Movement disorder therapy system, devices and methods, and intelligent methods of tuning

• US 9,717,920 B1
• Filed: 11/05/2015
• Issued: 08/01/2017
• Est. Priority Date: 09/10/2012
• Status: Active Grant

• Current Assignee: Great Lakes Neurotechnologies Inc.
• Original Assignee: Great Lakes Neurotechnologies Inc.
• Inventors: Pulliam, Christopher L, Heldman, Dustin A, Giuffrida, Joseph P, Mera, Thomas O
• Primary Examiner(s): Flory, Christopher A
• Application Number:
  US14/933,078
• Time in Patent Office: 635 Days
• Field of Search: 607 2, 607 9, 607 45, 128898
• CPC Class Codes: A61B 2505/07 Home care
• CPC Class Codes: A61B 2560/0214 of power generation or supply
• CPC Class Codes: A61B 2560/0271 using a remote monitoring unit
• CPC Class Codes: A61B 2560/0276 Determining malfunction
• CPC Class Codes: A61B 2560/0456 Apparatus provided with a docking unit
• CPC Class Codes: A61B 2562/0219 Inertial sensors, e.g. accelerometers, gyroscopes, tilt switches
• CPC Class Codes: A61B 2562/08 Sensors provided with means for identification, e.g. barcodes or memory chips
• CPC Class Codes: A61B 5/0022 Monitoring a patient using a global network, e.g. telephone networks, internet
• CPC Class Codes: A61B 5/11 Measuring movement of the entire body or parts thereof, e.g. head or hand tremor, mobility of a limb for measuring pulse A61B5/02 ;A61B5/1038 takes precedence; motion detection to correct for motion artifacts in physiological signals A61B5/721
• CPC Class Codes: A61B 5/1101 Detecting tremor
• CPC Class Codes: A61B 5/1118 Determining activity level
• CPC Class Codes: A61B 5/1124 Determining motor skills
• CPC Class Codes: A61B 5/1125 Grasping motions of hands
• CPC Class Codes: A61B 5/4082 Diagnosing or monitoring movement diseases, e.g. Parkinson, Huntington or Tourette
• CPC Class Codes: A61B 5/4836 Diagnosis combined with treatment in closed-loop systems or methods A61B5/0036 takes precedence
• CPC Class Codes: A61B 5/4839 combined with drug delivery
• CPC Class Codes: A61B 5/6825 Hand
• CPC Class Codes: A61B 5/6887 mounted on external non-worn devices, e.g. non-medical devices
• CPC Class Codes: A61B 5/7264 Classification of physiological signals or data, e.g. using neural networks, statistical classifiers, expert systems or fuzzy systems neural networks per se G06N3/00; expert systems per se G06N5/00
• CPC Class Codes: A61N 1/0534 Electrodes for deep brain stimulation
• 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 1/36132 : using patient feedback
• CPC Class Codes: A61N 1/36135 : using physiological parameters
• CPC Class Codes: A61N 1/36139 : with automatic adjustment
• CPC Class Codes: A61N 1/37235 : Aspects of the external programmer
• CPC Class Codes: A61N 1/37247 : User interfaces, e.g. input or presentation means
• CPC Class Codes: A61N 1/37282 : characterised by communication with experts in remote locations using a network
• CPC Class Codes: G16H 20/70 : relating to mental therapies, e.g. psychological therapy or autogenous training
• CPC Class Codes: G16H 40/63 : for local operation
• CPC Class Codes: G16H 50/20 : for computer-aided diagnosis, e.g. based on medical expert systems
• CPC Class Codes: G16H 50/50 : for simulation or modelling of medical disorders

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

1. A method of tuning a movement disorder therapy system comprising steps of:

providing a movement disorder diagnostic device to a subject having a deep brain stimulation (DBS) device with a first level of DBS parameters, the movement disorder diagnostic device comprising at least one movement sensor having a signal, and a processor comprising an algorithm;

instructing the subject to perform at least one movement disorder test(s) while the subject is undergoing DBS therapy or is under the effects of DBS therapy;

measuring and quantifying a severity of motor symptoms of the subject in real time based at least in part on the signal from the at least one movement sensor(s) during the at least one movement disorder test(s);

transmitting data corresponding to the severity of the subject'"'"'s measured and quantified motor symptoms to a clinician, physician or technician, the data being represented in the form of a tuning map that is a two-dimensional representation of a three-dimensional graph;

providing a second level of DBS parameters to reduce the severity of the measured and quantified motor symptoms based at least in part on a review of the tuning map by the clinician, physician or technician; and

entering the second level of DBS parameters into the subject'"'"'s DBS device such that the subject'"'"'s DBS device operates and provides an electric stimulus to the subject with the DBS device under the second level of DBS parameters.

2. The method of claim 1, further comprising a step of conducting a video or audio conference between the subject and the clinician, physician or technician whereby data corresponding to the quantified severity of motor symptoms is reviewed.

3. The method of claim 1, wherein the algorithm recommends a new B level of DBS parameters to the clinician, physician or technician, and the clinician, physician or technician reviews both the new level of DBS parameters and the tuning map in order to provide the second level of DBS parameters to be entered into the subject'"'"'s DBS device.

4. The method of claim 3, wherein the clinician, physician or technician must approve the second level of DBS parameters and directs the system to enter the second level of DBS parameters into the subject'"'"'s (DBS) device.

5. The method of claim 4, wherein the clinician, physician or technician directs the system to enter the second level of DBS parameters via a touch screen.

6. The method of claim 1, wherein the second level of DBS parameters corresponds to an increased ability for the subject to perform at least one activity of daily living.

7. The method of claim 1, wherein the second level of DBS parameters also increases battery life of the DBS device.