# US 12,109,417 B2 · Systems and methods for deep brain stimulation using kinematic feedback for treatment of movement disorders > Agents: this data is available as JSON from the patentgrep API and MCP server — see https://patentgrep.com/llms.txt - Number: US 12,109,417 B2 - Document ID: US12109417B2 - Status: Granted - Kind: B2 - Application number: 17/649,667 - Filed: 2022-02-01 - Published: 2022-08-04 - Granted: 2024-10-08 - Earliest claimed: 2021-02-01 - Assignees: The Board of Trustees of the Leland Stanford Junior University; University of Washington - Applicants: The Board of Trustees of the Leland Stanford Junior University; University of Washington - Inventors: Helen Bronte-Stewart; Yasmine Kehnemouyi; Matthew Petrucci; Jeffrey Herron; Johanna O'Day - Web page: https://patentgrep.com/patent/US12109417B2 ## CPC - A61N 1/36067: {Movement disorders, e.g. tremor or Parkinson disease (stimulating motor muscle A61N1/36003)} - A61B 5/1101: {Detecting tremor} - A61B 5/112: {Gait analysis} - A61B 5/1121: {Determining geometric values, e.g. centre of rotation or angular range of movement} - A61B 5/4064: {Evaluating the brain (for intracranial pressure A61B5/031; for cerebral blood gases A61B5/14553; using EEG A61B5/369)} - A61B 5/4082: {Diagnosing or monitoring movement diseases, e.g. Parkinson, Huntington or Tourette} - A61B 5/4836: {Diagnosis combined with treatment in closed-loop systems or methods (A61B5/0036 takes precedence)} - A61B 5/6828: {Leg} - A61N 1/0534: {Electrodes for deep brain stimulation} - A61N 1/36139: {with automatic adjustment} - A61B 5/1124: {Determining motor skills} - A61B 2505/07: Home care - A61B 2505/09: Rehabilitation or training - A61B 2562/0219: Inertial sensors, e.g. accelerometers, gyroscopes, tilt switches - A61N: ELECTROTHERAPY; MAGNETOTHERAPY; RADIATION THERAPY; ULTRASOUND THERAPY (measurement of bioelectric currents A61B; surgical instruments, devices or methods for transferring non-mechanical forms of energy to or from the body A61B18/00; anaesthetic apparatus in general A61M; incandescent lamps H01K; infrared radiators for heating H05B) - A61B: DIAGNOSIS; SURGERY; IDENTIFICATION (usefulness limited to only animals A61D) ## Abstract Systems and methods for deep brain stimulation using kinematic feedback in accordance with embodiments of the invention are illustrated. One embodiment includes a deep brain stimulation system, including an implantable neurostimulator, a first inertial measurement unit (IMU), a second IMU, and a controller, where the controller is communicatively coupled to the implantable neurostimulator, the first IMU, and the second IMU, and where the controller is configured to obtain kinematic data from the first IMU and the second IMU, identify an abnormal movement event based on the kinematic data, and modify deep brain stimulation provided by the implantable neurostimulator based on the identified abnormal movement event. ## Claims ### Claim 1 A deep brain stimulation system, comprising: an implantable neurostimulator; a first inertial measurement unit (IMU); a second IMU; and a controller, where the controller is communicatively coupled to the implantable neurostimulator, the first IMU, and the second IMU, and where the controller is configured to obtain kinematic data from the first IMU and the second IMU; predict a likelihood of a freezing of gait (FoG) event based on the kinematic data; and modify deep brain stimulation provided by the implantable neurostimulator based on the predicted likelihood, wherein the modification comprises: decreasing stimulation intensity when the predicted likelihood is below a minimum threshold; maintaining stimulation intensity when the predicted likelihood is between the minimum threshold and a maximum threshold; and increasing stimulation intensity when the predicted likelihood is above the maximum threshold. ### Claim 2 (depends on 1) The deep brain stimulation system of claim 1, wherein the first IMU is configured to be attached to the right leg of a patient; and the second IMU is configured to be attached to the left leg of the patient. ### Claim 3 (depends on 1) The deep brain stimulation system of claim 1, wherein the kinematic data comprises a signal of angular momentum over time. ### Claim 4 (depends on 1) The deep brain stimulation system of claim 1, wherein in order to predict a likelihood of the FoG event, the controller is further configured to: calculate metrics comprising: arrhythmicity over a most recent set of steps, stride time, swing angular range, and asymmetry over the most recent set of steps; and provide the calculated metrics to a logistic regression model to obtain a probability of the FOG event occurring. ### Claim 5 (depends on 1) The deep brain stimulation system of claim 1, further comprising modifying the deep brain stimulation according to a stimulation map, wherein the stimulation the stimulation map comprises the following changes in stimulation parameters: ramp stimulation frequency to 140 Hz when the predicted likelihood is below a minimum threshold; maintain stimulation frequency when the predicted likelihood is between the minimum threshold and a maximum threshold; and ramp stimulation frequency to 60 Hz when the predicted likelihood is above the maximum threshold. ### Claim 6 (depends on 5) The deep brain stimulation system of claim 5, wherein the minimum threshold is 30%, and the maximum threshold is 70%. ### Claim 7 A method for deep brain stimulation, comprising: obtaining kinematic data from a first inertial measurement unit (IMU) and a second IMU using a controller communicatively coupled to the first IMU and the second IMU; predict a likelihood of a freezing of gait (FoG) event based on the kinematic data using the controller; and modifying deep brain stimulation provided by an implantable neurostimulator communicatively coupled with the controller based on the predicted likelihood, wherein the modification comprises: decreasing stimulation intensity when the predicted likelihood is below a minimum threshold; maintaining stimulation intensity when the predicted likelihood is between the minimum threshold and a maximum threshold; and increasing stimulation intensity when the predicted likelihood is above the maximum threshold. ### Claim 8 (depends on 7) The method of deep brain stimulation of claim 7, wherein the first IMU is configured to be attached to the right leg of a patient; and the second IMU is configured to be attached to the left leg of the patient. ### Claim 9 (depends on 7) The method of deep brain stimulation of claim 7, wherein the kinematic data comprises a signal of angular momentum over time. ### Claim 10 (depends on 7) The method of deep brain stimulation of claim 7, wherein predicting the likelihood of the FoG event comprises: calculating metrics comprising: arrhythmicity over a most recent set of steps, stride time, swing angular range, and asymmetry over the most recent set of steps; and providing the calculated metrics to a logistic regression model to obtain a probability of the FOG event occurring. ### Claim 11 (depends on 7) The method of deep brain stimulation of claim 7, further comprising modifying the deep brain stimulation according to a stimulation map, wherein the stimulation map comprises the following changes in stimulation parameters: ramp stimulation frequency to 140 Hz when the predicted likelihood is below a minimum threshold; maintain stimulation frequency when the predicted likelihood is between the minimum threshold and a maximum threshold; and ramp stimulation frequency to 60 Hz when the predicted likelihood is above the maximum threshold. ### Claim 12 (depends on 11) The method of deep brain stimulation of claim 11, wherein the minimum threshold is 30%, and the maximum threshold is 70%.