Automatic detection of body planes of rotation

Patent metadata

Field	Value
Publication number	US-11596342-B2
Application number	US-202016909778-A
Country	US
Kind code	B2
Filing date	Jun 23, 2020
Priority date	Sep 19, 2019
Publication date	Mar 7, 2023
Grant date	Mar 7, 2023

Abstract

Techniques are disclosed for automatically calibrating a reference orientation of an implantable medical device (IMD) within a patient. In one example, sensors of an IMD sense a plurality of orientation vectors of the IMD with respect to a gravitational field. Processing circuitry of the IMD processes the plurality of orientation vectors to identify an upright vector that corresponds to an upright posture of the patient. The processing circuitry classifies the plurality of orientation vectors with respect to the upright vector to define a sagittal plane of the patient and a transverse plane of the patient. The processing circuitry determines, based on the upright vector, the sagittal plane, and the transverse plane, a reference orientation of the IMD within the patient. As the orientation of the IMD within the patient changes over time, the processing circuitry may recalibrate its reference orientation and accurately detect a posture of the patient.

First claim

What is claimed is:

1. A method comprising:
sensing, by one or more sensors of an implantable medical device (IMD), a plurality of orientation vectors of the IMD with respect to a gravitational field;
clustering, by processing circuitry of the IMD, the plurality of orientation vectors into a first subset of orientation vectors;
defining, by the processing circuitry and based on the first subset of orientation vectors, an upright vector, the upright vector corresponding to an upright posture of a patient;
clustering, by the processing circuitry, the plurality of orientation vectors into a second subset of orientation vectors;
defining, by the processing circuitry and based on the second subset of orientation vectors and the upright vector, a transverse plane of the patient;
clustering, by the processing circuitry, the plurality of orientation vectors into a third subset of orientation vectors;
defining, by the processing circuitry and based on the third subset of orientation vectors and the upright vector, a sagittal plane of the patient; and
determining, by the processing circuitry and based on the upright vector, the transverse plane, and the sagittal plane, a reference orientation of the IMD.

2. The method of claim 1 ,
wherein sensing the plurality of orientation vectors comprises sensing the plurality of orientation vectors over a period of time,
wherein clustering the plurality of orientation vectors into the first subset of orientation vectors comprises determining one or more orientation vectors of the plurality of orientation vectors that correspond to an activity level of the patient that exceeds a patient activity threshold, and
wherein defining, based on the first subset of orientation vectors, the upright vector comprises averaging the one or more orientation vectors to compute the upright vector.

3. The method of claim 1 ,
wherein sensing the plurality of orientation vectors comprises sensing the plurality of orientation vectors over a period of time,
wherein clustering the plurality of orientation vectors into the first subset of orientation vectors comprises determining one or more orientation vectors of the plurality of orientation vectors that correspond to a walking activity of the patient, and
wherein defining, based on the first subset of orientation vectors, the upright vector comprises averaging the one or more orientation vectors to compute the upright vector.

4. The method of claim 1 ,
wherein sensing the plurality of orientation vectors comprises sensing the plurality of orientation vectors over a period of time,
wherein clustering the plurality of orientation vectors into the first subset of orientation vectors comprises:
receiving, from an external device, an indication of a posture of the patient for each of the plurality of orientation vectors;
determining, based on the indications of the posture of the patient, one or more orientation vectors of the plurality of orientation vectors that correspond to an upright posture of the patient, and

wherein defining, based on the first subset of orientation vectors, the upright vector comprises averaging the one or more orientation vectors to compute the upright vector.

5. The method of claim 1 ,
wherein clustering the plurality of orientation vectors into the second subset of orientation vectors comprises:
for each orientation vector of the plurality of orientation vectors:
determining an angle between the orientation vector and the upright vector;
comparing the angle between the orientation vector and the upright vector to a predetermined upright angle; and
classifying, based on the comparison, the orientation vector as one of the first subset of orientation vectors, the first subset of orientation vectors associated with the upright posture of the patient or one of the second subset of orientation vectors, the second subset of orientation vectors associated with a recumbent posture of the patient, and

wherein defining, based on the second subset of orientation vectors and the upright vector, the transverse plane of the patient comprises defining the transverse plane of the patient as a plane between the first subset of orientation vectors associated with the upright posture of the patient and the second subset of orientation vectors associated with the recumbent posture of the patient.

6. The method of claim 5 , wherein clustering the orientation vector as one of the first subset of orientation vectors associated with the upright posture of the patient or one of the second subset of orientation vectors associated with the upright posture of the patient comprises:
in response to determining that the angle between the orientation vector and the upright vector is less than the predetermined upright angle, classifying the orientation vector as one of the first subset of orientation vectors associated with the upright posture of the patient; and
in response to determining that the angle between the orientation vector and the upright vector is greater than or equal to the predetermined upright angle, classifying the orientation vector as one of the second subset of orientation vectors associated with the recumbent posture of the patient.

7. The method of claim 1 ,
wherein clustering the plurality of orientation vectors into the third subset of orientation vectors comprises:
associating each orientation vector of the plurality of orientation vectors with a grid element of a plurality of grid elements of a sphere based on an angle formed by the orientation vector and the upright vector;
identifying a subset of the plurality of grid elements forming an angle with the upright vector that is less than a predetermined upright angle; and
applying a clustering algorithm to identify a cluster of grid elements of the plurality of grid elements that are neighbors to the subset of the plurality of grid elements,

wherein defining, based on the third subset of orientation vectors and the upright vector, the sagittal plane of the patient comprises:
determining a main eigenvector for the cluster of grid elements, wherein the main eigenvector comprises a higher eigenvalue than each other eigenvector of a plurality of eigenvectors of the cluster of grid elements; and
determining, based on the cross product of the upright vector with the main eigenvector, a normal vector, wherein the normal vector defines the sagittal plane of the patient.

8. The method of claim 1 ,
wherein the reference orientation of the IMD is a reference orientation of the IMD within the patient, and
wherein the method further comprises determining, based on the reference orientation of the IMD within the patient, a posture of the patient.

9. The method of claim 8 , wherein determining the posture of the patient comprises:
sensing, by the one or more sensors of an IMD, a current orientation vector of the patient with respect to the gravitational field; and
determining, by the processing circuitry and based on a relationship of the current orientation vector to the reference orientation of the IMD, the posture of the patient.

10. The method of claim 1 , wherein the defined transverse plane of the patient is not substantially perpendicular to the defined sagittal plane of the patient.

11. The method of claim 1 , wherein clustering the plurality of orientation vectors into the first subset of orientation vectors comprises:
determining at least one orientation vector of the plurality of orientation vectors that is concurrent with a high activity level of the patient; and
rejecting the at least one orientation vector to identify the upright vector of the plurality of orientation vectors.

12. The method of

Assignees

• Medtronic Inc

Inventors

• Radtke Andrew
• Haddad Tarek D
• Galarneau Michelle M
• Sharma Vinod
• Wilkinson Jeffrey D
• Lee Brian B
• Warman Eduardo N

Classifications

• G06F18/23

  Clustering techniques · CPC title

• A61B5/7207

  of noise induced by motion artifacts · CPC title

• A61B5/02156

  Calibration means · CPC title

• A61B5/1118

  Determining activity level · CPC title

• G06F18/2411

  based on the proximity to a decision surface, e.g. support vector machines · CPC title