HEART FAILURE EVENT DETECTION AND RISK STRATIFICATION USING HEART SOUND

• US 20150126878A1
• Filed: 10/09/2014
• Published: 05/07/2015
• Est. Priority Date: 11/04/2013
• Status: Abandoned Application

• Current Assignee: Cardiac Pacemakers Incorporated (Boston Scientific Corporation)
• Original Assignee: Cardiac Pacemakers Incorporated (Boston Scientific Corporation)
• Inventors: An, Qi, Zhang, Yi, Averina, Viktoria A., Beck, Kenneth C., Thakur, Pramodsingh Hirasingh
• Application Number:
  US14/510,498
• Publication Number:
  US 20150126878A1
• Time in Patent Office: Days
• US Class Current: 600/484
• CPC Class Codes: A61B 2560/0242 adapted to measure environmental factors, e.g. temperature, pollution
• CPC Class Codes: A61B 5/0031 Implanted circuitry
• CPC Class Codes: A61B 5/01 Measuring temperature of body parts ; Diagnostic temperature sensing, e.g. for malignant or inflamed tissue clinical contact thermometers G01K13/20
• CPC Class Codes: A61B 5/0205 Simultaneously evaluating both cardiovascular conditions and different types of body conditions, e.g. heart and respiratory condition
• CPC Class Codes: A61B 5/024 Detecting, measuring or recording pulse rate or heart rate A61B5/0205, A61B5/021 take precedence
• CPC Class Codes: A61B 5/08 Detecting, measuring or recording devices for evaluating the respiratory organs A61B5/0205 takes precedence
• CPC Class Codes: A61B 5/1118 Determining activity level
• CPC Class Codes: A61B 5/318 Heart-related electrical modalities, e.g. electrocardiography [ECG]
• CPC Class Codes: A61B 5/352 Detecting R peaks, e.g. for synchronising diagnostic apparatus; Estimating R-R interval
• CPC Class Codes: A61B 5/4809 Sleep detection, i.e. determining whether a subject is asleep or not
• CPC Class Codes: A61B 5/6869 Heart
• CPC Class Codes: A61B 5/7275 Determining trends in physiological measurement data; Predicting development of a medical condition based on physiological measurements, e.g. determining a risk factor
• CPC Class Codes: A61B 5/7282 Event detection, e.g. detecting unique waveforms indicative of a medical condition A61B5/4094, A61B5/4818, A61B5/349, A61B5/0823 take precedence
• CPC Class Codes: A61B 5/7292 Prospective gating, i.e. predicting the occurrence of a physiological event for use as a synchronisation signal
• CPC Class Codes: A61B 7/00 Instruments for auscultation
• CPC Class Codes: A61B 7/04 Electric stethoscopes microphones, acoustic transducers therefor H04R
• CPC Class Codes: G16H 50/20 for computer-aided diagnosis, e.g. based on medical expert systems
• CPC Class Codes: G16H 50/30 for calculating health indices; for individual health risk assessment

Abstract

Devices and methods for detecting heart failure (HF) events or identifying patient at elevated risk of developing future HF events are described. A medical device can detect contextual condition associated with a patient, such as an environmental context or a physiologic context, sense a heart sound signal, and perform multiple measurements of heart sound features in response to the detected patient contextual condition meeting specified criterion. The contextual condition includes information correlating to or indicative of a change in metabolic demand of a patient. The medical device can use the physiologic signals to calculate one or more signal metrics indicative of diastolic function of the heart such as a trend of the heart sound features. The medical device can use the signal metrics to detect an HF event or to predict the likelihood of the patient later developing an HF event.

Claims

1. A system, comprising:

an ambulatory medical device (AMD) including;

a context detector circuit configured to detect contextual condition associated with a patient, the contextual condition including information correlating to or indicative of a change in metabolic demand of a patient;

a heart sound analyzer circuit configured to sense from the patient a vibratory or acoustic heart sound (HS) signal, generate one or more HS features using the sensed HS signal, and perform a plurality of HS measurements of the one or more HS features in response to the detected patient contextual condition meeting a specified criterion;

a target event indicator generator circuit configured to calculate one or more signal metrics indicative of diastolic function of a heart of the patient using the plurality of HS measurements, the signal metrics including a trend of the one or more HS features; and

a physiologic event detector circuit coupled to the target event indicator generator circuit, the physiologic event detector circuit configured to detect a target physiologic event using the one or more signal metrics.

2. The system of claim 1, wherein the target event indicator generator circuit is configured to calculate the one or more signal metrics including a trend of third (S3) heard sound, and wherein the physiologic event detector circuit is configured to detect the worsening of heart failure using the trend of S3 heart sound.

3. The system of claim 1, comprising a cardiac signal sensor and an HS feature detection window generator coupled to the heart sound analyzer circuit, wherein:

the cardiac signal sensor is configured to sense a physiologic signal indicative of electrical activity of the heart and to generate one or more cardiac signal features using the sensed physiologic signal; and

the HS feature detection window generator is configured to generate one or more HS feature detection windows using the one or more cardiac signals features;

and wherein the heart sound analyzer circuit configured to detect the S3 heart sound within the one or more HS feature detection windows.

4. The system of claim 3, wherein the HS feature detection window generator is configured to generate an S3 heart sound detection window using at least one cardiac signal feature including an R-wave timing or at least one HS feature including timing of S2 heart sound.

5. The system of claim 1, wherein the heart sound analyzer circuit is configured to detect the S3 heart sound by adaptively tracking timing of historically detected S3 heart sounds.

6. The system of claim 1, wherein the context detector circuit includes a timer/clock circuit capable of determining time of a day, and wherein the heart sound analyzer circuit is configured to measure the plurality of HS measurements during specified time of a day correlating to or indicative of an elevated metabolic demand of the patient.

7. The system of claim 6, wherein the heart sound analyzer circuit is configured to measure the plurality of HS measurements during a period of time excluding night of the day.

8. The system of claim 1, wherein the context detector circuit includes a sleep state detector configured to detect in the patient a time of transition from a sleep state to an awake state, and wherein the heart sound analyzer circuit is configured to measure the plurality of HS measurements in response to the detected transition from the sleep state to the awake state.

9. The system of claim 1, wherein the context detector circuit includes a posture sensor configured to detect a posture of the patient and to classify the posture as one of two or more posture states, and wherein the heart sound analyzer circuit is configured to measure the plurality of HS measurements in response to the detected posture being classified as a specified state correlating to or indicative of an elevated metabolic demand.

10. The system of claim 1, wherein the context detector circuit includes one or more physiologic sensors configured to detect a change in metabolic demand of the patient during a specified period, and wherein the heart sound analyzer circuit is configured to measure the plurality of HS measurements in response to a detection of an increase in the metabolic demand.

11. The system of claim 10, wherein the physiologic sensor includes one or more of a body temperature sensor, a heart rate sensor, a pressure sensor, or a respiration sensor, and the heart sound analyzer circuit is configured to measure the plurality of HS measurements in response to a detection of one or more of an increase in body temperature, an increase in heart rate, an increase in pressure, or an increase in respiration rate.

12. The system of claim 11, further comprising an activity sensor configured to detect activity level of the patient, wherein the heart sound analyzer circuit is configured to measure the plurality of HS measurements in response to a detection of an increase in the metabolic demand and the detected activity level below a specified threshold.

13. A system, comprising:

a signal analyzer circuit, including;

a context detector circuit configured to receive contextual condition associated with a patient, the contextual condition including information correlating to or indicative of a change in the metabolic demand of a patient;

a heart sound analyzer circuit configured to receive a vibratory or acoustic heart sound (HS) signal of the patient, generate one or more HS features using the sensed HS signal, and measure a plurality of HS measurements of the one or more HS features in response to the received patient contextual condition meeting a specified criterion; and

a signal metrics generator circuit configured to calculate one or more signal metrics indicative of diastolic function of a heart of the patient using the plurality of HS measurements, the signal metrics including a trend of the one or more HS features; and

a risk stratifier circuit configured to generate a composite risk indicator using the one or more signal metrics, the composite risk indicator indicative of the likelihood of the patient developing a future event indicative of a new or worsening of an existing disease.

14. The system of claim 13, further comprising a cardiac signal sensor and a HS feature detection window generator coupled to the heart sound analyzer circuit, wherein:

the cardiac signal sensor is configured to sense a physiologic signal indicative of cardiac electrical activity and to generate one or more cardiac signal features using the sensed physiologic signal; and

the HS feature detection window generator is configured to generate one or more HS feature detection windows using the one or more cardiac signals features, the one or more HS feature detection windows including an S3 detection window;

and wherein the heart sound analyzer circuit is configured to detect an S3 heart sound within the S3 detection window.

15. The system of claim 13, wherein the risk stratifier circuit is configured to generate two or more categorical risk levels using a comparison between the composite risk indicator and a reference measure, the two or more categorical risk levels indicative of elevated risk of the patient developing a future event indicative of worsening of heart failure.

16. A method, comprising:

detecting a contextual condition associated with a patient, the contextual condition including information correlating to or indicative of elevated metabolic demand of a patient;

sensing from the patient a heart sound (HS) signal;

generating one or more HS features using the sensed HS signal;

measuring a plurality of HS measurements of the one or more HS features in response to the detected patient contextual condition meeting a specified criterion; and

calculating one or more signal metrics indicative of diastolic function of the heart using the plurality of HS measurements, the signal metrics including a trend of the one or more HS features.

17. The method of claim 16, wherein detecting the contextual condition includes detecting time of a day, and wherein measuring the plurality of HS measurements includes measuring a plurality of HS measurements of S3 heart sound in response to the detected time of the day correlating to or indicative of elevated metabolic demand.

18. The method of claim 16, wherein detecting the contextual condition includes, using one or more physiologic sensors, detecting at least one of a time of transition from a sleep state to an awake state, an increase in body temperature, an increase in heart rate, an increase in pressure, a decrease in activity level, or an increase in respiration rate.

19. The method of claim 16, comprising:

sensing a physiologic signal indicative of cardiac electrical activity; and

generating one or more cardiac signal features using the sensed physiologic signal;

and wherein generating the one or more HS features includes generating S3 heart sound using the one or more cardiac signals features and the sensed HS signal.

20. The method of claim 16, further comprising at least one of:

detecting a target physiologic event indicative of worsening of heart failure using the one or more signal metrics;

or

generating a composite risk indicator using the selected one or more signal metrics and classifying the patient into one of two or more categorical risk levels, the composite risk indicator indicative of the likelihood of the patient developing a future event indicative of worsening of heart failure.