Abstract: The present disclosure relates to a system for providing real-time warnings based on continuous sensor signals. In one implementation, such a system may include at least one measuring device configured to measure at least one variable related to a user and at least one processor configured to receive the measured at least one variable related to the user for processing and display. The processing may include context recognition and inference for estimating risk. The display may include a real-time warning presented to the user or a caregiver, e.g., using a device associated with the user or caregiver.

Abstract: A method of classifying a data record as belonging to one of a plurality of classes, the data records comprising a plurality of data samples, each sample comprising a plurality of features derived from a value sampled from a sensor signal at a point in time, the method including: defining a selection variable indicative of the temporal variation of the sensor signals within a time window; defining a selection criterion for the selection variable; comparing a value of the selection variable to the selection criterion to select an input representation for a self organising map, the map having a plurality of input and output units, and deriving an input from the data samples within the time window in accordance with the selected input representation; and applying the input to a self organising map corresponding to the selected input representation and classifying the data record based on a winning output unit of the self organising map.