Altering physiological signals based on patient movement

Abstract

This document describes ways in which to alter physiological signals to address corrupt, noisy, or otherwise faulty data. By so doing, accuracy and robustness in sensing and assessing a patient's cardiovascular health can be improved. These improved assessments permit better measures of health, such as relevant hemodynamics understood by heart rates, heart rate variability, cardiac arrhythmias, blood pressures, pulse-wave velocities, arterial stiffness, cardiac valve timing, thoracic fluids, ballistocardiogram force, photo-plethysmograms, blood oxygenation, and pressure-volume loops.

Description

Background technique [0001] Cardiovascular disease is a leading cause of morbidity and mortality worldwide. At the same time, this chronic disease is largely preventable. Medical science knows how to save most of these lives by removing the major risk factors of smoking, diabetes and high blood pressure. In addition, many people are simply told what they need to do to reduce these risk factors—quit smoking, reduce sugar intake, eat healthier, reduce alcohol intake, increase aerobic exercise, lose points, and, if needed, take Blood pressure medication. However, many people do not follow such good advice. Because of this, hundreds of people die needlessly from cardiovascular disease. [0002] People don't follow such good medical advice because they think they are different, they don't want to change their behaviors that cause disease, or they don't know how to change in their particular situation. For example, when doctors tell them that they are at risk for heart disease ...

AI Technical Summary

Problems solved by technology

Unfortunately, current methods used to measure heart health can be inconvenient, inaccurate and expensive

Simple home monitor products for measuring heart rate and blood pressure exist, but long-term user compliance is an issue due to inconvenience, and accuracy is easily compromised for almost all but the simplest monitors. Effects of incorrect use of the patient, signal noise or signal corruption

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