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Figure 4: Artificial intelligence, machine learning, and deep learning
development over time. (Source: elenabsl/Shutterstock.com)
AI with BCI
AI and its subsets, including machine learning and
deep learning (DL), are enabling approaches in
EEG-based BCIs (Figure 4). DL can offer automatic
classifications of EEG signals. This effort allows for
the data to be utilized in various applications and
other convolutional neural networks (CNN) training.
At present, human expertise supports AI approaches.
The desire is to eliminate artifacts, increase the data
quality, and continue to realize gains in AI technology
so that measured brain wave signals can continue
to exhibit exponential increases in their ability to be
classified by AI through DL techniques.
Conclusion
EEG-based BCI relies on high-performance electronic
signal chains. Careful consideration of all critical
electronic components, including reliable connectivity
in compact designs, are needed to accurately
measure EEG and other bodily functions. AI and
DL techniques enable dynamic EEG data to receive
better interpretations and allow humanity to realize
more benefits from BCI. BCI will continue to be an
emerging method for human-machine interfacing. And
one day, it might offer a cure to any mental block we
encounter, especially the empty page that any writer
will eventually face. n
