For each signal, the firing patterns of motor units (MUs) provided by the simulator were used to extract MUPs of each MU. For feature extraction, different wavelet families including Daubechies (db), Symlets, Coiflets, bi-orthogonal, reverse bi-orthogonal and discrete Meyer were investigated. Moreover, the possibility of reducing the dimensionality of MUP feature vector is explored in this work. The MUPs represented using wavelet-domain features are transformed into a new coordinate system using Principal Component Analysis (PCA). The features were evaluated regarding their capability in discriminating MUPs of individual MUs. RESULTS: Extensive studies on different mother wavelet functions revealed that db2, coif1, sym5, bior2.2, bior4.4, and rbior2.2 are the best ones in differentiating MUPs of different MUs. The best results were achieved at the 4th detail coefficient. Overall, rbior2.2 outperformed all wavelet functions studied; nevertheless for EMG signals composed of more than 12 MUPTs, syms5 wavelet function is the best function. Applying PCA slightly enhanced the results.
RESUMEN
The purpose of this study was to examine the diameter, location, and frequency of the appearance of the posterior superior alveolar artery (PSAA) in preoperative cone beam computed tomography (CBCT) scans. Two hundred and eleven pre-implant CBCT scans were reviewed. The following criteria were considered in all subjects: (1) the location of the artery: intra-sinus or below the membrane (type I), intraosseous (type II), or superficial (type III); (2) the distance between the lower border of the artery and the alveolar crest; (3) the bone height measured from the floor of the sinus to the crest of the ridge; (4) the distance from the lateral wall of the artery to the medial wall of the maxillary sinus; and (5) the diameter of the artery (in millimetres). The distance between the artery and the medial sinus wall, as well as the diameter of the artery, were greater in patients with an alveolar bone height ≤10mm than in those with a bone height >10mm. The distance from the artery to the medial sinus wall and the diameter of the artery were positively correlated with the number of missing teeth. It was also found that the diameter of the PSAA increased with increasing age.
