Contents I. Introduction
Mental health is a growing concern worldwide. Millions of people are affected by various mental health conditions each year [1]. Early detection and diagnosis of mental abnormalities are crucial to mitigating adverse conditions and promoting better mental health. Mobile health (m-health) has emerged as a possible solution for enhancing the promotion of early detection of mental illness, particularly in home or elderly care settings [2]. Recent research has shown that eye and head movement can reflect an individual's mental status and cognitive conditions [3], [4]. The movement are reliable biomarkers for the diagnosis of mental illness and dementia [5] - [9]. This has led to an increased interest in monitoring eye and head movement for early detection of mental illness and monitoring mental health status. Morita et al. explored using oculomotor alterations to detect neurological and mental diseases, such as cerebellar dysfunction, schizophrenia, and depression [10]. Their research indicated significant differences in eye movement between healthy individuals and those with schizophrenia. Zhao et al. investigated the relationship between abnormal head motions and psychiatric disorders in children with autism spectrum disorder (ASD) [11]. The study involved analyzing video recordings of face-to-face interactions between autistic children and their caretakers to identify instances of aberrant head motions, which were characterized as excessive or abnormal head movements during interactions. Recording and analyzing these distinct eye-head movement is valuable for understanding the functional integrity of mental illnesses.
