Multiclass Prediction and Assisted Diagnosis of Mental Disorders Based on Eye Movement and Other Physiological Signals
A special issue of Bioengineering (ISSN 2306-5354). This special issue belongs to the section "Biosignal Processing".
Deadline for manuscript submissions: 31 January 2025 | Viewed by 232
Special Issue Editor
Special Issue Information
Dear Colleagues,
This Special Issue explores the multiclass prediction and diagnosis of mental disorders via eye movement and other physiological signals. It involves leveraging technology to analyze eye movement, heart rate, skin conductance, and brain activity data to enhance the accuracy of diagnosing a variety of mental health conditions. By employing machine learning and artificial intelligence techniques, this research aims to differentiate between different mental disorders, such as depression, anxiety, schizophrenia, and more. This work may revolutionize mental healthcare by providing more precise and timely diagnoses, reducing the likelihood of misdiagnosis, and improving treatment planning. However, there are ethical and privacy concerns related to the collection and protection of sensitive physiological data. In summary, this represents an innovative approach that may make mental health assessment and diagnosis more effective and personalized, while simultaneously necessitating responsible data handling practices.
Dr. Quan Wang
Guest Editor
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Keywords
- physiological signals
- mental disorders
- eye movement
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