Do you want to publish a course? Click here

Data Acquisition System Design Using a Microcontroller and Digital Elliptic Filters that are able to Remove Noise from EEG signals

تصميم نظام تحصيل بيانات بالاعتماد على متحكم صغري و مرشحات رقمية ذات استجابة إهليلجية ELLIPTIC RESPONSE قابل للاستخدام في إلغاء الضجيج المرافق لإشارات التخطيط الكهربائي للدماغ EEG

2046   1   29   0 ( 0 )
 Publication date 2015
and research's language is العربية
 Created by Shamra Editor




Ask ChatGPT about the research

Since Electroencephalogram (EEG) signals have very small magnitude, it's very hard to capture these signals without having noise (produced by surrounding artifacts) affect the real EEG signals, so it is necessary to use Filters to remove noise. This work proposes a design of an electronic circuit using a microcontroller, an instrumentation amplifier and an operational amplifier able to capture EEG signals, convert the captured signals from analog state to digital one and send the converted signal (digital signal) to a group of three digital filters. This paper gives a design of three digital elliptic filters ready to be used in real time filtering of EEG signals (which preliminary represents the condition of the brain) making the software part which complements the hardware part in the EEG signals capturing system. Finally we are going to show the way of using the designed electronic circuit with the three designed digital filters, demonstrate and discuss the results of this work. We have used Eagle 6.6 software to design and draw the circuit, CodeVision AVR 3.12 software to write the program downloaded on the microcontroller, Mathworks MATLAB 2014a software to design the three digital filters and Mathworks MATLAB 2014a Simulink tool to make the appropriate experiments and get the results.

References used
Choy, TT.; Leung, PM. Real time microprocessor-based 50 Hz notch filter for ECG, J Biomed Eng. ,1988 May
Ferdjallah, M.; Barr, RE. Frequency domain digital filtering techniques for the removal of power line noise with application to the electrocardiogram, Computer Biomed Res. ,1990 Oct
Wu, Y.; Yang, Y. A new digital filter method for eliminating 50Hz interference from the ECG, Zhongguo Yi Liao Qi Xie Za Zhi.,1999 May
rate research

Read More

In order to keep up with the latest international technologies which have been achieved recently. We have to search continuously for the technological methods in order to improve the present situation of the institutions in the Syrian Arab Republic. This research aims to build a network of Programmable Logic Controllers (PLCs) with Human Machine Interface (HMI) and supervisory control and data acquisition (SCADA) system, as well as, studying the most suitable protocols to build the network beside identifying the causes of choosing the protocol. After studying and identifying it, we had better to use the automated industrial network to improve the present situation of water company concerning with getting meters data accurately as fast as possible. We build the mentioned network by means of a group of PLCs, so that, each one could be used to get the data for an avenue in Hama city. These distributed controllers would be connected by a central router in order to pass all the data to the water company center. We will use a HMI and SCADA system for showing collected data, controlling, and saving the collected data. This HMI and SCADA system will be connected to the same PLCs, and thus, we will get a distributed industrial network.
The research presents a design for an automated checking system for students. The system takes a picture of the student, then it extracts his/her basic facial features. The network was trained using the reverse spreading algorithm. If a training da tabase is generated for each student consisting of 15 training samples contained of the necessary facial expressions to identify the student for one time at the beginning of the semester, then the neural network will be trained on students database to obtain a trained neural network able to identify the students of each category depending on their physical appearance. That will result in knowing who attends and who does not attend the session. The system designed for this purpose was supplied with the trained network. The system provides the possibility of automated checking for students according to the content of the study giving the alarm in case of the existence of the picture of a student who does not belong to the same group.
The aim of this research is to study a simplified approach for the design of low-noise bipolar transimpedance preamplifiers for optical receivers. Analytical solutions for optimum biasing and minimum equivalent input-noise current were derived. The study was achieved by doing comparison between the designed circuits. The equivalent input noise current was calculated by entering the parameters in Matlab program and using Multisim as a simulation tool to detect a pulse signal of 30ns width.
The effect of thermal noise and shot noise on the receiver sensitivity in a digital optical communication system will be studied and analyzed. Also, the positive and negative effects of Parameters on the receiver sensitivity will be highlighted. Th e programming tools (MATLAB) is used to study the relationship between the receiver sensitivity and bit rate. It showed that the shot-noise-limited receiver sensitivity is much better than the thermal -noise-limited receiver sensitivity with best 30dB. The study also provided an explanation for the preference of optical detector (APD) compared to that in (PIN) optical detector from sensitivity side due to its internal gain, this can be achieved when the thermal noise is dominant. However, the preference of optical detector(PIN) will be better in case of shot noise is dominant. Analyzed results show that there is a significant improvement in the shot-noiselimited receiver sensitivity for high quantum efficiency and high wavelength. However, the sensitivity is deteriorated to get a lower error rate. The thermal -noise-limited receiver sensitivity showed an improving by increasing the responsivity and the load resistance. However, it decreases by increasing the number of noise and the error rate.
As we enter the age of artificial intelligence, the need for intelligent home appliances has become very important for what this smart equipment can provide in the provision of electrical energy and water resources that are treasures should human pre servation, in addition to the contribution of this equipment to protect the environment from pollution, where we face the challenges next: High prices of electrical equipment.  The number of hours of electricity supply in many areas is low because of the current conditions in our country. - Water shortage. - The rise in prices of materials used in daily life in general and household detergents in particular - Great waste of electricity. - Pollution of the environment and groundwater with detergents used in the laundry process. Moreover, the unjust economic blockade imposed on our country is pushing us to work to produce low-cost national housing equipment that competes with foreign products in order to alleviate the material burden on the citizens and promote the national economy. In order to accomplish this smart washing machine, we have written a code for f type-2 fuzzy microcontroller, using the Python programming language. This controller has received four entries, which are: The first income (clothing color), obtained by taking a picture of the clothes that we need to wash by a camera with a resolution of 8 megapixels, analyzed using OpenCV library, and the second income (clothing type), determined by the local binary pattern algorithm, which is common digital image processing algorithm that widely used to identify shapes that follow specific pattern and structure, the third income (degree of dirt), and was identified by taking a picture of the clothes after soaking them with water for two minutes. The image was then analyzed by the OpenCV library and the fourth (washing weight) that getting From the Load Cell, which measures the physical weights. The readings were converted to digital values via the HX711 digital analogue converter and then sent to Arduino UNO to determine the weight. The weight values were eventually sent to the Raspberry PI for use in the controller. The system generates three exits: washing time (the length of time the laundry was washed), the temperature required for washing, and the amount of detergent required. After selecting all the previous values, we transferred to control Wattar washing machine model 402, where the water valve was controlled to allow the water to pass into the powder box and from it to the washing basin. The water heater was controlled, which heated the water to the temperature determined by the Fuzzy algorithm, The temperature was monitored by the DS18B20 temperature sensor, which gives a signal to the Raspberry PI at the arrival of the temperature to the required value, and the washing machine engine is controlled for a third of the time specified in the Fuzzy algorithm and we controlled the pump Water to empty basin Washing from water, the process repeated for three consecutive times, we control using a software interface designed using TKinter library  We have been able to design a smart Fuzzy logic type-2 controller with the following advantages: o save electricity consumption o Provide quantity of detergents o Shortenwashingtime  We have been able to control the following physical components within the washing machine: o Control the water pump o control Water valve o controlMotor o controlTemperaturesensor o controlLCDscreen  We have built a smart washing machine with the following characteristics: o Have the ability to recognize the condition of clothes o Identify the type of clothing o Identify the color of clothes o Dothewashingwithoutusingapredefinedprogram.  The controller we designed gives good results to calculate the following: o Washingtime o Quantity of detergents o Temperature All diagrams appear in the case of the incremental gradient with an increased degree of dirt and as values correspond to each type of clothing. Keywords: smart washing machine, saving electricity, saving detergent, shortening washing time, color and clothing distinction, artificial intelligence, fuzzy logic type-2, Raspberry PI, control, Python programming language, HX711.
comments
Fetching comments Fetching comments
Sign in to be able to follow your search criteria
mircosoft-partner

هل ترغب بارسال اشعارات عن اخر التحديثات في شمرا-اكاديميا