CN2 - Design Specification EEG App Using Emotiv System Architecture

Transcription

1 CN2 - EEG App Using Emotiv System Architecture Figure 1: System Architecture

2 EPOC Neuroheadset It is a product from Emotiv, a headset that can read your brain waves signal by detecting the signals from 14 sensor points. We need the EPOC to make the program runnable; in order for the Emotiv s API to work it required a connection from the headset. User Profile When we run the program for the first time and connected the headset, the program will pop-up a windows called ADD USER. In this windows the user will have to input a username and click Save User to save that new user into the database. The program required at least one user to operate. The user then can delete the existing user or add additional user(s). User Tab This function can be called after one user is created. The user can select a game from game list to set keyboard button. In case of no game in the game list, the user can add game to the list by selecting game from the game directory. All games in the game list are stored in the database of each user. Key Configuration While in User Tab windows, when Adjust Key button is clicked, a Key Config windows will appeared. In this windows, this function allows user to set keyboard button for each cognitive action. Keys saved for each actions are stored in the database of that current user. Headset Status This function shows the status of the headset: - Connection: Tells whether the headset is connected to the program or not. - Connection Strength: Shows strength of the connection between the headset and the program in colors. - Wireless Signal: Shows wireless signal strength of the headset. - Battery Status: Show status of the battery of the headset. This function also show the 14 sensors in graph. Action Mapping This function shows available cognitive actions in a drop-down list. Cognitive Training & Key Calibrating In this function, the user can select cognitive action from the Action Mapping to train. The user can also test any trained cognitive action by clicking on the TEST button.

3 Database There are 2 tables keeping information which are Game and User. The program has to send a request to these tables to retrieve the stored data or when new data is insert. Detailed Design Database Design Figure 2: ER Diagram Game This table keeps information on game(s) selected by the user. It keep Game Name (as namegame), UserID(a foreign key from table User), and 4 Basic movement for that game(as forward, backward, left, right). User It keep username (as nameuser) once a new user was created.

4 User Interface Designs Figure 3: Add User Add User When the program is opened for the first time, the user must create a new user in order to access the program. The user can create a new user by typing the username in the provided space. Then, click Save User button to create a new user. This windows will disappear after Save User button is clicked. The Existing User box shows the list of current user. Before adding the first user, the Existing User box will show the message No Existing User. Figure 4: Headset Status (Connected) Headset Status This function shows the status of the headset: - Connection: Tells whether the headset is connected to the program or not. It will show text right of USER STATUS label: Connected in green and Disconnected in red. And it also show text next to SIGNAL : OK in blue and No Signal in grey.

5 - Connection Strength: Shows strength of the connection between the headset and the program in colors: Green is good connection, yellow is fair, orange is poor, red is very poor, and black is no signal. - Wireless Signal: Shows wireless signal strength of the headset. - Battery Status: Show status of the battery of the headset. This function also shows the 14 sensors in graph. It will plot graph from raw data shown in Figure 4. Figure 4.1: Headset Status (Disconnected) Action Mapping This function shows available cognitive actions in a drop-down list: Forward, Backward, Left, and Right. Figure 5: Action Mapping

6 Figure 5.1: Action Mapping tab Cognitive Training & Key Calibrating In this function, the user can select cognitive action to train by selecting an action from the drop-down list (Figure 5) and click TRAIN button to start the cognitive training. When the TRAIN button is clicked a small windows called Training will appeared (Figure 6). In this windows, the user can either click START button to start the training or ABORT button to cancel the training. Once the user click on START button, the process bar will start running for approximately 8 seconds. While the process bar is running, the user should think constantly until the process bar is full and close the current windows, this is to save the user s current thought into the selected action. When the process bar is full, the training is completed and the windows is closed, a small windows will pop up a message saying: Training Complete. (see Figure 6.1) The user can also test any trained cognitive action by clicking on the TEST button. While testing, the user can move the object in Figure 5.1. Figure 6: Training process

7 Figure 6.1: Training Complete Figure 7: User Tab Game list User Tab Once the USER TAB button is clicked, the windows called User Tab appeared. In this windows, the user can choose game from directory and save it into the Game List box.

8 Key Configuration While in User Tab windows, when Adjust Key button is clicked, a Key Config windows will appeared. In this windows, this function allows user to set keyboard button for each cognitive action. Keys saved for each action are stored in the database of that current user. Figure 8: Key Configuration