Method and apparatus for closed-loop deep brain stimulation in treating neurological diseases

• US 20100094377A1
• Filed: 06/29/2009
• Published: 04/15/2010
• Est. Priority Date: 10/09/2008
• Status: Active Grant

• Current Assignee: Daniel Graupe
• Original Assignee: Daniel Graupe
• Inventors: Graupe, Daniel
• Granted Patent: US 8,280,516 B2
• Time in Patent Office: Days
• US Class Current: 607/45
• CPC Class Codes: A61B 5/389 Electromyography [EMG]
• CPC Class Codes: A61B 5/395 Details of stimulation, e.g. nerve stimulation to elicit EMG response
• CPC Class Codes: A61B 5/4082 Diagnosing or monitoring movement diseases, e.g. Parkinson, Huntington or Tourette
• CPC Class Codes: A61N 1/36082 Cognitive or psychiatric applications, e.g. dementia or Alzheimer's disease

Abstract

A system that incorporates teachings of the present disclosure may include, for example, implanted deep brain stimulation electrodes, a stimulation sequence pulse generator, one or more implanted sensors for collecting data associated with one or more electrical signal from the vicinity of the site where stimulation is applied by the stimulation electrodes, and one or more noninvasive surface EMG electrodes to be attached to the patient'"'"'s skin, say, on certain limbs and which may incorporate a wireless transmitter microchip, and a controller. The controller may incorporate one or more wireless receiver microchips to receive inputs from the sensors. It may also have wire input, if placed under the skin of the skull, for inputs from the implanted sensors. It will incorporate a signal processor to process and coordinate the sensed data from the various sensors and to predict the timing for its output commands. The controller also incorporates a decision element to produce a control output to be sent by wire or wireless to the stimulation sequence generator and which may be an on-off command. The signal processor will also discriminate between tremors and intentional movements in the EMG signals utilizing the EMG spectrum. An electronic switch device may be incorporated to allow the implanted electrodes to switch between serving as stimulation electrodes and voltage sensors, thus eliminating the need to implant any separate sensing electrodes. Alternatively, only noninvasive EMG sensing may be employed for closed-loop control.

Claims

1. A device to apply deep brain stimulation (DBS) to persons with neurological disorders including Parkinson disease and other neurological tremors,

comprising

one or more implanted electrodes,

a stimulation sequence generator device,

a controller device

and

one or more sensor devices which may all be noninvasive

and where

stimulation is applied over a period of T seconds after which it is interrupted for a period of V seconds,

where the durations of T and of V are variable and are each individually determined by a feedback controller system or device, denoted as the controller, on the basis of input from one or more sensing systems or devices, that restarts stimulation over another round lasting for another T seconds,

where T is reset as determined by the controller, using same pulse-amplitude pulse-width and pulse-rate parameters as in the previous with round of stimulation,

and where

this new round of T seconds of stimulation is interrupted again by the controller for another different V seconds until being restarted by the controller system or device,

and where

the cycles of stimulation and subsequent interruption are repeated again and again,

and where

the controller system or device restarts stimulation via a decision algorithm or threshold device which serves to determine that stimulation should be renewed in accordance with data it receives from one or more sensing devices

which may be noninvasive surface-EMG electrodes attached to the skin of the patient being stimulated

and which

may also include an voltage sensor to sense the electrical activity in the vicinity of the site that is stimulated by DBS,

and where

this information is being processed by a signal processing sub-device that is part of the controller device, prior to being fed to the decision algorithm or device

and where

decision to restart a new round of stimulation is made a predictor sub-system of said signal processor to avoid the abnormal tremors and/or other motor-effects on the patient.

2. A device as in claim 1,

where the analysis of the surface-EMG signal, when employed in the signal processing sub-system or sub-device, is in terms of extracting surface-EMG parameters of that signal.

3. As in claim 2,

where surface-EMG parameters are dynamic time series parameters of the stochastic surface-EMG such as Autoregressive model parameters or ARMA (autoregressive and moving average) parameters or wavelet model parameters or their equivalents and which may serve for prediction over a short time span.

4. As in claim 3,

where the predictor of signal processing sub system or sub-device compensates for the time difference between any neural firing and tremor detected by the EMG sensor.

5. As in claim 4,

where compensation is predictive such that stimulation is re-started at every stimulation cycle slightly, say, a few seconds before tremors have been predicted to occur by the predictor that is incorporated in the signal processing sub-system.

6. As in claim 1,

where a decision algorithm of the predictor determines that a pre-determined threshold-level in the signal has been reached at the implanted sensing electrodes, or in parameters extracted by the signal processing algorithm and its prediction (predictor) sub-system from that signal

and which

has been determined to be one beyond which abnormal effects of the neurological disorder re-appear unless stimulation is restarted, this threshold level being adjustable by the responsible physician.

7. As in claim 1,

where the decision algorithm detects a pre-determined threshold-level in the signal detected by the surface raw-EMG electrodes or in parameters extracted by the signal processing algorithm from that signal,

and which

has been determined to be one beyond which abnormal effects of the neurological disorder re-appear unless stimulation is restarted, this threshold level being adjustable by the responsible physician.

8. As in claim 1 or 2 or 3 or 4 and or 5 or 6 or 7,

which employs no implanted sensors.

9. As in claim 1 or 8,

where EMG control is replaced by acceleration sensors.

10. As in claim 1 or 8,

where noninvasive sensor incorporates a wireless transmitter chip

and where

the controller incorporates a wireless receiver chip.

11. As in claim 1,

where an electronic switching device, which may be an optical switch, is incorporated to connect the stimulation sequence generator device with the implanted electrodes in order that a single implanted electrode can be switched from serving as voltage sensors to serving as implanted stimulation electrode,

where

this sharing is accomplished by the electronic switch device which switches between sending stimulation pulses to the implanted electrode from just before the beginning of the stimulation pulse and until just after the end of the pulse, and then switching to allow the same implanted electrode to serve as voltage sensor,

while

disallowing the sending a stimulus during the rest of the interval between two successive pulses, such that

the implanted electrode serves for say, 50 to 100 microseconds as a stimulating electrode and,

for the next 5000 to 7000 microseconds of each stimulation cycle, serving as a sensor, to allow sensing of voltage at the vicinity of the stimulation site in the brain,

while

eliminating the need to implant a separate sensor for voltage sensing in the brain.

12. As in claim 11,

where the electronic switch serves also to change impedance of the implanted electrode from one required when serving as stimulator to another when serving as sensor.

13. As in claim 1,

where the controller device also integrates the information from the various sensors above, and where integration may be performed by a neural network (NN) incorporated in the signal processor.

14. As in claim 11,

where the controller device discriminates between desired motor functions and tremors or other abnormal motor functions in the sensor signals, using the neural network as above.