IP Library Granted Patent US 8,444,564
Granted Patent B2
US 8,444,564 · App. 12/364,267 · Granted May 21, 2013

Noninvasive diagnostic system

Inventors: Mohamed M. Mahfouz (Knoxville, TN); Rick Komistek (Knoxville, TN); Ray C. Wasielewski (New Albany, OH)
Assignee: JointVue, LLC
View Patent ↗
Loading inventors, assignments & file history…
Monitor This Case
Get email alerts when status or documents change.
Order Certified Copies
Most orders are placed with the USPTO same day — all within 24 business hours.
Order via The Patent Place →
Pre-filled with this patent's details
Quick Facts
Patent No.
US 8,444,564
App. No.
12/364,267
Granted
May 21, 2013
Kind
B2
Abstract

A method for diagnosing a joint condition includes in one embodiment: creating a 3d model of the patient specific bone; registering the patient's bone with the bone model; tracking the motion of the patient specific bone through a range of motion; selecting a database including empirical mathematical descriptions of the motion of a plurality actual bones through ranges of motion; and comparing the motion of the patient specific bone to the database.

Claims (39)

1. A method of tracking motion of an actual patient bone using creating a patient specific bone model, the method comprising:

acquiring A-mode pulse echo ultrasound signals of the actual patient bone;

utilizing the ultrasound signals to capture a point cloud representative of the actual patient bone;

fitting a deformable 3-D bone model to the captured point cloud to generate a 3-D patient specific bone model;

registering the actual patient bone with the 3-D patient specific bone model;

generating at least one localized bone point from an output of one or more ultrasound transducers positioned proximate the actual patient bone;

tracking the at least one localized bone point by tracking the motion of the one or more ultrasound transducers using one or more inertial sensors; and

tracking motion of the actual patient bone through a range of motion using the at least one tracked localized bone point in combination with the 3-D patient specific bone model.

2. The method of claim 1 further comprising:

displaying said motion on the 3-D patient specific bone model.

3. The method of claim 1 , further comprising:

selecting from a database a set of empirical mathematical descriptions of the motion of the actual patient bone through the range of motion; and

comparing the motion of the actual patient bone to the selected set of empirical mathematical descriptions.

4. The method of claim 1 , further comprising:

collecting vibrational data as the actual patient bone is moved through the range of motion;

selecting from a database a set of empirical vibrational data descriptions of the vibration of the actual patient bone through the range of motion; and

comparing said vibrational data to the selected set of empirical vibration data descriptions.

5. The method of claim 1 , further comprising:

selecting one of a plurality of bone models;

measuring the actual patient bone to obtain patient specific measurements; and

applying the patient-specific measurements to the selected one of the plurality of bone models.

6. The method of claim 5 , wherein selecting one of the plurality of bone models includes considering at least one demographic characteristic of the patient.

7. The method of claim 5 , wherein applying the patient-specific measurements to the bone model includes conforming the model bone to the captured point cloud.

8. The method of claim 1 , further comprising:

placing an inertial sensor approximate the actual patient bone; and

gathering vibration data using the inertial sensor while moving the actual patient bone through the range of motion.

9. The method of claim 8 , further comprising:

simultaneously, with gathering the vibration data, gathering kinematics data pertaining to the actual patient bone.

10. The method of claim 9 , wherein the vibration data is time-synchronized with the kinematics data.

11. The method of claim 8 , further comprising:

analyzing the vibration data using a neural network.

12. The method of claim 11 , further comprising:

prior to analyzing the vibration data, training the neural network.

13. The method of claim 11 , wherein analyzing the vibration data using the neural network further comprises:

diagnosing at least one of a presence and severity of a joint condition.

14. The method of claim 13 , wherein the step of analyzing the vibration data using a neural network further comprises:

transmitting the vibration data across a network; and

receiving data pertaining to the joint condition via the network.

15. The method of claim 1 wherein the patient is a mammalian animal.

Assignments (1)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Jul 26, 2011
From: MAHFOUZ, MOHAMED M.; WASIELEWSKI, RAY C.; KOMISTEK, RICK
To: JOINTVUE, LLC
Reel/Frame 026651/0708 →
Continuity (1)
Related Publication 20100198067A1 · Aug 5, 2010