Machine learning predicts mental health impact on people with MS during lockdown

Published on October 5, 2022

Imagine you’re a fish in a cozy aquarium, swimming comfortably in your little world. Suddenly, a mysterious forcefield covers your tank, confining your movements and limiting your interaction with the outside world. Just like that, you realize the significant impact that isolation can have on your well-being. In a similar way, researchers have developed a clever machine learning model that accurately predicts the mental health conditions of people with multiple sclerosis (MS) during stay-at-home periods like the COVID-19 lockdown. By analyzing data from smartphones and fitness trackers, scientists collected valuable insights on depression, fatigue, poor sleep quality, and worsening MS symptoms during these unprecedented times. Using this data, they created predictive models to better understand how MS patients are affected by social restrictions. Excitingly, these findings can potentially lead to tailored interventions and support for individuals with MS, improving their overall quality of life. To dive deeper into the fascinating research and discover how technology can improve our understanding of neurological disorders, check out the full article!

A newly developed model can accurately predict how stay-at-home orders like those put in place during the COVID-19 pandemic affect the mental health of people with chronic neurological disorders such as multiple sclerosis. Researchers gathered data from the smartphones and fitness trackers of people with MS both before and during the early wave of the pandemic. Specifically, they used the passively collected sensor data to build machine learning models to predict depression, fatigue, poor sleep quality and worsening MS symptoms during the unprecedented stay-at-home period.

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