Heart rate correction system and methods for the detection of cardiac events
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Publication Number
US-9220428-B2
Publication Date
2015-12-29
Expiration Date
Abstract
A device for detecting a cardiac event is disclosed. Detection of an event is based on a test applied to a parameter whose value varies according to heart rate. Both the parameter value and heart rate (RR interval) are filtered with an exponential average filter. From these filtered values, the average change in the parameter and the RR interval are also computed with an exponential average filter. Before computing the average change in the parameter, large changes in the parameter over short times, which may be caused by body position shifts, are attenuated are removed, so that the average change represents an average of small/smooth changes in the parameter's value that are characteristic of acute ischemia, one of the cardiac events that may be detected. The test to detect the cardiac event depends on the heart rate, the difference between the parameter's value and its upper and lower normal values, and its average change over time, adjusted for heart rate changes. The upper and lower normal parameter values as a function of heart rate are determined from long term stored data of the filtered RR values and parameter values. Hysteresis related data and transitory deviations from normal (e.g. vasospasm related data) are excluded from the computation of normal upper and lower parameter bounds.
Core Innovation
The invention describes a cardiac event detection system for detecting a cardiac event in a patient. The system includes at least two sensors that sense an analog signal from the patient's heart and an analog-to-digital circuit system that digitizes the electrical signal to produce a digitized waveform. A processor computes heart rate time series data and a second parameter value data from the digitized waveform over a plurality of heart beats, and defines the heart rate as a first parameter.
The processor low pass filters and averages the heart rate time series data and the second parameter value data over a plurality of heart beats. It establishes upper and lower boundary values of the filtered and averaged heart rate time series, including upper and lower band curves B_high(RR) and B_low(RR), and compares the filtered parameter value data of at least one heart beat with the upper and lower boundary values determined from upper and lower normal boundaries established from the filtered and averaged heart rate time series data.
The invention further excludes transitory data tied to rapid heart-rate changes and other transient events, and uses long-term stored filtered data to form normal band curves while suppressing hysteresis-driven false positives. It applies gated long-term and short-term RR trend criteria, persistence criteria and programmable thresholds, and ischemia-event tests that combine absolute band deviation with long-term averaged slope, including multiple parameters combined in an OR/AND style. The system also includes body-position/QRS-amplitude shift compensation and periodic band update over RR bins, including mechanisms for band updating when data are missing and for excluding excluded-event data from band computation.
Claims Coverage
The independent claims (four total) cover a cardiac event detection system that digitizes heart signals, computes heart rate and heart-rate-dependent parameter behavior, builds upper and lower normal boundaries including heart-rate-dependent bands, and performs cardiac event detection by comparing per-beat parameter values to those boundaries with additional filtering, exclusions, and gating by heart-rate change criteria and corrected function values. The inventive features include boundary establishment from filtered and averaged data, exclusion of parameter data sets based on heart-rate-dependent or persistence-related criteria, detection tests as a function of computed change in heart rate, and correction of parameter-change functions based on changes in heart rate.
Filtering and averaged boundary-based event detection
Low pass filtering and averaging of the heart rate time series data and the second parameter value data, establishing upper and lower boundary values of the filtered and averaged heart rate time series, and performing a cardiac event detection test by comparing the filtered parameter value data of at least one beat with upper and lower normal boundaries established from the filtered and averaged heart rate time series data.
Excluding parameter data sets to generate heart-rate-dependent boundaries
Excluding a first parameter value data set as a function of heart rate and associated with normal sinus rhythm from determination of upper and lower boundary values, generating upper and lower normal boundary values based upon a non-excluded parameter set defining a non-excluded parameter set as a function of heart rate, and performing a cardiac event detection test by comparing a parameter value with its associated heart rate dependent upon the upper and lower normal boundary values.
Event detection test as a function of computed change in heart rate
Computing a change in the heart rate from filtered heart rate data and performing a cardiac event detection test, as a function of the computed change in heart rate.
Correcting a parameter-change function according to change in heart rate
Computing the value of a function as a function of changes in the value of the parameter, correcting the value of the function according to a change in heart rate to generate a corrected function value, and performing a cardiac event detection test based on the corrected function value.
Taken together, the independent claims define event detection that digitizes heart analog signals, computes heart rate and parameter value data, derives heart-rate-dependent normal boundaries from filtered and averaged data while optionally excluding certain parameter data sets, and performs detection tests using comparisons to boundaries or using detection logic based on computed heart-rate change or corrected parameter-change functions.
Stated Advantages
Not explicitly described in patent.
Documented Applications
Not explicitly described in patent.
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