First iteration (07.11.2014 04.12.2014)

Iteration description:

This iteration will focus only on the first part of the project, a Python based interface for processing and classyfying Emotiv Epoc raw signal into one of 4 desired inputs. For reading from Emotiv headset emokit or jasogun libraries will be used. Signal processing will probably consist of discrete fourier transform and a classifier model (to be decided soon, depends on DFT results).

Functional requirements related to iteration:

• Emotiv Epoc raw signal reading
• Processing said signal
• Classifying processed signal

Specific Tasks

• Task-1 Reading raw signal

• Description: Acquire raw signal from Emotic headset with one of aforementioned libraries

• Task depends on the other tasks: no

• Risk factors: both libraries are open sourced, community made - no foolproof guarantee

• Estimation: 16h

• Task was accomplished: -

• Estimation was accurate: -

• Task-2 Signal processing

• Description: Process acquired singal using discrete fourier transform and check what results it gives

• Task depends on the other tasks: yes, task-1

• Risk factors: none

• Estimation: 8h

• Task was accomplished: -

• Estimation was accurate: -

• Task-3 Signal classification

• Description: Classify processed signal into one of 4 classes, choose aplicable model, train it, test it, create training sets for future reference

• Task depends on the other tasks: yes, #1, #2

• Risk factors: train data sets need to be created with user in the same mind state

• Estimation: 24h

• Task was accomplished: -

• Estimation was accurate: -