Abstract: Systems, methods, devices, and techniques for analyzing and applying features of a T-wave derived from an electrocardiogram. A computing system can receive a set of data that characterizes an electrocardiogram of a patient. The system can analyze the set of data to identify a T-wave that occurs in the electrocardiogram. The system can determine values of one or more features of the T-wave and provide the information that identifies the values of the one or more features of the T-wave to a user.

Abstract: Systems, methods, and other techniques for estimating the level of an analyte present in a patient during a time interval using electrocardiogram (ECG) signals. The estimate can be improved using information about the patient's posture.

Abstract: Systems, methods, devices, and techniques for analyzing and applying features of a T-wave derived from an electrocardiogram. A computing system can receive a set of data that characterizes an electrocardiogram of a patient. The system can analyze the set of data to identify a T-wave that occurs in the electrocardiogram. The system can determine values of one or more features of the T-wave and provide the information that identifies the values of the one or more features of the T-wave to a user.

Abstract: Systems, methods, and other techniques for estimating the level of an analyte present in a patient during a time interval using electrocardiogram (ECG) signals. The estimate can be improved using information about the patient's posture.

Abstract: Among the techniques described herein is a method that includes obtaining data indicating electrocardiogram results from a human. A plurality of beats represented in the electrocardiogram results can be identified. For each beat in the plurality of beats represented in the electrocardiogram results, a value for a first feature of the beat can be determined. Statistical analysis can be performed on the values for the first feature of the plurality of beats. An indication of the level of the analyte within the human can be generated based on a result of the statistical analysis performed on the values for the first feature of the plurality of beats. The indication of the level of the analyte within the human can be provided.

Abstract: This document describes, among other things, a computer-implemented method that includes accessing, by a computer system, electrogram data for a patient, wherein the electrogram data is obtained using one or more leads that sense physiological electrical activity of the patient. The computer system can identify one or more waveform features from the electrogram data, and one or more correlations between values of the one or more waveform features and analyte levels. One or more estimated analyte levels in the patient are determined based on 1) the one or more waveform features identified from the electrogram data and 2) the one or more correlations. The computer system can output information related to the one or more estimated analyte levels.

Abstract: A computing device receives a first user input requesting an estimated revenue for a projected time period. The computing device receives a second user input. The computing device determines an expected revenue for the projected time period from new maintenance contracts and renewed maintenance contracts and an expected revenue for the projected time period from warranty upgrades on units based on at least the current number of installed units as of the base time period, the expected number of unit installations for the projected time period, the attrition rate and the warranty option upgrade rate. The computing device determines a total expected revenue for the projected time period based on at least the computing device determining the expected revenue for the projected time period from new maintenance contracts and renewed maintenance contracts and the expected revenue for the projected time period from warranty upgrades on installed units.