A method for processing data from at least one sensor configured to measure events, comprising: applying an output relating to the events from the at least one sensor to a resistive switching component, wherein each event is a neurological event; receiving data values representing a sequence of resistive state changes of the resistive switching component resulting from applying the output from the at least one sensor to the resistive switching component, wherein the resistive switching component is capable of undergoing a non-volatile resistive state change when a voltage above a threshold voltage is applied across the resistive switching component, wherein the resistive switching component is configured to change its resistive state as a function of the integral of the voltage; and processing the received data values by identifying for each event a corresponding resistive state change and obtaining information about each event other than temporal information from the corresponding resistive state change; wherein the identifying of a resistive state change corresponding to an event comprises identifying a feature in the received data values, the feature being a portion of the received data values, the data values of said portion being received consecutively during a corresponding time window, wherein the data values are resistance values and a ratio of change of the data values in the portion to the time period of the time window is greater than a predetermined value; wherein obtaining information about each event other than temporal information from the corresponding resistive state change comprises obtaining information about each event from both 1) a size of the change in the data values of the corresponding feature; and 2) a size of a reference data value of the corresponding feature; and the processing further comprises determining for each event, based on the corresponding obtained information, which class of a plurality of classes the event belongs to, the method being characterized in that: for each event, the reference data value of a corresponding feature is the data value at the start of the corresponding feature; and the classifying is carried out exclusively on data values of the features for which the corresponding reference data value is below a threshold, such that only a subset of the data values of the features are used for the classifying. applying an output relating to the events from the at least one sensor to a resistive switching component, wherein each event is a neurological event; receiving data values representing a sequence of resistive state changes of the resistive switching component resulting from applying the output from the at least one sensor to the resistive switching component, wherein the resistive switching component is capable of undergoing a non-volatile resistive state change when a voltage above a threshold voltage is applied across the resistive switching component, wherein the resistive switching component is configured to change its resistive state as a function of the integral of the voltage; and processing the received data values by identifying for each event a corresponding resistive state change and obtaining information about each event other than temporal information from the corresponding resistive state change; wherein the identifying of a resistive state change corresponding to an event comprises identifying a feature in the received data values, the feature being a portion of the received data values, the data values of said portion being received consecutively during a corresponding time window, wherein the data values are resistance values and a ratio of change of the data values in the portion to the time period of the time window is greater than a predetermined value; wherein obtaining information about each event other than temporal information from the corresponding resistive state change comprises obtaining information about each event from both 1) a size of the change in the data values of the corresponding feature; and 2) a size of a reference data value of the corresponding feature; and the processing further comprises determining for each event, based on the corresponding obtained information, which class of a plurality of classes the event belongs to, the method being characterized in that: for each event, the reference data value of a corresponding feature is the data value at the start of the corresponding feature; and the classifying is carried out exclusively on data values of the features for which the corresponding reference data value is below a threshold, such that only a subset of the data values of the features are used for the classifying. for each event, the reference data value of a corresponding feature is the data value at the start of the corresponding feature; and the classifying is carried out exclusively on data values of the features for which the corresponding reference data value is below a threshold, such that only a subset of the data values of the features are used for the classifying.