Noninvasive diagnostic system
Inventors
Mahfouz, Mohamed R. • Wasielewski, Ray C. • Komistek, Richard D.
Assignees
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Publication Number
US-11342071-B2
Publication Date
2022-05-24
Expiration Date
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.
Core Innovation
The invention relates to a noninvasive joint diagnostic system that reconstructs patient-specific 3D bone models and analyzes a patient's joint motion to perform injury diagnosis. The system uses tracked pulse-echo A-mode ultrasound with atlas-based deformable modeling to reconstruct a registered joint model and provides registration and tracking of bone motion using ultrasound transducer braces with inertial localizers.
The inertial localizers include accelerometer-based sensors positioned to register and track joint motion as the patient moves. Joint motion is tracked through a weight bearing range of motion to provide continuous, loaded dynamic assessment, and a vibration detection module may detect joint vibration using thin-film accelerometers in addition to motion tracking.
In automated injury diagnosis, the system extracts kinematic and vibration feature vectors and compares them to diagnostic motion data stored in a database. A trained multilayer backpropagation neural network classifies the motion data to determine diagnosis type and severity, including detection of anterior cruciate ligament deficiency (ACLD) and injury type and severity.
Claims Coverage
The independent claim covers analyzing a patient's joint motion by non-invasively attaching an inertial sensor near the joint, registering the joint with a virtual joint model, collecting motion data during weight bearing range of motion, and comparing the motion data to a diagnostic database for diagnosis. Seven inventive features are identified across the claims, with dependent claims further specifying ultrasound transducer use via a bone tracking brace and wireless data transmission during the range of motion.
Non-invasive inertial sensing near a joint
Attaching an inertial sensor near a patient's joint non-invasively to collect motion-related data.
Registration with a virtual joint model
Registering the patient's joint with a virtual joint model.
Weight-bearing range of motion data collection using inertial tracking
Gathering motion data by non-invasively tracking motion of the patient's joint using the inertial sensor as the patient's joint is moved through a weight bearing range of motion.
Diagnosis by comparison to a diagnostic motion database
Comparing the motion data to a database including diagnostic motion data for diagnosis.
Ultrasound transducer as part of the inertial sensor
Using an inertial sensor that includes an ultrasound transducer.
Releasably coupled bone tracking brace with an ultrasound transducer
Releasably coupling a bone tracking brace near the joint, where the brace includes an ultrasound transducer.
Wireless transmission of inertial sensor data during range of motion
Wirelessly transmitting data obtained by the inertial sensor while moving the patient's joint through the range of motion.
The claim set centers on non-invasive inertial-sensor-based joint motion analysis using virtual joint model registration, weight-bearing range of motion data collection, and comparison to a diagnostic database, with refinements that add an ultrasound transducer, including via a releasably coupled bone tracking brace, and wireless transmission during measurement.
Stated Advantages
Avoidance of radiation (X-ray/fluoroscopy) for joint assessment.
Enables continuous, loaded dynamic assessment through a weight bearing range of motion.
Supports real-time or recorded and time-synchronized display for diagnosis.
Enables remote/at-home monitoring.
Documented Applications
Joint condition diagnosis for a human knee, including detection of anterior cruciate ligament deficiency (ACLD) and injury type and severity.
Remote/at-home monitoring of joint conditions using the described diagnostic system.
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