A computer implemented method for identifying time-frequency features of physiological events, the method comprising: a) receiving, by a computing system: a time period in which a physiological event occurred; a set of physiological signals associated with said physiological event, each signal of said set of physiological signals corresponding to a different spatial location of a body part of a living being; a time-frequency region of interest, said time-frequency region being defined by a minimum and a maximum time instant and a minimum and a maximum frequency, wherein said minimum and maximum time instants are comprised within said time period in which the physiological event occurred and said maximum frequency is lower or equal than the sampling rate of the physiological signals; and a plurality of time-frequency windows defined on the time-frequency region of interest; b) filtering the set of physiological signals within each of said plurality of time-frequency windows, obtaining as a result a filtered set of physiological signals for each time-frequency window; c) calculating, by the computing system, for each defined time-frequency window, a given feature for the filtered set of physiological signals, each one of the signals of the filtered set of physiological signals having a given feature value, providing for each time-frequency window a set of feature values; and d) calculating, by the computing system, for each time-frequency window, at least one of: a first quantifier defined as a function of said set of features values and comparing the calculated first quantifier with a given first threshold, the computing system further selecting the time-frequency windows satisfying the first threshold; and/or a second quantifier defined as a function of an empirical distribution of said set of feature values and comparing the calculated second quantifier with a given second threshold, the computing system further selecting the time-frequency windows satisfying the second threshold. a) receiving, by a computing system: a time period in which a physiological event occurred; a set of physiological signals associated with said physiological event, each signal of said set of physiological signals corresponding to a different spatial location of a body part of a living being; a time-frequency region of interest, said time-frequency region being defined by a minimum and a maximum time instant and a minimum and a maximum frequency, wherein said minimum and maximum time instants are comprised within said time period in which the physiological event occurred and said maximum frequency is lower or equal than the sampling rate of the physiological signals; and a plurality of time-frequency windows defined on the time-frequency region of interest; a time period in which a physiological event occurred; a set of physiological signals associated with said physiological event, each signal of said set of physiological signals corresponding to a different spatial location of a body part of a living being; a time-frequency region of interest, said time-frequency region being defined by a minimum and a maximum time instant and a minimum and a maximum frequency, wherein said minimum and maximum time instants are comprised within said time period in which the physiological event occurred and said maximum frequency is lower or equal than the sampling rate of the physiological signals; and a plurality of time-frequency windows defined on the time-frequency region of interest; b) filtering the set of physiological signals within each of said plurality of time-frequency windows, obtaining as a result a filtered set of physiological signals for each time-frequency window; c) calculating, by the computing system, for each defined time-frequency window, a given feature for the filtered set of physiological signals, each one of the signals of the filtered set of physiological signals having a given feature value, providing for each time-frequency window a set of feature values; and d) calculating, by the computing system, for each time-frequency window, at least one of: a first quantifier defined as a function of said set of features values and comparing the calculated first quantifier with a given first threshold, the computing system further selecting the time-frequency windows satisfying the first threshold; and/or a second quantifier defined as a function of an empirical distribution of said set of feature values and comparing the calculated second quantifier with a given second threshold, the computing system further selecting the time-frequency windows satisfying the second threshold. a first quantifier defined as a function of said set of features values and comparing the calculated first quantifier with a given first threshold, the computing system further selecting the time-frequency windows satisfying the first threshold; and/or a second quantifier defined as a function of an empirical distribution of said set of feature values and comparing the calculated second quantifier with a given second threshold, the computing system further selecting the time-frequency windows satisfying the second threshold.