3D Bone Model Generation Using Ultrasound and Inertial Tracking
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Solution Overview
Problem
Current methods for diagnosing knee joint injuries are invasive, require radiation, and provide discontinuous data, making them inefficient and potentially harmful.
Innovation Solution
A diagnostic system that uses patient-specific 3D tissue models, kinematic data, and sound data analysis via a neural network to automatically determine the presence and extent of knee joint injuries without invasive procedures or radiation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional imaging technologies (CT, MRI, X-ray) are used to diagnose knee joint injuries, then diagnostic data can be obtained, but the patient is exposed to radiation and invasive procedures
Solution Approach 1:
The patent replaces conventional imaging technologies (CT, MRI, X-ray) that use radiation with a mechanical vibration-based diagnostic system. Accelerometers detect vibrations generated by the knee joint during movement, and these mechanical signals are processed to diagnose ligament and soft tissue injuries without exposing the patient to ionizing radiation.
Solution Approach 2:
The patent introduces an intermediary diagnostic approach by using sound vibrations and accelerometers as mediators between the patient's movement and the diagnostic information. Instead of directly imaging internal structures with radiation, the system captures mechanical vibrations produced by joint movement and uses signal processing to extract diagnostic data about ligament integrity and joint function.
2Loss of information
If conventional imaging methods are used, then diagnostic information is obtained, but the data is discontinuous and requires multiple separate procedures
Solution Approach 1:
The patent implements continuous data collection by capturing vibrations throughout the entire range of motion of the knee joint in a single procedure. The accelerometers continuously record mechanical vibrations as the joint moves through flexion and extension, providing uninterrupted diagnostic information about ligament function and joint stability across all movement phases.
Solution Approach 2:
The patent merges multiple diagnostic functions into a single integrated system. The same accelerometer-based system simultaneously evaluates ACL, PCL, MCL, and LCL integrity, cartilage condition, and overall joint function during one continuous measurement session, eliminating the need for multiple separate imaging procedures.
3Measurement precision
If manual diagnostic analysis is performed, then clinical expertise is utilized, but diagnostic precision and consistency vary
Solution Approach 1:
The patent implements automated feedback processing where the accelerometer signals are continuously analyzed by software algorithms that compare observed vibration patterns against known diagnostic criteria for various ligament injuries. This automated feedback system provides consistent, objective diagnostic recommendations that reduce variability between different clinicians while maintaining high diagnostic precision.
Solution Approach 2:
The patent enables the diagnostic system to perform self-analysis through automated signal processing and interpretation algorithms. The system automatically processes the raw accelerometer data, identifies characteristic vibration patterns associated with different injuries, and generates diagnostic conclusions without requiring manual interpretation, thereby ensuring consistent results across different patients and clinicians.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
Enables accurate and non-invasive diagnosis of knee joint injuries, providing continuous data analysis that correlates with patient-specific conditions, thereby improving diagnostic precision and patient safety.
Implementation Method 1
the pattern and spatial distribution of sound(s) (i.e., vibrations) produced by movement of the patient's knee joint
Implementation Method 2
patient-specific sound data is generated using accelerometers to monitor the knee joint
Implementation Method 3
utilizing A-mode ultrasound echo morphing technology to generate data necessary to construct 3D tissue models
Implementation Method 4
A-mode ultrasound echo morphing technology
Data Source
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AI summary
A method of evaluating a physiological condition of bodily tissue, the method comprising: repositioning one or more ultrasound transducers (150) over a patient's epidermis to generate ultrasound transducer data of a bone of the patient; tracking the repositioning of the one or more ultrasound transducers in three dimensions using at least one inertial measurement unit (170) to generate 3D position data; correlating the ultrasound transducer data and the 3D position data to generate a 3D map comprising a plurality of 3D points representing a surface of the bone; using the 3D map to carry out a deformation process of a default 3D bone model resulting in a patient-specific, virtual 3D model of the bone; visually displaying the virtual 3D model of the bone.