Medical device with acoustic sensor

• US 10,321,877 B2
• Filed: 03/18/2016
• Issued: 06/18/2019
• Est. Priority Date: 03/18/2015
• Status: Active Grant

• Current Assignee: Zoll Medical Corporation (Asahi Kasei Corporation)
• Original Assignee: Zoll Medical Corporation (Asahi Kasei Corporation)
• Inventors: Volpe, Shane S., Frank, Gregory R., Kaib, Thomas E., Szymkiewicz, Steven J., Freeman, Gary A.
• Primary Examiner(s): Layno, Carl H
• Assistant Examiner(s): Morales, Jon Eric C
• Application Number:
  US15/074,020
• Publication Number:
  US 20160270738A1
• Time in Patent Office: 1,187 Days
• Field of Search: 600587, 600301, 600509, 600528, 600586, 607 6, 704270
• CPC Class Codes: A61B 2562/0219 Inertial sensors, e.g. accelerometers, gyroscopes, tilt switches
• CPC Class Codes: A61B 2562/17 Comprising radiolucent components
• CPC Class Codes: A61B 5/08 Detecting, measuring or recording devices for evaluating the respiratory organs A61B5/0205 takes precedence
• CPC Class Codes: A61B 5/25 Bioelectric electrodes therefor
• CPC Class Codes: A61B 5/256 Wearable electrodes, e.g. having straps or bands
• CPC Class Codes: A61B 5/276 Protection against electrode failure
• CPC Class Codes: A61B 5/28 for electrocardiography [ECG]
• CPC Class Codes: A61B 5/363 Detecting tachycardia or bradycardia
• CPC Class Codes: A61B 5/4818 Sleep apnoea
• CPC Class Codes: A61B 5/6805 Vests
• CPC Class Codes: A61B 5/6823 Trunk, e.g., chest, back, abdomen, hip
• CPC Class Codes: A61B 5/6844 Monitoring or controlling distance between sensor and tissue
• CPC Class Codes: A61B 5/721 using a separate sensor to detect motion or using motion information derived from signals other than the physiological signal to be measured
• CPC Class Codes: A61B 5/7278 Artificial waveform generation or derivation, e.g. synthesising signals from measured signals A61B5/327 takes precedence
• CPC Class Codes: A61B 7/003 Detecting lung or respiration noise
• CPC Class Codes: A61B 7/04 Electric stethoscopes microphones, acoustic transducers therefor H04R
• CPC Class Codes: A61N 1/046 Specially adapted for shock therapy, e.g. defibrillation
• CPC Class Codes: A61N 1/0484 Garment electrodes worn by the patient
• CPC Class Codes: A61N 1/36542 controlled by body motion, e.g. acceleration
• CPC Class Codes: A61N 1/3655 controlled by body or blood temperature
• CPC Class Codes: A61N 1/37247 : User interfaces, e.g. input or presentation means
• CPC Class Codes: A61N 1/37258 : Alerting the patient
• CPC Class Codes: A61N 1/37282 : characterised by communication with experts in remote locations using a network
• CPC Class Codes: A61N 1/3904 : External heart defibrillators [EHD]
• CPC Class Codes: A61N 1/39044 : in combination with cardiopulmonary resuscitation [CPR] therapy
• CPC Class Codes: A61N 1/3993 : User interfaces for automatic external defibrillators

Abstract

In at least one example, a medical device is provided. The medical device includes at least one therapy electrode, at least one electrocardiogram (ECG) electrode, at least one acoustic sensor, and at least one processor coupled with the at least one acoustic sensor, the at least one ECG electrode, and the at least one therapy electrode. The at least one processor can receive at least one acoustic signal from the at least one acoustic sensor, receive at least one electrode signal from the ECG electrode, detect at least one unverified cardiopulmonary anomaly using the at least one electrode signal, and verify the at least one unverified cardiopulmonary anomaly with reference to data descriptive of the at least one acoustic signal.

Claims

1. A medical device comprising:

at least one electrocardiogram (ECG) electrode;

at least one acoustic sensor comprising at least one accelerometer; and

at least one processor coupled with the at least one acoustic sensor and the at least one ECG electrode and configured

to receive at least one signal from the at least one accelerometer,

to partition the at least one signal into at least one acoustic signal comprising frequencies greater than approximately 10 hertz and at least one motion signal comprising frequencies less than approximately 10 hertz,

to receive at least one electrical signal from the at least one ECG electrode, and

to detect at least one cardiopulmonary anomaly using the at least one electrical signal and the at least one acoustic signal.

2. The medical device of claim 1, wherein the at least one processor is configured to detect the at least one cardiopulmonary anomaly at least in part by identifying the at least one cardiopulmonary anomaly using the at least one electrical signal and verifying the at least one cardiopulmonary anomaly using the at least one acoustic signal.

3. The medical device of claim 1, further comprising a garment, wherein the at least one ECG electrode and the at least one acoustic sensor are integrated with the garment.

4. The medical device of claim 3, further comprising at least one therapy electrode coupled with the at least one processor, the at least one therapy electrode integrated with the garment.

5. The medical device of claim 1, wherein the at least one acoustic signal comprises at least one of S1, S2, S3, and S4 signals.

6. The medical device of claim 1, wherein the at least one processor is configured to detect the at least one cardiopulmonary anomaly at least in part by calculating, based on the at least one acoustic signal, at least one of electromechanical activation time (EMAT), EMAT as a percentage of cardiac cycle time, systolic dysfunction index, and left ventricular systolic time.

7. The medical device of claim 1, wherein the at least one cardiopulmonary anomaly comprises at least one of supraventricular tachycardia, ventricular tachycardia, pulseless electrical activity, asystole, a heart murmur, sleep apnea, and respiratory failure.

8. The medical device of claim 1, wherein the at least one processor is configured to detect disconnection of the at least one ECG electrode from a patient'"'"'s skin based on the at least one acoustic signal.

9. The medical device of claim 1, wherein the at least one processor is configured to partition the at least one signal into a first frequency band for subject motion, a second frequency band for chest compression motion, a third frequency band for heart sounds, and a fourth frequency band for breath sounds.

10. The medical device of claim 9, wherein the first frequency band comprises frequencies less than approximately 3 hertz, the second frequency band comprises frequencies between approximately 3 and 20 hertz, the third frequency band comprises frequencies between approximately 20 hertz and 150 hertz, and the fourth frequency band comprises frequencies between approximately 300 to 1200 hertz.

11. The medical device of claim 1, wherein the medical device comprises an ambulatory medical device.

12. A method of monitoring a subject using a wearable defibrillator comprising at least one electrocardiogram (ECG) electrode and at least one acoustic sensor comprising at least one accelerometer, the method comprising:

receiving at least one signal from the at least one accelerometer;

partitioning the at least one signal into at least one acoustic signal comprising frequencies greater than approximately 10 hertz and at least one motion signal comprising frequencies less than approximately 10 hertz;

receiving at least one electrical signal from the at least one ECG electrode; and

detecting at least one cardiopulmonary anomaly using the at least one electrical signal and the at least one acoustic signal.

13. The method of claim 12, wherein partitioning the at least one signal comprises partitioning the at least one signal into at least one of S1, S2, S3, and S4 signals.

14. The method of claim 12, wherein detecting the at least one cardiopulmonary anomaly comprises calculating, based on the at least one acoustic signal, at least one of electromechanical activation time (EMAT), EMAT as a percentage of cardiac cycle time, systolic dysfunction index, and left ventricular systolic time.

15. The method of claim 12, wherein detecting the at least one cardiopulmonary anomaly comprises detecting at least one of supraventricular tachycardia, ventricular tachycardia, pulseless electrical activity, asystole, a heart murmur, sleep apnea, and respiratory failure.

16. The method of claim 12, further comprising detecting the at least one cardiopulmonary anomaly using the at least one electrical signal, the at least one acoustic signal, and the at least one motion signal.

17. The method of claim 12, wherein detecting the at least one cardiopulmonary anomaly comprises identifying the at least one cardiopulmonary anomaly using the at least one electrical signal and verifying the at least one cardiopulmonary anomaly using the at least one acoustic signal.

18. A medical device comprising:

at least one electrocardiogram (ECG) electrode;

at least one acoustic sensor comprising at least one accelerometer; and

at least one processor coupled with the at least one acoustic sensor and the at least one ECG electrode and configured

to receive at least one signal from the at least one accelerometer,

to partition the at least one signal into at least one acoustic signal and at least one motion signal,

wherein to partition the at least one signal into the at least one acoustic signal and the at least one motion signal comprises to partition the at least one signal into a first frequency band comprising frequencies less than approximately 3 hertz for subject motion, a second frequency band comprising frequencies between approximately 3 hertz and 20 hertz for chest compression motion, a third frequency band comprising frequencies between approximately 20 hertz and 150 hertz for heart sounds, and a fourth frequency band comprising frequencies between approximately 300 hertz to 1200 hertz for breath sounds,

receive at least one electrical signal from the at least one ECG electrode, and

detect at least one cardiopulmonary anomaly using the at least one electrical signal and the at least one signal.

19. The medical device of claim 18, wherein the at least one processor is configured to detect the at least one cardiopulmonary anomaly at least in part by identifying the at least one cardiopulmonary anomaly using the at least one electrical signal and verifying the at least one cardiopulmonary anomaly using the at least one acoustic signal.

20. The medical device of claim 18, further comprising a garment, wherein the at least one ECG electrode and the at least one acoustic sensor are integrated with the garment.

21. The medical device of claim 20, further comprising at least one therapy electrode coupled with the at least one processor, the at least one therapy electrode integrated with the garment.

22. The medical device of claim 18, wherein the at least one acoustic signal comprises at least one of S1, S2, S3, and S4 signals.

23. The medical device of claim 22, wherein the at least one processor is configured to detect the at least one cardiopulmonary anomaly at least in part by calculating, based on the at least one acoustic signal, at least one of electromechanical activation time (EMAT), EMAT as a percentage of cardiac cycle time, systolic dysfunction index, and left ventricular systolic time.

24. The medical device of claim 18, wherein the at least one cardiopulmonary anomaly comprises at least one of supraventricular tachycardia, ventricular tachycardia, pulseless electrical activity, asystole, a heart murmur, sleep apnea, and respiratory failure.

25. The medical device of claim 18, wherein the at least one processor is configured to detect disconnection of the at least one ECG electrode from a patient'"'"'s skin based on the at least one acoustic signal.