Fred Bergman Healthcare Pty Ltd

Jian Huang

David Albert Barda

Hadi Mashin-Chi

Mohammad Hadi Mashinchi

A method for analyzing incoming data, comprising the steps of processing the incoming data in segments to output a sequence of segment types by extracting one or more properties of an incoming data segment and forming an Unknown Property Vector for each segment of data in the incoming data, and processing the sequence of segment types to identify events in the incoming data. The sequence of segment types is determined, for each segment, by analyzing the Unknown Property Vector by reference to one or more collections of vectors obtained from a set of Reference Property Vectors. This may each of the one or more collections of vectors being selected from the set of Reference Property Vectors randomly or based on relevance or clustering.

Detecting fecal and urine events by reference to collections of data

A method for analyzing incoming data, comprising the steps of processing the incoming data in segments to output a sequence of segment types by extracting one or more properties of an incoming data segment and forming an Unknown Property Vector for each segment of data in the incoming data, and processing the sequence of segment types to identify events in the incoming data. The sequence of segment types is determined, for each segment, by reference to a set of Reference Property Vectors that are relevant to the Unknown Property Vector. This may involve application of first and/or second and/or further functions to identify at least a first subset of Reference Property Vectors that are relevant to the Unknown Property Vector. Alternatively, a logistic regression algorithm, derived using clustering or classification methods for identifying candidate vectors, may be used.

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North Sydney, Australia

Jian Huang