Noninvasive Diagnostic System

• US 20100198067A1
• Filed: 02/02/2009
• Published: 08/05/2010
• Est. Priority Date: 02/02/2009
• Status: Active Grant

• Current Assignee: JointVue, LLC
• Original Assignee: JointVue, LLC
• Inventors: Mahfouz, Mohamed M., Komistek, Rick, Wasielewski, Ray C.
• Granted Patent: US 8,444,564 B2
• Time in Patent Office: Days
• US Class Current: 600/443
• CPC Class Codes: A61B 2034/105 Modelling of the patient, e.g. for ligaments or bones
• CPC Class Codes: A61B 2034/2048 using an accelerometer or inertia sensor
• CPC Class Codes: A61B 2034/2051 Electromagnetic tracking systems
• CPC Class Codes: A61B 2562/02 Details of sensors specially adapted for in-vivo measurements
• CPC Class Codes: A61B 2562/0204 Acoustic sensors
• CPC Class Codes: A61B 2562/0219 Inertial sensors, e.g. accelerometers, gyroscopes, tilt switches
• CPC Class Codes: A61B 2562/0247 Pressure sensors
• CPC Class Codes: A61B 2562/046 in a matrix array
• CPC Class Codes: A61B 34/20 Surgical navigation systems; Devices for tracking or guiding surgical instruments, e.g. for frameless stereotaxis
• CPC Class Codes: A61B 5/0002 Remote monitoring of patients using telemetry, e.g. transmission of vital signals via a communication network A61B5/07 takes precedence; transmission systems for measured values G08C; transmission H04B; transmission of digital information H04L; wireless communication networks H04W
• CPC Class Codes: A61B 5/0004 characterised by the type of physiological signal transmitted
• CPC Class Codes: A61B 5/002 Monitoring the patient using a local or closed circuit, e.g. in a room or building A61B5/0017 takes precedence
• CPC Class Codes: A61B 5/0059 using light, e.g. diagnosis by transillumination, diascopy, fluorescence A61B5/0093, A61B5/1455, A61B5/02416 and A61B5/0261 take precedence
• CPC Class Codes: A61B 5/1036 Measuring load distribution, e.g. podologic studies
• CPC Class Codes: A61B 5/1038 Measuring plantar pressure during gait
• CPC Class Codes: A61B 5/11 Measuring movement of the entire body or parts thereof, e.g. head or hand tremor, mobility of a limb for measuring pulse A61B5/02 ;A61B5/1038 takes precedence; motion detection to correct for motion artifacts in physiological signals A61B5/721
• CPC Class Codes: A61B 5/1114 Tracking parts of the body
• CPC Class Codes: A61B 5/112 Gait analysis
• CPC Class Codes: A61B 5/1121 Determining geometric values, e.g. centre of rotation or angular range of movement
• CPC Class Codes: A61B 5/1127 using markers
• CPC Class Codes: A61B 5/24 : Detecting, measuring or recording bioelectric or biomagnetic signals of the body or parts thereof
• CPC Class Codes: A61B 5/389 : Electromyography [EMG]
• CPC Class Codes: A61B 5/4528 : Joints A61B5/4533, A61B5/4538 take precedence
• CPC Class Codes: A61B 5/4533 : Ligaments
• CPC Class Codes: A61B 5/4585 : Evaluating the knee
• CPC Class Codes: A61B 5/6807 : Footwear
• CPC Class Codes: A61B 5/6828 : Leg
• CPC Class Codes: A61B 5/6831 : Straps, bands or harnesses
• CPC Class Codes: A61B 5/6833 : Adhesive patches
• CPC Class Codes: A61B 5/72 : Signal processing specially adapted for physiological signals or for diagnostic purposes character recognition, recognising digital ink, document-oriented image-based pattern recognition G06V30/00; recognition or understanding of postal images G06V30/424
• CPC Class Codes: A61B 5/7267 : involving training the classification device
• CPC Class Codes: A61B 5/743 : Displaying an image simultaneously with additional graphical information, e.g. symbols, charts, function plots
• CPC Class Codes: A61B 5/7435 : Displaying user selection data, e.g. icons in a graphical user interface
• CPC Class Codes: A61B 8/0858 : involving measuring tissue layers, e.g. skin, interfaces
• CPC Class Codes: A61B 8/0875 : for diagnosis of bone A61B5/4504 takes precedence
• CPC Class Codes: A61B 8/4227 : characterised by straps, belts, cuffs or braces
• CPC Class Codes: A61B 8/4236 : characterised by adhesive patches
• CPC Class Codes: A61B 8/4254 : using sensors mounted on the probe
• CPC Class Codes: A61B 8/4263 : using sensors not mounted on the probe, e.g. mounted on an external reference frame
• CPC Class Codes: A61B 8/4472 : Wireless probes
• CPC Class Codes: A61B 8/4477 : using several separate ultrasound transducers or probes
• CPC Class Codes: A61B 8/466 : adapted to display 3D data 3D imaging and stereoscopic displays in devices for short-range imaging with acoustic waves G01S15/8993 and G01S7/52068, respectively; 3D image rendering G06T15/00; manipulating 3D models for computer graphics G06T19/00
• CPC Class Codes: A61B 8/467 : characterised by special input means
• CPC Class Codes: A61B 8/483 : involving the acquisition of a 3D volume of data
• CPC Class Codes: A61B 8/5223 : for extracting a diagnostic or physiological parameter from medical diagnostic data for algorithms to analyse biomedical images G06T7/0012
• CPC Class Codes: A61B 8/5238 : for combining image data of patient, e.g. merging several images from different acquisition modes into one image for image registration algorithms G06T7/30
• CPC Class Codes: G06N 3/084 : Backpropagation, e.g. using gradient descent
• CPC Class Codes: G16H 20/30 : relating to physical therapies or activities, e.g. physiotherapy, acupressure or exercising
• CPC Class Codes: G16H 40/63 : for local operation
• CPC Class Codes: G16H 50/50 : for simulation or modelling of medical disorders

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

1. A method of creating a patient specific bone model, comprising the steps of:

utilizing ultrasound to capture a point cloud of a patient'"'"'s bone; and

fitting a deformable 3d bone model to the captured points.

2. A method of tracking the motion of a patient'"'"'s bone and displaying a 3d model of said motion, comprising the steps of:

creating a 3d patient specific bone model;

registering the actual patient bone with the bone model;

tracking the motion of the patient'"'"'s actual bone through a range of motion; and

displaying said motion on an imaging apparatus.

3. A device for collecting data to produce a 3d model of a bone and to collect motion and vibrational data from the bone, comprising:

a semi flexible housing;

a plurality of ultrasonic transducers contained within the housing;

a plurality of inertia based localizers contained with the housing; and

a wireless transmission system contained within the housing for transmitting vibrational, locational, and imaging data to a CPU from the transducers and the localizers.

4. A device for collecting data to produce a 3d model of a bone and to collect motion and vibrational data from the bone comprising:

a semi flexible housing;

a plurality of ultrasonic transducers contained within the housing; and

a plurality of inertia based localizers contained with the housing.

5. A method of comparing the motion of a patient specific bone to a database, comprising the steps of:

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 comprising empirical mathematical descriptions of the motion of a plurality of actual bones through range of motion; and

comparing the motion of the patient specific bone to the database.

6. A method of using vibration data during the relative motion of bone and soft tissue in patient'"'"'s joint for diagnostic purposes, comprising the steps of:

attaching at least three inertia based sensors near a patient'"'"'s joint;

moving the patient'"'"'s joint through a range of motion;

collecting vibrational data as the patient joint is moved through a range of motion;

comparing said vibrational data to a database of empirical vibration data for the relative motion of bones in a patient'"'"'s joint for diagnostic purposes.

7. A method of creating a patient-specific bone model comprising the steps of:

a. selecting one of a plurality of bone models;

b. measuring a patient'"'"'s bone to obtain patent specific measurements; and

c. imposing the patient-specific measurements on the bone model.

8. The method of claim 7, wherein the step of selecting one of the plurality of bone models includes considering at least one demographic characteristic of the patient.

9. The method of claim 7, wherein the step of measuring the patient'"'"'s bone includes performing ultrasound imaging.

10. The method of claim 9, wherein the ultrasound imaging includes pulse echo A-mode ultrasound imaging.

11. The method of claim 7, wherein the step of imposing the patient-specific measurements on the bone model includes conforming the model bone to the imaging data.

12. A method of diagnosing joint disease comprising the steps of:

creating a three dimensional model of a joint;

attaching a sensor proximate the joint;

obtaining data using the sensor while the joint is articulated;

analyzing the data using a neural network; and

diagnosing a condition relevant to the joint.

13. The method of claim 12, wherein the step of attaching the sensor proximate the joint includes attaching an ultrasound transducer and an inertial sensor proximate the joint.

14. The method of claim 13, wherein the step of attaching an ultrasound transducer and an inertial sensor proximate a joint includes releasably coupling a bone tracking brace proximate the joint;

wherein the bone tracking brace includes the ultrasound transducer and the inertial sensor.

15. The method of claim 12, wherein the step of obtaining data using the sensor includes wirelessly transmitting data obtained by the inertial sensor while moving the joint through a range of motion.

16. A method of monitoring a joint comprising the steps of:

placing an inertial sensor approximate a joint; and

gathering vibration data using the inertial sensor while moving the joint through a range of motion.

17. The method of claim 16, further comprising, simultaneously with gathering vibration data, gathering kinematics data pertaining to the joint.

18. The method of claim 17, wherein the vibration data is time-synchronized with the kinematics data.

19. The method of claim 16, further comprising analyzing the vibration data using a neural network.

20. The method of claim 19, further comprising, prior to the step of analyzing the vibration data, training the neural network.

21. The method of claim 19, wherein the step of analyzing the vibration data using the neural network includes diagnosing at least one of a presence and severity of a joint condition.

22. The method of claim 19, wherein the step of analyzing the vibration data using a neural network includes transmitting the vibration data across a network and receiving data pertaining to the joint condition via the network.

23. A bone tracking brace comprising:

a frame adapted to be attached proximate a joint;

at least one ultrasound transducer mounted to the frame, the ultrasound transducer being operative to sense a position of the at least one bone of the joint; and

at least one inertial sensor mounted to the frame, the inertial sensor being operative to detect vibration originating from the joint.

24. The bone tacking brace of claim 23, wherein the frame is at least one of a flexible frame and a rigid frame.

25. The bone tacking brace of claim 23, wherein the ultrasound transducer is a pulse echo A-mode ultrasound transducer.

26. The bone tacking brace of claim 23, further comprising a wireless transmitter operatively connected to receive ultrasound data from the ultrasound transducer and vibration data from the inertial sensor.

27. A method of diagnosing a joint condition comprising the steps of:

creating a model of a joint;

obtaining vibration data and kinematics data while moving a joint through a range of motion;

correlating the kinematics data with the model of the joint to generate a model of the joints motion; and

analyzing the vibration data and the model of the joint'"'"'s motion to diagnose at least one of the presence and severity of a joint condition.

28. The method of claim 27, wherein the step of creating the model of the joint includes creating three dimensional models of a plurality of bones of the joint.

29. The method of claim 27, wherein the step of creating the three dimensional models of the plurality of bones of the joint includes conforming at least one model bone using measured data.

30. The method of claim 29, wherein the measured data is ultrasound imaging data.

31. The method of claim 27, wherein the step of obtaining vibration data and kinematics data includes obtaining time-synchronized vibration and kinematics data.

32. The method of claim 31, wherein the step of obtaining vibration data and kinematics data includes attaching a frame proximate the joint;

wherein the frame includes at least one inertial sensor and at least one ultrasound transducer.

33. The method of claim 27, wherein the step of analyzing the vibration data is performed using a neural network.

34. The method of claim 33, further comprising training the neural network