# US 10,368,767 B2 · Medical devices for mapping cardiac tissue

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- Number: US 10,368,767 B2
- Document ID: US10368767B2
- Status: Granted
- Kind: B2
- Application number: 16/154,258
- Filed: 2018-10-08
- Published: 2019-02-07
- Granted: 2019-08-06
- Earliest claimed: 2014-06-20
- Assignees: Boston Scientific Scimed, Inc.
- Applicants: Boston Scientific Scimed Inc.
- Inventors: Jacob I. Laughner; Shibaji Shome; Paul Hultz; Kevin J. Stalsberg; Pramodsingh H. Thakur
- Web page: https://patentgrep.com/patent/US10368767B2

## CPC

- A61B 5/367: Electrophysiological study [EPS], e.g. electrical activation mapping or electro-anatomical mapping
- A61B 5/287: Holders for multiple electrodes, e.g. electrode catheters for electrophysiological study [EPS]
- A61B 5/339: Displays specially adapted therefor
- A61B 5/35: by template matching
- A61B 5/361: Detecting fibrillation
- A61B 5/363: Detecting tachycardia or bradycardia
- A61B 5/6858: {with a distal basket, e.g. expandable basket}
- A61B 5/743: {Displaying an image simultaneously with additional graphical information, e.g. symbols, charts, function plots}
- A61B 18/1492: {having a flexible, catheter-like structure, e.g. for heart ablation (A61B18/1477 takes precedence)}
- A61B 5/7264: {Classification of physiological signals or data, e.g. using neural networks, statistical classifiers, expert systems or fuzzy systems}
- A61B 2018/00357: {Endocardium}
- A61B 2018/00577: {Ablation}
- A61B 2018/00839: {Bioelectrical parameters, e.g. ECG, EEG}
- A61B 2505/05: Surgical care
- A61B: DIAGNOSIS; SURGERY; IDENTIFICATION (usefulness limited to only animals A61D)

## Abstract

Medical devices and methods for making and using medical devices are disclosed. An example medical device may include a system for mapping the electrical activity of the heart. The system may include a catheter shaft with a plurality of electrodes. The system may also include a processor. The processor may be capable of collecting a set of signals from at least one of the plurality of electrodes. The set of signals may be collected over a time period. The processor may also be capable of calculating at least one propagation vector from the set of signals, generating a data set from the at least one propagation vector, generating a statistical distribution of the data set and generating a visual representation of the statistical distribution.

## Claims

### Claim 1

A method for mapping the electrical activity of a targeted tissue region in a body, the method comprising:
receiving a data set corresponding to a plurality of cardiac signals sensed over a period of time;
determining propagation angles for the plurality of signals using the data set, the propagation angles including at least one propagation angle exceeding a threshold level of randomness; and
generating a propagation map including a visual indicator corresponding to the at least one propagation angle exceeding the threshold level of randomness.

### Claim 2 (depends on 1)

The method of claim 1, further comprising determining vector magnitudes for the plurality of signals.

### Claim 3 (depends on 1)

The method of claim 1, further comprising generating a diagnostic image including a visual representation, wherein the visual representation includes displaying one or more of a histogram, a circular histogram, a two-dimensional grid, a three-dimensional model, a three-dimensional surface and a propagation vector.

### Claim 4 (depends on 1)

The method of claim 1, further comprising performing a statistical analysis on the propagation angles.

### Claim 5 (depends on 4)

The method of claim 4, wherein performing the statistical analysis comprises determining statistical distributions of the propagation angles and the method further comprising comparing the statistical distributions.

### Claim 6 (depends on 5)

The method of claim 5, further comprising characterizing a shape of the statistical distributions by performing algorithmic computations.

### Claim 7 (depends on 6)

The method of claim 6, wherein performing an algorithmic computation comprises calculating at least one of the following: standard deviation, entropy, kurtosis, skewness or the circular average of the data set.

### Claim 8 (depends on 1)

The method of claim 1, further comprising generating at least one representative metric and wherein the at least one representative metric correlates to the propagation angles.

### Claim 9 (depends on 8)

The method of claim 8, further comprising correlating the at least one representative metric to a metric indicator.

### Claim 10 (depends on 9)

The method of claim 9, wherein the metric indicator comprises at least one of a representative: number, color, texture, shape, and other visual indicator that can be easily visualized on a display.

### Claim 11

A non-transitory computer-readable medium comprising executable instructions that, when executed by one or more processors, cause the one or more processors to:
receive a data set corresponding to a plurality of cardiac signals sensed by a plurality of electrodes over a period of time;
determine propagation angles for the plurality of signals;
determine when at least one propagation angle of the propagation angles exceeds a threshold level of randomness; and
generate a propagation map including a visual indicator corresponding to the at least one propagation angle.

### Claim 12 (depends on 11)

The non-transitory computer-readable medium of claim 11, further comprising executable instructions that when executed by one or more processors cause the one or more processors to determine vector magnitudes for the plurality of signals.

### Claim 13 (depends on 11)

The non-transitory computer-readable medium of claim 11, further comprising executable instructions that when executed by one or more processors cause the one or more processors to generate a diagnostic image including a visual representation, wherein the visual representation includes displaying one or more of a histogram, a circular histogram, a two-dimensional grid, a three-dimensional model, a three-dimensional surface and a propagation vector.

### Claim 14 (depends on 11)

The non-transitory computer-readable medium of claim 11, further comprising executable instructions that when executed by one or more processors cause the one or more processors to perform a statistical analysis on the propagation angles.

### Claim 15 (depends on 14)

The non-transitory computer-readable medium of claim 14, wherein performing the statistical analysis comprises determining statistical distributions of the propagation angles and the method further comprising comparing the statistical distributions.

### Claim 16 (depends on 15)

The non-transitory computer-readable medium of claim 15, further comprising executable instructions that when executed by one or more processors cause the one or more processors to characterize a shape of the statistical distributions by performing algorithmic computations.

### Claim 17 (depends on 16)

The non-transitory computer-readable medium of claim 16, wherein performing an algorithmic computation comprises calculating at least one of the following: standard deviation, entropy, kurtosis, skewness or the circular average of the data set.

### Claim 18 (depends on 11)

The non-transitory computer-readable medium of claim 11, further comprising executable instructions that when executed by one or more processors cause the one or more processors to generate at least one representative metric and wherein the at least one representative metric correlates to the propagation angles.

### Claim 19 (depends on 18)

The non-transitory computer-readable medium of claim 18, further comprising executable instructions that when executed by one or more processors cause the one or more processors to correlate the at least one representative metric to a metric indicator.

### Claim 20 (depends on 19)

The non-transitory computer-readable medium of claim 19, wherein the metric indicator comprises at least one of a representative: number, color, texture, shape, and other visual indicator that can be easily visualized on a display.