Partitioning medical binary decision diagrams for analysis optimization

An apparatus comprising:

• one or more processors;
• and a memory coupled to the processors comprising instructions executable by the processors, the processors operable when executing the instructions to:
• access medical sensor data from one or more medical sensors measuring physiological stimulus from a person's body, the medical sensor data being stored as a first binary decision diagram (BDD), wherein the first BDD comprises one or more rooted directed acyclic graphs representing a Boolean function, the binary decision diagram comprising a plurality of nodes and a plurality of edges connecting the nodes thereby forming a plurality of paths, each path in the first BDD representing a set of variable assignments setting the represented Boolean function, wherein:
• the medical sensor data comprise a plurality of components, each component being defined based on a structural characteristic of a waveform of a signal outputted by the one or more sensors;
• and
• the first BDD comprises a plurality of portions respectively corresponding to the plurality of components;
• select, from the plurality of portions, one or more portions based on ease-of-analysis for increasing the speed or efficiency of analyzing the medical sensor data;
• and
• construct a second BDD and one or more third BDDs by partitioning the first BDD, wherein the second BDD represents the one or more selected portions, and the one or more third BDDs respectively represent one or more non-selection portions of the first BDD.

One or more computer-readable non-transitory storage media embodying software that is operable when executed to:

• access medical sensor data from one or more medical sensors measuring physiological stimulus from a person's body, the medical sensor data being stored as a first binary decision diagram (BDD), wherein the first BDD comprises one or more rooted directed acyclic graphs representing a Boolean function, the binary decision diagram comprising a plurality of nodes and a plurality of edges connecting the nodes thereby forming a plurality of paths, each path in the first BDD representing a set of variable assignments setting the represented Boolean function, wherein:
• the medical sensor data comprise a plurality of components, each component being defined based on a structural characteristic of a waveform of a signal outputted by the one or more sensors;
• and
• the first BDD comprises a plurality of portions respectively corresponding to the plurality of components;
• select, from the plurality of portions, one or more portions based on ease-of-analysis for increasing the speed or efficiency of analyzing the medical sensor data;
• and
• construct a second BDD and one or more third BDDs by partitioning the first BDD, wherein the second BDD represents the one or more selected portions, and the one or more third BDDs respectively represent one or more non-selection portions of the first BDD.

A system comprising:

• means for accessing medical sensor data from one or more medical sensors measuring physiological stimulus from a person's body the medical sensor data being stored as a first binary decision diagram (BDD), wherein the first BDD comprises one or more rooted directed acyclic graphs representing a Boolean function, the binary decision diagram comprising a plurality of nodes and a plurality of edges connecting the nodes thereby forming a plurality of paths, each path in the first BDD representing a set of variable assignments setting the represented Boolean function, wherein:
• the medical sensor data comprise a plurality of components, each component being defined based on a structural characteristic of a waveform of a signal outputted by the one or more sensors;
• and
• the first BDD comprises a plurality of portions respectively corresponding to the plurality of components;
• means for selecting, from the plurality of portions, one or more portions based on ease-of-analysis for increasing the speed or efficiency of analyzing the medical sensor data;
• and
• means for constructing a second BDD and one or more third BDDs by partitioning the first BDD, wherein the second BDD represents the one or more selected portions, and the one or more third BDDs respectively represent one or more non-selection portions of the first BDD.