EP-4734847-A1 - CARDIAC SIGNAL T-WAVE END TIME DETECTION USING MAXIMUM POINT OF GRADIENT SIGNAL

Abstract

An example device for detecting one or more parameters of a cardiac signal is disclosed herein. The device includes one or more electrodes and sensing circuitry configured to sense a cardiac signal via the one or more electrodes. The device further includes processing circuitry configured to determine a representative signal based on the cardiac signal, the representative signal having a single polarity, and determine a T-wave end time of the cardiac signal based on a maximum point on a gradient signal of the cardiac signal.

Inventors

• ARANDA HERNANDEZ, ALFONSO
• DEGROOT, PAUL J.
• LOEN, Vera
• VOS, Marc A.
• MEINE, MATHIAS

Assignees

• Medtronic, Inc.
• UMC Utrecht Holding B.V.

Dates

Publication Date

20260506

Application Date

20240521

Claims (15)

1. 1. A medical device comprising: a memory device; sensing circuitry configured to sense a cardiac signal via a plurality of electrodes; and processing circuitry configured to: determine, by the processing circuitry based on the cardiac signal sensed by the sensing circuitry of the medical device, a digital signal comprising a plurality of digital samples representing the cardiac signal; determine, by the processing circuitry and based a time window of the plurality of digital samples, a gradient signal of a set of digital samples; determine, by the processing circuitry and during the time window, a maximum point of the gradient signal; and store on the memory device, by the processing circuitry and based on the maximum point, data indicating a T-wave end time.
2. 2. The medical device of claim 1, wherein to determine the gradient signal the processing circuitry is further configured to: blank samples outside the time window; and determine a plurality of differences between amplitudes of the plurality of digital samples within the time window.
3. 3. The medical device of claim 1 or 2, wherein to determine the maximum point of the gradient signal, the processing circuitry is further configured to: filter, by a bandpass filter, the gradient signal into a filtered signal; determine, based on a peak of the filtered signal, the maximum point of the filtered signal.
4. 4. The medical device of any one or more of claims 1 to 3, wherein to determine the time value, the processing circuitry is further configured to: determine, based on the gradient signal, a squared gradient signal; and determine, based on the squared gradient signal, a programmable energy point of the squared gradient signal.
5. 5. The medical device of any one or more of claims 1 to 4, wherein the time window corresponds to the set of digital samples and wherein the set of digital samples has a predetermined relationship to a sample of the plurality of digital samples.
6. 6. The medical device of any one or more of claims 1 to 5, wherein the time window comprises adjacent samples determined during a fixed time duration, and wherein a center of the time window corresponds to a middle sample of the set of digital samples.
7. 7. The medical device of any one or more of claims 1 to 6, wherein the time window corresponds to samples determined during a time duration, and the time duration is based on a heart rate represented by the cardiac signal.
8. 8. The medical device of any one or more of claims 1 to 7, wherein to determine the time window the processing circuitry is configured to: determine, based on the gradient signal, a squared gradient signal; determine, based on the squared gradient signal, the programmable energy point by an area under the squared gradient signal; and determine the time window based on the programmable energy point.
9. 9. The medical device of any one or more of claims 1 to 8, wherein the medical device comprises an implantable medical device.
10. 10. The medical device of any one or more of claims 1 to 9, wherein the medical device comprises at least one of a pacemaker, a cardioverter, or a defibrillator.
11. 11. A system comprising: an implantable medical device configured to sense a cardiac signal; and processing circuitry configured to: determine, by the processing circuitry and based on the cardiac signal sensed by the implantable medical device of the system, a digital signal comprising a plurality of digital samples representing the cardiac signal; determine, by the processing circuitry and based on a time window of the plurality of digital samples, a gradient signal of a set of digital samples; determine, by the processing circuitry and during the time window, a maximum point of the gradient signal; and store on a memory device of the implantable medical device, by the processing circuitry and based on the maximum point, data indicating a T-wave end time.
12. 12. The system of claim 11, wherein to determine the gradient signal the processing circuitry is further configured to: blank samples outside the time window; and determine a plurality of differences between amplitudes of the plurality of digital samples with the time window.
13. 13. The system of claim 11 or 12, wherein to determine the maximum point of the gradient signal, the processing circuitry is further configured to: filter, by a bandpass filter, the gradient signal into a filtered signal; determine, based on a peak of the filtered signal, the maximum point of the filtered signal.
14. 14. The system of any one or more of claims 11 to 13, wherein to determine the time value, the processing circuitry is further configured to: determine, based on the gradient signal, a squared gradient signal; and determine, based on the squared gradient signal, a programmable energy point of the squared gradient signal.
15. 15. The system of any one or more of claims 11 to 14, wherein the time window corresponds to the set of digital samples and wherein the set of digital samples has a predetermined relationship to a sample of the plurality of digital samples.

Description

CARDIAC SIGNAL T- WAVE END TIME DETECTION USING MAXIMUM POINT OF GRADIENT SIGNAL [0001] This application claims the benefit of priority from U.S. Provisional Patent Application No. 63/511,396, filed June 30, 2023, the entire content of which is incorporated herein by reference. TECHNICAL FIELD [0002] This disclosure relates to cardiac monitoring and, more particularly, to evaluation of features of cardiac signals. BACKGROUND [0003] Cardiac signal analysis may be performed by a variety of devices, such as implantable medical devices (IMDs) and external devices (e.g., smart watches, fitness monitors, mobile devices, Holter monitors, wearable defibrillators, or the like). For example, devices may be configured to process cardiac signals (e.g., cardiac electrograms (EGMs) and electrocardiograms (ECGs)) sensed by one or more electrodes. Features of cardiac signals may include the P-wave, Q-wave, R-wave, S-wave, QRS-complex, and T-wave. Accurate detection and delineation of features cardiac signals, such as T-waves, may be of importance for improving operation of devices. As examples, detection of an occurrence of T-waves may be used to better identify clinically significant cardiac intervals, such as a QT interval or another cardiac activation recovery interval, or time delivery of therapy from the IMD. [0004] Cardiac pacing is one type of therapy delivered to patients to treat a wide variety of cardiac dysfunctions. Cardiac pacing is often delivered by the IMD. An implantable cardioverter-defibrillator (ICD) may provide pacing functionality and also provide cardioversion or defibrillation (referred to as antitachyarrhythmia shock therapy) in response to a detection of a cardiac tachyarrhythmias, if needed. Detection of a variety of features of the cardiac signal may be used by the IMD to determine whether IMD should deliver therapy, for example pacing or antitachyarrhythmia shock therapy, to the patient. SUMMARY [0005] In general, the disclosure is directed to devices and techniques for identifying one or more features and/or determining one or more parameters of a cardiac signal (e.g., EGM and/or ECG) of a patient. For example, the disclosure describes techniques for identifying the end of a T-wave, which may allow a more robust delineation of cardiac signal features. This improved identification of the end of the T-wave may, for example, allow determination of variability of the activation recovery interval (ARI), e.g., a QT interval or interval measured from the start of the QRS complex to the end of the T-wave, which may enable determining whether a patient is experiencing or will experience a tachyarrhythmia. In some examples, a determination that a patient is experiencing or will experience a tachyarrhythmia may enable an IMD to deliver therapy to the patient to terminate or prevent a predicted tachyarrhythmia, which therapy need not necessarily include an anti-tachyarrhythmia shock. Because, anti-tachyarrhythmia shocks may cause significant patient discomfort and do not always terminate a lethal tachyarrhythmia, the ability to deliver a non-shock therapy that prevents or terminates a predicted tachyarrhythmia may be considered a significant improvement to the operation of a medical device system to monitor and treat a patient. [0006] Signal processing techniques that may be used by processing circuitry, e.g., of the IMD, to delineate the one or more features may include, for example, determining a programmable energy point or a maximum point of a gradient signal. The gradient signal may be calculated from a representative signal created based on the cardiac signal by derivation, and has a single polarity. The processing circuitry may be configured to determine the end of a T-wave based on determining a programmable energy point or a maximum point of a gradient signal of the cardiac signal. The processing circuitry may blank a portion of the cardiac signal to prevent some features of the signal (e.g., QRS complex) from interfering with the processing circuitry determining a programmable energy point or maximum of the gradient signal. [0007] The processing circuitry may determine, based on a portion of the signal that has not been blanked, a squared gradient signal having a programmable energy point. By multiplying the gradient signal by an exponential (e.g., squaring the blanked signal), the processing circuitry may determine a squared gradient signal. Using a technique to determine the area under the curve, the IMD may set, as a predetermined percentage value, a programmable energy point corresponding to a quotient based on an area under the squared gradient curve. The quotient may result from the division of a portion of the area under the squared gradient signal divided by the total area under the squared gradient signal. The processing circuitry may determine the programmable energy point by calculating a plurality of quotients based on a plurality of area portions under the squared gradient sign