Revolutionizing Mental Health Diagnosis: Senseye’s Eye-Tracking App and the Growing Trend of Tech-Based Solutions
Senseye, a Texas-based mental health platform, is working to bring research out of the lab and into therapists’ offices and patients’ homes. They are testing a phone app that measures how people’s eyes respond to visual tasks to detect PTSD. This initiative is part of a growing trend of tech-based solutions aiming to improve the accuracy and speed of mental health diagnoses.
Digital tools like Clinicom, an adaptive assessment tool that screens for over 80 mental health conditions in five languages, are being used by various health systems, schools, criminal justice systems, and clinical offices. Clinicom uses augmented intelligence to learn from how clinicians respond to recommended diagnoses, providing more accurate assessments while allowing clinicians to retain diagnostic control.
Christopher Lucas, a psychiatrist at Upstate Medical University, mentioned in an open letter that Clinicom efficiently and accurately assesses the full picture of a patient’s presentation, reducing false positives and negatives. The ability to screen an entire school district or state in a day with Clinicom is seen as a significant advancement in mental health diagnosis. Handal, a user of Clinicom, noted that the tool feels like it’s listening, which helps build trust with those being assessed.
Senseye’s app measures eye movements using sensors attached to smartphones or tablets. It analyzes how people respond to visual tasks such as following moving objects or identifying objects on a screen. The app can detect signs of PTSD such as avoidance behaviors or difficulty focusing on visual cues. This technology has the potential to revolutionize the way mental health conditions are diagnosed and treated by providing clinicians with objective data about their patients’ eye movements and responses to visual stimuli.
Tech-based solutions like Senseye’s app are becoming increasingly popular due to their ability to improve accuracy and speed of mental health diagnoses. These tools provide clinicians with valuable insights into their patients’ psychological states by leveraging cutting-edge technologies such as machine learning and artificial intelligence.
The use of these digital tools also helps address some of the challenges associated with traditional methods of diagnosing mental health conditions such as subjectivity and bias. By providing objective data about patients’ eye movements and responses to visual stimuli, these apps can help reduce false positives and negatives in diagnosis.
Overall, Senseye’s app represents an exciting new development in the field of mental health diagnosis
