# US 10,478,626 B1 · Movement disorder therapy system, devices and methods, and intelligent methods of tuning

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- Number: US 10,478,626 B1
- Document ID: US10478626B1
- Status: Granted
- Kind: B1
- Application number: 15/632,540
- Filed: 2017-06-26
- Granted: 2019-11-19
- Earliest claimed: 2012-09-10
- Assignees: Great Lakes NeuroTechnologies Inc.
- Applicants: Dustin A Heldman; Christopher L Pulliam; Joseph P Giuffrida; Thomas O Mera
- Inventors: Dustin A Heldman; Christopher L Pulliam; Joseph P Giuffrida; Thomas O Mera
- Web page: https://patentgrep.com/patent/US10478626B1

## CPC

- A61N 1/37235: {Aspects of the external programmer}
- A61B 5/0022: {Monitoring a patient using a global network, e.g. telephone networks, internet}
- A61B 5/11: Measuring movement of the entire body or parts thereof, e.g. head or hand tremor or mobility of a limb {(A61B5/1038 takes precedence; motion detection to correct for motion artifacts in physiological signals A61B5/721)}
- A61B 5/1101: {Detecting tremor}
- A61B 5/1118: {Determining activity level}
- A61B 5/1124: {Determining motor skills}
- 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 5/4839: {combined with drug delivery}
- A61B 5/6825: {Hand}
- A61B 5/7264: {Classification of physiological signals or data, e.g. using neural networks, statistical classifiers, expert systems or fuzzy systems}
- A61N 1/36067: {Movement disorders, e.g. tremor or Parkinson disease (stimulating motor muscle A61N1/36003)}
- A61N 1/36082: {Cognitive or psychiatric applications, e.g. dementia or Alzheimer's disease}
- A61N 1/36132: {using patient feedback}
- A61N 1/36135: {using physiological parameters}
- A61N 1/36139: {with automatic adjustment}
- A61N 1/37282: {characterised by communication with experts in remote locations using a network}
- G16H 20/70: relating to mental therapies, e.g. psychological therapy or autogenous training
- G16H 40/63: for local operation
- G16H 50/20: for computer-aided diagnosis, e.g. based on medical expert systems
- G16H 50/50: for simulation or modelling of medical disorders
- A61B 5/1125: {Grasping motions of hands}
- A61B 5/6887: {mounted on external non-worn devices, e.g. non-medical devices}
- A61B 2505/07: Home care
- A61B 2560/0214: of power generation or supply
- A61B 2560/0271: using a remote monitoring unit
- A61B 2560/0276: Determining malfunction
- A61B 2560/0456: Apparatus provided with a docking unit
- A61B 2562/0219: Inertial sensors, e.g. accelerometers, gyroscopes, tilt switches
- A61B 2562/08: Sensors provided with means for identification, e.g. barcodes or memory chips
- A61N 1/0534: {Electrodes for deep brain stimulation}
- A61N 1/37247: {User interfaces, e.g. input or presentation means}
- 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)
- G16H: HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA

## Abstract

The present invention relates to methods for tuning treatment parameters in movement disorder therapy systems. The present invention further relates to a system for screening patients to determine viability as candidates for certain therapy modalities, such as deep brain stimulation (DBS). The present invention still further provides methods of quantifying movement disorders for the treatment of patients who exhibit symptoms of such movement disorders including, but not limited to, Parkinson's disease and Parkinsonism, Dystonia, Chorea, and Huntington's disease, Ataxia, Tremor and Essential Tremor, Tourette syndrome, stroke, and the like. The present invention yet further relates to methods of tuning a therapy device using objective quantified movement disorder symptom data acquired by a movement disorder diagnostic device to determine the therapy setting or parameters to be provided to the subject via his or her therapy device. The present invention also provides treatment and tuning remotely, allowing for home monitoring of subjects.

## Claims

### Claim 1

A movement disorder therapy system comprising:
a movement disorder diagnostic device comprising at least one physiological or movement sensor adapted to be worn, attached or held at different locations on the surface of the subject's body and having a signal related to a subject's motion, the movement disorder diagnostic device adapted to provide therapy to a subject with a deep brain stimulation (DBS) device operable with adjustable DBS parameters, and to measure movement data based at least in part on the signal of the at least one sensor while the subject performs at least one movement disorder test, the movement disorder diagnostic device further comprising at least one electronic component adapted to collect and transmit the measured movement data;
a processor comprising a quantification algorithm and a determination algorithm, the processor adapted to, at least in part, extract at least one kinematic feature from the measured movement data, the quantification algorithm adapted to receive data corresponding to the subject's measured motor symptoms and the at least one extracted kinematic feature and to quantify motor symptoms of the subject based thereon, and the determination algorithm adapted to provide a suggested level of DBS parameters based on a mode of therapy or treatment corresponding to the subject's needs based at least in part on the quantified motor symptoms; and
a tuning output adapted to interface with the subject's DBS device to provide a second level of DBS parameters for the subject's DBS device to alter the subject's symptomatic movement and to be entered into the subject's DBS device such that the subject's DBS device operates under the second level of DBS parameters,
wherein the at least one kinematic feature is selected from the group consisting of peak power angular velocity, peak power angle, RMS angular velocity, frequency, maximum amplitude, maximum peak-to-peak amplitude, mean angular velocity, and wavelet parameters, peak power acceleration, peak power velocity, peak power position, RMS acceleration, RMS velocity, RMS position, mean acceleration, wavelet parameters, covariance of any of the kinematic features, and standard deviation over time of any of these kinematic features.

### Claim 2 (depends on 1)

The system of claim 1, wherein the quantification algorithm includes and artificial neural network, a Bayesian network, and/or a genetic algorithm.

### Claim 3 (depends on 2)

The system of claim 2, further comprising a data output comprising data corresponding to the subject's measured and quantified motor symptoms and/or the suggested DBS parameters, the data output adapted to be displayed visually for review by a clinician, physician, or technician to determine the second level of DBS parameters for the tuning output based on the data output.

### Claim 4 (depends on 3)

The system of claim 3, wherein the data output is adapted to be displayed in the form of a tuning map that is a two-dimensional representation of a three-dimensional graph.

### Claim 5 (depends on 4)

The system of claim 4, wherein the suggested level of DBS parameters corresponds to a quantifiable decrease in the severity and/or occurrence of at least one motor symptom, the quantifiable decrease being about 25% or greater.

### Claim 6 (depends on 4)

The system of claim 4, wherein the suggested level of DBS parameters corresponds to a quantifiable decrease in the severity of at least one side effect, the quantifiable decreases being about 25% or greater.

### Claim 7 (depends on 2)

The system of claim 2, wherein the second level of DBS parameters are also based on a constraint of maximizing battery life of the DBS device.

### Claim 8

A movement disorder therapy system comprising:
a movement disorder diagnostic device comprising at least one physiological or movement sensor adapted to be worn, attached or held at different locations on the surface of the subject's body and having a signal related to a subject's motion, the movement disorder diagnostic device adapted to provide therapy to a subject with a deep brain stimulation (DBS) device operable with adjustable DBS parameters, and to measure movement data based at least in part on the signal of the at least one sensor while the subject performs at least one movement disorder test, the movement disorder diagnostic device further comprising at least one electronic component adapted to collect and transmit the measured movement data;
a processor comprising a quantification algorithm and a determination algorithm, the processor adapted to, at least in part, extract at least one kinematic feature from the measured movement data, the quantification algorithm adapted to receive data corresponding to the subject's measured motor symptoms and the at least one extracted kinematic feature and to quantify motor symptoms of the subject based thereon, and the determination algorithm adapted to provide a suggested level of DBS parameters based on a mode of therapy or treatment corresponding to the subject's needs based at least in part on the quantified motor symptoms;
a data output comprising data corresponding to the subject's measured and quantified motor symptoms and/or the suggested DBS parameters, the data output adapted to be displayed visually for review by a clinician, physician, or technician to determine a second level of DBS parameters for a tuning output based on the data output; and
the tuning output adapted to interface with the subject's DBS device to provide the second level of DBS parameters for the subject's DBS device to alter the subject's symptomatic movement and to be entered into the subject's DBS device such that the subject's DBS device operates under the second level of DBS parameters,
wherein the at least one kinematic feature is selected from the group consisting of peak power angular velocity, peak power angle, RMS angular velocity, frequency, maximum amplitude, maximum peak-to-peak amplitude, mean angular velocity, and wavelet parameters, peak power acceleration, peak power velocity, peak power position, RMS acceleration, RMS velocity, RMS position, mean acceleration, wavelet parameters, covariance of any of the kinematic features, and standard deviation over time of any of these kinematic features.

### Claim 9 (depends on 8)

The system of claim 8, wherein the data output is adapted to be displayed in the form of a tuning map that is a two-dimensional representation of a three-dimensional graph.

### Claim 10 (depends on 9)

The system of claim 9, wherein the suggested level of DBS parameters corresponds to a quantifiable decrease in the severity and/or occurrence of at least one motor symptom, the quantifiable decrease being about 25% or greater.

### Claim 11 (depends on 9)

The system of claim 9, wherein the suggested level of DBS parameters corresponds to a quantifiable decrease in the severity and/or occurrence of at least one side effect in the severity of at least one side effect, the quantifiable decrease being about 25% or greater.

### Claim 12 (depends on 9)

The system of claim 9, wherein the quantification algorithm includes and artificial neural network, a Bayesian network, and/or a genetic algorithm.

### Claim 13 (depends on 9)

The system of claim 9, wherein the second level of DBS parameters are also based on a constraint of maximizing battery life of the DBS device.

### Claim 14

A movement disorder therapy system comprising:
a movement disorder diagnostic device comprising at least one physiological or movement sensor adapted to be worn, attached or held at different locations on the surface of the subject's body and having a signal related to a subject's motion, the movement disorder diagnostic device adapted to provide therapy to a subject with a deep brain stimulation (DBS) device operable with adjustable DBS parameters, and to measure movement data based at least in part on the signal of the at least one sensor while the subject performs at least one movement disorder test, the movement disorder diagnostic device further comprising at least one electronic component adapted to collect and transmit the measured movement data;
a processor comprising a quantification algorithm and a determination algorithm, the processor adapted to, at least in part, extract at least one kinematic feature from the measured movement data, the quantification algorithm adapted to receive data corresponding to the subject's measured motor symptoms and the at least one extracted kinematic feature and to quantify motor symptoms of the subject based thereon, and the determination algorithm adapted to provide a second level of DBS parameters based on a mode of therapy or treatment corresponding to the subject's needs based at least in part on the quantified motor symptoms; and
a tuning output adapted to interface with the subject's DBS device to provide the second level of DBS parameters for the subject's DBS device to alter the subject's symptomatic movement and to be automatically entered into the subject's DBS device such that the subject's DBS device operates under the second level of DBS parameters,
wherein the quantification algorithm includes and artificial neural network, a Bayesian network, and/or a genetic algorithm.

### Claim 15 (depends on 14)

The system of claim 14, further comprising a data output comprising data corresponding to the subject's measured and quantified motor symptoms and/or the second level of DBS parameters, the data output adapted to be displayed visually for review by a clinician, physician, or technician.

### Claim 16 (depends on 15)

The system of claim 15, wherein the data output is adapted to be displayed in the form of a tuning map that is a two-dimensional representation of a three-dimensional graph.

### Claim 17 (depends on 14)

The system of claim 14, wherein the second level of DBS parameters corresponds to a quantifiable decrease in the severity and/or occurrence of at least one motor symptom, the quantifiable decreases being about 25% or greater.

### Claim 18 (depends on 14)

The system of claim 14, wherein the second level of DBS parameters corresponds to a quantifiable decrease in the severity of at least one side effect, the quantifiable decreases being about 25% or greater.

### Claim 19 (depends on 14)

The system of claim 14, wherein the second level of DBS parameters corresponds to a quantifiable increased ability for the subject to perform at least one activity of daily living.

### Claim 20 (depends on 14)

The system of claim 14, wherein the second level of DBS parameters are also based on a constraint of maximizing battery life of the DBS device.
