INTERNATIONAL JOURNAL OF ARTIFICIAL INTELLIGENCE
ISSN: 2692-5206, Impact Factor: 12,23
American Academic publishers, volume 05, issue 08,2025
Journal:
https://www.academicpublishers.org/journals/index.php/ijai
687
ASSESSMENT TOOLS FOR EVALUATING MOTOR ACTIVITY DIFFERENCES IN
INFANTS WITH AUTISM SPECTRUM DISORDER UNDER SIX MONTHS OF AGE
Narbayeva Zamira Ravshanbekovna
4th year student, Faculty of Pedagogy, Defectology, Alfraganus University
+998933190294
Abstract
: Early motor development is a vital indicator of neurological functioning in infants.
Research increasingly suggests that motor activity differences may emerge in infants later
diagnosed with autism spectrum disorder well before the first signs of social or communication
challenges. This article explores the current tools used to assess motor behaviors in infants
under six months of age and their relevance for early identification of autism. Highlighting
modern, evidence-based observational methods and standardized assessments, the article
discusses how early motor markers could enhance screening accuracy and support earlier
intervention.
Keywords
: Autism spectrum disorder, infant motor activity, early detection, neurodevelopment,
movement assessment, motor delay, observational tools
Introduction
Autism spectrum disorder is a neurodevelopmental condition characterized by difficulties in
communication, social interaction, and repetitive behaviors. While core symptoms typically
become more evident in the second year of life, subtle signs may appear much earlier, even
during infancy. One such early domain is motor development. Research shows that motor
delays or atypical movement patterns can be observed in infants who are later diagnosed with
autism. Since motor development is tightly linked to the maturation of neural systems, its early
assessment could provide important clues about broader neurodevelopmental trajectories.
Motor development in infancy is closely connected to the functional maturation of the central
nervous system. Subtle disruptions in this process may be among the earliest observable
markers of neurodevelopmental conditions such as autism spectrum disorder. Although autism
is not primarily diagnosed through motor deficits, mounting evidence suggests that deviations
in motor behavior can precede social and communication symptoms by several months.
Consequently, early motor assessment tools offer a unique window into the
neurodevelopmental status of infants, even before behavioral signs of autism become apparent.
General Movement Assessment (GMA)
GMA is one of the most well-validated observational methods for assessing spontaneous motor
activity in infants from birth to five months. Developed by Heinz Prechtl, it evaluates the
quality and complexity of general movements—non-voluntary, spontaneous movement patterns
involving the whole div. These movements are expected to evolve naturally, becoming
increasingly variable and fluent over time.
In typical development, infants display "writhing movements" in early infancy, followed by the
emergence of "fidgety movements" around nine to fifteen weeks post-term. Absence or
abnormal quality of fidgety movements is strongly associated with neurological risk, including
INTERNATIONAL JOURNAL OF ARTIFICIAL INTELLIGENCE
ISSN: 2692-5206, Impact Factor: 12,23
American Academic publishers, volume 05, issue 08,2025
Journal:
https://www.academicpublishers.org/journals/index.php/ijai
688
autism. In infants later diagnosed with autism, studies have observed a lack of smoothness,
monotonous motion, and decreased variability in spontaneous movements, indicating early
central nervous system dysregulation.
One advantage of GMA is that it requires only a simple video recording and trained evaluators,
making it practical in both clinical and research settings. Its predictive validity is especially
high when paired with the Motor Optimality Score.
Motor Optimality Score (MOS)
The MOS complements the GMA by providing a standardized scoring system that quantifies
qualitative aspects of general movements. It assesses parameters such as movement fluency,
postural patterns, and symmetry. A lower MOS in early infancy has been found to correlate
with developmental challenges in later childhood, including features consistent with autism.
Unlike GMA alone, the MOS allows for a finer-grained analysis, helping clinicians differentiate
between various neurodevelopmental risks. It considers five domains and yields a cumulative
score, making it useful for monitoring progress over time or evaluating the effects of early
intervention.
Alberta Infant Motor Scale (AIMS)
AIMS is a standardized tool used to assess gross motor development in infants from birth to
eighteen months. It involves structured observation of posture and movement in four positions:
prone, supine, sitting, and standing. It is norm-referenced, allowing clinicians to compare an
infant’s motor performance to a typical developmental trajectory.
Although AIMS is not autism-specific, it has shown utility in identifying motor delays and
atypical development patterns in infants who later receive an autism diagnosis. Delayed
acquisition of head control, rolling, and antigravity movements may suggest broader
neurodevelopmental disruption. Some research also indicates that infants with later-diagnosed
autism may demonstrate plateauing or uneven motor progress on AIMS scoring.
Video-Based Analysis and Home Recordings
Retrospective analysis of home videos has been a valuable research method to identify early
motor markers of autism. Subtle abnormalities, such as poor trunk stability, asymmetric limb
movement, or reduced movement diversity, are often detectable by trained observers even at
two to four months of age. Home video analysis helps researchers understand developmental
patterns outside clinical settings, capturing spontaneous behavior in a natural environment.
Advances in computer vision have enabled automated video analysis that detects movement
patterns, postural control, and coordination metrics. These technologies are increasingly used to
complement human observation, reduce bias, and potentially scale up screening efforts.
Wearable Sensors and Digital Biomarkers
Recent technological innovations have introduced wearable motion sensors that provide precise
measurements of limb movement, frequency, range, and velocity. Using accelerometers or
gyroscopes, these devices track motor activity continuously and objectively. Research shows
that infants with elevated autism risk may exhibit reduced movement variability and atypical
postural transitions as measured by sensors.
These data can be transformed into digital biomarkers that, when combined with behavioral
metrics, may improve the sensitivity of early autism screening. While these tools are still in the
early stages of validation, they represent a promising step toward real-time, low-burden motor
analysis.
Clinical Implications and Limitations
INTERNATIONAL JOURNAL OF ARTIFICIAL INTELLIGENCE
ISSN: 2692-5206, Impact Factor: 12,23
American Academic publishers, volume 05, issue 08,2025
Journal:
https://www.academicpublishers.org/journals/index.php/ijai
689
While early motor assessment offers significant promise, several challenges remain. First, many
motor abnormalities seen in autism overlap with those in other neurodevelopmental disorders,
such as cerebral palsy or developmental coordination disorder. Thus, specificity remains limited,
and these tools should not be used for diagnosis in isolation.
Second, most current assessments rely on trained professionals and can be time-consuming or
resource-intensive in routine care. Widespread adoption will require further simplification,
training, and integration into pediatric screening systems.
Third, cultural and environmental factors can influence motor development, potentially
affecting scoring on norm-referenced scales like AIMS. Future research must ensure that these
tools are validated across diverse populations to avoid misclassification or diagnostic delay.
Nevertheless, when combined with family history, genetic risk profiles, and behavioral
assessments, early motor assessment tools offer a valuable strategy for identifying children who
may benefit from early intervention. Intervening in the first year of life, when brain plasticity is
highest, can significantly alter developmental outcomes for children with autism.
Infants typically show a progression of motor skills, from spontaneous movements in the
neonatal period to purposeful reaching and head control by six months. Deviations in this
developmental path—such as reduced variability of movement, poor head and trunk control, or
asymmetry—may indicate underlying neurological differences. Identifying and measuring these
deviations requires sensitive and reliable assessment tools designed for early infancy.
Several standardized and observational tools are currently used to assess motor development in
infants under six months of age, particularly those at risk for autism. These tools are primarily
designed to capture quality, coordination, and timing of spontaneous and intentional
movements.
One widely used method is
General Movement Assessment (GMA)
, which evaluates the
spontaneous movement patterns of infants from birth to five months. GMA focuses on the
presence and quality of “fidgety movements,” which typically emerge around three months. In
infants later diagnosed with autism, studies have reported abnormalities in these movements,
such as reduced complexity or variability. GMA is considered a reliable and non-invasive early
screening tool for neurodevelopmental disorders, including autism.
Another tool is the
Motor Optimality Score (MOS)
, which builds upon GMA by offering a
more detailed scoring system to quantify movement quality. Infants with lower scores often
show increased risk of developmental disorders. MOS evaluates not only general movements
but also postural patterns, symmetry, and movement fluency, which are all sensitive to
neurological functioning.
Additionally,
the Alberta Infant Motor Scale (AIMS)
is a norm-referenced observational tool
used to assess gross motor development in infants from birth to eighteen months. It examines
posture and movement in prone, supine, sitting, and standing positions. While not autism-
specific, AIMS has been applied in early risk detection due to its ability to reveal motor delays
or unusual developmental timing.
Video-based analysis
has also gained traction, particularly in research settings. Home videos or
structured recordings analyzed by developmental specialists can reveal subtle motor signs that
are often missed during routine pediatric examinations. These include unusual limb postures,
asymmetrical kicking, or a lack of anticipatory postural control.
More recently,
wearable sensors and computer-vision-based technologies
have been
developed to objectively quantify infant movement. These tools track limb movement
trajectories, frequency, and coordination, offering high-resolution data for early risk profiling.
INTERNATIONAL JOURNAL OF ARTIFICIAL INTELLIGENCE
ISSN: 2692-5206, Impact Factor: 12,23
American Academic publishers, volume 05, issue 08,2025
Journal:
https://www.academicpublishers.org/journals/index.php/ijai
690
Such technologies are still emerging but hold promise for future large-scale screening
applications.
Collectively, these tools enable clinicians and researchers to detect early motor markers that
may signal elevated autism risk, allowing for earlier monitoring and potentially earlier
intervention.
Conclusion
Differences in motor activity during the first six months of life may serve as early indicators of
autism spectrum disorder. Through validated assessment tools like the General Movement
Assessment, Motor Optimality Score, and Alberta Infant Motor Scale, along with emerging
technologies, it is now possible to detect atypical motor patterns well before traditional
behavioral symptoms emerge. Early identification based on motor function could play a vital
role in timely diagnosis and early support strategies. Continued research and refinement of
these tools are essential to improve early screening accuracy and to better understand the
developmental pathways leading to autism.
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