Wearable devices may be a means to monitor psychological states through effortless data collection using artificial intelligence. Researchers at Mount Sinai have shown that data from wearable devices like the Apple Watch, analyzed through machine learning, can accurately assess a person's mental
, as a way to monitor and assess psychological states remotely without requiring the completion of mental health questionnaires.
“Wearables provide a means to continually collect information about an individual’s physical state. Our results provide insight into the feasibility of assessing psychological characteristics from this passively collected data,” said first author Robert P. Hirten, MD, Clinical Director, Hasso Plattner Institute for Digital Health at Mount Sinai.
To determine if machine learning models could be trained to distinguish an individual’s degree of resilience and psychological well-being using the data from wearable devices, the Icahn Mount Sinai researchers analyzed data from the. Leveraged for the current digital observational study, the data set comprised 329 healthcare workers enrolled at seven hospitals in New York City.
“We hope that this approach will enable us to bring psychological assessment and care to a larger population, who may not have access at this time,” said Micol Zweig, MPH, co-author of the paper and Associate Director of Clinical Research, Hasso Plattner Institute for Digital Health at Mount Sinai. “We also intend to evaluate this technique in other patient populations to further refine the algorithm and improve its applicability.
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