Methods and systems using mathematical analysis and machine learning to diagnose disease
US9910964B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Jun 24, 2016 |
| Grant date | Mar 6, 2018 |
| Priority date | — |
| Expiry date | Jun 24, 2036 |
Classification
- Technology area (CPC A)Human Necessities
- CPC primaryA61B5/7267
- WIPO fieldMedical technology
- WIPO sectorInstruments
Abstract
Exemplified method and system facilitates monitoring and/or evaluation of disease or physiological state using mathematical analysis and machine learning analysis of a biopotential signal collected from a single electrode. The exemplified method and system creates, from data of a singularly measured biopotential signal, via a mathematical operation (i.e., via numeric fractional derivative calculation of the signal in the frequency domain), one or more mathematically-derived biopotential signals (e.g., virtual biopotential signals) that is used in combination with the measured biopotential signals to generate a multi-dimensional phase-space representation of the body (e.g., the heart). By mathematically modulating (e.g., by expanding or contracting) portions of a given biopotential signal, in the frequency domain, the numeric-based operation gives emphasis or de-emphasis to certain measured frequencies of the biopotential signals, which, when coupled with machine learning, facilitates improved diagnostics of certain pathologies.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.