1. A method for analyzing time series data to identify an event of interest, said method comprising: receiving, at a computing device, image time series data that includes the event of interest, the event of interest corresponding to an action performed by a subject; identifying, using the computing device, a start time of the event of interest and an end time of the event of interest by modeling at least one transitional pattern in the image time series data, wherein the modeling comprises: modeling an onset segment that represents a transition between a first neutral event and the event of interest as a first function of a joint angle of a joint of the subject; and modeling an offset segment that represents a transition between the event of interest and a second neutral event as a second function of the joint angle; and categorizing, using the computing device, the event of interest based on the at least one transitional pattern.