Antonello Semeraro
Cardiac and Respiratory analysis from photoplethysmographic (PPG) signal for stress and mental workload assessment.
Rel. Danilo Demarchi, Irene Buraioli, Gabriele Luzzani. Politecnico di Torino, Corso di laurea magistrale in Ingegneria Biomedica, 2025
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Abstract
The World Health Organization (WHO) has included burnout in the International Classification of Diseases. Consequently, real-time monitoring of an individual’s stress levels and mental load while performing a task is crucial to assess whether the person is actually able to complete the assigned task. The analysis of physiological signals is the best strategy for real-time monitoring of mental workload, which have distinctive characteristics related to the individual’s physiological state. In particular, the cardiac and respiratory signals have characteristic features, such as heart rate (HR), heart rate variability (HRV), and respiratory rate (RR), that are highly dependent on mental workload levels.However, the necessity of acquiring each signal with a dedicated system gives rise to issues concerning the footprint, which hinders the task to be performed.
In order to overcome these limitations, recent wearable devices can be utilised for the purpose of acquiring the photoplethysmographic (PPG) signal from which the extraction of both cardiac and respiratory characteristics is possible
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