High-density channels are often used to acquire electroencephalogram (EEG) spatial information in different cortical regions of the brain in brain-computer interface (BCI) systems. However, applying excessive channels is inconvenient for signal acquisition, and it may bring artifacts. To avoid these defects, the common spatial pattern (CSP) algorithm was used for channel selection and a selection criteria based on norm-2 is proposed in this paper. The channels with the highest M scores were selected for the purpose of using fewer channels to acquire similar rate with high density channels. The Dataset III a from BCI competition 2005 were used for comparing the classification accuracies of three motor imagery between whole channels and the selected channels with the present proposed method. The experimental results showed that the classification accuracies of three subjects using the 20 channels selected with the present method were all higher than the classification accuracies using all 60 channels, which convinced that our method could be more effective and useful.
Algorithms ; Brain-Computer Interfaces ; Electroencephalography ; Humans ; Pattern Recognition, Physiological

With the new-style thoracentesis needles with spring-loaded valve designed by ourselves, thoracentesis were carried out in 60 patients with ages ranging from 2 to 74 years. The successful rate for the operation was 100% (198/198), without any major complications such as pneumothorax, hemothorax, pleural shock or infection. The results show that this kind of puncture needle is multi-purpose and easy to operate, with high safety and reliability.
Adolescent ; Adult ; Aged ; Child ; Child, Preschool ; Equipment Design ; Female ; Humans ; Male ; Middle Aged ; Needles ; Paracentesis ; instrumentation ; methods ; Pleural Effusion ; diagnosis ; therapy ; Young Adult