US 12,318,616 B2
Systems and methods for determining optimal temporal patterns of neural stimulation
Warren M. Grill, Durham, NC (US); Isaac Cassar, Durham, NC (US); and Nathan Titus, Durham, NC (US)
Assigned to Duke University, Durham, NC (US)
Filed by Duke University, Durham, NC (US)
Filed on Jun. 22, 2021, as Appl. No. 17/355,092.
Application 17/355,092 is a continuation of application No. 16/303,812, granted, now 11,103,708, previously published as PCT/US2017/035556, filed on Jun. 1, 2017.
Claims priority of provisional application 62/344,033, filed on Jun. 1, 2016.
Prior Publication US 2021/0322775 A1, Oct. 21, 2021
Int. Cl. A61N 1/36 (2006.01); A61N 1/02 (2006.01); A61N 1/372 (2006.01); G16H 20/40 (2018.01); G16H 50/50 (2018.01)
CPC A61N 1/36178 (2013.01) [A61N 1/025 (2013.01); A61N 1/36139 (2013.01); A61N 1/36185 (2013.01); A61N 1/37235 (2013.01); G16H 20/40 (2018.01); G16H 50/50 (2018.01)] 14 Claims
OG exemplary drawing
 
7. A computing device comprising:
a temporal pattern selection unit comprising at least one processor and memory configured to:
determine one or more features among a plurality of features of a temporal pattern of neuronal stimulation associated with a fitness of the temporal pattern, wherein the fitness is based on a measured efficacy and/or efficiency of the temporal pattern, wherein a temporal pattern is a sequence of interpulse intervals;
store only the determined one or more features among the plurality of features of the temporal pattern of neuronal stimulation associated with a fitness of the temporal pattern;
determine a probability distribution of the one or more features;
select the one or more features utilizing the probability distribution of the one or more features;
determine a probability distribution of interpulse intervals of the temporal pattern;
generate a predictive temporal pattern of neuronal stimulation including the stored one or more features;
skew the probability distribution of the interpulse intervals towards longer interpulse intervals and shorter interpulse intervals;
determine a number of times each interpulse interval is to be selected utilizing the skewed probability distribution;
generate a pattern of pulses by ordering the pulses in a pattern of shorter interpulse intervals to longer interpulse intervals and longer interpulse intervals to shorter interpulse intervals; and
include the predictive temporal pattern in a population of temporal patterns of neuronal stimulation.