Early prediction of unexplained syncope by support vector machines

Daniel Schang (1, 2) , Mathieu Feuilloy (1, 2) , Guy Plantier (1, 2) , Jacques-Olivier Fortrat , Pascal Nicolas

1 GSII - ESEO-GSII
2 LAUM - Laboratoire d'Acoustique de l'Université du Mans

The goal of the present study was to develop and evaluate a new method for the prediction of unexplained syncope occurrences. Diagnosis of syncope is currently based on the reproduction of symptoms in combination with hypotension and bradycardia induced by a 45 min 60?70° head-upright tilt test (HUTT). The main drawback of this widely used test concerns its duration that reaches 55 min if the patient does not faint. Our method is a first step in the avoidance of the HUTT. An electrocardiogram and a transthoracic impedance waveform were recorded for 10 min of supine rest of a HUTT in 128 patients with a history of unexplained recurrent syncope. Seven indices were computed on the transthoracic impedance and its first derivative. The prediction quality of every subset of these variables, mixed with age and sex, has been tested by a support vector machine in a retrospective group of 64 patients (100% of sensitivity and 100% of specificity was reached). The best subset obtained has been evaluated prospectively in a group of 64 patients (94% of sensitivity and 79% of specificity was reached). These results compare very favorably with published results for other unexplained syncope detectors

Domaines: Traitement du signal et de l'image [eess.SP]

Daniel Schang, Mathieu Feuilloy, Guy Plantier, Jacques-Olivier Fortrat, Pascal Nicolas. Early prediction of unexplained syncope by support vector machines. Physiological Measurement, 2007, 28 (2), pp.185--197. ⟨hal-01166462⟩