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AI Biotech/Diagnostics: Cardio
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Application US20180325460
Published 2018-11-15
Multivariate Residual-based Health Index For Human Health Monitoring
Ambulatory or in-hospital monitoring of patients is provided with early warning and prioritization, enabling proactive intervention and amelioration of both costs and risks of health care. Multivariate physiological parameters are estimated by empirical model to remove normal variation. Residuals are tested using a multivariate probability density function to provide a multivariate health index for prioritizing medical effort.
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- 1. A system for monitoring the health of a human, comprising:
a device disposed to receive multiple physiological signals from a plurality of sensors arranged to capture physiological signals from a monitored human, having microprocessor hardware programmed to derive multiple physiological features from said signals; a computer configured to receive monitored observations of said multiple physiological features from said device, to generate estimates of said features in the monitored observations using a model embodying behavior of said multiple physiological features under normal health conditions, and to generate residuals of said features by differencing the monitored observations with the estimates thereof; and a computer-accessible memory storing a set of exemplary observations of residuals of said multiple physiological features characteristic of a normal health state for the monitored human, generated using said model; said computer being specially configured to determine a likelihood that said residuals are representative of a pattern of residuals for said normal health state, using a Gaussian mixture model based on said set of exemplary observations of residuals to approximate a probability distribution for normal residual patterns, whereby said likelihood consolidates the behaviors of the individual residuals for each of the features into one overall index to summarize any deviation of the physiological health of said human from normal.
- 16. A computerized system for monitoring the health of a human, configured by program code to perform the steps of:
receiving multivariate monitored observations of multiple vital sign features derived from physiological signals captured by at least one sensor on the monitored human; storing a model embodying behavior of said multiple vital sign features under normal health conditions personalized to the monitored human; generating estimates of at least some of said multiple vital sign features in the multivariate monitored observations using said model; generating monitored residuals of the at least some of said multiple vital sign features by differencing those features of the monitored observations that are estimated with the estimates thereof; storing a set of exemplary observations of residuals of said multiple vital sign features characteristic of a normal health state personalized to the monitored human and generated using said model; and determining a likelihood that said monitored residuals are representative of a pattern of residuals for said normal health state, using a Gaussian mixture model based on said set of exemplary observations of residuals to approximate a probability distribution for normal residual patterns, whereby said likelihood consolidates the behaviors of the individual residuals for each of the features into one overall index to summarize any deviation of the physiological health of said human from normal.
