scholarly journals Developing a 3- to 6-state EEG-based brain-computer interface for a robotic manipulator control

2017 ◽  
Author(s):  
Yuriy Mishchenko ◽  
Murat Kaya ◽  
Erkan Ozbay ◽  
Hilmi Yanar
Keyword(s):  
Error Rate ◽  
High Performance ◽  
Processing System ◽  
Robotic Control ◽  
Signal Processing System ◽  
Eeg Data ◽  
Recent Developments ◽  
Assistive Systems ◽  
Time Required ◽  
Bci System

AbstractRecent developments in BCI techniques have demonstrated high-performance control of robotic prosthetic systems primarily via invasive methods. In this work we develop an electroencephalography (EEG) based noninvasive BCI system that can be used for a similar, albeit lower-speed robotic control, and a signal processing system for detecting user’s mental intent from EEG data based on up to 6-state motor-imagery BCI communication paradigm. We examine the performance of that system on experimental data collected from 12 healthy participants and analyzed offline. We show that our EEG BCI system can correctly identify different motor imageries in EEG data with high accuracy: 3 out of 12 participants achieved accuracy of 6-state communication in 80-90% range, while 2 participants could not achieve a satisfactory accuracy. We further implement an online BCI system for control of a virtual 3 degree-of-freedom prosthetic manipulator and test it with our 3 best participants. The participants’ ability to control the BCI is quantified by using the percentage of successfully completed BCI tasks, the time required to complete a task, and the error rate. 2 participants were able to successfully complete 100% of the test tasks, demonstrating on average the error rate of 80% and requiring 5-10 seconds to execute a manipulator move. 1 participant failed to demonstrate a satisfactory performance in online trials. Our results lay a foundation for further development of EEG BCI-based robotic assistive systems and demonstrate that EEG-based BCI may be feasible for robotic control by paralyzed and immobilized individuals.

A High-Performance Signal Processing System for Monopulse Tracking Radar

2011 ◽  
Vol 383-390 ◽  
pp. 471-475
Author(s):  
Yong Bin Hong ◽  
Cheng Fa Xu ◽  
Mei Guo Gao ◽  
Li Zhi Zhao
Keyword(s):  
Signal Processing ◽  
High Performance ◽  
Dynamic Range ◽  
Signal To Noise Ratio ◽  
Processing System ◽  
Digital Signal ◽  
Radar Signal ◽  
Signal Processing System ◽  
Parallel Pipelined ◽  
Tracking Radar

A radar signal processing system characterizing high instantaneous dynamic range and low system latency is designed based on a specifically developed signal processing platform. Instantaneous dynamic range loss is a critical problem when digital signal processing is performed on fixed-point FPGAs. In this paper, the problem is well resolved by increasing the wordlength according to signal-to-noise ratio (SNR) gain of the algorithms through the data path. The distinctive software structure featuring parallel pipelined processing and “data flow drive” reduces the system latency to one coherent processing interval (CPI), which significantly improves the maximum tracking angular velocity of the monopulse tracking radar. Additionally, some important electronic counter-countermeasures (ECCM) are incorporated into this signal processing system.

A Multi-Channel Radar Signal Process System

2010 ◽  
Vol 20-23 ◽  
pp. 884-888
Author(s):  
Cheng Fa Xu ◽  
Jun Ling Wang ◽  
Rong Gang Wu
Keyword(s):  
Signal Processing ◽  
High Performance ◽  
Processing System ◽  
General Purpose ◽  
Radar Signal ◽  
Radar Signal Processing ◽  
Signal Processing System ◽  
Signal Processing Algorithm ◽  
High Data ◽  
Advantages And Disadvantages

In order to meet multi-channel, high data rate, intensive computing capacity of modern radar signal processing, a standard, scalable, high-performance general-purpose radar signal processing system platform is proposed. The main processor of this system platform is the DSP and FPGA. In the analysis of different kinds of radar signal processing algorithm, and taking into account the respective advantages and disadvantages of DSP and FPGA, In this paper, a software architecture method for radar signal processing is given to decide how to distribute different algorithm into DSP and FPGA. At last, for a certain type of circular array radar, an implementation of radar signal processing by using the general-purpose radar signal processing system platform is proposed.

High Performance Materials Development in the 21st Century: Trends and Directions

2004 ◽  
Vol 449-452 ◽  
pp. 7-12
Author(s):  
James C. Williams
Keyword(s):  
Material Properties ◽  
Gas Turbines ◽  
High Performance ◽  
Matrix Composites ◽  
New Materials ◽  
Materials Development ◽  
Recent Developments ◽  
New Material ◽  
Time Required ◽  
The Cost

Product performance including the cost of ownership is becoming increasingly dependent on the availability of high quality, high performance, affordable materials of construction. Today, the requirements placed on a new material for a high performance structural application extend well beyond the improvement of one or more material properties. This makes the introduction of a new material a multi-faceted activity. Modern structural materials derive their performance from a combination of composition and processing, the results of which are inextricably intertwined. This statement pertains to both metallic alloys and to fiber reinforced composite materials. In addition, material cost and the reproducibility of material properties are becoming more central as acceptance criteria for incorporating new materials into new products. This paper will use examples of recent developments in materials for aircraft gas turbines to depict the materials introduction process. Some of these developments have been successful and others have not. These examples illustrate the changing picture that represents the successful introduction of a new structural material, even in a high performance, high value product such as a gas turbine. Specific examples will include metal matrix composites, Ni-base alloys and improved reliability Ti alloys. The basis for successful introduction, or lack thereof will be discussed. While the examples are specific to gas turbines, they are generally instructive and depict the growing complexity of the process of developing and introducing new materials into a high value product. An additional issue for all new materials introduction is the time required to achieve product readiness. As the time required for product design decreases, there has been little commensurate reduction in materials development cycle time. This matter also will be discussed and some possible reasons and potential solutions will be described.

scholarly journals An FPGA-Embedded Brain-Computer Interface System to Support Individual Autonomy in Locked-In Individuals

Sensors ◽  
2022 ◽  
Vol 22 (1) ◽  
pp. 318
Author(s):  
Arrigo Palumbo ◽  
Nicola Ielpo ◽  
Barbara Calabrese
Keyword(s):  
High Performance ◽  
Visual Stimulation ◽  
Event Related Potentials ◽  
Individual Autonomy ◽  
Motor Disabilities ◽  
Eeg Data ◽  
Field Programmable ◽  
Severe Motor ◽  
Related Potentials ◽  
Bci System

Brain-computer interfaces (BCI) can detect specific EEG patterns and translate them into control signals for external devices by providing people suffering from severe motor disabilities with an alternative/additional channel to communicate and interact with the outer world. Many EEG-based BCIs rely on the P300 event-related potentials, mainly because they require training times for the user relatively short and provide higher selection speed. This paper proposes a P300-based portable embedded BCI system realized through an embedded hardware platform based on FPGA (field-programmable gate array), ensuring flexibility, reliability, and high-performance features. The system acquires EEG data during user visual stimulation and processes them in a real-time way to correctly detect and recognize the EEG features. The BCI system is designed to allow to user to perform communication and domotic controls.

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