Patent Document ID: 20160378936
Application ID: 15192639
Patent Flag: 0

Claim One:
1. A method of pre-processing data to extract variables for use in machine learning to diagnose a pathology, the method comprising: receiving a biopotential signal data associated with a subject, said biopotential signal data being associated with a biopotential signal collected from one or more electrical leads; generating, via a processor, a first and a second fractional derivative signal data by numerically performing one or more fractional derivative operations of the biopotential signal data in a frequency domain and converting a result of the one or more fractional derivative operations to a time domain signal data, wherein each of the first and second generated fractional derivative signal data comprises a same length and a same sampling frequency as the biopotential signal data; and generating, via the processor, a three-dimensional space wherein each corresponding value of the biopotential signal data, the first fractional derivative signal data, and the second fractional derivative signal data forms a three-dimensional point in said space, wherein geometric features and dynamical properties of the three-dimensional space are used as variables representative of the subject in machine learning to detect one or more diagnosable pathology of the subject.