IEEE Systems, Man and Cybernetics Magazine - October 2021 - 2

Editorial
by Saeid Nahavandi
W
e have observed tremendous
progress in the areas
of artificial intelligence
(AI), the availability of real-time
multimodal data, and the proliferation
of cloud computing in the first
two decades of the 21st century.
The recent advances in AI technologies
have created new opportunities
for novel and revolutionary
applications in different fields of
science and engineering. Every
day, we are ob serving groundbreaking
and astonishing AI applications
for information retrieval, computer
vision, information fusion, and
health care.
The use of AI is quickly becoming
the norm in health care. It is going to
solely drive the rapid and reliable
digitalization of the whole healthcare
ecosystem. In the upcoming decade,
AI agents in the health-care domain
will autonomously collect data
from different sensors and sources,
fuse them, extract useful patterns,
and provide reliable decision-making
assistance for medical practitioners.
In this issue of IEEE Systems,
Man, and Cybernetics Magazine,
we present four articles related to
the field of AI and its applications for
health-care and engineering problems.
The article " AI-Augmented
Behavior Analysis for Children With
Developmental Disabilities " proposes
a novel AI-based learning platform
providing customized treatment and
learning plans to individuals with
autism as well as intellectual and
developmental disabilities. The proposed
platform can fuse and process
multimodal sensory data, including
electroencephalograms (EEGs),
gait and limb movements, and body
Digital Object Identifier 10.1109/MSMC.2021.3103217
Date of current version: 18 October 2021
2
Applying Artificial
Intelligence to
Real-World Problems
behavior using reinforcement learning-based
augmented or virtual reality
and other mobile platforms. The
reinforcement learning paradigm
is also applied to personalize treatments
for individuals. It is the cornerstone
of the proposed framework
for continuous, personalized, and
adaptive learning.
The second article, " Artificial InSaeid
Nahavandi
tracking, for supporting decision
making in treatments and the learning
paradigms of behavior analysts.
There are four key components in
its architecture:
◆ the multimodal data acquisition
system
◆ an AI-augmented treatment personalizer
◆
explainable AI algorithms
◆ integration with
various presentation
formats or
front-end technologies,
such as
augmented and
virtual reality.
The proposed framework
can effectively
and efficiently promote
self-regulative
IEEE SYSTEMS, MAN, & CYBERNETICS MAGAZINE October 2021
telligence for Dynamical Systems in
Wireless Communications, " provides
a short overview of the applications
of dynamical systems theory to wireless
communications in the past
30 years. The authors aim to highlight
the possibility and importance of
treating a wireless network as a dynamic
a l system. They then claim
that the combination of dynamical
systems theory and AI has the potential
to radically change wi reless
communications per formance. The
authors also offer some initial results
motivated by recent developments in
this field.
The third article, " The CoherThe
reinforcement
learning paradigm
is also applied
to personalize
treatments for
individuals.
ence of the Working Memory Study
Between Deep Neural
Networks and
Neurophysiology, "
comprehensively
invest igates the
conc l u s i on co -
herence of working
memory study
between the approach
from the deep
lear n i ng- b a s e d
IEEE Systems, Man and Cybernetics Magazine - October 2021

Table of Contents for the Digital Edition of IEEE Systems, Man and Cybernetics Magazine - October 2021
