Nerve monitoring during electrosurgery

• US 8,989,855 B2
• Filed: 01/30/2009
• Issued: 03/24/2015
• Est. Priority Date: 01/30/2009
• Status: Active Grant

• Current Assignee: Medtronic Xomed Incorporated (Medtronic Plc)
• Original Assignee: Medtronic Xomed Incorporated (Medtronic Plc)
• Inventors: Murphy, John Murdock, Meyer, John A., Mendez, Adnorin Luis, McFarlin, Kevin Lee, Hacker, David C.
• Primary Examiner(s): EISEMAN, ADAM JARED
• Application Number:
  US12/363,154
• Publication Number:
  US 20100198099A1
• Time in Patent Office: 2,244 Days
• Field of Search: 600544-546
• US Class Current: 600/546
• CPC Class Codes: A61B 17/32 Surgical cutting instruments A61B18/042 takes precedence; suture cutters A61B17/0467; instruments for ligaturing or cutting A61B17/128; instruments for rupturing the amniotic membrane A61B17/4208; specially adapted knives for eye surgery A61F9/0133
• CPC Class Codes: A61B 5/316 Modalities, i.e. specific diagnostic methods
• CPC Class Codes: A61B 5/389 Electromyography [EMG]
• CPC Class Codes: A61B 5/7217 of noise originating from a therapeutic or surgical apparatus, e.g. from a pacemaker
• CPC Class Codes: A61B 5/7264 Classification of physiological signals or data, e.g. using neural networks, statistical classifiers, expert systems or fuzzy systems neural networks per se G06N3/00; expert systems per se G06N5/00

Abstract

A signal processing module includes an input module electronically coupled to a sensing probe of a nerve integrity monitoring system. The probe senses electrical signals from a patient during operation of an electrosurgical unit. The input module receives an input signal from the probe. An EMG detection module is coupled to the input module and is adapted to detect conditions in the input signal. The conditions are classified as a function of a level of electromyographic activity. An output module, coupled to the EMG detection module, provides an indication of electromyographic activity in the input signal based on the detected conditions.

Claims

1. A signal processing module for a nerve integrity monitoring system adapted to sense electrical signals from a patient during operation of an electrosurgical unit and/or surgical metal-to-metal artifacts, the signal processing module comprising:

an input module electrically coupled to a plurality of sensing probes and adapted to simultaneously receive a plurality of input signals from each of the plurality of sensing probes, a first input signal of the plurality of input signals indicative of electromyographic (EMG) activity of the patient and a second input signal of the plurality of input signals indicative of an artifact of metal-to-metal contact;

an EMG detection module coupled to the input module and adapted to detect conditions in the first input signal and classify the conditions as a function of a level of EMG activity received from the patient;

an artifact detection module adapted to detect the artifact in the second signal; and

an output module coupled to the EMG detection module and the artifact detection module and adapted to simultaneously provide a first output signal indicative of the detected conditions in the first input signal and provide a second output signal indicative of the artifact.

2. The signal processing module of claim 1 wherein the artifact is detected based on an estimate of power in the second input signal.

3. The signal processing module of claim 1 wherein the artifact is detected based on an estimate of the frequency content of the second input signal.

4. The signal processing module of claim 1 wherein the artifact detection module is adapted to selectively suppress the second input signal.

5. The signal processing module of claim 1 and further comprising a direct current filter module adapted to suppress noise in the second input signal having a frequency lower than a threshold.

6. The signal processing module of claim 1 wherein the EMG detection module is adapted to compare a level of EMG activity detected in the plurality of input signals to a threshold and provide an indication of the comparison to the output module.

7. The signal processing module of claim 6 wherein the EMG detection module estimates a level of energy in the plurality of input signals to determine if the EMG activity is greater than an energy level threshold.

8. The signal processing module of claim 7 wherein the EMG detection module calculates an autocovariance or autocorrelation of the plurality of input signals to detect the level of EMG activity.

9. The signal processing module of claim 7 wherein the EMG detection module calculates an autocovariance or autocorrelation of the plurality of input signals using multiple samples of the input signal.

10. The signal processing module of claim 8 where the EMG detection module uses a wavelet or sigmoid classification function of the plurality of input signals using multiple samples of the input signal.

11. The signal processing module of claim 1 and further comprising an EMG recovery module adapted to filter noise created by the electrosurgical unit and provide to the output module an indication of EMG activity in the patient.

12. The signal processing module of claim 11 wherein the EMG recovery module uses a reference probe to estimate the noise created by the electrosurgical unit.

13. A nerve integrity monitoring system for use during operation of an electrosurgical unit, comprising:

a plurality of sensing probes adapted to generate a plurality of input signals, the plurality of input signals including a first input signal indicative of electromyographic (EMG) activity of the patient and a second input signal indicative of an artifact of metal-to-metal contact;

an input module electrically coupled to the sensing probe and adapted to receive the plurality of input signals;

an EMG detection module coupled to the input module and adapted to detect conditions in the first input signal and classify the conditions as a function of a level of EMG activity received from the patient;

an artifact detection module adapted to detect the artifact in the second input signal; and

an output module, coupled to the EMG detection module and the artifact detection module, and adapted to simultaneously provide a first output signal indicative of the detected conditions in the first input signal and provide a second output signal indicative of the artifact.

14. The nerve integrity monitoring system of claim 13 wherein the artifact is detected based on an estimate of power in the input signal.

15. The nerve integrity monitoring system of claim 13 wherein the artifact is detected based on an estimate of frequency content of the input signal.

16. The nerve integrity monitoring system of claim 13 wherein the artifact detection module is adapted to selectively suppress the second input signal.

17. The nerve integrity monitoring system of claim 13 and further comprising a direct current filter module adapted to suppress noise in the input signal that has a frequency lower than a threshold.

18. The nerve integrity monitoring system of claim 13 wherein the EMG detection module is adapted to compare a level of EMG activity detected in the plurality of input signals to a threshold and provide an indication of the comparison to the output module.

19. The nerve integrity monitoring system of claim 18 wherein the EMG detection module estimates a level of energy in the plurality of input signals to determine if the EMG activity is greater than an energy level threshold.

20. The nerve integrity monitoring system of claim 19 wherein the EMG detection module calculates an autocovariance or autocorrelation of the plurality of input signals to detect the level of EMG activity.

21. The nerve integrity monitoring system of claim 20 wherein the EMG detection module calculates an autocovariance or autocorrelation of the plurality of input signals using multiple samples of the input signal.

22. The nerve integrity monitoring system of claim 13 and further comprising an EMG recovery module adapted to filter noise created by the electrosurgical unit and provide to the output module an indication of EMG activity in the patient.

23. The nerve integrity monitoring system of claim 22 wherein the EMG recovery module uses a reference probe to estimate the noise created by the electrosurgical unit.

24. The nerve integrity monitoring system of claim 23 wherein the probe includes a filter to filter a fundamental frequency of a noise signal generated by the electrosurgical unit.

25. The nerve integrity monitoring system of claim 23 wherein the EMG recovery module uses a reference probe to cancel or filter the noise created by the electrosurgical unit.