Development of single channel EEG Acquisition system for BCI applications

2021 ◽  
pp. 4705-4709
Author(s):  
V.G. Rajendran ◽  
Jayalalitha S. ◽  
Adalarasu K. ◽  
Nirmalraj T.
Keyword(s):  
Integrated Circuits ◽  
Bandpass Filter ◽  
Single Channel ◽  
Acquisition System ◽  
Computer Interface ◽  
Brain Machine Interface ◽  
Instrumentation Amplifier ◽  
Signal Acquisition ◽  
Level Shifter ◽  
Machine Interface

Brain-Computer Interface (BCI) plays a major role in current technologies such as rehabilitation, control of devices, and various medical applications. BCI or brain-machine interface provides direct communication between a brain signal and an external device. In this paperwork, a detailed survey was carried out with the design of single-channel EEG system for various applications. Also, this paper mainly focused on the development of single-channel electroencephalography (EEG) signal acquisition system which includes a preamplifier, bandpass filter, post-amplifier and level shifter circuits. The design of the preamplifier and post-amplifier circuit was carried out by integrated circuits (IC) such as instrumentation amplifier IN128P and bandpass filter with the help of low power operational amplifier LM324. The developed single-channel acquisition board was tested by acquiring an electrooculogram (EOG) signal with closed and opened eye conditions. The acquired signal is displayed and stored in the computer with the help of the HBM-DAQ unit.

Clinical Diagnosis of Psychiatry Based on Electroencephalography

2021 ◽  
Vol 11 (3) ◽  
pp. 955-963
Author(s):  
Lixue Yuan ◽  
Yinyan Fan ◽  
Quanxi Gan ◽  
Huibin Feng
Keyword(s):  
Environmental Control ◽  
Low Cost ◽  
Training System ◽  
Brain Machine Interface ◽  
Signal Acquisition ◽  
Eeg Signal ◽  
Eeg Signals ◽  
Feedback Information ◽  
Machine Interface ◽  
Neural Feedback

At present, neurophysiological signals used for neuro feedback are EEG (Electroencephalogram), functional magnetic resonance imaging. Among them, the acquisition of EEG signals has the advantages of non-invasive way with low cost. It has been widely used in brain-machine interface technology in recent years. Important progress has been made in rehabilitation and environmental control. However, neural feedback and brainmachine interface technology are completely similar in signal acquisition, signal feature extraction, and pattern classification. Therefore, the related research results of brain-machine interface can be used to closely cooperate with clinical needs to research and develop neural feedback technology based on EEG. Based on neurophysiology and brain-machine interface technology, this paper develops a neural feedback training system based on the acquisition and analysis of human EEG signals. Aiming at the autonomous rhythm components in the EEG signal, such as sensorimotor rhythm and alpha rhythm, the characteristic parameters are extracted through real-time EEG signal processing to generate feedback information, and the subject is self-regulated and trained from a physiological-psychological perspective by providing adjuvant treatment, a practical and stable treatment platform for the clinic.

Design of Data Acquisition System Based on LabVIEW

2012 ◽  
Vol 569 ◽  
pp. 808-813 ◽  
Author(s):  
Ling Gang Liu ◽  
Jun Hui Li ◽  
Lu Hua Deng
Keyword(s):  
Data Acquisition ◽  
Virtual Instrument ◽  
Development Time ◽  
Single Channel ◽  
Data Acquisition System ◽  
Signal Acquisition ◽  
Graphical Programming ◽  
Development Platform ◽  
Data Acquisition Card ◽  
Machine Interface

Based on LabVIEW, this paper presents a design scheme of data acquisition, which it proposes using computer and ordinary data collection card as the main hardware and LabVIEW as software development platform, thus constructs the virtual instrument system for signal acquisition. The system can realize synchronous data acquisition of single channel or multi-channel signal, as well as real-time display and preservation. The practice shows that this scheme can not only effectively play performance of ordinary data acquisition card, but also reduce greatly program development time and beautify interface through LabVIEW which has powerfully visual human-machine interface editor and graphical programming function.

scholarly journals Home Automation using Brain Computer Interface for the Physically Challenged

2019 ◽  
Vol 9 (1) ◽  
pp. 5018-5021
Keyword(s):  
Brain Computer Interface ◽  
Brain Structures ◽  
Computer Interface ◽  
Brain Machine Interface ◽  
Home Automation ◽  
Eeg Signals ◽  
Machine Interface ◽  
Physically Challenged ◽  
The Brain ◽  
Bci System

A Brain-Computer Interface (BCI)is labeledas Mind-Machine Interface (MMI) or a Brain-Machine Interface (BMI). It affords a non-muscular channel of messagein between the computer and a human brain. Using the enhancements in interface equipment to electronics,and the necessity to helpindividuals suffering from disabilities, a new area in this study has begun by acceptingtasks of brain. The Electro-Encephalogram (EEG) is an electrical activity created by brain structures and verified from the scalp using electrodes. The EEG signal is used in actualspell to accomplishperipheral devices using a broad BCI system. The post-processed output signals are converted to suitable instructions to regulate output devices. The main seek is to aidparalyzed and physically immobilizedpersons to govern the home appliances making use of Electro-Encephalogram (EEG) signals, such that they grow to beautonomous. According to the brain responsiveness the devices can be designated then usingrelays, the switching of the home-basedmachinescan be completedconsequently.

scholarly journals Non-Invasive Brain-Computer Interface Technology (BCI) Modalities and Implementation: A Review Article and Assimilation of BCI Models

2021 ◽  
Vol 4 (2) ◽  
Author(s):  
Dalia Mirghani Mahmoud Saadabi
Keyword(s):  
Brain Computer Interface ◽  
Computer Interface ◽  
Brain Machine Interface ◽  
Output Stage ◽  
Important Place ◽  
Non Invasive ◽  
System Input ◽  
Pros And Cons ◽  
Machine Interface ◽  
Bci System

Brain-computer interface (BCI) technology or brain-machine interface (BMI) technology has become the most attractive field for researchers in various disciplines and has occupied an important place in many scientific and even recreational applications. This review first highlights the different and most frequently used methods for implementing brain-computer interface (BCI) systems with a focus on non-invasive BCI models. Secondly, it analyzes the different stages of building a BCI system (input stage, signal processing stage, and output stage). Then it compares the different methods in terms of the algorithms used and the pros and cons. The aim of the study is to find the most adequate and price method to record the EEG by means of electrodes placed on the scalp. Then some features will be extracted from the EEG and sent to a classifier, whose response is translated features into some action whose execution provides feedback to the user.

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