BACKGROUND AND PURPOSE Our previous studies demonstrated that mental imagery intervention enhanced poststroke patients relearning daily task performance. This study aimed to test the efficacy of mental imagery for promoting generalization of the task skills learned in a training environment to trained and untrained tasks carried out in a novel environment. METHODS Thirty-five acute poststroke...

Due to the non-stationarity of EEG signals, online training and adaptation is essential to EEG based brain-computer interface (BCI) systems. Asynchronous BCI offers more natural human-machine interaction, but it is a great challenge to train and adapt an asynchronous BCI online because the user’s control intention and timing are usually unknown. This paper proposes a novel motor imagery based a...

This paper describes our approach to the DSTL Satellite Imagery Feature Detection challenge [11] run by Kaggle. The primary goal of this challenge is accurate semantic segmentation of different classes in satellite imagery. Our approach is based on an adaptation of fully convolutional neural network for multispectral data processing. In addition, we defined several modifications to the training...

In this paper, we propose a set of wavelet-based combined feature vectors and a Gaussian mixture model (GMM)-supervector to enhance training speed and classification accuracy in motor imagery brain-computer interfaces. The proposed method is configured as follows: first, wavelet transforms are applied to extract the feature vectors for identification of motor imagery electroencephalography (EEG...

Recent work has focused on generating synthetic imagery and augmenting real imagery to increase the size and variability of training data for learning visual tasks in urban scenes. This includes increasing the occurrence of occlusions or varying environmental and weather effects. However, few have addressed modeling the variation in the sensor domain. Unfortunately, varying sensor effects can d...

Motor imagery is a common control strategy in EEG-based brain-computer interfaces (BCIs). However, voluntary control of sensorimotor (SMR) rhythms by imagining a movement can be skilful and unintuitive and usually requires a varying amount of user training. To boost the training process, a whole class of BCI systems have been proposed, providing feedback as early as possible while continuously ...

The main purpose of this study was to examine whether the use of internal imagery would affect high jumping performance for active high jumping athletes. Over a period of six weeks, a group of active high jumpers were trained with an internal imagery program for a total of 72 minutes. This group was compared to a control group consisting of active high jumpers that only maintained their regular...

Research in sports, dance and rehabilitation has shown that basic action concepts (BACs) are fundamental building blocks of mental action representations. BACs are based on chunked body postures related to common functions for realizing action goals. In this paper, we outline issues in research methodology and an experimental method, the structural dimensional analysis of mental representation ...

This paper shows the potential of LIDAR for extracting buildings and other objects from medium resolution satellite imagery. To that end, the study integrated multispectral and LIDAR elevation data in a single imagery file and then classified it using the Support Vector Machine. To determine the method’s potential, the study used a SPOT5 satellite from an area situated southeast of Madrid, Spai...