68% of autistic children have been aggressive toward a caregiver at some point.
56% still are. 49% toward other people. 1,380 children, ages 4 to 17.
Emozu / Research
Research
The problem in numbers, four studies that predict episodes from a wearable, the gap at home, how our pilot works, and every source. Updated November 2026.
The problem
This started with one family close to us. Then we read what other parents write, and saw the same picture. The child often cannot say what is wrong. The parent looks for a trigger after the fact, and the next one comes without warning.
“How do other parents sense that a meltdown is coming?”
“My child wakes up already on the edge, and I can't see why.”
“I'm looking for a wearable that could help us avoid meltdowns.”
Share of posts that touch each topic. One post can touch several.
Our own tagging of 409 public posts: 370 from r/Autism_Parenting, 39 from other parent communities. Most are from 2025 and 2026. Not a clinical sample. The three lines above are paraphrased, not quotes.
In the published numbers
Each card links to its source. All links are also listed at the end of the page.
56% still are. 49% toward other people. 1,380 children, ages 4 to 17.
A pooled estimate from 37 studies and 14,379 people.
Among those who went missing, 65% had a close call with traffic and 24% with drowning. 1,218 children.
A meta-analysis of studies with comparison groups. The gap was large.
They wait for it with anxiety, and feel helpless and judged. Six in-depth parent interviews.
CDC monitoring network, 2022 data, 16 US sites.
What it is based on
Four studies from 2019 to 2026 use a wearable sensor to catch an episode. Three of them predict it, 1 to 10 minutes ahead. The models look for this: heart rate goes up, heart rate variability goes down, and skin conductance bursts come more often.
Minutes before the episode. Curves are illustrative. The window comes from Imbiriba 2023 (3 min) and Kartha 2026, preprint (10 min).
AUROC measures how well a model separates “episode soon” from “all quiet”. 0.5 is a coin flip, 1.0 is perfect. Models, groups, and horizons differ, so compare with care. In these studies an “episode” means aggression or other challenging behavior, which is not always what a parent calls a meltdown.
20 young people, ages 6 to 17 · inpatient psychiatric unit · 1 minute ahead
General model 0.71Personal model 0.84
The first study of this kind, and the only one where a personal model clearly won. The group was small, so this result is quoted often but should not stand alone.
Plain-language summary: Northeastern University.
70 young people, ages 5 to 19 · 4 psychiatric hospitals · 3 minutes ahead
Main result 0.80Best case 0.87
9 males, ages 10 to 21 · special-ed class · 10 minutes ahead
At 10 minutes 0.78 ± 0.10
11 boys, ages 10 to 20 · The Center for Discovery · detection, not ahead
Accelerometer 0.71
This study detects an episode as it happens, it does not warn ahead. An uncomfortable result worth saying out loud: the best channel here was motion, not skin conductance. Personal models did not win consistently. A cheap accelerometer should not be written off.
This group likely overlaps with Kartha 2026, so we do not add these 11 children to the total.
Better in 2019, worse in 2023. The pilot tests it directly: a general model plus two weeks of personal calibration.
In one study an accelerometer alone beat skin conductance at detecting episodes (AUROC 0.71). So even a simple module carries signal.
On the ankle, in a classroom. The sensor went there because children keep it on, and that matters as much as the model.
A parent who gets pulled away for nothing stops listening. So we do not start with alerts. We start silent: record, label, and look back. “Yesterday at 16:40 it began eight minutes before you noticed” has no false alarms at all. Live alerts come later, and only if the numbers hold.
Where to measure
Sweat glands are denser on the hands and feet. In a lab comparison of 45 students, the wrist responded least of all sites. So the same pod moves: wrist, arm, ankle. The pilot chooses the place by data, and by what the child will actually keep on.
Wrist and ankle are not in the source table. Their values are estimates from nearby sites, not measurements.
The gap
Every model was trained in a hospital, a clinic, or a classroom. Home is where a parent needs the warning most, and we found no labeled data from there. That is the piece Emozu wants to collect first.
hospital unit
4 psychiatric hospitals
special-ed class
labeled episodes
Why now
Kartha and Bahrami Rad used it
First model, 20 children
70 children, 4 hospitals
Imbiriba used it
Best channel: motion
10 minutes, preprint
A family device and home data
Sources: Q-Sensor · Empatica E4 sunset. A school student in Ukraine also built a similar band on their own this year (Ukrainska Pravda), so the idea is in the air.
Our reading of public product descriptions, November 2026. Awake Labs.
A wearable for a child that was sold as a consumer product and turned out to be a medical one: Owlet.
From an FDA warning letter to De Novo clearance. The FDA fee for De Novo is now $191,020, or $47,755 for a small business (FY2027).
“Predicts a meltdown” can make a product a medical device. So we make no such claim today, and we will talk to the regulator before we ever do.
Method
A target of about 15 episodes per child, which at home means 6 to 8 weeks. The parent marks an episode with one tap. Every “what helped” mark is one more label.
“What helped” goes back into the data. The loop teaches the model this child.
The final protocol will be set with a clinical partner and an ethics committee, and pre-registered. Video labeling follows Imbiriba 2023, where raters agreed at κ 0.86 to 0.95.
At 3, 5, and 10 minutes ahead:
In phase B we compare how often and how long episodes last on “on” days and “off” days.
A labeling bot for parents is built and being tried out.
Sources
Write to us
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