Systems, apparatuses and methods for adaptive noise reduction

1. An apparatus, comprising:

a sensor module configured for receiving sensed information indicative of a sensed signal, the sensed signal including a source signal component and a source noise component;

a reference module configured for receiving reference information indicative of a reference signal, the reference signal including a reference noise component, the reference noise component associated with the source noise component;

a filter module configured as a fixed lag Kalman smoother, the filter module configured for adaptively filtering the reference signal to generate an estimate of the source noise component, including:

setting the observation data to be the same as the source signal;

setting the observation matrix to be the same as the reference signal; and

setting the oblivion coefficient to be about one;

a processing module configured for calculating an output signal associated with the source signal component, the output signal based on the sensed signal and the estimate of the source noise component; and

an interface module configured for transmitting an indication of the output signal, the filter module further configured for:

based on the output signal, tuning at least one of the following aspects of the Kalman smoother:

the state noise covariance;

the oblivion coefficient; and

an order of the Kalman smoother; and

introducing a delay of half the order of the Kalman smoother between the source signal and the output signal, and between the reference signal and the output signal.

2. The apparatus of claim 1 , wherein the sensed information includes sensed photoplethysmographic information, further comprising a photoplethysmographic sensor configured for capturing the photoplethysmographic information.

3. The apparatus of claim 1 , wherein the reference information includes accelerometer information, further comprising an accelerometer configured for capturing the reference information.

4. The apparatus of claim 1 , the filter module configured to tune the Kalman smoother by modifying the state noise covariance, the filter module configured to modify the state noise covariance by:

when at least one of (a) the sensed signal exceeds a sensed signal threshold, or (b) the reference signal exceeds a reference signal threshold, incrementing the state noise covariance up to a state noise covariance threshold based on a state noise covariance increment; and

when (c) the sensed signal is below the sensed signal threshold, and (d) the reference signal is below the reference signal threshold, decrementing the state noise covariance based on the state noise covariance increment.

5. The apparatus of claim 4 , the interface module further configured for modifying at least one of the sensed signal threshold, the reference signal threshold, the state noise covariance threshold, or the state noise covariance increment.

6. The apparatus of claim 1 , the filter module configured to tune the Kalman smoother by modifying the oblivion coefficient.

7. The apparatus of claim 1 , the filter module configured to tune the Kalman smoother by modifying the order of the Kalman smoother.

8. The apparatus of claim 1 , the processing module configured to calculate the output signal by subtracting the estimate of the source noise component from the sensed signal to generate the output signal.

9. The apparatus of claim 1 , further comprising:

a database storing the sensed information; and

a database module operably coupled to the database, the database module configured to communicating the sensed information from the database to the sensor module.

10. The apparatus of claim 1 , further comprising:

a database storing the sensed information and the reference information; and

a database module operably coupled to the database, the database module configured for communicating the sensed information from the database to the sensor module, the database module further configured for communicating the reference information to the reference module.

11. A method, comprising:

receiving, at a processor, sensed information indicative of a sensed signal, the sensed signal including a source signal component and a source noise component;

receiving, at the processor, reference information indicative of a reference signal, the reference signal including a reference noise component, the reference noise component associated with the source noise component;

adaptively filtering the reference signal to generate an estimate of the source noise component using a fixed lag Kalman smoother, including:

setting the observation data to be the same as the source signal;

setting the observation matrix to be the same as the reference signal; and

setting the oblivion coefficient to be about one;

calculating an output signal associated with the source signal component, the output signal based on the sensed signal and the estimate of the source noise component;

transmitting an indication of the output signal; and

based on the output signal, tuning at least one of the following aspects of the Kalman smoother:

the state noise covariance;

the oblivion coefficient; or

an order of the Kalman smoother; and

introducing a delay of half the order of the Kalman smoother between the source signal and the output signal, and between the reference signal and the output signal.

12. The method of claim 11 , wherein the sensed information includes photoplethysmographic information, further comprising sensing the photoplethysmographic information via a photoplethysmographic sensor.

13. The method of claim 11 , the tuning the Kalman smoother including modifying the state noise covariance, further comprising:

when at least one of (a) the sensed signal exceeds a sensed signal threshold, or (b) the reference signal exceeds a reference signal threshold, incrementing the state noise covariance up to a state noise covariance threshold based on a state noise covariance increment; and

when (c) the sensed signal is below the sensed signal threshold, and (d) the reference signal is below the reference signal threshold, decrementing the state noise covariance based on the state noise covariance increment.

14. The method of claim 13 , further comprising modifying at least one of the sensed signal threshold, the reference signal threshold, the state noise covariance threshold, or the state noise covariance increment.

15. The method of claim 11 , the tuning the Kalman smoother including modifying the oblivion coefficient.

16. The method of claim 11 , the tuning the Kalman smoother including modifying the order of the Kalman smoother.

17. The method of claim 11 , wherein the order of the Kalman smoother is an even number.

18. The method of claim 11 , the calculating the output signal including subtracting the estimate of the source noise component from the sensed signal to generate the output signal.