Decision support systems in pathological or physiological stress by assessing the state of the autonomic nervous system through signal processing

Autonomic nervous system (ANS) dysfunctions have been associated with various diseases including hypertension, heart failure, obesity, diabetes, sleep apnea, and mental disorders. Stress, mediated by ANS, has been related to the worsening of previous illnesses, as well as some physiological situations. The ANS measurement is a potential tool for the monitoring and evaluation of these applications. Since the activity of the ANS creates characteristic patterns in the cardiovascular signals, the non-invasive measurement of the ANS has been proposed through the processing of these signals. In this project we intend to monitor the ANS response in stress-related clinical situations by analyzing the variability of biological signals in order to decide the best personalized treatment in pathological situations and the best planning in physiological situations. The clinical applications addressed in this project include physiological, pathological and psychological stress, and are as follows:

– Identification of pregnant women at risk of hypotension during spinal anesthesia in cesarean sections, who can benefit from prophylaxis, minimizing the negative effects of it in fetuses.

– Quantification of the stress level in healthy young subjects subjected to controlled stress through the analysis of biological signals.

To achieve the above objectives, the development of techniques for the robust analysis of the biological signals recorded in stress situations is essential, fundamentally of the variability of the heart rate and the photoplethysmographic pulse signal, as well as the interpretation of the results guided by physiology. This requires the collaboration of experts in signal processing and experts in medicine and physiology. The project will contribute to the research and development of technology to obtain personalized treatments, the effective evaluation of therapies and the identification of the population at risk, which will reduce the costs of the Health System. The participation of hospitals and companies in the project guarantees the application and transfer of its results. The results will have a high social impact by improving various highly prevalent diseases, which is why the project is aligned with the challenges of society “Health, Demographic Change and Wellbeing” (Horizon2020).