This paper presents a new 3D object representation called a modified exoskeleton (mES) which is another type of skeleton that is more stable and less sensitive to rotation and noise than the conventional skeletons. The mES preserves significant characteristics about an object, that are meaningful for object recognition and reconstruction, as the skeleton does. Then a fast and reliable matching algorithm for recognition and classification system which can identify and classify an observed object is introduced. The main advantage of our matching algorithm is that it can recognize the observed 3D object regardless of its orientation and noise. The first experiment was conducted on a set of artificial 3D objects and the average recognition rate of 92.60% based on the mES is achieved. The second experiment was tested on the classification of volumetric lung tumor data sets and the obtained results are promising.

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Electrocorticography (ECoG) has emerged as a new sig-nal platform for brain–computer interface (BCI) systems. Classically, the cortical physiology that has be-en commonly investigated and utilized for device control in humans has been brain signals from the sensorimotor cortex. Hence, it was unknown whether other neurophysiological substrates, such as the speech network, could be used to further improve on or complement existing motor-based control paradigms. We de-monstrate here for the first time that ECoG signals associated with different overt and imagined phoneme articulation can enable invasively monitored human patients to control a one-dimensional computer cursor rapidly and accurately. This phonetic content was distinguishable within higher gamma frequency osci-llations and enabled users to achieve final target accuracies between 68% and 91% within 15 min. Addi-tionally, one of the patients achieved robust control using recordings from a microarray consisting of 1 mm spaced microwires. These findings suggest that the cortical network associated with speech could pro-vide an additional cognitive and physiologic substrate for BCI operation and that these signals can be ac-quired from a cortical array that is small and minimally invasive.

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