Pain management based on muscle tension measurements

• US 10,729,905 B2
• Filed: 01/11/2018
• Issued: 08/04/2020
• Est. Priority Date: 01/11/2017
• Status: Active Grant

• Current Assignee: Boston Scientific Neuromodulation Corporation (Boston Scientific Corporation)
• Original Assignee: Boston Scientific Neuromodulation Corporation (Boston Scientific Corporation)
• Inventors: Annoni, Elizabeth Mary, Gu, Jianwen, Thakur, Pramodsingh Hirasingh, Clark, Bryan Allen, Srivastava, Kyle Harish
• Primary Examiner(s): Fairchild, Mallika D
• Application Number:
  US15/867,767
• Publication Number:
  US 20180193644A1
• Time in Patent Office: 936 Days
• CPC Class Codes: A61B 5/1107 Measuring contraction of parts of the body, e.g. organ, muscle apparatus for measuring work or force in general G01L
• CPC Class Codes: A61B 5/389 Electromyography [EMG]
• CPC Class Codes: A61B 5/4824 Touch or pain perception evaluation A61B5/4821 takes precedence
• CPC Class Codes: A61B 5/4836 Diagnosis combined with treatment in closed-loop systems or methods A61B5/0036 takes precedence
• CPC Class Codes: A61N 1/0534 Electrodes for deep brain stimulation
• CPC Class Codes: A61N 1/0551 Spinal or peripheral nerve electrodes
• CPC Class Codes: A61N 1/36062 Spinal stimulation
• CPC Class Codes: A61N 1/36071 Pain
• CPC Class Codes: A61N 1/36139 with automatic adjustment
• CPC Class Codes: A61N 1/37217 characterised by the communication link, e.g. acoustic or tactile
• CPC Class Codes: A61N 1/37247 User interfaces, e.g. input or presentation means
• CPC Class Codes: A61N 1/37264 Changing the program; Upgrading firmware

Abstract

This document discusses, among other things, systems and methods for managing pain of a subject. A system may include one or more sensors configured to sense a signal indicative of muscle electrical or mechanical activity at a specific body location. The muscle electrical or mechanical activity signal may include an electromyography or a mechanical contraction signal. A pain analyzer circuit may extract from the sensed signal one or more signal metrics indicative of muscle tension, and generate a pain score using the signal metrics. The pain score may be output to a user or a process. The system may include a neurostimulator that can adaptively control the delivery of pain therapy by automatically adjusting stimulation parameters based on the pain score.

Claims

1. A system for managing pain of a patient, the system comprising:

a sensor circuit coupled to one or more sensors configured to sense from the patient at least one muscle mechanical contraction signal at a specific body location;

a pain analyzer circuit coupled to the sensor circuit, the pain analyzer circuit configured to;

detect muscle tension using one or more signal metrics generated from the sensed at least one muscle mechanical contraction signal at the specific body location; and

generate a pain score using the generated one or more signal metrics; and

an output unit configured to output the pain score to a user or a processing device.

2. The system of claim 1, further comprising:

an electrostimulator configured to generate electrostimulation energy to treat pain; and

a controller circuit coupled to the pain analyzer circuit and the electrostimulator, the controller circuit configured to control the electrostimulator to deliver a pain therapy and to control the electrostimulation energy generated by the electrostimulator according to the pain score.

3. The system of claim 2, wherein the electrostimulator is further configured to deliver at least one of:

a spinal cord stimulation;

a brain stimulation;

or a peripheral nerve stimulation.

4. The system of claim 2, wherein the controller circuit is further configured to deliver first electrostimulation to the patient in response to the pain score exceeding a threshold value, and to deliver second electrostimulation to the patient in response to the pain score falling below the threshold value;

wherein the first and second electrostimulations differ in at least one of an electrostimulation energy, an electrostimulation pulse shape, or an electrostimulation pattern.

5. The system of claim 2, further comprising an implantable neuromodulator device (IND) that includes one or more of the sensor circuit, the pain analyzer circuit, or the electrostimulator.

6. The system of claim 1, wherein the sensor circuit is coupled to an electromyography (EMG) sensor configured to sense an EMG signal at the specific body location.

7. The system of claim 1, wherein the sensor circuit is coupled to a force sensor configured to measure a muscle force parameter at the specific body location of the patient.

8. The system of claim 1, wherein the sensor circuit is coupled to a sonomicrometry crystal configured to record muscle shortening.

9. The system of claim 1, wherein:

the sensor circuit is coupled to first and second sensors, the first sensor configured to be positioned at a first patient location to sense a first muscle tension signal at one side of a specific muscle, and the second sensor configured to be positioned at a second patient location to sense a second muscle tension signal at an opposite side of the specific muscle; and

the pain analyzer circuit is further configured to;

detect a bilateral asymmetry indicator using first signal metrics generated from the first muscle tension signal and second signal metrics generated from the second muscle tension signal, the bilateral asymmetry indicator indicating asymmetric muscle activities between the one side and the opposite side of the specific muscle; and

generate the pain score further using the detected bilateral asymmetry indicator.

10. The system of claim 1, wherein the pain analyzer circuit is further configured to generate the pain score using a combination of a plurality of the signal metrics weighted by their respective weight factors.

11. A method for managing pain of a patient using an implantable neuromodulator device (IND), the method comprising:

sensing at least one muscle mechanical contraction signal at a specific body location of the patient using one or more sensors;

generating, from the sensed at least one muscle mechanical contraction signal, one or more signal metrics indicative of muscle tension at the specific body location of the patient;

detecting a muscle tension using the one or more signal metrics;

generating a pain score based on the one or more signal metrics; and

outputting the pain score to a user or a process.

12. The method of claim 11, further comprising delivering a pain therapy via the IND, the pain therapy including electrostimulation energy determined according to the pain score.

13. The method of claim 11, further comprising sensing an electromyography (EMG) signal from a patient skin area next to a target muscle, the EMG signal indicative of an electrical activity of muscle tension contributing to or affected by patient pain.

14. The method of claim 11, further comprising sensing an EMG signal from a face of the patient, the EMG signal indicative of an electrical activity of facial muscle tension associated with pain-related emotional distress.

15. The method of claim 11, wherein the muscle mechanical contraction signal includes information about muscle force or muscle shortening.

16. The method of claim 11, wherein:

sensing the muscle mechanical contraction signal includes sensing first and second muscle tension signals via respective first and second sensors, the first muscle tension signal indicative of a muscle tension at one side of a specific muscle, the second muscle tension signal indicative of a muscle a tension at an opposite side of the specific muscle;

detecting the muscle tension includes detecting a bilateral asymmetry indicator using first signal metrics generated from the first muscle tension signal and second signal metrics generated from the second muscle tension signal, the bilateral asymmetry indicator indicating asymmetric muscle activities between the one side and the opposite side of the specific muscle; and

generating the pain score further using the detected bilateral asymmetry indicator.

17. The method of claim 11, wherein generating the pain score includes using a combination of a plurality of the signal metrics weighted by their respective weight factors.

18. A non-transitory machine-readable storage medium, comprising a plurality of instructions that, responsive to being executed with processor circuitry of a computing device, cause the computing device to:

sense at least one muscle mechanical contraction signal at a specific body location of the patient using one or more sensors;

generate, from the sensed at least one muscle mechanical contraction signal, one or more signal metrics indicative of muscle tension at the specific body location of the patient;

detect a muscle tension using the one or more signal metrics;

generate a pain score based on the one or more signal metrics; and

output the pain score to a user or a processing device.

19. The non-transitory machine-readable storage medium of claim 18, wherein the instruction that causes the computing device to sense at least one muscle mechanical contraction signal includes an instruction causing the computing device to sense information about muscle force or muscle shortening.

20. The non-transitory machine-readable storage medium of claim 18, further comprising an instruction that causes the computing device to:

sense the muscle mechanical contraction signal including first and second muscle tension signals via respective first and second sensors, the first muscle tension signal indicative of a muscle tension at one side of a specific muscle, the second muscle tension signal indicative of a muscle a tension at an opposite side of the specific muscle;

detect the muscle tension includes detecting a bilateral asymmetry indicator using first signal metrics generated from the first muscle tension signal and second signal metrics generated from the second muscle tension signal, the bilateral asymmetry indicator indicating asymmetric muscle activities between the one side and the opposite side of the specific muscle; and

generate the pain score further using the detected bilateral asymmetry indicator.