JAN 16, 2019 02:54 PM PST

Wearable Sensor Helps Detect Childhood Anxiety

WRITTEN BY: Nouran Amin

Many young children, as high as one in five kids, experience anxiety and depression. Often, these conditions can be hard to detect by parents, health-care providers, and teachers—giving them the name "internalizing disorders”. These conditions are not insignificant and if left unrecognized can cause problems in later life with greater risks substance abuse and/or suicide. "Because of the scale of the problem, this begs for a screening technology to identify kids early enough so they can be directed to the care they need," states Ryan McGinnis, a biomedical engineer at the University of Vermont.

Now, a study published in PLOS ONE describes a tool that was recently developed to help screen internalizing disorders in children that aims to catch symptoms early. "Children with anxiety disorders need an increased level of psychological care and intervention. Our paper suggests that this instrumented mood induction task can help us identify those kids and get them to the services they need," explains Ellen McGinnis.

Ellen McGinnis and Ryan McGinnis of the University of Vermont, lead researchers on a study published in PLOS ONE that showed wearable sensors could detect hidden anxiety and depression in young children.

Photo: Josh Brown via University of Vermont

The researchers used a "mood induction task” to produce specific behaviors and feelings such as anxiety in 63 children, some of whom had internalizing disorders. They then used a wearable motion sensor to monitor a child's movement with a machine learning algorithm. "The way that kids with internalizing disorders moved was different than those without," says Ryan McGinnis.

Learn more about childhood anxiety:

The study can open a world of possibilities in using technology to help screen for childhood mental health issues and psychological disorders and to identify those that need treatment. "If anxiety symptoms do not get detected early in life, they might develop into a full-blown anxiety and mood disorder," says Ellen McGinnis. "Something that we usually do with weeks of training and months of coding can be done in a few minutes of processing with these instruments.”

Source: University of Vermont

About the Author
  • Nouran enjoys writing on various topics including science & medicine, global health, and conservation biology. She hopes through her writing she can make science more engaging and communicable to the general public.
You May Also Like
DEC 12, 2019
Clinical & Molecular DX
DEC 12, 2019
Patients can Self-Inject Easily Using an Integrated Pre-Filled Syringe and Autoinjector
The patients suffering from chronic disease require a regular dose of medicines, either orally or as injections. To prevent a monthly visit...
DEC 12, 2019
Technology
DEC 12, 2019
Machine-Learning and Epigenetics Drug Discovery
Machine learning is known for detecting patterns seen in complex data—such uniqueness has proven it roles in health and medicine. Now, researchers at...
DEC 12, 2019
Technology
DEC 12, 2019
How Computer Science Breaks Down Cultural Barriers
Children at Kenyan refugee camp are working together to develop a rudimentary video game about Malaria. Many of the children are inputting their ideas thro...
DEC 12, 2019
Earth & The Environment
DEC 12, 2019
Study Triples Estimate of Sea Level Rise Vulnerability
The estimate of people at risk from coastal flooding due to climate-change-related sea level rise has tripled, thanks to a new study from published today i...
DEC 12, 2019
Space & Astronomy
DEC 12, 2019
Hayabusa-2 Departs Ryugu Asteroid to Return to Earth with Samples
It’s been just over a year since JAXA’s renowned Hayabusa-2 mission arrived at asteroid 162173 Ryugu to study the dynamics of the distant space...
DEC 12, 2019
Cancer
DEC 12, 2019
Using AI to determine which patients are best suited for immunotherapy
A new study published in the journal Cancer Immunology Research suggests that we can use artificial intelligence to help determine which people with lung c...
Loading Comments...