Key result
Photoplethysmogram (PPG) signal morphology showed significant changes corresponding to early signs of mental disorders through emotional and stress levels.
Why the study?
The paper aims to provide an overview of photoplethysmogram for detecting early symptoms of mental disorders encompassing physiology using different stimuli.
Can photoplethysmogram (PPG) detect early signs of mental disorders?
Can photoplethysmogram (PPG) detect early signs of mental disorders?
This review highlights the potential of photoplethysmogram (PPG) signal morphology and machine learning in detecting early signs of mental disorders.
Answers are grounded in this paper and cite their sources.
PPG-based mental disorder screening via ML may aid early detection; leaves open clinical adoption pending prospective validation.
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.
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Awang et al. (2021) conducted a review in Mental disorders. Photoplethysmogram (PPG) was evaluated on Early signs of mental disorders through emotional and stress levels from PPG signal morphology. Photoplethysmogram (PPG) signal morphology showed significant changes corresponding to early signs of mental disorders through emotional and stress levels.
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