NEURAL EVENT DETECTION

• US 20150051506A1
• Filed: 08/13/2013
• Published: 02/19/2015
• Est. Priority Date: 08/13/2013
• Status: Active Grant

• Current Assignee: Innovative Surgical Solutions, LLC (Johnson & Johnson)
• Original Assignee: Innovative Surgical Solutions, LLC (Johnson & Johnson)
• Inventors: Wybo, Christopher, Scarfe, Darren, Shah, Aashish
• Granted Patent: US 10,478,096 B2
• Time in Patent Office: Days
• US Class Current: 600/554
• CPC Class Codes: A61B 2505/05 Surgical care
• CPC Class Codes: A61B 2562/0204 Acoustic sensors
• CPC Class Codes: A61B 2562/0219 Inertial sensors, e.g. accelerometers, gyroscopes, tilt switches
• CPC Class Codes: A61B 2562/0261 Strain gauges
• CPC Class Codes: A61B 5/1106 to assess neuromuscular blockade, e.g. to estimate depth of anaesthesia
• CPC Class Codes: A61B 5/1109 of wounds, e.g. at the operation site

Abstract

A neural monitoring system for detecting an artificially-induced mechanical muscle response to an electrical stimulus at a stimulation frequency includes a mechanical sensor and a processor in communication with the mechanical sensor. The mechanical sensor is configured to be placed in mechanical communication with the muscle and to generate a mechanomyography output signal corresponding to a sensed mechanical movement of the muscle. The processor is configured to receive the mechanomyography output signal from the mechanical sensor and determine a frequency component of the mechanomyography output signal that has a peak magnitude and to detect the occurrence of an artificially-induced mechanical muscle response therefrom.

Claims

1. A neural monitoring system for detecting an artificially-induced mechanical response of a muscle to an electrical stimulus provided within an intracorporeal treatment area of a human subject at a stimulation frequency, the intracorporeal treatment area including a nerve that innervates the muscle, the neural monitoring system comprising:

a non-invasive mechanical sensor configured to be placed in mechanical communication with the muscle and to generate a mechanomyography output signal corresponding to a sensed mechanical movement of the muscle; and

a processor in communication with the mechanical sensor and configured to;

receive the mechanomyography output signal from the mechanical sensor;

determine a frequency component of the mechanomyography output signal, wherein the frequency component has a peak magnitude relative to adjacent frequencies; and

provide an indication to a user if the determined frequency component is either equal to, or an integer multiple of the stimulation frequency.

2. The neural monitoring system of claim 1, wherein the processor is further configured to attenuate frequency content of the mechanomyography output signal that is above a cutoff frequency.

3. The neural monitoring system of claim 2, wherein the cutoff frequency is in the range of about 20 Hz to about 50 Hz.

4. The neural monitoring system of claim 1, wherein the processor is configured to determine a frequency component of the mechanomyography output signal that has a peak magnitude by:

converting the received mechanomyography output signal from a time domain to a frequency domain, wherein the frequency domain is characterized by a plurality of discrete frequencies, each having a corresponding magnitude; and

identifying the frequency component from the plurality of discrete frequencies that corresponds to a magnitude peak.

5. The neural monitoring system of claim 1, wherein the frequency component is within the range of greater than 0 Hz to about 20 Hz.

6. The neural monitoring system of claim 1, wherein the mechanical sensor includes an accelerometer, a microphone, a strain gauge, or a piezoelectric device.

7. The neural monitoring system of claim 1, wherein the frequency component is a fundamental frequency of the mechanomyography output signal.

8. The neural monitoring system of claim 1, further comprising an elongate medical instrument that is configured to selectively provide the electrical stimulus within the intracorporeal treatment area of the subject at the stimulation frequency.

9. The neural monitoring system of claim 8, wherein the electrical stimulus includes a periodic pulse having a pulse width between about 30 μ

s and about 500 μ

s.

10. A neural monitoring system for detecting an artificially-induced mechanical response of a muscle to an electrical stimulus provided within an intracorporeal treatment area of a human subject at a stimulation frequency, the intracorporeal treatment area including a nerve that innervates the muscle, the neural monitoring system comprising:

a non-invasive mechanical sensor configured to be placed in mechanical communication with the muscle and to generate a mechanomyography output signal corresponding to a sensed mechanical movement of the muscle; and

a processor in communication with the mechanical sensor and configured to;

receive the mechanomyography output signal from the mechanical sensor;

determine a fundamental frequency of the mechanomyography output signal;

provide an indication to a user if the determined fundamental frequency is either equal to, or an integer multiple of the stimulation frequency.

11. The neural monitoring system of claim 10, wherein the processor is further configured to attenuate frequency content of the mechanomyography output signal that is above a cutoff frequency.

12. The neural monitoring system of claim 11, wherein the cutoff frequency is in the range of about 20 Hz to about 50 Hz.

13. The neural monitoring system of claim 10, wherein the processor is configured to determine a fundamental frequency of the mechanomyography output signal by:

converting the received mechanomyography output signal from a time domain to a frequency domain, wherein the frequency domain is characterized by a plurality of discrete frequencies, each having a corresponding magnitude;

identifying a subset of the plurality of discrete frequencies wherein each discrete frequency belonging to the subset corresponds to a respective magnitude peak; and

determining a greatest common factor of the frequencies belonging to the subset.

14. The neural monitoring system of claim 10, wherein the fundamental frequency is within the range of greater than 0 Hz to about 10 Hz.

15. The neural monitoring system of claim 10, wherein the mechanical sensor includes an accelerometer, a microphone, a strain gauge, or a piezoelectric device.

16. The neural monitoring system of claim 10, further comprising an elongate medical instrument that is configured to selectively provide the electrical stimulus within the intracorporeal treatment area of the subject at the stimulation frequency.

17. The neural monitoring system of claim 16, wherein the electrical stimulus includes a periodic pulse having a pulse width between about 30 μ

s and about 500 μ

s.

18. A neural monitoring system for detecting an artificially-induced mechanical response of a muscle to an electrical stimulus provided within an intracorporeal treatment area of a human subject at a stimulation frequency, the intracorporeal treatment area including a nerve that innervates the muscle, the neural monitoring system comprising:

a non-invasive mechanical sensor configured to be placed in mechanical communication with the muscle and to generate a mechanomyography output signal corresponding to a sensed mechanical movement of the muscle; and

a processor in communication with the mechanical sensor and configured to;

receive the mechanomyography output signal from the mechanical sensor;

determine a frequency component of the mechanomyography output signal, wherein the frequency component has a peak magnitude relative to adjacent frequencies; and

provide an indication to a user if the determined frequency component is either equal to, or an integer multiple of the stimulation frequency, and either;

the determined frequency component is within the range of greater than 0 Hz to about 20 Hz;

or

the peak magnitude is above an established noise floor by a threshold amount.

19. The neural monitoring system of claim 18, wherein the mechanical sensor includes an accelerometer, a microphone, a strain gauge, or a piezoelectric device.