Signal quality monitoring and control for a medical device system

• US 7,146,211 B2
• Filed: 10/15/2003
• Issued: 12/05/2006
• Est. Priority Date: 10/15/2002
• Status: Active Grant

• Current Assignee: Medtronic Incorporated (Medtronic Plc)
• Original Assignee: Medtronic Incorporated (Medtronic Plc)
• Inventors: Frei, Mark G., Osorio, Ivan
• Primary Examiner(s): MANUEL, GEORGE C
• Application Number:
  US10/687,348
• Publication Number:
  US 20040138580A1
• Time in Patent Office: 1,147 Days
• Field of Search: 607 39- 46, 607/2, 128/901, 600/544, 600/545
• US Class Current: 607/2
• CPC Class Codes: A61B 5/316 Modalities, i.e. specific diagnostic methods
• CPC Class Codes: A61B 5/374 Detecting the frequency distribution of signals, e.g. detecting delta, theta, alpha, beta or gamma waves
• CPC Class Codes: A61B 5/4094 Diagnosing or monitoring seizure diseases, e.g. epilepsy
• CPC Class Codes: A61B 5/7203 for noise prevention, reduction or removal
• CPC Class Codes: A61B 5/7217 of noise originating from a therapeutic or surgical apparatus, e.g. from a pacemaker
• CPC Class Codes: A61B 5/7221 Determining signal validity, reliability or quality A61B5/7207 and A61B5/7217 take precedence
• CPC Class Codes: A61N 1/36031 using physiological parameters for adjustment
• CPC Class Codes: A61N 1/36064 Epilepsy
• CPC Class Codes: A61N 1/36082 Cognitive or psychiatric applications, e.g. dementia or Alzheimer's disease
• CPC Class Codes: A61N 1/36135 using physiological parameters
• CPC Class Codes: A61N 1/3702 Physiological parameters A61N1/365 takes precedence; evoked response A61N1/371
• CPC Class Codes: A61N 1/37229 Shape or location of the implanted or external antenna

Abstract

Method and apparatus for detecting possible interference in a neurological signal received from a monitoring element of a medical device system. The monitoring element monitors a condition or a symptom of a nervous system disorder being treated and provides a neurological signal to the medical device system for purposes of providing closed-loop feedback control. The system analyzes various parameters of the received signal by taking instantaneous measurements of data points in moving window and thereby determining whether the signal is of poor quality. If the signal is of determined poor quality, it is removed from consideration in the closed-loop feedback control system until it is determined that the signal quality has sufficiently been restored.

Claims

1. In a medical device system having a plurality of monitoring elements, a method for detecting poor signal quality comprising the steps of:

(a) receiving a neurological signal from one of the monitoring elements;

(b) processing the received signal to generate a plurality of data points for the signal in a moving time window;

(c) detecting that the received signal has poor signal quality by determining that an amount of the data points exhibiting poor signal quality within the moving time window has exceeded a predetermined threshold; and

(d) ignoring the received signal experiencing poor signal quality in signal processing.

2. The method of claim 1, further comprising the step of (e) delivering a notification that the signal from one of the monitoring elements is experiencing poor signal quality.

3. The method of claim 1, further comprising the step of (e) providing a substituted signal for the ignored signal experiencing poor signal quality.

4. The method of claim 1, wherein the step of detecting comprises the step of determining that percentage of the data points exhibiting poor signal quality within the moving time window has exceeded a predetermined threshold percentage.

5. The method of claim 1, wherein the step of ignoring comprises the step of ignoring the received signal experiencing poor signal quality in a closed-loop feedback control of a treatment therapy.

6. The method of claim 1, wherein the step of receiving comprises the step of receiving the neurological signal selected from the group consisting of an electrical signal, a chemical signal, a biological signal, a temperature signal, a pressure signal, a respiration signal, a heart rate signal, a ph-level signal, and a peripheral nerve signal.

7. The method of claim 1, wherein the step of receiving comprises the step of receiving the signal from the monitoring element selected from the group consisting of an electrode and a sensor.

8. The method of claim 1, wherein the step of processing comprises the step of identifying a value of at least one variable quantifying signal quality.

9. The method of claim 8, wherein the step of identifying a value comprises the step of determining a flat-line fraction signal to determine whether a signal is experiencing a flat-lining artifact.

10. The method of claim 8, wherein the step of identifying a value comprises the step of determining a flat-line fraction signal to determine whether a signal is experiencing amplifier saturation clipping.

11. The method of claim 8, wherein the step of identifying a data value comprises the step of determining an amplitude at a predetermined frequency to determine whether a signal is experiencing a mains artifact.

12. The method of claim 11, wherein the step of determining an amplitude comprises the step of determine an amplitude at about 60 Hz.

13. The method of claim 11, wherein the step of determining an amplitude comprises the step of determine an amplitude at about 50 Hz.

14. The method of claim 11, further comprising the step of (e) resuming consideration of the poor signal in the closed-loop feedback control once it is determined that the amount of the data points exhibiting poor signal quality within the time window has fallen below a second threshold.

15. The method of claim 1, wherein the step of detecting comprises the step of performing a time-averaging of the data points.

16. The method of claim 1, wherein the step of detecting comprises the step of performing a time-averaging of the data points using exponential forgetting.

17. The method of claim 1, wherein the step of receiving further comprises the step of receiving the neurological signal for purposes of providing closed-loop feedback control of a treatment therapy.

18. The method of claim 1, wherein step (c) comprises:

(i) determining a signal power to noise power ratio.

19. The method of claim 1, wherein step (c) comprises:

(i) determining a fraction of a foreground window that contains noisy data.

20. The method of claim of claim 1, further comprising:

(e) detecting a movement artifact with at least one accelerometer; and

(f) utilizing an output of the at least one accelerometer to reduce the movement artifact.

21. A medical device system for managing a nervous system disorder and capable of detecting poor signal quality comprising in combination:

(a) at least one monitoring element, each generating a neurological signal of a sensed neurological condition; and

(b) computer executable instructions for performing the steps of (i) generating a plurality of instantaneous data points of the received neurological signal for a moving time window;

(ii) detecting that the received signal has poor signal quality by determining that an amount of the data points exhibiting poor signal quality within the time window has exceeded a predetermined threshold; and

(iii) ignoring the received signal experiencing poor signal quality in signal processing.

22. The medical device system of claim 21, wherein computer executable instructions further performs the step (iv) delivering a notification that the signal from one of the monitoring elements is experiencing poor signal quality.

23. The medical device system of claim 21, wherein computer executable instructions further performs the step (iv) providing a substituted signal for the ignored signal experiencing poor signal quality.

24. The medical device system of claim 21, wherein the step of detecting comprises the step of determining that percentage of the data points exhibiting poor signal quality within the moving time window has exceeded a predetermined threshold percentage.

25. The medical device system of claim 21, wherein the step of ignoring comprises the step of ignoring the received signal experiencing poor signal quality in a closed-loop feedback control of a treatment therapy.

26. The medical device system of claim 21, wherein the nervous system disorder is selected from the group consisting of a disorder of a central nervous system, a disorder of a peripheral nervous system, and mental health disorder, and psychiatric disorder.

27. The medical device system of claim 21, wherein the nervous system disorder is selected from the group consisting of epilepsy, Parkinson'"'"'s disease, essential tremor, dystonia, multiple sclerosis (MS), anxiety, a mood disorder, a sleep disorder, obesity, and anorexia.

28. The medical device system of claim 21, wherein the treatment therapy is selected from the group consisting of electrical stimulation, magnetic stimulation, drug infusion, and brain cooling.

29. The medical device system of claim 21, wherein the neurological signal is selected from the group consisting of a electrical signal, a chemical signal, a biological signal, a temperature signal, a pressure signal, a respiration signal, a heart rate signal, a ph-level signal, and a peripheral nerve signal.

30. The medical device system of claim 21, wherein the monitoring element is selected from the group consisting of an electrode and a sensor.

31. The medical device system of claim 21, wherein the medical device system is selected from the group consisting of an external system, a hybrid system, and an implanted system.

32. The medical device system of claim 21, wherein the computer executable instructions are further configured to perform the step of identifying a data value of at least one parameter.

33. The medical device system of claim 21, wherein the computer executable instructions are further configured to perform the step of identifying a data value by determining a clip fraction signal to determine whether a signal is experiencing a clipping artifact.

34. The medical device system of claim 21, wherein the computer executable instructions are further configured to perform the step of identifying a data value by determining an amplitude at a predetermined frequency to determine whether a signal is experiencing a mains artifact.

35. The medical device system of claim 34, wherein the step of determining an amplitude comprises the step of determine an amplitude at about 60 Hz.

36. The medical device system of claim 21, wherein the step of determining an amplitude comprises the step of determine an amplitude at about 50 Hz.

37. The medical device system of claim 21, wherein the computer executable instructions are further configured to perform the step of (iv) resuming consideration of the poor signal in the closed-loop feedback control once it is determined that the amount of the data points exhibiting poor signal quality within the time window has fallen below a second threshold.