A method for processing sensor signals representing a wetness event in an absorbent article, the method including: receiving from a sensor sensor signals representing a plurality of wetness events in an absorbent article; processing the sensor signals to determine a wetness event characteristic of at least one of the wetness events in the absorbent article; characterised in that processing the sensor signals includes identifying automatically a sensor signal that is representative of each individual wetness event in the plurality of events and, from the sensor signals representative of each individual wetness event: (i) generating a representative vector for that wetness event including one or more values derived from the sensor signal for that event; (ii) normalizing the elements of the representative vector with respect to a reference range; (iii) allocating weightings to the normalised elements of the representative vector to generate a weighted representative vector for that wetness event; and (iv) comparing the weighted representative vector with clusters of weighted representative vectors to determine which one or more of the clusters the weighted representative vector is most similar to and allocating a wetness event characteristic of the one or more clusters to the weighted representative vector for that wetness event, wherein the characteristic indicates volume of exudate in that wetness event. receiving from a sensor sensor signals representing a plurality of wetness events in an absorbent article; processing the sensor signals to determine a wetness event characteristic of at least one of the wetness events in the absorbent article; characterised in that processing the sensor signals includes identifying automatically a sensor signal that is representative of each individual wetness event in the plurality of events and, from the sensor signals representative of each individual wetness event: (i) generating a representative vector for that wetness event including one or more values derived from the sensor signal for that event; (ii) normalizing the elements of the representative vector with respect to a reference range; (iii) allocating weightings to the normalised elements of the representative vector to generate a weighted representative vector for that wetness event; and (iv) comparing the weighted representative vector with clusters of weighted representative vectors to determine which one or more of the clusters the weighted representative vector is most similar to and allocating a wetness event characteristic of the one or more clusters to the weighted representative vector for that wetness event, wherein the characteristic indicates volume of exudate in that wetness event. (i) generating a representative vector for that wetness event including one or more values derived from the sensor signal for that event; (ii) normalizing the elements of the representative vector with respect to a reference range; (iii) allocating weightings to the normalised elements of the representative vector to generate a weighted representative vector for that wetness event; and (iv) comparing the weighted representative vector with clusters of weighted representative vectors to determine which one or more of the clusters the weighted representative vector is most similar to and allocating a wetness event characteristic of the one or more clusters to the weighted representative vector for that wetness event, wherein the characteristic indicates volume of exudate in that wetness event.