IP Library Granted Patent US 12,214,202
Granted Patent B2
US 12,214,202 · App. 17/224,953 · Granted Feb 4, 2025

On-line autocalibration method for a computer brain interface device and computer brain interface device

Inventors: Bálint Várkuti (Munich, DE); Saman Hagh-Gooie (Hamburg, DE); Brian Blischak (San Diego, CA)
Assignee: Ceregate GmbH
A61N1/36139A61N1/36132A61N1/36171A61N1/36175A61N1/36178G06F3/015
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Quick Facts
Patent No.
US 12,214,202
App. No.
17/224,953
Granted
Feb 4, 2025
Kind
B2
Abstract

A computer brain interface (CBI) device of an individual is self-calibrated. A neurostimulation test signal is generated based on a selected set of test signal parameters. The neurostimulation signal is applied to the afferent sensory nerve fibers to elicit a bioelectric response via a neurostimulation interface operably connected to or integrated with the CBI device. The neurostimulation interface senses the bioelectric responses of the stimulated afferent sensory nerve fibers. The CBI devices determines, based on the sensed bioelectric responses, whether an excitation behavior of the stimulated afferent sensory nerve fibers with respect to the neurostimulation interface has changed. When the excitation behavior has changed, a set of recalibrated neurostimulation signal parameters is determined based on the sensed bioelectric responses. The CBI device is operated using the recalibrated neurostimulation signal parameters to communicate information to the individual via neurostimulation of the afferent sensory nerve fibers.

Claims (84)

1. A method for self-calibrating a computer brain interface, CBI, device of an individual, the method comprising:

selecting a set of test signal parameters;

generating, based on the selected set of test signal parameters, at least one neurostimulation test signal configured to elicit a bioelectric response in one or more afferent sensory nerve fibers;

applying the generated neurostimulation test signal to the afferent sensory nerve fibers via a neurostimulation interface operably connected to or integrated with the CBI device;

sensing via the neurostimulation interface, one or more bioelectric responses of the one or more stimulated afferent sensory nerve fibers;

determining, based on the sensed bioelectric responses, whether an excitation behavior of the stimulated afferent sensory nerve fibers with respect to the neurostimulation interface has changed;

when the excitation behavior has changed, determining, based on the sensed bioelectric responses, a set of recalibrated neurostimulation signal parameters, wherein determining the set of recalibrated neurostimulation signal parameters comprises comparing the sensed bioelectric responses to a set of reference bioelectric responses stored in a memory module of the CBI device or obtained via a communication interface of the CBI device; and

operating the CBI device, using the recalibrated neurostimulation signal parameters, to communicate information to the individual via neurostimulation of the one or more afferent sensory nerve fibers.

2. The method of claim 1 , further comprising:

generating, based on the determined set of recalibrated signal parameters, a communication neurostimulation signal, configured to elicit an artificial sensation in a sensory cortex area via stimulating the one or more afferent sensory nerve fiber terminating in the specific sensory cortex area,

wherein the artificial sensation is associated with a block of information to be communicated by the CBI device.

3. The method of claim 1 , wherein determining the set of recalibrated neurostimulation signal parameters comprises:

comparing the sensed bioelectric responses to a set of reference bioelectric responses stored in a memory module of the CBI device or obtained via a communication interface of the CBI device.

4. The method of claim 3 ,

wherein the set of reference bioelectric responses is associated with a set of artificial sensations that can be elicited by the CBI device via the neurostimulation m interface in a sensory cortex area of the individual and that are associated with one or more blocks of information that can be communicated via the CBI device to the individual.

5. The method of claim 3 , further comprising:

determining the set of reference bioelectric responses based on one or more of:

an initial or on-line calibration procedure involving the individual providing subjective feedback on artificial sensations elicited by a set of reference neurostimulation test signals;

a plurality of reference calibration measurements performed on a plurality of individuals prior to determining the set of reference bioelectric responses for the individual; and

an initial or online calibration procedure involving the individual performing one or more tasks with objectifiable outcomes that are supported by the operation of the CBI device and recording stimulation parameters and corresponding bioelectric responses that optimize performance of the task without recording subjective feedback by the individual.

6. The method of claim 1 ,

wherein a plurality of different neurostimulation test signals is generated and applied to the afferent sensory nerve fibers interleaved with a plurality of sensing periods of corresponding bioelectric responses of the afferent sensory nerve fibers.

7. The method of claim 6 ,

wherein the plurality of different neurostimulation test signals is generated such that one or more test signal parameters are varied in a systematic manner in order to estimate a systematic dependence of the excitation behavior of the afferent sensory nerve fibers on the one or more systematically varied test signal parameters.

8. The method of claim 7 ,

wherein the one or more test signal parameters are varied in form of an increasing or decreasing ramp, and/or

wherein the one or more signal parameters comprise one or more of the following:

a spatial activation pattern of the neurostimulation interface,

a signal amplitude,

an inter-pulse frequency,

an inter-burst frequency,

a pulse width,

a wave form shape,

a density of pulses within a burst,

signal polarity, and

a burst duration.

9. The method of claim 1 ,

wherein determining the set of recalibrated neurostimulation signal parameters comprises fitting a response function to a plurality of data points, wherein each data point comprises a set of test signal parameters and a corresponding bioelectric response level sensed by the CBI device; and

wherein determining the set of recalibrated neurostimulation signal parameters comprises aggregating several bioelectric response recordings for the selected set of test signal parameters.

10. The method of claim 1 ,

wherein the sensed bioelectric responses correspond to one or more of:

one or more extracellularly recorded action potentials;

local field potentials; and

evoked compound action potentials elicited by the at least one neurostimulation test signal.

11. The method of claim 10 , wherein the response function relates two or more different test signal parameters to an excitation threshold of the afferent sensory nerve fiber.

12. The method of claim 1 , the method further comprising:

repeating the method for self-calibrating the CBI device to obtain updated sets of recalibrated neurostimulation signal parameters; and

communicating information to the individual via neurostimulation of the one or more afferent sensory nerve fibers using the updated sets of recalibrated neurostimulation signal parameters.

13. A computer program comprising instructions executable by a processor and neurostimulation circuitry of a neurostimulation device to:

select a set of test signal parameters;

generate, based on the selected set of test signal parameters, at least one neurostimulation test signal configured to elicit a bioelectric response in one or more afferent sensory nerve fibers;

apply the generated neurostimulation test signal to the afferent sensory nerve fibers via a neurostimulation interface operably connected to or integrated with the neurostimulation device;

sense via the neurostimulation interface, one or more bioelectric responses of the one or more stimulated afferent sensory nerve fibers;

determine, based on the sensed bioelectric responses, whether an excitation behavior of the stimulated afferent sensory nerve fibers with respect to the neurostimulation interface has changed;

when the excitation behavior has changed, determine, based on the sensed bioelectric responses, a set of recalibrated neurostimulation signal parameters; and

operate the neurostimulation device, using the recalibrated neurostimulation signal parameters, to communicate information to the individual via neurostimulation of the one or more afferent sensory nerve fibers.

14. The computer program of claim 13 , wherein the instructions are further executable to cause the neurostimulation device to:

generate, based on the determined set of recalibrated signal parameters, a communication neurostimulation signal, configured to elicit an artificial sensation in a sensory cortex area via stimulating the one or more afferent sensory nerve fiber terminating in the specific sensory cortex area,

wherein the artificial sensation is associated with a block of information to be communicated by the neurostimulation device.

15. The computer program of claim 13 , wherein in determining the set of recalibrated neurostimulation signal parameters, the instructions are executable to cause the neurostimulation device to:

compare the sensed bioelectric responses to a set of reference bioelectric responses stored in a memory module of the neurostimulation device or obtained via a communication interface of the neurostimulation device.

16. The computer program of claim 15 ,

wherein the set of reference bioelectric responses is associated with a set of artificial sensations that can be elicited by the neurostimulation device via the neurostimulation interface in a sensory cortex area of the individual and that are associated with one or more blocks of information that can be communicated via the neurostimulation device to the individual.

17. A computer-brain-interface, CBI, device, comprising:

a neurostimulation interface comprising one or more stimulation and recording channels adapted to elicit and record a bioelectric response of one or more afferent sensory nerve fibers terminating in a sensory cortex area of an individual; and

data and signal processing circuitry, wherein the CBI device is configured to:

select a set of test signal parameters;

generate, based on the selected set of test signal parameters, at least one neurostimulation test signal configured to elicit the bioelectric response in the one or more afferent sensory nerve fibers;

apply the generated neurostimulation test signal to the afferent sensory nerve fibers via the neurostimulation interface; and

sense, by the neurostimulation interface, one or more bioelectric responses of the one or more stimulated afferent sensory nerve fibers;

determine, based on the sensed bioelectric responses, whether an excitation behavior of the stimulated afferent sensory nerve fibers with respect to the neurostimulation interface has changed;

when the excitation behavior has changed, determine, based on the sensed bioelectric responses, a set of recalibrated neurostimulation signal parameters; and

using the neurostimulation interface, communicate information to the individual using the recalibrated neurostimulation signal parameters via neurostimulation of the one or more afferent sensory nerve fibers.

18. The CBI device of claim 17 , further comprising

a memory module operably connected to the data and signal processing circuitry, wherein the memory stores one or both of:

a first mapping between one or more artificial sensations that can be elicited by the CBI device in one or more sensory cortex areas of the individual and one or more bioelectric responses; and

a second mapping between a plurality of sets of neurostimulation signal parameters and a plurality of bioelectric responses of the one or more afferent sensory nerve fibers.

19. The CBI device of claim 17 , wherein the CBI device is further configured to:

determine the set of reference bioelectric responses based on one or more of:

an initial or on-line calibration procedure involving the individual providing subjective feedback on artificial sensations elicited by a set of reference neurostimulation test signals;

a plurality of reference calibration measurements performed on a plurality of individuals prior to determining the set of reference bioelectric responses for the individual; and

an initial or online calibration procedure involving the individual performing one or more tasks with objectifiable outcomes that are supported by the operation of the CBI device and recording stimulation parameters and corresponding bioelectric responses that optimize performance of the task without recording subjective feedback by the individual.

20. The CBI device of claim 17 ,

wherein a plurality of different neurostimulation test signals is generated and applied to the afferent sensory nerve fibers interleaved with a plurality of sensing periods of corresponding bioelectric responses of the afferent sensory nerve fibers.

Assignments (2)
CHANGE OF ADDRESS OF ASSIGNEE Recorded Mar 17, 2023
From: CEREGATE GMBH
To: CEREGATE GMBH
Reel/Frame 063115/0923 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Apr 7, 2021
From: VÁRKUTI, BÁLINT; HAGH-GOOIE, SAMAN; BLISCHAK, BRIAN
To: CEREGATE GMBH
Reel/Frame 055857/0917 →
Continuity (1)
Related Publication 20220323763A1 · Oct 13, 2022
References Cited (76)
US 4445512A · Krupka et al. · 1984 [cited by applicant]
US 4488555A · Imran · 1984 [cited by applicant]
US 7751884B2 · Ternes et al. · 2010 [cited by applicant]
US 7774056B2 · Torgerson · 2010 [cited by applicant]
US 8193766B2 · Rondoni et al. · 2012 [cited by applicant]
US 8290596B2 · Wei et al. · 2012 [cited by applicant]
US 8352029B2 · Ternes et al. · 2013 [cited by applicant]
US 8364271B2 · De Ridder · 2013 [cited by applicant]
US 8380314B2 · Panken et al. · 2013 [cited by applicant]
US 8423145B2 · Pless et al. · 2013 [cited by applicant]
US 8475172B2 · Lieberman et al. · 2013 [cited by applicant]
US 8494633B2 · Tobacman · 2013 [cited by applicant]
US 8509904B2 · Rickert et al. · 2013 [cited by applicant]
US 8812128B2 · Kothandaraman · 2014 [cited by applicant]
US 9095314B2 · Osorio et al. · 2015 [cited by applicant]
US 9357938B2 · Ang et al. · 2016 [cited by applicant]
US 9636497B2 · Bradley et al. · 2017 [cited by applicant]
US 9713720B2 · Zhu · 2017 [cited by applicant]
US 9974478B1 · Brokaw et al. · 2018 [cited by applicant]
US 10568559B2 · Parker et al. · 2020 [cited by applicant]
US 20030065366A1 · Merritt et al. · 2003 [cited by applicant]
US 20060129205A1 · Boveja et al. · 2006 [cited by applicant]
US 20060241717A1 · Whitehurst et al. · 2006 [cited by applicant]
US 20060241718A1 · Tyler et al. · 2006 [cited by applicant]
US 20070027397A1 · Fischell et al. · 2007 [cited by applicant]
US 20070250134A1 · Miesel et al. · 2007 [cited by applicant]
US 20080129517A1 · Crosby et al. · 2008 [cited by applicant]
US 20080139954A1 · Day et al. · 2008 [cited by applicant]
US 20090306741A1 · Hogle et al. · 2009 [cited by applicant]
US 20100057161A1 · Machado et al. · 2010 [cited by applicant]
US 20100063411A1 · Donoghue et al. · 2010 [cited by applicant]
US 20130150914A1 · Kelly et al. · 2013 [cited by applicant]
US 20130253299A1 · Weber et al. · 2013 [cited by applicant]
US 20140081348A1 · Fischell · 2014 [cited by applicant]
US 20140379046A1 · Tcheng et al. · 2014 [cited by applicant]
US 20150018724A1 · Hsu et al. · 2015 [cited by applicant]
US 20150073492A1 · Kilgard et al. · 2015 [cited by applicant]
US 20150290453A1 · Tyler et al. · 2015 [cited by applicant]
US 20160022992A1 · Franke et al. · 2016 [cited by applicant]
US 20160121118A1 · Franke et al. · 2016 [cited by applicant]
US 20170080226A1 · Akhoun · 2017 [cited by applicant]
US 20180050198A1 · Mazanec et al. · 2018 [cited by applicant]
US 20180229046A1 · Parker et al. · 2018 [cited by applicant]
US 20190030338A1 · Wu et al. · 2019 [cited by applicant]
US 20200269049A1 · Varkuti · 2020 [cited by applicant]
US 20200376272A1 · Block et al. · 2020 [cited by applicant]
DE 102019202666A1 · 2020 [cited by applicant]
DE 102019209096A1 · 2020 [cited by applicant]
EP 2552304B1 · 2015 [cited by applicant]
EP 3229893A1 · 2017 [cited by applicant]
EP 3431138A1 · 2019 [cited by applicant]
EP 2486897B1 · 2019 [cited by applicant]
KR 20170132055 · 2017 [cited by applicant]
KR 101841625B1 · 2018 [cited by applicant]
WO 2012003451A3 · 2012 [cited by applicant]
WO 2016116397A1 · 2016 [cited by applicant]
WO 2018057667A1 · 2018 [cited by applicant]
WO 2018109715A1 · 2018 [cited by applicant]
WO 2020174051A1 · 2020 [cited by applicant]
European Search Report issued in European Application No. 22151438.3, mailed on Jun. 17, 2022, 4 pages. [cited by applicant]
International Search report and Written Opinion in International Application No. PCT/EP2022/059282, mailed on Jul. 11, 2022, 21 pages. [cited by applicant]
Donati, A., Shokur, S., Morya, E. et al. “Long-Term Training with a Brain-Machine Interface-Based Gait Protocol Induces Partial Neurological Recovery in Paraplegic Patients” Sci Rep 6, 30383 (2016); https://doi.org/10.1… [cited by applicant]
Examination Report for German Application No. 1020192014752.6, dated Jun. 16, 2020, 8 pgs. [cited by applicant]
First Office Action issued Oct. 16, 2019 for German Application No. DE 10 2019 202 666.4, 14 pp. [cited by applicant]
Heming EA et al: Designing a Thalamic Somatosensory Neural Prosthesis: Consistency and Persistence of Percepts Ecoked by 1 Electrical Simulation, IEEE Transactions on neural Systems and Rehabilitatinonengineering; IEEE … [cited by applicant]
Invitation to Pay Additional Fees and, Where Applicable, Protest Fee and Partial International Search Report for PCT/EP2020/055156, date mailed May 29, 2020, 21 pgs. [cited by applicant]
Beauchamp et al., “Dynamic Electrical Stimulation of Sites in Visual Cortex Produces Form Vision in Sighted and Blind Humans,” bioRxiv preprint, http://dx.doi.org/10.1101/462697, Nov. 5, 2018. [cited by applicant]
Lee et al., “Engineering Artificial Somatosensation Through Cortical Stimulation in Humans,” Frontiers in Systems Neuroscience, www.frontiersin.org, Jun. 4, 2018, vol. 12, Article 24. [cited by applicant]
Roelfsema et al., “Mind Reading and Writing: The Future of Neurotechnology,” Trends in Cognitive Sciences, https://doi.org/10.1016/j.tics.2018.04.001, May 6, 2018, Elsevier Ltd. [cited by applicant]
Anderson et al., “Optimized Programming Algorithm for Cylindrical and Directional Deep Brain Stimulation Electrodes,” https://doi.org/10.1088/1741-2552/aaa14b, Journal of Neural Engineering, Jan. 24, 2018, IOP Publishin… [cited by applicant]
Swan et al., “Sensory Percepts Induced by Microwire Array and DBS Microstimulation in Human Sensory Thalamus,” https://doi.org/10.1016/j.brs.2017 .10.017, Brain Stimulation 11 (2018) 416-422, Elsevier Inc. [cited by applicant]
Yadav, A.P., Li, D. & Nicolelis, M.A.L. : “A Brain to Spine Interface for Transferring Artificial Sensory Information”. Sci Rep 10, 900 (2020), 15 pgs. [cited by applicant]
“Sensory Electrical Stimulation Cueing May Reduce Freezingof Gait Episodes in Parkinson's Disease”; L. Rosenthal et. al.; Hindawi Journal of Healthcare Engineering; 2018, Article ID 4684925, 6 pgs. [cited by applicant]
“Effect of rhythmic auditory cueingon parkinsonian gait: A systematic review and meta-analysis”; S. Ghai et al.; Nature Scientic Reports; (2018) 8:506; DOI:10.1038/s41598-017-16232-5, 19 pgs. [cited by applicant]
Examination Report for German Application No. 1020192014752.6, dated Apr. 16, 2021, 5 pgs. [cited by applicant]
European Search Report for European Application No. 21168408.9, mailed on Oct. 6, 2021, 4 pages. [cited by applicant]