An electronic platform can read facial cues and vocal patterns, and integrate readings from smartwatch sensors to detect psychological stress, according to Texas A&M University (TAMU) researchers.
They developed the monitoring and feedback system with Houston Methodist Hospital collaborators and other researchers in Texas and Hawaii, using smartwatch-collected data to train machine learning algorithms to recognize patterns that correspond with the normal state of arousal.
The algorithms can then monitor readings from the sensors and recognition applications to identify the state of hyperarousal, a sign of psychiatric distress.
TAMU's Farzan Sasangohar said the technology “will give providers and counselors continuous access to patient variables and patient status, and I think it’s going to have a lifesaving implication because they can reach out to patients when they need it. Plus, it will empower patients to manage their mental health better.”
From Texas A&M Today
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