ARTIFICIAL BODY PART CONTROL SYSTEM USING ULTRASOUNIC IMAGING

• US 20130041477A1
• Filed: 08/01/2012
• Published: 02/14/2013
• Est. Priority Date: 08/01/2011
• Status: Active Grant

• Current Assignee: George Mason University
• Original Assignee: Siddhartha Sikdar
• Inventors: SIKDAR, Siddhartha, Pancrazio, Joseph J., Hunt, Ira A., Nelson, Andrew J., Al-Imran, Abdullah
• Granted Patent: US 9,931,230 B2
• Time in Patent Office: Days
• US Class Current: 623/57
• CPC Class Codes: A61B 5/1107 Measuring contraction of parts of the body, e.g. organ, muscle apparatus for measuring work or force in general G01L
• CPC Class Codes: A61B 8/085 for locating body or organic structures, e.g. tumours, calculi, blood vessels, nodules
• CPC Class Codes: A61B 8/4227 characterised by straps, belts, cuffs or braces
• 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: A61F 2/583 Hands; Wrist joints
• CPC Class Codes: A61F 2/72 Bioelectric control, e.g. myoelectric
• CPC Class Codes: A61F 2002/6809 acoustic
• CPC Class Codes: A61F 2002/7615 Measuring means
• CPC Class Codes: G16H 50/30 for calculating health indices; for individual health risk assessment

Abstract

The artificial body part control system using ultrasonic imaging includes of an ultrasonic transducer coupled with an ultrasonic image analyzer which may be adapted to transmit a control signal to an artificial body part.

Claims

1. An artificial body part control system using ultrasonic imaging, comprising:

at least one ultrasonic transducer producing at least two-dimensional image ultrasound data;

an ultrasonic image analyzer coupled to the at least one ultrasonic transducer to perform real time analysis on the ultrasonic data; and

an artificial body part coupled to the ultrasonic image analyzer.

2. The artificial body part control system using ultrasonic imaging according to claim 1, wherein the at least one ultrasonic transducer is configured to monitor at least one tissue movement.

3. The artificial body part control system using ultrasonic imaging according to claim 1, further comprising an array of ultrasonic sensors suitable for acquiring ultrasonic data from multiple dimensions, including the at least one ultrasonic transducer.

4. The artificial body part control system using ultrasonic imaging according to claim 1, wherein the at least one ultrasonic transducer is adjustable to acquire ultrasonic images at different angles.

5. The artificial body part control system using ultrasonic imaging according to claim 1, wherein the at least one ultrasonic transducer may be locked in at least one specific angle.

6. The artificial body part control system using ultrasonic imaging according to claim 1, wherein the ultrasonic image analyzer executes an image-processing algorithm configured to calculate the pixel intensity changes between at least two ultrasonic images.

7. The artificial body part control system using ultrasonic imaging according to claim 1, wherein the ultrasonic image analyzer executes an optimization algorithm configured to target at least one region of interest as at least one template window by detecting pixel intensity changes between at least two ultrasonic images.

8. The artificial body part control system using ultrasonic imaging according to claim 1, wherein the ultrasonic image analyzer executes a sum of difference algorithm configured to detect the pixel intensity differences between at least two ultrasonic frames over time.

9. The artificial body part control system using ultrasonic imaging according to claim 1, wherein the ultrasonic image analyzer executes an image-processing algorithm configured to detect a characteristic pattern of pixel intensity changes associated with a unique desired movement

10. The artificial body part control system using ultrasonic imaging according to claim 1, wherein the ultrasonic image analyzer executes and image-processing algorithm configured to decode a desired movement by finding the closest match of a characteristic pattern of pixel intensity changes associated with a movement from a database of characteristic patterns of pixel intensity changes associated with different movements.

11. The artificial body part control system using ultrasonic imaging according to claim 1, wherein the ultrasonic image analyzer executes an image-processing algorithm, configured to identify skeletal landmarks by recognizing echogenicity patterns.

12. A method for tissue movement identification executed by an artificial body part control system using ultrasonic imaging, comprising:

transmitting ultrasonic waves to a tissue group;

acquiring ultrasonic data of signals corresponding to user'"'"'s internal structures;

generating an at least two-dimensional ultrasonic image corresponding to the received signals;

analyzing in real time an ultrasonic image for movement based on changes of the received signals;

transmitting a control signal to an artificial body part based on the analyzed movement.

13. The method for tissue movement identification according to claim 12, wherein the analyzing includes identifying the internal structure that generated a tissue movement.

14. The method for tissue movement identification according to claim 12, wherein the analyzing includes identifying the internal structure that generated a tissue movement by locating respective surrounding skeletal landmarks.

15. The method for tissue movement identification according to claim 12, wherein the analyzing includes identifying the internal structure that generated a tissue movement by comparing pixel intensity changes between at least two ultrasonic frames over time.

16. The method for tissue movement identification according to claim 12;

wherein the analyzing includes determining the rate, intensity, and duration of the tissue movement.

17. The method for tissue movement identification in claim 12, wherein the analyzing comprises:

analyzing the height of a characteristic movement waveform derived from the received signals to determine the degree of tissue movement;

analyzing the width of a characteristic movement waveform derived from the received signals to determine the duration of tissue movement; and

analyzing the slope of a characteristic movement waveform derived from the received signals to determine the rate of tissue movement.

18. The method for tissue movement identification in claim 12, wherein the analyzing comprises executing a vector tissue Doppler imaging algorithm to determine the velocity of tissue movement.

19. A method for training an artificial body part controller, the method comprising:

analyzing ultrasonic data from a transducer for a tissue at rest to generate a corresponding baseline signal;

comparing the baseline signal to at least one subsequent signal of tissue contraction to select a tow-dimensional image area with the greatest pixel intensity change as the template window;

storing the template window on a data storage device; and

comparing in real time frames of subsequent tissue movements within the template window.

20. A control system using ultrasonic imaging comprising:

at least one ultrasonic transducer producing at least two-dimensional image ultrasound data; and

an image analyzer coupled to the at least one ultrasonic transducer and constructed and arranged to generate in real time output signals adapted to control an artificial body part.

21. The control system using ultrasonic imaging according to claim 20, wherein the ultrasonic image analyzer executes an optimization algorithm configured to identify tissue movement by calculating pixel intensity changes between at least two ultrasonic images.

22. The control system using ultrasonic imaging according to claim 20, wherein the ultrasonic image analyzer executes a sum of difference algorithm configured to detect the pixel intensity differences between at least two ultrasonic frames over time.

23. The control system using ultrasonic imaging according to claim 20, wherein the ultrasonic image analyzer executes an image-processing algorithm configured to detect a characteristic pattern of echogenicity and/or echo texture.

24. The control system using ultrasonic imaging according to claim 20, wherein the ultrasonic image analyzer executes an image-processing algorithm configured to identify a desired movement by finding a closest match of a characteristic pattern of pixel intensity changes associated with the movement from a database of characteristic patterns of pixel intensity changes associated with different movements.