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Sensory information, such as the tactile or proprioceptive signals, helps motor brain-machine interface (mBMI) work more naturally. Before applying sensory feedback, we need to explore if the neural activities are discriminative to different stimuli during a BMI task. Previous studies on the cortical discrimination are mainly focused on the rat whisker system. In this paper, we design a BMI task,...
Neurons' tuning describes how the neural activity responses to the stimulus. As the prior knowledge, understanding more about the neuron tuning helps better decode the movement information from the neural firings for brain machine interfaces. We are interested in qualifying the neural tuning and observe whether there are similar tunings among the ensemble recordings and how they change over time....
Decoding algorithm in motor Brain Machine Interfaces translates the neural signals to movement parameters. They usually assume the connection between the neural firings and movements to be stationary, which is not true according to the recent studies that observe the time-varying neuron tuning property. This property results from the neural plasticity and motor learning etc., which leads to the degeneration...
Motor brain-machine interface (BMI) has great potentials in neural motor prostheses and has received increasing attention during the past decades in the neural engineering field. It requires an approach to decode neural activities that represents desired movements. Much of the progress in decoding algorithms has been driven by the availability of neural data, e.g. spike trains, in some research groups...
The long-term stability is one of the most important issues to be considered when designing practical Brain Machine Interfaces(BMIs). Because Local Field Potentials (LFPs) could provide durable recording, they were supposed to be an alternative promising signal source. Previous studies have shown that much kinematics information could be extracted from LFPs in motor cortex, especially from the low...
Face recognition has attracted great interest especially in computer vision, but poses and illumination of the face lay great difficulty in recognition accuracy. Studies on human face in the field of cognitive neuroscience found some face-specific event-related potential (ERP) components, such as N170, VPP. And some researchers used these face-specific ERP components to achieve face detection based...
“Semantic gap” is the major bottleneck of semantic-based multimedia retrieval technique in the field of information retrieval. Studies have shown that robust semantic-based image retrieval can be achieved by single-trial visual evoked event related potential (ERP) detection. However, the question remains whether auditory evoked ERP can be utilized to achieve semantic-based sound retrieval. In this...
The reform of teaching approach has been the focus of modern opening educational reform and research. The real science thrives on both revolutionary and frontier progress that the textbook can not include. Based on the analysis of the characteristics of several the engineering courses, we build the academic frontier-based approach (AFA) for the purpose of combination of the basic and academic frontier...
Decoding with the important neuron subset has been widely used in brain machine interfaces (BMIs), as an effective strategy to reduce computational complexity. Previous works usually assume stationary of neuron importance, which may not be true according to recent research. We propose to conduct a mutual information evaluation to track the time-varying neuron importance over time. We found worth noting...
This paper presents a method for extracting and recognizing the billet numbers according to the feature of each number. Its advantages lie in that no template image is required, the requirement to the number in the image is low, and the anti-interference performance is strong. This method is able to recognize the numbers on the billet with a high efficiency
Bulk data transfers account for a large portion of inter-datacenter traffic, such as backups, propagation of bulky updates and migration of data. These bulk data transfers not only consume massive inter-datacenter bandwidth, but also increase the transmission cost of datacenters. To solve this problem, we first employ the max-min fairness to the design of optimal multiple bulk data transfers scheduling...
The rising cost of electricity has forced business organizations to find new ways to cut energy spending. This paper studies how to reduce energy consumption in virtual network embedding, which embeds virtual networks (VNs) requested by users to a shared substrate network (SN) run by an infrastructure provider (InP). Previous research has primarily focused on finding embedding methods to increase...
For the particular application in infrared camera based electronic whiteboard, a simple and rapid method of target recognition is proposed to address the conflict between accuracy and speed of identification, which is based on the pixels' sparse characteristic in gray scale distribution and space distribution. An experimental platform is built to verify the method. The method is proved to be capable...
Real-time computation, portability and flexibility are crucial for practical brain-machine interface (BMI) applications. In this work, we proposed Hardware Processing Modules (HPMs) as a method for accelerating BMI computation. Two HPMs have been developed. One is the field-programmable gate array (FPGA) implementation of spike sorting based on probabilistic neural network (PNN), and the other is...
Brain Machine Interfaces (BMI) aim at building a direct communication link between the neural system and external devices. The decoding of neuronal signals is one of the important steps in BMI systems. Existing decoding methods commonly fall into two categories, i.e., linear methods and nonlinear methods. This paper compares the performance between the two kinds of methods in the decoding of motor...
The article presents a new method for motor-related EEG recognition which comprehensively optimizes the frequency-time-space features in a user-specific way. The method creates optimized time and frequency grids and adaptively selects channels for common spatial pattern (CSP) filters to enhance its power. The results show that the optimized features denotes a specific perspective to visualize frequency-time-spatial...
Brain machine interfaces (BMIs), offer a direct path for brain to communicate with outside world, mainly use central neural activities to control artificial external devices. These techniques to collect the brain signals could be distinguished as non-invasive or invasive BMIs according to the position of recoding electrodes. Compared with non-invasive BMIs, invasive BMIs have wide potential in assisting,...
In this paper, a method of resource sharing fast encryption and decryption algorithm is proposed. By changing the traditional encrypting and decrypting s_box of AES and using a look-up table to realize the resource sharing during the encryption and decryption, the area of the hardware is effectively reduced. Moreover, the series-mixed transform of AES encryption and decryption is improved in order...
Knowledge service is the integration of knowledge and services. Introducing the concept of “people-oriented” in pervasive computing to knowledge service, this paper constructs a kind of pervasive knowledge service model by means of multidisciplinary research achievements such as intelligence computing, system science, ecology, system science, knowledge science and service science, especially generalized...
As intermodulated sinusoids are generated when a nonlinear system is subject to multiple fundamental frequencies, an approach is proposed in this paper to detect and to estimate, or simply to retrieve the intermodulated sinusoids. It is shown that both detection and estimation performance are improved by using the intermodulation relationship as an additional constraint. Although the periodogram method...
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