Low cost EEG signal acquisition system

2013 ◽  
Author(s):  
P. Arulmozhivarman ◽  
G. R. Reddy ◽  
R. Tatavarti
Keyword(s):  
Low Cost ◽  
Acquisition System ◽  
Signal Acquisition ◽  
Eeg Signal

A Portable EEG Signal Acquisition System

2012 ◽  
Vol 14 (1) ◽  
pp. 222-226
Author(s):  
Dong-Gyu Kim ◽  
Yong-Wan Roh ◽  
Kwang-Seok Hong
Keyword(s):  
Acquisition System ◽  
Signal Acquisition ◽  
Eeg Signal

A New Design of Portable EEG Signal Acquisition System

2013 ◽  
Vol 846-847 ◽  
pp. 804-807 ◽  
Author(s):  
Yong Xiang Li ◽  
Nian Qiang Li ◽  
Yang Liu
Keyword(s):  
Development Trend ◽  
Electrical Signal ◽  
Acquisition System ◽  
Input Circuit ◽  
Portable Devices ◽  
Signal Acquisition ◽  
Testing Time ◽  
Eeg Signal ◽  
Integration Density ◽  
Signal Amplifier

Most of the electroencephalograph (EEG) acquisition systems use group of high precision electrical signal amplifier to record and analysis. But the huge input circuit and testing time is difficult to application for portable devices. In this paper, a new design of portable EEG signal acquisition system is designed. This paper presents an effective chip (ADS1299) implementation of an eight-channel EEG signal acquisition. Compared with the existing system, this design greatly simplifies the front-end circuits and improves the common mode rejection ratio (CMRR). The system has the features of high integration density, good flexibility and practicability. It is in line with the development trend of modern EEG, and meets the new requirements of modern EEG.

scholarly journals Development of A Low-Cost Arduino-Based 12-Lead Ecg Acquisition System And Accompanied Labview Application

2019 ◽  
Vol 9 (1) ◽  
pp. 1641-1648
Keyword(s):  
Signal Processing ◽  
Real Time ◽  
Low Cost ◽  
Numerical Data ◽  
Digital Signal ◽  
Acquisition System ◽  
Signal Acquisition ◽  
Frequency Noise ◽  
Ecg Signal ◽  
Active Analog

In this paper, the design of a real-time digital multi--channel ECG signal acquisition system is presented. With the purpose of fabrication towards a simple, compact and low-cost tool for bioelectrical signal processing laboratories, the system is developed to acquire the 12 leads EGC signals and converted to numerical data based on an Arduino module named as Leonardo equipped 12 channels ADC. To observe the EGC waves, the ECG signals are amplified through designed amplifiers with the gain of 60 dB. To reduce the effects from the DC component as well as the baseline wandering and the high frequency noise, the active analog bandpass filter ranged in 0,05 Hz to 100 Hz was designed. The power line noise of 50 Hz also decreased with an active analog bandstop filter with attenuation -38 dB. Under the PC application was built using Labview programing, the low-cost digital ECG signal acquisition system was demonstrated with the requirement of observation in real-time. To clarify the small wave in the digital EGG signal, the limitation of the analog signal processing is improved through the digital filters parameterized in the software to increase the SNR from 1.4 dB to 27.6 dB. Practically, the system is evaluated through a series of experiments on a volunteer person resulting the ECG data is recorded and stored in a TDMS file. Since the system is designed as opened-system, a series of developments towards various applications in biomedical diagnosis based on digital signal analysis techniques is promised to be feasible in the near future.

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.

scholarly journals Design of EEG Signal Acquisition System Using Arduino MEGA1280 and EEGAnalyzer

2016 ◽  
Vol 75 ◽  
pp. 04003
Author(s):  
Debyo Saptono ◽  
Bambang Wahyudi ◽  
Benny Irawan
Keyword(s):  
Acquisition System ◽  
Signal Acquisition ◽  
Eeg Signal

Design of Data Acquisition System of Vibration Signal for Civil Engineering Structure

2014 ◽  
Vol 584-586 ◽  
pp. 2023-2027
Author(s):  
Wei Sun ◽  
Ying Zhang ◽  
Shao Fei Jiang
Keyword(s):  
Data Acquisition ◽  
Virtual Instrument ◽  
Low Cost ◽  
Vibration Signal ◽  
Data Acquisition System ◽  
Frame Structure ◽  
Acquisition System ◽  
Signal Acquisition ◽  
Online Data ◽  
Structure Vibration

A vibration signal acquisition system was designed based virtual instrument technology. The process and principle design of structure vibration signal acquisition system based on LabVIEW software and CompactRIO hardware were discussed in detail. Finally, system test was conducted by a three story steel frame structure. And the test results were compared with traditional instruments system. The experiment showed that the data acquisition system of structure vibration signal which based on CompactRIO is precise and reliable in measurement results, and can realize multi channel synchronous data acquisition, storage, and support the real-time online data filtering and spectrum analysis and so on.Compared with the traditional platforms, the system proposed in the paper has short development cycle, low cost, user-defined functions, rugged, portable and other advantages. It can be widely used in complex and special building environment, so it will have a broad application prospect in the field of SHM.

Sign in / Sign up

Export Citation Format

Share Document