A method of generating a correction plan for a knee of a patient includes obtaining a ratio of reference bone density to reference ligament tension in a reference population. A bone of the knee of the patient may be imaged. From the image of the bone, a first dataset may be determined including at least one site of ligament attachment and existing dwell points of a medial femoral condyle and lateral femoral condyle of the patient on a tibia of the patient. Desired positions of contact in three dimensions of the femoral condyles of the patient with the tibia of the patient may be obtained by determining a relationship in which a ratio of bone density to ligament tension of the patient is substantially equal to the ratio of reference bone density to reference ligament tension.

A device, method, and system are provided for measuring the fit and mechanical properties of an intended ligament or tendon graft during a surgical procedure. The device includes a sensor body, a set of temporary fixation securements that terminate a set of opposing sides of the sensor body, and electronic circuitry in communication with the sensor body, where the electronic circuitry generates electric signals in proportion to the mechanical properties experienced by the sensor body. The set of temporary fixation securements are adapted to attach to at least one of: (i) one or more patient bones, or (ii) permanent fixation hardware assembled to one or more patient bones.

A method for modeling soft tissue includes receiving one or more images showing an anatomical geometry of a first subject. The anatomical geometry includes a soft tissue. The method also includes measuring a plurality of parameters of the anatomical geometry of the first subject using one or more sensors attached to the first subject. The method also includes receiving a first set of material properties for the soft tissue of the first subject, a second subject, or both. The method also includes identifying a second set of material properties that characterizes the soft tissue while the first subject performs a task. The method also includes determining a strain on the soft tissue, a stress on the soft tissue, or both based at least partially upon the one or more images, the parameters, the first set of material properties, and the second set of material properties.

A joint tensioning device and methods of use thereof are disclosed. The joint tensioning device includes a flexing arm and a loading arm having a tensioning tip and a loading tip, respectively, configured for insertion into a joint. The flexing arm is coupled to the loading arm such that, during use, the loading arm may be adjusted to separate the tensioning tip and the loading tip to apply a distraction force to the joint. A strain gauge measures strain applied to the flexing arm based on the applied distraction force. The measured strain is used to determine the amount of force applied to the joint. The force data is employed in surgical planning to determine the amount of joint laxity when a particular load is applied to the joint.

A method of evaluating a human knee joint including a femur bone, a tibia bone, and ligaments. The method includes: inserting into the joint a tensioner-balancer that includes at least one force sensor; providing an electronic receiving device; moving the knee joint through at least a portion of its range of motion; using the electronic receiving device to collect data from the at least one force sensor; processing the collected force data to produce a digital geometric model of the knee joint, wherein the data includes: a medial spline representing a locus of points of contact of a medial condyle of the femur F with the tensioner-balancer, over a range of knee flexion angles; and a lateral spline representing the locus of points of contact of the femur F with the tensioner-balancer, over a range of knee flexion angles; and storing the digital geometric model for further use.

The present invention relates to enhancing mechanical properties of tissue such as collagenous or collagen-containing or elastin-containing tissue (e.g., tendons, ligaments, and cartilage) and treating related musculoskeletal and non-musculoskeletal conditions or injuries.

A method includes obtaining rotational data and translational data for a joint, the rotational and translational data being indicative of rotational and translational movement of the joint during rotational and translational joint testing, respectively, the rotational and translational joint testing being implemented by a robotic testing apparatus applied to the joint. A quantity indicative of joint play of the joint is computed. The quantity is computed via a function of the rotational data and the translational data. The method includes determining whether the computed quantity exceeds a joint play threshold and, if the computed quantity exceeds the joint play threshold, comparing the rotational data and the translational data with preset rotational data and preset translational data for the rotational and translation joint testing, respectively.

The present invention provides a novel system and device for wearables for humans and animals that capture and store kinematic and kinetic data and movement during training, rehabilitation, real-time events, and the like, analyze such data and movement in real-time during and after such activities, and provide output, feedback, assessment, and actionable biomechanical data and information about the wearer.

A method of calculating in vivo force on an anterior cruciate ligament (ACL) by measuring one or more biomechanical properties during a biomechanical screening task to obtain one or more biomechanical datum from the measured one or more biomechanical properties, and calculating a total load on an anterior cruciate ligament from an ACL force model using the one or more biomechanical datum as inputs to the ACL force model. The ACL force model is defined by F.sub.ACL=F.sub.ACL.sup.sag+F.sub.ACL.sup.front+F.sub.ACL.sup.trans+Σ.sub.jCT.sub.j, wherein F.sub.ACL is the total force on the ACL, F.sub.ACL.sup.sag is the force on the ACL in a sagittal plane, F.sub.ACL.sup.front is the force on the ACL in the frontal plane, F.sub.ACL.sup.trans is the force on the ACL in the transverse plane, and CT.sub.j is the ACL force interaction relationships among the sagittal-frontal (SF), sagittal-transverse (ST), and frontal-transverse (FT) planes, where j=SF, ST, FT.

A method is provided for monitoring and managing muscle activity and soft tissue loading. The method includes providing to a subject a plurality of sensors for measuring muscle activity and soft tissue loading levels; directing the subject to undertake a program of exercise; measuring muscle activity and soft tissue loading during the program of exercise; comparing the measured muscle activity and soft tissue loading levels against calibrated muscle activity and soft tissue loading levels for the subject; and alerting the subject if the comparison of measured muscle activity and soft tissue loading levels against calibrated muscle activity and soft tissue loading levels indicates that a desirable level of muscle activity and/or soft tissue loading is being exceeded.