| dc.description.abstract | Artificial intelligence computation system assisted by brainwave signal has been
built in this study. We add the electroencephalography as input data to the neural
networks to optimize the computing system. We examine the signal recognition
ability before and after adding brainwave data.
The input signals consist of the triangular and rectangular waves. The waves are
incorporated with white Gaussian noise to increase the difficulty of signal
recognition. The corresponding output signals to the input triangular and
rectangular waves are 0 and 1, respectively. The subjects listen to the triangular
and rectangular waves. The brainwave data of the subjects are collected by using
MindWave mobile. Using the short-time Fourier transform (STFT) with a
nonoverlapped Hamming window, the brainwaves are transformed to
encephalogram(EEG) spectra. Using Reservoir Computing (RC), the EEG signals
of different frequencies were added into the RC program as input data.
In RC. ??? and ? are the input and recurrent weight matrices, respectively,
which consist of random numbers. We obtain three main results:
1. The value in the arbitrarily generated ??? and ? matrices have small
influence on the calculation results.
2. In the measured results for 10 different times on the same subject, it can be
found that brainwave calculations at 8, 12, 52, 54 and 68 Hz, the MSE results have
significant difference. They have characteristics that vary for different time.
3. With the EEG signal from 14 to 42 Hz and from 58 to 62 Hz frequency, the
signal recognition error rate can be reduced effectively.
iv
Brainwave signals were added into artificial intelligence computation system in
this study. The signal recognition error rate can be reduced effectively (using the
EEG signals at 14-42 Hz or 58-62 Hz). This result (using the EEG signals at 8,
12, 52, 54 and 68 Hz) also demonstrates the artificial intelligence computation
involved in different human responses (like personality and preferences, emotions
or physical and psychological conditions). In the future, it can be extended to
determine personal preferences. If one day the brain of the deceased persons could
be kept active, the response signal of the brain can also added into the computation.
It might make the personality or the spirit immortal.
This research project was approved by Research Ethics Committee National
Taiwan University. NTU-REC No.：202103EM011. (See Appendix 1) | en_US |