Signal quality monitoring and control for a medical device system

• US 7,174,206 B2
• Filed: 10/15/2003
• Issued: 02/06/2007
• Est. Priority Date: 10/15/2002
• Status: Active Grant

• Current Assignee: Medtronic Incorporated (Medtronic Plc)
• Original Assignee: Medtronic Incorporated (Medtronic Plc)
• Inventors: Werder, Jonathan C., Frei, Mark G., Osorio, Ivan, Carlson, David L.
• Primary Examiner(s): Marmar, II; Charles A
• Assistant Examiner(s): Natnithithadha; Navin
• Application Number:
  US10/687,557
• Publication Number:
  US 20040138581A1
• Time in Patent Office: 1,210 Days
• Field of Search: 600/544, 600/545, 600/300, 600/301, 600/481, 600/483, 600/484, 600/485, 600/508, 600/509, 600/529, 600/534, 600/538, 600/549, 600500-503, 600/347, 600/365, 600/309, 600/345
• US Class Current: 600/544
• 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 5/7221 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 1/3702 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. A method for detecting poor signal quality and for phase shifting neurological signals received from the plurality of monitoring elements, comprising the steps of:

(a) receiving a first neurological signal from a first monitoring element and a second neurological signal from a second monitoring element;

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

(c) detecting whether the first neurological 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;

(d) if the first neurological signal has poor signal quality, ignoring the first neurological signal experiencing poor signal quality in signal processing; and

(e) if the first neurological signal does not have poor signal quality, performing (i) sampling the first and second neurological signals at different time instances resulting in a time shift between the first and second neurological signal samples; and

(ii) time shifting signal samples of the second neurological signal to correct for the time shift so the second neurological signal is synchronized with the first neurological signal.

2. The method of claim 1, further comprising the step of (f) 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 (f) 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 first 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 first neurological signal from the first 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 1, wherein the step of detecting comprises the step of performing a time-averaging of the data points.

15. 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.

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

17. 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.

18. The method of claim 8, wherein the step of identifying a value comprises the step of determining a clip fraction signal to determine whether a signal is experiencing a clipping artifact.