Waveform shapes for treating neurological disorders optimized for energy efficiency

1. A system for neurological tissue stimulation comprising

a lead sized and configured for implantation in a targeted tissue stimulation region,

a pulse generator coupled to the lead, the pulse generator including a power source comprising a battery and a microprocessor coupled to the battery and being operable to apply to the lead a stimulation waveform derived at least in part through the use of a global optimization algorithm, and

wherein the microprocessor controls a generation of the stimulation waveform through a software implementation of a function comprising:

f

⁡

(

t

)

=

A

*

ⅇ

-

(



t

-

μ



α

L

)

β

L

⁢

⁢

for

⁢

⁢

t

≤

μ

,

and

=

A

*

ⅇ

-

(



t

-

μ



α

R

)

β

R

⁢

⁢

for

⁢

⁢

t

>

μ

,

⁢

wherein the stimulation waveform has parameters including amplitude and pulse width, wherein μ is greater than zero and less than the pulse width, wherein A is the peak current amplitude of the waveform at time μ, wherein α L and α R are scale parameters for times less than or equal to μ and greater than μ, respectively, and wherein β L and β R are shape parameters for times less than or equal to μ and greater than μ, respectively.

2. A system according to claim 1 , wherein the stimulation waveform is derived through the use of a prescribed genetic algorithm (GA) coupled to a computational model of extracellular stimulation of a mammalian myelinated axon, wherein the waveform is optimized for energy efficiency to prolong battery life.

3. A system according to claim 1

wherein the waveform consists essentially of a Gaussian curve.

4. A system according to claim 1

wherein the waveform consists essentially of a truncated Gaussian curve.

5. A system according to claim 1

wherein the waveform is monophasic.

6. A system according to claim 1

wherein the waveform is biphasic.

7. A system according to claim 1

wherein the pulse generator is implantable.

8. A system according to claim 1 , wherein A, β, α L , α R , β L , and β R are selectively programmable.

9. A system according to claim 1 , wherein A is within a range of about 10 microamps to about 10 milliamps.

10. A system according to claim 9 , wherein α L and α R are greater than zero milliseconds and less than infinity milliseconds.

11. A system according to claim 1 , wherein α L and α R are within a range of about 0.008 milliseconds to about 0.1 milliseconds.

12. A system according to claim 11 , wherein β L and β R are greater than zero and less than infinity.

13. A system according to claim 12 , wherein β L and β R are within a range of about 0.8 to about 1.8.

14. A system for creating a stimulation waveform optimized for energy efficiency comprising a population of parent stimulation waveforms, first means including a genetic algorithm (GA) for generating a population of offspring stimulation waveforms by mating the population of parent stimulation waveforms,

second means consisting essentially of a computational model of extracellular stimulation of a mammalian myelinated axon, being operative for assessing the fitness of individual offspring stimulation waveforms generated by the first means in terms of energy efficiency and selecting as a new population of parent stimulation waveforms the current offspring stimulation waveforms having the highest energy efficiency values, the selection terminating when predetermined termination criteria is met.

15. A system according to claim 14

wherein the termination criteria includes the fitness of successive populations of offspring stimulation waveforms converging toward a common energy-efficiency value.

16. A system according claim 14

wherein the stimulation waveform optimized for energy efficiency consists essentially of a Gaussian curve.

17. A system according claim 14

wherein the stimulation waveform optimized for energy efficiency consists essentially of a truncated Gaussian curve.