Using wearable technology to diagnose depression and anxiety

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The problem with mental health diagnosis

Depression and anxiety are worryingly prevalent in the United States, yet diagnosis and treatment are often inadequate.

Over half of the people who suffer from these mental illnesses are not properly identified and therefore not treated.

The challenge for mental health professionals is to find effective, non-invasive ways to detect these disorders early.

They recently turned their attention to a device many of us already own: wearable fitness monitors.

Wearable technology to the rescue?

Wearable fitness trackers like Fitbits not only monitor physical activity, but also collect data on the user’s physiological parameters.

These devices record everything from daily steps, calorie burn rates to heart rate and exercise minutes.

The data generated by these trackers presents an exciting opportunity for healthcare providers. The question then becomes: can this data be used to detect mental health issues?

Studies at Washington University

Researchers at Washington University in St. Louis investigated this question. They developed a deep learning model called WearNet that analyzed 10 variables collected by the Fitbit activity tracker over more than 60 days.

The results were promising. WearNet performed better than other machine learning models in detecting risk factors for depression and anxiety.

Predictions have also been made at the individual level, a critical requirement for personalized healthcare.

Deep Learning and Mental Health

“Deep learning uncovers the complex relationships between these variables and mental disorders,” says Chenyang Lu, a professor at the McKelvey School of Engineering and School of Medicine.

His team provided evidence that detecting mental disorders with wearables is indeed possible.

“Our work provided evidence that it is possible to detect mental disorders using wearables. The next step is to convince a hospital system or a company to implement it.”

Benefits of portable data

Lu also emphasized the benefits of using wearable data in mental health diagnosis.

Traditional diagnostic methods, such as completing questionnaires with a psychiatrist, can be time-consuming and intimidating for some people.

“This AI model can tell you if you have depression or anxiety disorders. Think of portable data as an automated screening tool that might recommend you see a psychiatrist.”

The scope of the study

The researchers analyzed data from more than 10,000 Fitbit users, making this study the largest of its kind. Previous studies have only considered cohorts of up to a few hundred users.

The data covered a wide range of ages, races, ethnicities and educational levels, which increased the credibility of the results.

The future of wearables in mental health

This study offers insight into the potential future of mental health diagnosis.

As wearable technology continues to evolve and become more accessible, it could become an important tool for the early detection and treatment of mental disorders.

It also contributes to a growing body of research supporting the use of digital phenotypes, such as sleep and behavioral patterns, in mental health assessments.

The results of this study were presented at the ACM/IEEE Conference on Design and Implementation of the Internet of Things, where they received the Best Paper Award for IoT Data Analytics.

If you are interested in depression, please read studies about it how dairy products can affect depression risk, And B vitamins may help prevent depression and anxiety.

For more information on mental health, see recent studies on popular anti-anxiety medications. The results show that some vegetarian diets may be linked to depression.

The study has been published Here.

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