Abstract
Mental disorder is defined as psychological disorders that involve instabilities in brain function. This paper aims to provide an overview of photoplethysmogram (PPG) for detecting early symptoms of mental disorders encompassing physiology using different stimuli. This paper discusses mental disorder studies that have been highlighted in the previous literature. The contribution of the PPG is summarized through feature extraction and its accuracy classified using machine learning. Moreover, research challenges and recommendations in the field are discussed. In conclusion, there were significant changes against the early signs of mental disorders through emotional and stress levels from PPG signal morphology.
Published Version
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