scholarly journals A 64-channel ultra-low power bioelectric signal acquisition system for brain-computer interface

Author(s):  
Akshay Mahajan ◽  
Alireza Karimi Bidhendi ◽  
Po T. Wang ◽  
Colin M. McCrimmon ◽  
Charles Y. Liu ◽  
...  
2013 ◽  
Vol 284-287 ◽  
pp. 1616-1621 ◽  
Author(s):  
Jzau Sgeng Lin ◽  
Sun Ming Huang

A wireless EEG-based brain-computer interface (BCI) and an FPGA-based system to control electric wheelchairs through a Bluetooth interface was proposed in this paper for paralyzed patients. Paralytic patients can not move freely and only use wheelchairs in their daily life. Especially, people getting motor neuron disease (MND) can only use their eyes and brain to exercise their willpower. Therefore, real-time EEG and winking signals can help these patients effectively. However, current BCI systems are usually complex and have to send the brain waves to a personal computer or a single-chip microcontroller to process the EEG signals. In this paper, a simple BCI system with two channels and an FPGA-based circuit for controlling DC motor can help paralytic patients easily to drive the electric wheelchair. The proposed BCI system consists of a wireless physiological with two-channel acquisition module and an FPGA-based signal processing unit. Here, the physiological signal acquisition module and signal processing unit were designed for extracting EEG and winking signals from brain waves which can directly transformed into control signals to drive the electric wheelchairs. The advantages of the proposed BCI system are low power consumption and compact size so that the system can be suitable for the paralytic patients. The experimental results showed feasible action for the proposed BCI system and drive circuit with a practical operating in electric wheelchair applications.


2021 ◽  
Vol 39 (7) ◽  
pp. 1117-1132
Author(s):  
Samaa S. Abdulwahab ◽  
Hussain K. Khleaf ◽  
Manal H. Jassim

A Brain-Computer Interface (BCI) is an external system that controls activities and processes in the physical world based on brain signals. In Passive BCI, artificial signals are automatically generated by a computer program without any input from nerves in the body. This is useful for individuals with mobility issues. Traditional BCI has been dependent only on recording brain signals with Electroencephalograph (EEG) and has used a rule-based translation algorithm to generate control commands. These systems have developed very accurate translation systems. This paper is about the different methods for adapting the signals from the brain. It has been mentioned that various kinds of surveys in the past to serve the purpose of the present research. This paper shows a simple and easy analysis of each technique and its respective benefits and drawbacks, including signal acquisition, signal pre-processing, feature classification and classification. Finally,  discussed is the application of EEG-based BCI.


Author(s):  
Yue Zhang ◽  
Linwei Tao

In order to realize the acquisition and storage of underwater acoustic signals for aiming at the requirements of multi-channel, low power consumption and small volume for underwater receiver extension of sonar system, a multi-channel signal acquisition and storage system based on FPGA and STM32 with variable number of working channels and sampling frequency is designed, in which the system is consisted of 8 pieces, 8 channel and 24 bits high dynamic range Δ-Σ ADS1278 ADC chip to synchronous multi-channel analog signal acquisition. FPGA, as the acquisition sequence and logic control, reads and collates the ADC chip data and writes it into the internal high-capacity FIFO, and adds corresponding operations according to the characteristics of FIFO in an application. SMT32 single-chip microcomputer reads the FIFO data through the high-speed SPI interface with FPGA and writes the multi-channel data into the high-capacity SD card. The testing results have verified that the system has characteristics such as stable and reliable, easy configuration, low power consumption, can guarantee the multichannel data serial transmission, storage, accurate, up to 64 analog signals at the same time the real-time collection and storage, top 20 kHz sampling rate, the system total power of the system of about 3W, data rates up to 100 Mb/s, fully meet the needs of underwater sound acquisition system.


2018 ◽  
Vol 18 (4) ◽  
pp. 86-95
Author(s):  
Piotr WOS ◽  
Ryszard DINDORF

The aim of the study was to perform bioelectric signal analysis focusing on its applicability to control of the electro-hydraulic servo drive. The natural bioelectric signals generated by brain, facial muscles and eye muscles read by the NIA (Neural Impulse Actuator) are translated into control commands in the controller of electro-hydraulic servo drive. Bioelectric signals detected by means of special forehead band with three sensors are sent to the actuator box, where they are interpreted as control signals. The test stand was constructed to control of the electro-hydraulic servo drive by means of bioelectric signals generated by the operator. The control signals from the actuator box are transmitted via a wireless network to the controller of electro-hydraulic positioning drive.


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