Real-Time, Portable EEG Signal Acquisition System

2018 ◽  
Author(s):  
Mustafa Guner ◽  
Burcu Erkmen
Keyword(s):  
Real Time ◽  
Acquisition System ◽  
Signal Acquisition ◽  
Eeg Signal

A portable real-time EEG signal acquisition and tele-medicine system

2020 ◽  
pp. 1-11
Author(s):  
Qiang Zhang ◽  
Peng Wang ◽  
Shanshan Li ◽  
Yonghao Jing
Keyword(s):  
Real Time ◽  
Sql Server ◽  
Signal Acquisition ◽  
Eeg Signal ◽  
Eeg Signals ◽  
Eeg Data ◽  
Sql Server Database ◽  
High Power Consumption ◽  
Machine Interface ◽  
Sd Card

Since electroencephalogram (EEG) signals contain a variety of physiological and pathological information, they are widely used in medical diagnosis, brain machine interface and other fields. The existing EEG apparatus are not perfect due to big size, high power consumption and using cables to transmit data. In this paper, a portable real-time EEG signal acquisition and tele-medicine system is developed in order to improve performance of EEG apparatus. The weak EEG signals are induced to the pre-processing circuits via a noninvasive method with bipolar leads. After multi-level amplifying and filtering, these signals are transmitted to DSP (TMS320C5509) to conduct digital filtering. Then, the EEG signals are displayed on the LCD screen and stored in the SD card so that they can be uploaded to the server through the internet. The server employs SQL Server database to manage patients’ information and to store data in disk. Doctors can download, look up and analyze patients’ EEG data using the doctor client. Experimental results demonstrate that the system can acquire weak EEG signals in real time, display the processed results, save data and carry out tele-medicine. The system can meet the requirement of the EEG signals’ quality, and are easy to use and carry.

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.

Design and Application of Human Movement Respiratory and ECG Signal Acquisition System

2020 ◽  
Vol 10 (4) ◽  
pp. 890-897
Author(s):  
Huayu Zhao
Keyword(s):  
Real Time ◽  
Monitoring System ◽  
Human Movement ◽  
Acquisition System ◽  
Signal Acquisition ◽  
Ecg Signal ◽  
Baseline Drift ◽  
Respiratory Signal ◽  
Power Frequency ◽  
Guide System

To realize the design of mobile phone human movement breathing and electrocardiograph (ECG) signal acquisition system based on Bluetooth transmission, the principle of the generation and detection of ECG and respiratory signal and the guide system of signal acquisition are analyzed. Additionally, the hardware of the system is designed, including the hardware of the signal acquisition system, the design of ADS1292R ECG and respiratory signal acquisition module, the design of the main control chip and the design of the Bluetooth module. Then, the digital filtering processing of the ECG and respiratory signals is completed, including the baseline drift filtering and the suppression of the power frequency interference. The results show that the monitoring system runs well and it can effectively collect ECG and respiratory signals, calculate heart rate and respiratory frequency in real time, and display ECG waveform in real time. To sum up, the monitoring system is of great significance for real-time monitoring of the patient's condition.

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