Projects:2019s1-156 Ear-Plug Brain Wave Reader
Motivation The brain as the control center of advanced creature not only controls the biological's motor function, but also plays a decisive role in mood and personality. In additional, it could provide information about brain diseases but are also useful for assessing cognitive states and monitoring sleep.
In 1791, L. GalVani found that the current was generated when the muscles contracted, which provided a theoretical basis for the development of EEG. Besides, researchers have begun to realize that brain activity is also accompanied by the electrical signals. Since then, EEG technology has developed rapidly. After entering the 20th century, with the generation of transistors, the recording method for EEG has also evolved to magnify EEG through a transistor amplifier and record it with an oscilloscope. In recent years, with the development of EEG technology, it has begun to enter the ordinary family and is used as a medical device for home use. At the same time, some small-scale portable EEG acquisition systems have appeared in the domestic and international markets for home health monitoring and other fields.
Background The aim of our project is to design EEG sensor that collect brain waves via earplug, in the future, can be integrated in earphone. The purpose of our project is to design a ear-plug electrodes to collect EEG signal, to design circuit board to realize the the layout of the system and drawing of the PCB board for signal processing, and design an application of Android system to display brainwaves.
Methodology Electrodes In order to collect the brain waves data through ear canals, we manufactured two earplugs with electrodes being carried on them. We found the 3D model of human outer and middle ear canal from the Internet, then we use the Autodesk Inventor Professional software to do a little bit of modifying to the 3D model to fit our ears’ conditions. The earplugs were made of silicone rubber, and they are both elastic and safe to touch the skin. For the electrodes, as the earplugs are quite soft, we use conductive thread for electrodes instead of metallic electrodes due to its comfortability. The material of conductive thread was silver laced nylon, it was sewed on the head part of the earplugs and will contact the middle part of ear canal. The other side of conductive thread was connected to 1.2m copper wires separately. There are four sewed electrodes on each earplug and two earplugs worn by the user, so there were eight channels of input to the hardware system.
ADS1299 MODULE The ADS1299 is the high performance chip as control core to ensure the stability of the system and it integrates a programmable gain amplifier, internal reference source and on-chip clock. ADS1299 data interaction with Bluetooth module: pin43 and pin34; It has three power supplies, two analog power supplies (AVDD and AVSS) and one digital power supply Source (AVDD). Each power supply of the chip is connected to the ground through 10 μ F and 0.1 μ f to filter the power supply
Bluetooth module Data exchange between the Bluetooth module and the ADS1299: Bluetooth power is supplied using VDD3.3V; Bluetooth 1-pin is used as the data exchange output, and 2-pin is used as the data exchange input; The 31-pin is connected to the LED light to indicate the working state of the module. The module flashes after power-on, and the blinking intervals of different states are different
Power module U0: Power supply for USB, 5V voltage source, is the source of the entire power supply; U2: TPS60403, -5V voltage, as an input to AVSS; U3: TPS73225, output AVDD, providing analog power for ADS1299; U4: TPS72325, output AVSS, providing analog power for ADS1299; U5: MIC5501-3.3YMT, output 3.3V, providing digital power for ADS1299 and Bluetooth; R0: single point grounding of analog ground and digital ground C0: Filter between AVDD and AVSS
Application We have made an Android app for our users to monitor their brainwaves through their Android devices live. The app was written in Java, which is a popular language in writing Android apps. This app requires the use of Bluetooth of Android devices and it receives data from the hardware system after getting access to Bluetooth. The app then separates the amplitude information from the data and shows it as a dynamic plot on the screen. Therefore, users can see their brain wave plot from the app.
Further Work There are still functions which could be added to our device. Firstly is the deep learning systems, which makes the computer study the brain waves data of the user and learn the difference among various frequencies of brain waves from human activities. Therefore, the app can identify the condition of the user’s brain. Alerting programs can also be added to the app, alerting messages can be announced while the system detects abnormal brain waves data. This may help in family members monitoring the conditions of elder people.
