IEEE Systems, Man and Cybernetics Magazine - October 2021 - 8

words repetitively. However, despite the many intervention
models described in the research, only a few focus
on the impact of intervention models in vocal stereotypy
and the secondary impacts in other behaviors [41].
Problem behaviors can be evaluated in multiple settings
and environments by collecting multimodal sensor
data including EEG, gait and limb movements, and body
tracking using cameras. Figure 2 illustrates one such
method to index mild versus intense actions in humans.
By generating a temporal map of body movements, a spatiotemporal
long short-term memory-based attention network
is used to highlight the areas of the body with rapid
movements to classify actions. A kinetic fuzzy intensity
analysis network generates an action intensity based on
the temporal action map and DL prediction. Attention
and agitation can be studied by a temporal analysis of
the facial muscle movements and emotional states.
Attention span can be studied using a temporal analysis of
EEG signals as illustrated in Figure 3(a). Brain attention
maps can be generated using DL algorithms to understand
the pre and post brain states, leading to a more detailed
understanding than traditional methods. Vocal stereotypy can
be detected by observing the lower facial muscle movements
for repetitive motions. This is illustrated in Figure 3(b). Here,
Camera
Camera
VR
Wearables
Tablets
Reading Area
Play Area
Goals,
Lesson Plans,
etc.
Multimodal
Sensory Data
AI-Augmented Treatment Personalizer (ATP)
Reinforcement Learning Paradigm for Continuous Learning
Gathers multimodal sensor data and generators the parameters required to define personalized
treatment plan and activities for the child.
Repetitive
Behavior
Delayed and
Disoriented Language
Impaired Social
Interaction
Personalized Treatment Plan and Syllabi for Individual
Human Understandable Explainer of Individual Treatment Plans
Figure 1. The system architecture of the AI-ABA platform. Multimodal sensory information is collected using both
invasive and noninvasive sensors, which is processed by AI algorithms to support decision making in treatment
and learning paradigms of BAs. All data are stored securely in the cloud accessible by practitioners. Reinforcement
paradigms are set up in a personalized fashion unique to each individual. (Source: VR image: Flaticon.)
8
IEEE SYSTEMS, MAN, & CYBERNETICS MAGAZINE October 2021
Restricted Range of
Interest
Interventions
Behavioral Data

IEEE Systems, Man and Cybernetics Magazine - October 2021

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