Real-time periodic artifact extraction from a physiological signal

1. A physiological activity detection system, comprising:

a signal acquisition module configured for non-invasively acquiring a signal from an anatomical structure of a user, the acquired signal having a physiological-encoded component and a periodic artifact component that dominates the physiological-encoded component;

a phase-locked loop (PLL) component configured for estimating a phase of the periodic artifact component of the acquired signal, and generating a periodic reference signal having a phase representative of the estimated phase of the periodic artifact component of the acquired signal; and

an artifact cancellation component configured for generating an estimated periodic artifact component by scaling and offsetting the periodic reference signal to the periodic artifact component in the acquired signal, and filtering the periodic artifact component from the acquired signal based on the estimated periodic component, thereby yielding a reduced-artifact signal.

2. The physiological activity detection system of claim 1 , wherein the anatomical structure of the user is a brain, and wherein the physiological-encoded component is a neurological-encoded component.

3. The physiological activity detection system of claim 2 , wherein the periodic artifact component is a cardiac artifact component.

4. The physiological activity detection system of claim 2 , wherein the acquired signal comprises signal light.

5. The physiological activity detection system of claim 4 , wherein the signal acquisition module is configured for non-invasively acquiring the signal light from the brain of the user via functional near-infrared spectroscopy (fNIRS).

6. The physiological activity detection system of claim 1 , wherein the periodic reference signal varies in accordance with a sine wave.

7. The physiological activity detection system of claim 1 , wherein the signal acquisition module is configured for digitizing the acquired signal into acquired data, and wherein the PLL component is configured for estimating the phase of the periodic artifact component in the acquired data, and generating periodic reference data having a phase representative of the estimated phase of the periodic artifact component in the acquired data.

8. The physiological activity detection system of claim 7 , wherein the acquired data comprises a time-series of data samples, and the PLL component is configured for respectively estimating phases of the periodic artifact component in the acquired data samples, and generating periodic reference data samples respectively having phases representative of the estimated phases of the periodic artifact component in the acquired data samples.

9. The physiological activity detection system of claim 1 , wherein the PLL component comprises:

a phase comparator; and

a voltage-controlled oscillator (VCO) arranged in a closed feedback loop with the phase comparator;

wherein the phase comparator is configured for computing a difference between the phase of the periodic artifact component of the acquired signal and the phase of the periodic reference signal, thereby respectively generating a phase error signal; and

wherein the VCO is configured for generating the periodic reference signal, and varying the frequency of the periodic reference signal in accordance with the phase error signal, thereby varying the phase of the periodic reference signal.

10. The physiological activity detection system of claim 1 , further comprising a frequency computation component configured for computing a frequency of the periodic artifact component.

11. The physiological activity detection system of claim 10 , wherein the periodic artifact component is a cardiac artifact component, the frequency computation component is a heart rate (HR) computation component, and the computed frequency of the cardiac artifact component is a heart rate (HR) of the user.

12. The physiological activity detection system of claim 1 , wherein the artifact cancellation component is configured for filtering the periodic artifact component from the acquired signal by subtracting the estimated periodic artifact component from the acquired signal, thereby yielding the reduced-artifact signal.

13. The physiological activity detection system of claim 1 , wherein the physiological-encoded component dominates the periodic artifact component in the reduced-artifact signal.

14. The physiological activity detection system of claim 1 , wherein the periodic artifact component is substantially eliminated from the reduced-artifact signal.

15. The physiological activity detection system of claim 1 , further comprising a signal processor configured for determining an existence of physiological activity in the user based on the reduced-artifact signal.

16. The physiological activity detection system of claim 15 , wherein the anatomical structure of the user is a brain, the physiological-encoded component is neurological-encoded component, and the physiological activity is neural activity.

17. The physiological activity detection system of claim 16 , wherein the neural activity is within cortical region of the brain of the user, wherein the periodic artifact component is a cardiac artifact component, and the physiological activity detection system further comprises a heart rate (HR) computation component configured for computing a heart rate (HR) of the user based on the phase of the periodic reference signal, wherein the signal processor is configured for determining an existence of neural activity in subcortical region of the brain of the user based on the computed HR of the user.

18. The physiological activity detection system of claim 1 , wherein the artifact cancellation component comprises:

a first signal comparator;

an adaptive filter arranged in a feedback loop with the first signal comparator; and

a second signal comparator;

wherein the first signal comparator is configured for computing a difference between a magnitude of the estimated periodic artifact component and a magnitude of the periodic reference signal, thereby generating a magnitude error signal;

wherein the adaptive filter is configured for varying a transfer function in response to the magnitude error signal, and filtering the acquired signal in accordance with the varied transfer function, thereby generating the estimated periodic artifact component;

wherein the second signal comparator is configured for computing the difference between a magnitude of the acquired signal and a magnitude of the estimated periodic artifact component to yield the reduced-artifact signal.

19. The physiological activity detection system of claim 1 , wherein the artifact cancellation component comprises:

a signal comparator;

an adaptive filter arranged in a feedback loop with the first signal comparator;

wherein the signal comparator is configured for computing a difference between a magnitude of the acquired signal and a magnitude of the estimated periodic artifact component, thereby generating a magnitude error signal representative of the reduced-artifact signal;

wherein the adaptive filter is configured for varying a transfer function in response to the magnitude error signal, and filtering the periodic reference signal in accordance with the varied transfer function, thereby generating the estimated periodic artifact component.

20. The physiological activity detection system of claim 1 , wherein the artifact cancellation component is configured for utilizing a recursive least squares (RLS) algorithm to map the periodic reference signal to the acquired signal by varying a transfer function.

21. A method of detecting physiological activity in an anatomical structure of a person, comprising:

non-invasively acquiring a signal from the anatomical structure of the person, the acquired signal having a physiological-encoded component and a periodic artifact component that dominates the physiological-encoded component; and

computing a difference between an actual phase of the periodic artifact component of the acquired signal and an estimated phase of the periodic artifact component of the acquired signal, thereby generating a phase error signal; and

updating the estimated phase of the periodic artifact component of the acquired signal based on the phase error signal;

repeating the phase difference computation and estimated phase updating steps;

generating a periodic reference signal having a phase equal to the estimated phase of the periodic artifact component of the acquired signal;

generating an estimated periodic artifact component by scaling and offsetting the periodic reference signal to the periodic artifact component in the acquired signal; and

removing at least a portion of the periodic artifact component from the acquired signal based on the estimated periodic artifact component, thereby yielding a reduced-artifact signal.

22. The method of claim 21 , wherein the anatomical structure of the user is a brain of the user, and wherein the physiological-encoded component is a neurological-encoded component.

23. The method of claim 22 , wherein the periodic artifact component is a cardiac artifact component.

24. The method of claim 22 , wherein the acquired signal comprises signal light.

25. The method of claim 24 , wherein signal light is non-invasively acquired from the brain of the user via functional near-infrared spectroscopy (fNIRS).

26. The method of claim 21 , wherein the periodic reference signal varies in accordance with a sine wave.

27. The method of claim 21 , further comprising digitizing the acquired signal into acquired data, wherein the periodic reference signal comprises periodic reference data.

28. The method of claim 27 , wherein the acquired data comprises a time-series of acquired data samples, and the periodic reference data comprises a time-series of periodic reference data samples.

29. The method of claim 21 , wherein the phase error generation step and estimated phase updating step comprises:

computing a difference between the phase of the periodic artifact component of the acquired signal and the phase of the periodic reference signal, thereby respectively generating the phase error signal; and

varying the frequency of the periodic reference signal in accordance with the phase error signal, thereby varying the phase of the periodic reference signal.

30. The method of claim 21 , further comprising deriving a frequency of the periodic artifact component from the phase of the periodic reference signal.

31. The method of claim 30 , wherein the periodic artifact component is a cardiac artifact component, and the derived frequency of the periodic artifact component is a heart rate (HR) of the user.

32. The method of claim 21 , wherein removing the at least a portion of the periodic artifact component from the acquired signal comprises subtracting the estimate cardiac component from the acquired signal, thereby yielding the reduced-artifact signal.

33. The method of claim 21 , wherein the physiological-encoded component dominates the periodic artifact component in the reduced-artifact signal.

34. The method of claim 21 , wherein the periodic artifact component is substantially eliminated from the reduced-artifact signal.

35. The method of claim 21 , further comprising determining an existence of physiological activity in the user based on the reduced-artifact signal.

36. The method of claim 35 , wherein the anatomical structure of the user is a brain of the user, the physiological-encoded component is neurological-encoded component, and the physiological activity is neural activity.

37. The method of claim 36 , wherein the neural activity is within cortical region of the brain of the user, wherein the periodic artifact component is a cardiac artifact component, and the method further comprises computing a heart rate (HR) of the user based on the phase of the periodic reference signal, and determining an existence of neural activity in subcortical region of the brain of the user based on the computed HR of the user.

38. The method of claim 21 , wherein removing at least a portion of the periodic artifact component from the acquired signal comprises:

computing a difference between a magnitude of an estimated periodic artifact component and a magnitude of the periodic reference signal, thereby generating a magnitude error signal;

varying a transfer function in response to the magnitude error signal;

filtering the acquired signal in accordance with the varied transfer function, thereby generating the estimated periodic artifact component; and

computing the difference between a magnitude of the acquired signal and a magnitude of the estimated periodic artifact component to yield the reduced-artifact signal.

39. The method of claim 21 , wherein removing at least a portion of the periodic artifact component from the acquired signal comprises:

computing a difference between a magnitude of the acquired signal and a magnitude of an estimated periodic artifact component, thereby generating a magnitude error signal representative of the reduced-artifact signal;

varying a transfer function in response to the magnitude error signal; and

filtering the periodic reference signal in accordance with the varied transfer function, thereby generating the estimated periodic artifact component.

40. The method of claim 21 , wherein removing the at least portion of the periodic artifact component from the acquired signal comprises utilizing a recursive least squares (RLS) algorithm to map the periodic reference signal to the acquired signal by varying a transfer function.