Method and system for managing pain

Abstract

A method of managing pain using neurophysiological data acquired from the brain of a subject is disclosed. The method comprises: identifying activity-related features in the data; parceling the data according to the activity-related features to define a plurality of capsules, each representing a spatiotemporal activity region in the brain; comparing at least some of the defined capsules to at least one reference capsule; and assessing the likelihood that the subject is experiencing pain responsively to the comparison.

What is claimed is: 
     
         1 . A method of managing labor pain using neurophysiological data acquired from the brain of a female subject, the method comprising:
 identifying activity-related features in said data;   constructing a subject-specific brain network activity (BNA) pattern having a plurality of nodes, wherein each node represents a feature of said activity-related features, and each pair of nodes is assigned with a connectivity weight;   calculating a BNA pattern similarity describing a comparison between said constructed BNA pattern and a baseline BNA pattern; and   assessing the likelihood that the subject is experiencing labor pain responsively to said BNA pattern similarity.   
     
     
         2 . The method according to  claim 1 , wherein said baseline BNA pattern corresponds to neurophysiological data acquired from the same subject at a different time. 
     
     
         3 . The method according to  claim 1 , wherein said baseline BNA pattern is based on a group BNA pattern characterizing a group of subjects identified as not experiencing labor pain. 
     
     
         4 . The method according to  claim 1 , wherein said baseline BNA pattern is based on a group BNA pattern characterizing a group of subjects identified as experiencing labor pain. 
     
     
         5 . The method according to  claim 1 , further comprising repeating said construction of subject-specific BNA and said calculation of BNA pattern similarity at least once. 
     
     
         6 . The method according to  claim 1 , further comprising repeating said construction of subject-specific BNA and said calculation of BNA pattern similarity at least once, wherein each subject-specific BNA is constructed based on different reference data or model but using the same neurophysiological data of the subject, wherein each subject-specific BNA is compared to a baseline BNA pattern being associated with a different brain condition, and wherein said assessment is responsively to at least two BNA pattern similarities. 
     
     
         7 . The method according to  claim 6 , wherein at least one baseline BNA pattern characterizes a group of subjects identified as not experiencing labor pain, and at least one baseline BNA pattern characterizes a group of subjects identified as experiencing labor pain. 
     
     
         8 . The method according to  claim 1 , further comprising determining a pain index based on at least said BNA pattern similarity. 
     
     
         9 . The method according to  claim 1 , further comprising constructing several BNA patterns corresponding to different time intervals, and displaying said BNA patterns on a time axis. 
     
     
         10 . The method according to  claim 1 , wherein said neurophysiological data comprises data acquired before, during and/or after a treatment. 
     
     
         11 . The method according to  claim 10 , further comprising applying said treatment. 
     
     
         12 . The method according to  claim 10 , further comprising assessing the effect of said treatment by comparing a BNA pattern similarity calculated using at least said baseline BNA pattern and a subject-specific BNA pattern constructed based on data acquired before a treatment, to a BNA pattern similarity calculated using at least said baseline BNA pattern and a subject-specific BNA pattern constructed based on data acquired after a treatment. 
     
     
         13 . The method according to  claim 10 , further comprising assessing the effect of said treatment by comparing a BNA pattern corresponding to data acquired before a treatment to a BNA pattern corresponding to data acquired during and/or after a treatment. 
     
     
         14 . The method according to  claim 10 , wherein said treatment comprises a pharmacological treatment employing an active agent. 
     
     
         15 . The method according to  claim 10 , wherein said treatment comprises local stimulation to the brain. 
     
     
         16 . The method according to  claim 15 , wherein said local stimulation is at one or more locations corresponding to a spatial location of at least one of said nodes. 
     
     
         17 . The method according to  claim 1 , further comprising, prior to said calculation of said BNA pattern similarity, applying a feature selection procedure to said BNA pattern to provide at least one BNA sub-pattern, wherein said calculation of said BNA pattern similarity is executed separately for each of said at least one BNA sub-pattern. 
     
     
         18 . The method according to  claim 15 , wherein said assessment of said likelihood is executed repeatedly, and the method comprises varying said local stimulation responsively to variations in said likelihood. 
     
     
         19 . A system for managing labor pain using neurophysiological data, comprising a data processor configured for receiving the neurophysiological data, and executing the method according to  claim 1 . 
     
     
         20 . A computer software product, comprising a non-volatile computer-readable medium in which program instructions are stored, which instructions, when read by a data processor, cause the data processor to receive the neurophysiological data and execute the method according to  claim 1 . 
     
     
         21 . A system for managing labor pain using neurophysiological data recorded from a brain of a female subject, the system comprises:
 a data processor configured for identifying activity-related features in the data, and assessing the likelihood that the subject is experiencing labor pain based on said activity-related features; and   a controller connectable to a brain stimulation system and configured for controlling said brain stimulation system to apply local stimulation to the brain responsively to said likelihood;   wherein said estimation of said brain function is executed repeatedly, and said controller is configured to vary said local stimulation responsively to variations in said likelihood.   
     
     
         22 . The system according to  claim 21 , wherein said brain stimulation system is configured to apply both transcranial stimulation and deep brain stimulation, and wherein said controller is configured to control said brain stimulation system to apply said transcranial stimulation to control activation thresholds for said deep brain stimulation.