HHT-based Analysis of ECG Signals of Patients with Borderline Mental Disorders

This paper describes a solution for borderline mental disorders detection. This approach is based on the ECG processing by Hilbert-Huang Transformation. The described approach allows to develop an additional module for mental disorders diagnostic systems. The research is based on the fact that in the conditions of borderline mental disorders there are changes in patients' heart function. Detection of significant ECG informative parameters is based on the effective and accurate measurement of amplitude, time, frequency and energy parameters of the ECG signal. A verified and registered database of 780 ECG signals of patients with borderline mental disorders and healthy people is used. The proposed method is described and the results are shown. The errors of the method with current sampling do not exceed 4%. The developed approach using volumetric spectral surfaces has showed a high probability of determining the period of occurrence of psycho-traumatic situations in various patients using the ECG.