The present invention relates to a method of associating at least one state in a plurality of states to a new value output by a drifting sensor, the method comprising: /a/ receiving a signal from the sensor, said signal comprising a plurality of values; /b/clustering the values of said signal into a number of clusters equal to the number of the plurality of states, each cluster being associated with a respective state in the plurality of states; /c/ for the new value of the signal, associating at least one state in said plurality of states or a probability rating representing the probability to be associated with one state in said plurality of states for said new value of the signal, the associated state or the associated probability rating being determined based on at least distances (dH, dL) of said new value of the signal to respective clusters.
Please help me write a proper abstract based on the patent claims. CLAIM: 1. A method of associating at least one state in a plurality of states to a new value output by a drifting sensor, the method comprising: /a/ receiving a signal from the sensor, said signal comprising a plurality of values; /b/ clustering the values of said signal into a number of clusters equal to the number of the plurality of states, each cluster being associated with a respective state in the plurality of states; /c/ for the new value of the signal, associating at least one state in said plurality of states or a probability rating representing the probability to be associated with one state in said plurality of states for said new value of the signal, the associated state or the associated probability rating being determined based on at least distances (dH, dL) of said new value of the signal to respective clusters. 2. The method according to claim 1, wherein, prior to step /b/, the signal is compressed into a compressed signal having compressed values, the compressed values of the compressed signal being used as the values of the signal in step /b/, and wherein said compressing comprises: /d/ initializing an average value to a first value of the signal, /e/ for each second value in a plurality of second values of the signal output after the first value from the sensor: /θ1/ if a distance (ΔV) between the second value and the average value is greater than a predetermined threshold, storing the average value as a compressed value into a memory and setting the average value to the second value, /e2/ otherwise, updating the average value to a new average value as a function of the second value and the average value. 3. The method according to claim 2, wherein, in the step /e/ and prior to the test /e2/, another test is executed: /e3/ if a number of second values used to determine the average value is greater than a predetermined threshold, setting the average value to the second value. 4. The method according to claim 3, wherein, in test /e3/, storage of the average value into a memory is performed prior to setting the average value to the second value. 5. The method according to claim 2, wherein, in step /e/, the average value is stored along a number of second values used for the determination of the average value after a previous storage of the average value. 6. The method according to claim 2, wherein each of the second value is associated with a respective time, and wherein in step /e/, the average value is stored along a minimum time among all the times associated with a second value used for the determination of the average value after a previous storage of the average value. 7. The method according to claim 1, wherein the clustering of step /b/ comprises the use of a k-means algorithm. 8. The method according to claim 1, wherein the clustering of step /b/ comprises the use of an unsupervised clustering algorithm. 9. The method according to claim 2, wherein the clustering of step /b/ comprises a weighting of the values of the signal by a number of second values used for the determination of the average value after a previous storage of the average value. 10. The method according to claim 1, wherein step /c/ comprises the use of a forward algorithm. 11. The method according to claim 1, wherein step /c/ comprises the use of a decision tree. 12. A non-transitory computer readable storage medium, having stored thereon a computer program comprising program instructions for associating at least one state in a plurality of states to a new value output by a drifting sensor, the computer program being loadable into a data-processing unit and adapted to cause the data-processing unit to carry out, when the computer program is run by the data-processing device: /a/ receiving a signal from the sensor, said signal comprising a plurality of values; /b/ clustering the values of said signal into a number of clusters equal to the number of the plurality of states, each cluster being associated with a respective state in the plurality of states; /c/ for the new value of the signal, associating at least one state in said plurality of states or a probability rating representing the probability to be associated with one state in said plurality of states for said new value of the signal, the associated state or the associated probability rating being determined based on at least distances of said new value of the signal to respective clusters. 13. A device comprising: a sensor for outputting a signal, said signal comprising a plurality of values; a memory; a circuit for clustering the values of said signal into a number of clusters equal to the number of a plurality of states, each cluster being associated with a respective state in the plurality of states; a circuit for associating at least one state in said plurality of states or a probability rating representing the probability to be associated with one state in said plurality of states for a new value of the signal, the associated state or the associated probability rating being determined based on at least distances of said new value of the signal to respective clusters.