Wearable fingertip sensor identifies physical patterns linked to stress and anxiety
Researchers have developed a wearable fingertip sensor that uses light to measure blood flow and tissue activity, combined with machine learning, to identify physical patterns associated with stress, anxiety, and depression. A study involving 132 adults found that the models could distinguish individuals reporting stress-related symptoms with moderate success, with blood-flow patterns and tissue metabolism measurements being key contributors.
Why it matters
This technology could offer a non-invasive method for early detection and monitoring of mental health conditions, potentially leading to more timely interventions and personalized care.
edited by Lisa Lock , reviewed by Robert Egan
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Add as preferred source Credit: Unsplash/CC0 Public Domain Researchers have shown that measurements taken from a person's fingertip could help identify physical patterns associated with stress, anxiety and depression. The international study, involving experts from Aston University, used a wearable device that shines light into the skin to measure blood flow through the smallest blood vessels as well as changes in the activity of the surrounding tissue.
These measurements were then combined with machine learning to investigate whether people reporting symptoms of stress, anxiety or depression displayed recognizable physical patterns. The results are published in the journal Communications Medicine .
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