Tim Steenbergh recently attended the Conference for the Society for Ambulatory Assessment at Penn State University. Here are his highlights from this exciting event.
Every other year, a group of experts on mobile assessment and intervention get together to talk about the latest developments in the field at the Conference for the Society for Ambulatory Assessment. I had high hopes going into the conference, and I wasn’t disappointed.
A couple of highlights from the conference included:
- Mobile Seizure Detection
MIT professor Rosalind Picard gave an exciting talk about her lab’s cutting-edge work on the use of mobile sensing to detect seizure activity.
While there were many highlights from her talk, one of them involved the possibilities of detecting seizure activity and preventing sudden death among those who suffer from seizure disorders. Although seizures are relatively rare, according to Dr. Picard, more people die from them than from ordinary house fires. So the mobile alarms that Picard’s team is developing hold great promise.
- Integrating Behavioral Intervention Technologies Into Daily Life
Another exciting presentation, given by David Mohr of Northwestern University, focused on behavioral intervention technologies and the various ways these can be integrated into daily life by using passive sensing.
One of the most surprising findings he discussed involved the ability to predict depression scores based on phone usage and GPS data. These data were found to be a significant predictor of depression scores on the PHQ-9. According to Mohr, the mobile data appeared to explain about 25% of the variability in participants’ depression scores.
To my knowledge, this is the first behavioral indicator of depression. And this is exciting it was detected passively using mobile sensing technology.
- Open Source Software for Researchers
While there were many other exciting developments I could share, one that is particularly relevant to EMA researchers involves open source software that researchers are providing for those who are developing EMA systems. However, for most researchers, the code that’s provided still doesn’t do much good. It’s difficult to maneuver, especially since they are more interested in designing and conducting research studies, rather than trying to create software. (A system that allows somebody to create EMA protocols without needing to write code for their project, like LifeData’s, hopefully, can help remedy this problem.)
I walked away from the conference encouraged to see the way the field is expanding and the high quality work my colleagues are doing. I was also excited to meet researchers who are just beginning to use EMA. At LifeData, we hope to support veterans and novices alike, as they seek to understand people in the everyday moments of life.