Feasibility of personalized nonparametric analytics for predictive monitoring of heart failure using continuous mobile telemetry

Pipke, Wegerich, Saidi, Stehlik

Perturbation analysis demonstrates that individual patient physiological behavior is effectively learned by the analytics, with high sensitivity to changes in physiological dynamics. Comparison of the analytics results with absence of unplanned medical events and self-reported wellness during regular patient follow-up demonstrate a very low false alert burden, suggesting this approach is efficient for remote clinical surveillance.

Published in Proceedings of the 4th Conference on Wireless Health (2013)

WH '13: Proceedings of the 4th Conference on Wireless HealthNovember 2013 Article No.: 7Pages 1–8