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To propose a new test to evaluate the autonomic nervous system in patients with syncope: Multimodal Monitoring for Diagnosis of Dysautonomia (MMDD). We included 21 patients with syncope (16 female, 6 male, mean age 43.5 years) and 21 with no-syncope subjects (15 female, 7 male, mean age 45.1 years) to perform a test of nine 2-min stages: four while resting and four during active testing of autonomic response. Transcranial-Doppler, electrocardiogram, and photoplethysmography blood pressure pulse-to-pulse monitoring, allow registering six variables from the Middle Cerebral Artery and four from the Cardiovascular System. We analyze each variable's mean differences in each stage and its change when they pass from one stage to another with the T and Z tests. To understand the significance of the change, we use a logistic regression model for a certain subgroup of variables. Since we have a small dataset, we use the bootstrap technique to infer the general behavior that characterizes a syncope. Our data confirm differences between syncope and non-syncope patients during MMDD stress stages 2, 4, 6 and 8. Bootstrap and multivariate logistic regression allow us to identify which sets of variables in each of these stages of the MMDD are sufficiently sensitive to recognizing syncope. MMDD protocol can recognize a syncope patient with some confidence by detecting subtle changes in the autonomic nervous system. This protocol encourages us to continue to study the effectiveness of MMDD protocol allowing a new approach to future research.