3 Things I’ve Learned from Developing Autism Technology

Contributed by Awake Labs

At Awake Labs we are developing a tool to empower autistic individuals and their caregivers to better understand anxiety with the goal of preventing behaviour meltdowns. This tool is called Reveal. It’s a wearable device (it looks a bit like a fitbit) and app that measures and tracks anxiety in real time. I’m new to the team and the first couple of months have been eye opening. So far, these have been my main takeaways.

1) The best way to tackle a problem is to look for what’s missing.

As we research anxiety and how it presents itself in Autism Spectrum Disorders, we are working with Nathan Searle, MS BCBA with the ABLE Developmental Clinic in British Columbia. He tells us that, “Anxiety is silent suffering and it is often missed in kids who have autism.” When behaviour is used to communicate anxiety, individuals are often seen as “acting out” instead of a way to inform those around them that something is wrong.

While anxiety may seem invisible from the outside, physiologically our body sends off signals that we can measure and track. For example, knowing you have a big test coming up, or hearing a loud noise can evoke nervous system reactions. That’s because our body’s nervous system automatically responds to physical, emotional, and cognitive stressors. The autonomic nervous system then responds to these stressors by activating the sympathetic nervous system, which results in a number of physiological and behavioural changes.

2) Technology can offer new approaches to old problems.

By measuring and tracking electrodermal activity (emotional sweat), heart rate and skin temperature, we can track anxiety. Using these metrics, the device we’re developing will provide an unbiased, quantified measure of anxiety in real time. It will notify you when a rise in anxiety is detected, and giveyou more insight at the right time to allow you to take action. It will allow you to study trends in anxiety, identify what causes it, and see which treatments and strategies work most effectively. All behaviour is communication – and this device will provide access to information to help you better understand what behaviours mean.

3) The best way to learn is to ask.

An invaluable part of the development of our Reveal device that I can’t overstate is listening and engaging the community. We’ve been involved and out talking to the community from day one and we continue to make it a priority.

The conversations I have with people in the community are by far the most meaningful learning experiences I could ask for. Take Tricia Sloan for example. I reached out to her because of her blog, Never Less Than (which is really wonderful by the way). She graciously answered my questions and provided invaluable feedback about the project. She had a lot of interesting things to say about Reveal, which she talks about in a blog post she wrote. She pointed out a few of the concerns, and filled me in on conversations happening in the community. These first hand, lived experiences are the reason the idea behind Reveal exists. It’s important to listen to them because they’re often seeing what you’re not. When you’re working on something, you can get stuck in confirmation bias and if you don’t ask someone who the problem matters to, you risk missing out on something you surely didn’t think of. So ask. Always ask. Even if you’re mostly sure, still ask. Because there is no one who can tell you better than the people you’re designing for.

All the best,

Katie and the Team at Awake Labs

Kushki et. al. (2013). Investigating the Autonomic Nervous System Response to Anxiety in Children with Autism Spectrum Disorders. PLoS ONE 8(4)

Fletcher et. al. (2010). iCalm: Wearable Sensor and Network Architecture for Wirelessly Communicating and Logging Autonomic Activity. IEEE Transactions on Information Technology in Biomedicine, Vol.

Poh et. al. (2010). A Wearable Sensor for Unobtrusive, Long-Term Assessment of Electrodermal Activity. IEEE Transaction on Biomedical Engineering, Vol. 57(5)

Liu et. al. (2008). Physiology-based affect recognition for computer-assisted intervention of children with Autism Spectrum Disorder. International Journal of Human-Computer Studies, 66.



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