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Abstract
Image and signal processing modalities play critical roles in the diagnosis and treatment efficacy of medical complications in people today. However, these tools have not yet been utilized to aid in the clinical diagnosis or treatment of neurocognitive disorders, such as Attention Deficit Hyperactivity Disorder (ADHD). The subjective nature of diagnosing neurodevelopmental disorders like ADHD has many merits. Yet, there is inadequate training for many doctors that can diagnosis ADHD without being a specialist in psychological disorder or disabilities, which leads to a concern for such subjective processes arising from those struggling to find a diagnosis and therapy to aid them in daily life. Therefore, a need for objective measurements to aid in the treatment and diagnoses processes exists. The objective of this work is to create an inexpensive method to be utilized in doctors’ offices and research to aid in the treatment efficacy and eventual diagnosis processes of neurodevelopmental disorders, beginning with ADHD. This thesis work analyzes the potential for various image and signal processing modalities, and highlights the viability of a computer vision modality. Part of the goal and inspiration for this work is to eventually utilize various measurements from a single camera, beginning with the physiological measurement of heart rate variability (HRV). HRV provides great insight into the autonomic nervous system, which is affected in persons with neurodevelopmental disorders. This work therefore focuses on improving upon previous works that came close to a distanced distinction of HRV detection for a person via a face camera, and compares the results of these algorithms to other HRV capturing methods.