Wearable Sensors to Detect Early Autism Signs in Infancy

Summary: Researchers are developing a wearable technology designed to catch subtle motor delays, one of the earliest yet most overlooked signs of autism spectrum disorder (ASD). The five-year project uses miniature sensors, similar to fitness trackers, to monitor infant movements in the home.

By identifying coordination and grasping issues as early as three months of age, the team aims to bypass the limitations of traditional checkups and fast-track infants into life-changing early interventions.

Key Facts

The “Cascading” Effect: Motor difficulties often precede language delays. If untreated, they can limit a child’s ability to explore their environment and engage socially, creating a “cascade” of further developmental delays.
Underrecognized Symptoms: While motor issues are as common as language struggles in ASD, they are frequently missed during standard pediatric checkups that only screen for major milestones like sitting or crawling.
Home-Based Data: The study monitors 120 high-risk infants (siblings of children with ASD) from ages 3 to 12 months using sensors on wrists and ankles, capturing natural movement patterns in a real-world setting.
Predictive Machine Learning: UCLA researchers are using machine learning to analyze “movement variability” metrics, which have already shown high accuracy in predicting later autism diagnoses.

Source: UCLA

UCLA Health researchers are seeking to develop a new wearable technology to catch one of the earliest but often overlooked signs of autism and other developmental conditions in infants.

Supported by a $3.1 million grant from the National Institute of Neurologic Disorders and Stroke, the five-year research project will test wearable sensors akin to tiny fitness trackers to monitor babies’ movements in their first year.

This shows a baby's hand and wrist monitor. — Catching movement issues early is crucial to ensuring referral to interventions that improve independence and wellbeing. Credit: Neuroscience News

“Early detection and intervention are the two most important factors for optimal developmental outcomes in autistic individuals, yet early identification remains a major challenge in autism, despite the fact that we know changes in the brain happen as early as prenatally in those who go on to have autism,” said Dr. Rujuta Wilson, the study’s lead investigator and pediatric neurologist at UCLA Health.

“Our team seeks to improve early identification by developing robust clinical predictors of autism that are scalable to the home and clinic.”

Motor concerns, such as difficulty in coordinating movements or grasping objects, are among the earliest signals that a child may have autism. While these motor difficulties are as common, if not more common, than verbal language difficulties in children with autism, studies have shown they are significantly underrecognized and undertreated, even by pediatric neurologists, for various reasons. Regular checkups often only test basic movement such as sitting up or crawling, which may overlook the more subtle movement issues that can point to autism.

Wilson said these movement difficulties can persist if untreated, creating cascading issues on the child’s ability to explore their surroundings, engage socially and develop language and communication skills as they age.

“Catching these movement issues as early as possible in a child’s life is crucial to helping clinicians know who to monitor more closely and to ensure referral to earlier intervention that can improve their functional abilities, independence and wellbeing throughout the rest of their lives,” Wilson said.

The new study will recruit about 120 infants who have an increased likelihood of having autism because they have an older sibling with autism spectrum disorder. Wearable sensors will be placed on the infants’ wrists and ankles in comfortable arm and leg warmers to capture data on how the baby moves in their homes from ages 3 months to 12 months, with assessments being made at three-month intervals. Researchers will also conduct behavioral assessments at each time point and assessments for autism spectrum disorder and other developmental conditions at ages 12 months and 24 months.

Additionally, most of the time points can occur in the infants’ homes to increase accessibility to the study for a large range of families. Families will be provided with verbal and written feedback on their infants’ development and can discuss any concerns that they may have with Dr. Wilson and the expert study team.

The new study will advance earlier UCLA research from Wilson’s lab that has already shown promising metrics of infant movement variability that are highly predictive of a later autism diagnosis.

“We are excited to really advance this work through the support of the National Institute of Neurologic Disorders and Stroke to validate these metrics, use machine learning methods to develop a battery of movement metrics that aid in early prediction of developmental concerns, and examine how we can utilize these measures in typical well child pediatric visits,” Wilson said. “Achieving these goals will allow us improve early surveillance and referral to appropriate interventions.”

The study has recently started in January and will end in December 2030.

Funding: The study is funded by the National Institute of Neurologic Disorders and Stroke (1R01NS142720-01A1).

Key Questions Answered:

Q: Why look at movement instead of eye contact or speech?

A: Motor issues are often the very first “red flag” to appear, sometimes months before social or language symptoms are detectable. Catching these early signs allows for intervention during the brain’s most plastic period, potentially improving long-term independence.

Q: Is this just a fancy baby monitor?

A: It’s much more. Standard monitors watch for safety; these sensors record high-resolution data on coordination, limb symmetry, and “movement variability”, the tiny nuances in how a baby reaches or kicks that the human eye often misses.

Q: Will this technology be available in my pediatrician’s office?

A: That is the ultimate goal. The study aims to validate a “battery of movement metrics” that are scalable and affordable enough to be integrated into routine well-child visits, making early screening accessible to all families.