Removal of Stimulation Artifact in Multi-Channel Neural Recordings

• US 20200129766A1
• Filed: 03/14/2018
• Published: 04/30/2020
• Est. Priority Date: 03/15/2017
• Status: Active Grant

• Current Assignee: Regents of the University of California (University of California)
• Original Assignee: Regents of the University of California (University of California)
• Inventors: Sabes, Philip, O'Doherty, Joseph
• Granted Patent: US 11,596,797 B2
• Time in Patent Office: Days
• CPC Class Codes: A61B 5/24 Detecting, measuring or recording bioelectric or biomagnetic signals of the body or parts thereof
• CPC Class Codes: A61B 5/377 using evoked responses
• CPC Class Codes: A61B 5/4836 Diagnosis combined with treatment in closed-loop systems or methods A61B5/0036 takes precedence
• CPC Class Codes: A61B 5/7217 of noise originating from a therapeutic or surgical apparatus, e.g. from a pacemaker
• CPC Class Codes: A61F 2/72 Bioelectric control, e.g. myoelectric
• CPC Class Codes: A61N 1/025 Digital circuitry features of electrotherapy devices, e.g. memory, clocks, processors
• CPC Class Codes: A61N 1/05 for implantation or insertion into the body, e.g. heart electrode A61N1/06 takes precedence
• CPC Class Codes: A61N 1/0531 Brain cortex electrodes
• 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 1/36 for stimulation
• CPC Class Codes: A61N 1/36017 with leads or electrodes penetrating the skin
• CPC Class Codes: A61N 1/36025 for treating a mental or cerebral condition
• CPC Class Codes: A61N 1/3603 Control systems
• CPC Class Codes: A61N 1/36053 adapted for vagal stimulation A61N1/36114 takes precedence
• CPC Class Codes: A61N 1/36064 Epilepsy
• CPC Class Codes: A61N 1/36067 Movement disorders, e.g. tremor or Parkinson disease stimulating motor muscle A61N1/36003
• CPC Class Codes: A61N 1/36082 Cognitive or psychiatric applications, e.g. dementia or Alzheimer's disease
• CPC Class Codes: A61N 1/36096 Mood disorders, e.g. depression, anxiety or panic disorder
• CPC Class Codes: A61N 1/36128 Control systems
• CPC Class Codes: A61N 1/36135 : using physiological parameters

Abstract

Stimulation of nervous system components by electrodes can be used in many applications, including in the operation of brain-machine interfaces, bidirectional neural interfaces, and neuroprosthetics. The optimal operation of such systems requires a means of accurately measuring neural responses to such stimulations. However, currently the measurement of neural responses is difficult due to heavy stimulation artifacts arising from stimulatory pulses. The invention encompasses novel methods of estimating stimulation artifacts in measurements attained by recording electrodes and the effective removal of these artifacts. This provides improved neural recording systems and enables the deployment of closed-loop neural stimulation systems.

Claims

1-12. -12. (canceled)

13. A method of method of estimating the stimulation artifact signal on a selected recording electrode at a selected timepoint;

wherein the selected recording electrode is one of an array, the array comprising a plurality of recording electrodes implanted in a neural structure, the method comprising the steps of;

recording a signal on each recording electrode of the array at the selected timepoint;

inputting the recorded signals into a mathematical function, wherein the function outputs an estimated value for the stimulation artifact signal on the selected electrode;

wherein the function utilizes the recorded signals measured for the electrodes of the array other than the selected electrode and a previously-established mathematical relationship between signal measured on the selected electrode and the signal measured on the other recording electrodes of the array.

14. The method of claim 13, wherein

the stimulation artifact of the selected electrode is calculated as

15. The method of claim 13, wherein

a matrix is generated and applied for the simultaneous calculation of stimulation artifact across the signal data measured by each electrode of the array.

16. The method of claim 15, wherein

the matrix, W, is generated as W=−

Λ

Y, wherein,

Y≡

(XX^T)<sup>−

1</sup>, and

17. The method of claim 13, wherein

the array is implanted in a neural structure selected from the group consisting of the cerebral cortex, the visual cortex, the motor cortex, the somatosensory cortex, the sensimotor cortex, the spinal cord, or a component of the peripheral nervous system.

18. The method of claim 13, comprising the further step of estimating a neural response at the selected recording electrode at the selected timepoint by subtracting the estimated stimulation artifact from the signal measured at the selected electrode at the selected timepoint.

19. A closed-loop neural stimulation system, the closed loop neural stimulation system comprising

one or more stimulation electrodes, the operation of the one or more stimulation electrodes being under the control of a controller device;

a system for calculating artifact-corrected neural response signals generated in response to one or more stimulation pulses, the system comprising;

an array, the array comprising a plurality of recording electrodes;

a plurality of amplifiers, wherein one or more amplifiers is in connection with each recording electrode of the array;

a plurality of analog to digital converters, wherein each analog to digital converter is configured to convert recoding electrode outputs to digital signals;

one or more signal storage devices capable of storing signals output by the plurality of analog to digital converters; and

a processing device, the processing device configured to calculate artifact-corrected signals at a selected timepoint for each recording electrode in the array in response to a stimulation pulse by a method comprising the steps of;

recording a signal on each recording electrode of the array at the selected timepoint;

for each electrode in the array, inputting the signals recorded at the selected timepoint into a mathematical function, wherein the function outputs an estimated value for the stimulation artifact signal on the selected electrode;

wherein the function utilizes the recorded signals measured for the electrodes of the array other than the selected electrode and a previously-established mathematical relationship between signal measured on the selected electrode and the signal measured on the other recording electrodes of the array;

wherein the artifact-corrected signal is calculated for each electrode in the recording array at the selected timepoint by subtracting the estimated stimulation artifact of a selected electrode from the signal measured by that electrode at the selected timepoint; and

wherein the processing device is configured to output the artifact-corrected signals of the electrodes in the recording array to the controller device;

wherein the controller is configured to determine the parameters of stimulation pulses delivered by the one or more stimulation electrodes based upon the artifact-corrected signal values received from the processor device.

20. The closed-loop neural stimulation system of claim 19, wherein

the stimulation artifact of the selected electrode is calculated as

21. The closed-loop neural stimulation system of claim 19, wherein a matrix is generated and applied for the simultaneous calculation of stimulation artifact across the signal data measured by each electrode of the array.

22. The closed-loop neural stimulation system of claim 21, wherein the matrix, W, is generated as W=−

Λ

Y, wherein,

Y≡

(XX^T)<sup>−

1</sup>, and

23. The closed-loop neural stimulation system of claim 19, wherein

the system comprises a brain-machine interface, a neuroprosthetic, or bidirectional neural interface.

24. A method of feedback-guided delivery of stimulation pulses to a target neural structure, comprising the steps of:

delivering one or more stimulatory pulses to the target neural structure by means of one or more stimulation electrodes implanted therein, wherein the one or more stimulation electrodes are operated under the control of a controller device;

measuring one or more neural response signals in a responsive neural structure, the measurement accomplished by means of an array of recording electrodes implanted in the responsive neural structure;

calculating stimulation artifact-corrected neural response signals in the responsive neural structure by a method comprising the steps of;

recording a signal on each recording electrode of the array at the selected timepoint;

for each electrode in the array, inputting the signals recorded at the selected timepoint into a mathematical function, wherein the function outputs an estimated value for the stimulation artifact signal on the selected electrode;

wherein the function utilizes the recorded signals measured for the electrodes of the array other than the selected electrode and a previously-established mathematical relationship between signal measured on the selected electrode and the signal measured on the other recording electrodes of the array;

wherein the artifact-corrected neural response is calculated at for each electrode in the recording array at the selected timepoint by subtracting the estimated stimulation artifact of a selected electrode from the signal measured by that electrode at the selected timepoint;

inputting the calculated neural response signals to the controller device, wherein a rule-based decision process defines the parameters of subsequent pulse delivery to the target neural structure based on neural responses measured in the responsive neural structure; and

delivering stimulatory pulses to the target neural structure according to the defined parameters.

25. The method of claim 24, wherein

the stimulation artifact of the selected electrode is calculated as

26. The method of claim 24, wherein

a matrix is generated and applied for the simultaneous calculation of stimulation artifact across the signal data measured by each electrode of the array.

27. The method of claim 26, wherein

the matrix, W, is generated as W=−

Λ

Y, wherein,

Y≡

(XX^T)<sup>−

1</sup>, and

28. The method of claim 24, wherein

the feedback-guided delivery of stimulatory pulses is implemented in a process selected from the group consisting of the following:

cognitive control of a prosthetic device;

proprioception-based guidance of a prosthetic or body part;

vagus nerve stimulation for control of epilepsy;

vagus nerve stimulation for control of depression;

deep brain stimulation for controlling essential tremor;

deep brain stimulation for controlling Parkinson'"'"'s disease;

deep brain stimulation for controlling dystonia;

,and deep brain stimulation for controlling depression.