DETECTING A BIOMETRIC EVENT IN A NOISY SIGNAL

1 . A method of detecting a biometric event in an input signal, the method comprising:

performing principal component analysis PCA on samples of a plurality of model signals to generate a transformation matrix having more informative components and less informative components, each of the model signals comprising a known signal which includes the event to be detected;

reducing a dimensionality of the transformation matrix by discarding one or more of the more informative components;

transforming a plurality of samples of the input signal using the reduced dimensionality transformation matrix;

determining a probability that the event is present in the plurality of samples of the input signal, by calculating a predefined probability function for the transformed samples; and

determining that the input signal includes the event if the probability is higher than a threshold.

2 . The method of claim 1 , wherein the plurality of samples of the input signal are selected by applying a time window to the input signal, the time window having the same duration as the plurality of model signals, the method further comprising:

moving the window in time through the input signal and recalculating the probability function for each one of a plurality of positions of the window, to determine whether the event is present at different times in the input signal.

3 . The method of claim 1 , wherein the plurality of model signals are each arranged to have a peak amplitude at the same position within the signal, and in response to a determination that the input signal includes the event the method further comprises:

identifying a time index of one of the plurality of samples of the input signal at an equivalent position to the position of the peak amplitude within the model signals; and

recording the time index of the identified sample for the detected event.

4 . The method of claim 1 , wherein the biometric event comprises one of a heartbeat, a variation in a heartbeat and a user's activity.

5 . The method of claim 1 , wherein the biometric event to be detected is a heartbeat, and the plurality of model signals comprise a plurality of known heartbeat signals.

6 . The method of claim 1 , wherein determining that the input signal includes a heartbeat comprises:

identifying a probable heartbeat, in response to the probability being higher than the threshold;

determining a time period between the probable heartbeat and an immediately preceding heartbeat in the input signal; and

determining whether the probable heartbeat is an actual heartbeat based on a comparison between the determined time period and a known pulse rate.

7 . The method of claim 6 , wherein determining whether the probable heartbeat is an actual heartbeat comprises:

determining an expected interval between heartbeats based on the known pulse rate, and

determining that the probable heartbeat is not an actual heartbeat if the determined time period differs by more than a threshold amount from the expected interval.

8 . The method of claim 6 or 7 , wherein the threshold amount is ±30% of the expected interval.

9 . The method of claim 1 , comprising a further step prior to determining the probability, of setting the probability of the biometric event occurring to zero for a predefined time following each detection of a biometric event.

10 . The method of claim 6 , wherein determining whether the probable heartbeat is an actual heartbeat comprises:

determining that the probable heartbeat is not an actual heartbeat if the determined time period is less than a predefined time period.

11 . The method of claim 9 , wherein the predefined time period is set to less than or equal to 200 milliseconds.

12 . The method of claim 1 , further comprising:

identifying a subject from which the input signal was obtained by comparing the transformation matrix to a plurality of stored transformation matrices, each associated with a particular subject.

13 . The method of claim 1 , further comprising:

validating the input signal by determining the standard deviation of the standard deviation of the input signal,

wherein the input signal is rejected if the standard deviation of the standard deviation is higher than a preset threshold.

14 . (canceled)

15 . Apparatus for detecting a biometric event in an input signal, the apparatus comprising:

a principal component analysis PCA unit configured to perform PCA on samples of a plurality of model signals to generate a transformation matrix having more informative components and less informative components, each of the model signals comprising a known signal which includes the biometric event to be detected, and to reduce a dimensionality of the transformation matrix by discarding one or more of the more informative components;

a sample transformation unit configured to transform a plurality of samples of the input signal using the reduced dimensionality transformation matrix;

a probability determining unit configured to determine a probability that the biometric event is present in the plurality of samples of the input signal, by calculating a predefined probability function for the transformed samples; and

a biometric event detecting unit configured to determine that the input signal includes the biometric event if the probability is higher than a threshold.

16 . Apparatus for detecting a biometric event in an input signal, the apparatus comprising:

a processing unit comprising one or more processors; and

memory arranged to store computer program instructions which, when executed by the processing unit, cause the apparatus to:

perform principal component analysis PCA on samples of a plurality of model signals to generate a transformation matrix having more informative components and less informative components, each of the model signals comprising a known signal which includes the biometric event to be detected;

reduce a dimensionality of the transformation matrix by discarding one or more of the more informative components;

transform a plurality of samples of the input signal using the reduced dimensionality transformation matrix;

determine a probability that the biometric event is present in the plurality of samples of the input signal, by calculating a predefined probability function for the transformed samples; and

determining that the input signal includes the biometric event if the probability is higher than a threshold.

17 . The apparatus of claim 15 , wherein the biometric event to be detected is a heartbeat and the plurality of model signals comprise a plurality of known heartbeat signals, the apparatus further comprising:

a sensor configured to obtain the input signal by recording values of a physiological parameter over time.

18 . The apparatus of claim 17 , wherein the sensor is a photoplethysmography sensor.

19 . The apparatus of claim 16 , wherein the biometric event to be detected is a heartbeat and the plurality of model signals comprise a plurality of known heartbeat signals, the apparatus further comprising:

a sensor configured to obtain the input signal by recording values of a physiological parameter over time.