Systems and methods as described include a system for monitoring health of a user. The system can include a plurality of sensors worn by or implanted in a user. The plurality of sensors can include at least one sensor implanted in the user. The system can include a communication unit electronically coupled with the plurality of sensors and receiving data therefrom. The system can include a controller electronically coupled with the communication unit, the controller configured to perform predictive analytics on data from the plurality of sensors, wherein the controller is configured to output a personalized intervention recommendation to at least one of the user or a health care provider for use by the user to preemptively address one or more health conditions prior to or in lieu of a surgical intervention for the user.

Systems and methods for estimating anatomic alignment between two or more bones are described herein. An example method can include registering an anatomic reference frame. Additionally, the method can include establishing a respective rotational relationship between each of one or more bones and an orientation sensor attached to each of the one or more bones. The method can also include receiving, from each of the orientation sensors, orientation information, and then calculating an orientation of a bone relative to the anatomic reference frame. The method can further include calculating, using the respective orientations of the bones relative to the anatomic reference frame, an anatomic alignment parameter between first and second bones.

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.

An electromechanical device for rehabilitation includes pedals coupled to radially-adjustable couplings, an electric motor coupled to the pedals via the radially-adjustable couplings, and a control system including a processing device operatively coupled to the electric motor. The processing device configured to, responsive to a first trigger condition occurring, control the electric motor to operate in a passive mode by independently driving the radially-adjustable couplings rotationally coupled to the pedals. The processing device also configured to, responsive to a second trigger condition occurring, control the electric motor to operate in an active-assisted mode by measuring revolutions per minute of the radially-adjustable couplings, and cause the electric motor to drive the radially-adjustable couplings when the measured revolutions per minute satisfy a threshold condition, and responsive to a third trigger condition occurring, control the electric motor to operate in a resistive mode by providing resistance to rotation of the radially-adjustable couplings.

Apparatus and methods are described for setting rehabilitation goals for a patient, measuring patient movements, storing the movement data for later transfer to a computer, displaying progress indicators and inspirational messages based on progress towards goals, reporting movement, skin temperature and swelling data to a caregiver so that they monitor compliance and be aware of potential infection. The invention consolidates data from motion, temperature and swelling sensors placed on the patient with data received directly from the patient in response to questions displayed on a tablet computer screen, to create one or more representative values indicating the patient's current status. These representative values may include the patient's degree of compliance with their prescribed exercise and icing regimen; their degree of wellness based on their self-reported pain scale and sensed temperature and limb swelling; and their current level of physical activity as detected by the motion sensors.

A method of determining wear of an artificial knee assembly (AKA) includes acquiring a first set of computed tomography (CT) data about the AKA in vivo. A first volumetric file is generated based on the first set of CT data. A first point cloud data set is generated based on the first volumetric AKA file. A first dimensional analysis of the AKA is performed using the first point cloud data set. A second volumetric file is generated based on a second set of acquired CT data before implantation or from a model. A second point cloud data set is generated based on the second volumetric AKA file. A second dimensional analysis is performed using the second point cloud data set. The first dimensional analysis is compared to the second dimensional analysis and a determination is made if they are different from each other.

A system for monitoring a joint of a patient includes multiple sensors to be disposed near a joint and to measure or observe actions or physical quantities associated with the joint; and at least one communications module coupled to the sensors to receive data from the sensors and to transmit sensor information to an external device. The system also includes a patient device and clinician device which can be used to, for example, monitor and display information obtained from the sensors, determine range of motion measurements from the sensor data, show progress in physical therapy, take a photograph or video of the site on the patient, obtain a pain score, and include friends for providing encouragement during physical therapy.

A system that includes: a force sensor assembly adapted to monitor a load as applied on a subject's knee joint when the force sensor assembly remains in direct contact with the subject's lower extremity and the load is monitored from inside a main magnet of an MRI scanner; a mobile unit comprising tracks configured to adjust a position of the force sensor assembly; a stationary base on which the mobile unit and the force sensor assembly are located, the mobile unit translatable solely axially on the stationary base; and a processor coupled to the force sensor assembly and programmed to read information encoding the load being monitored by the force sensor assembly, wherein an MRI scan of the knee joint is initiated only when a pre-determined load has been applied to the subject's knee joint for a pre-determined period of time.

Systems and methods may be used to perform robot-aided surgery. A system may include a robotic controller to monitor a position and orientation of an end effector coupled to an end of a robotic arm. The robotic controller may apply a force to a bone using the end effector, such as via a soft tissue balancing component. The robotic controller may determine soft tissue balance using information from a tracking system, such as a position of a first tracker affixed to the bone. The soft tissue balance may be output, such as to a display device.

A measurement device suitable to measure a force, pressure, or load applied by the muscular-skeletal system is disclosed. The measurement module includes a unitary circuit board that couples electronic circuitry to sensors. In one embodiment, the sensors are integrated in the unitary circuit board. Using more than one sensor allows the position of applied load by the muscular-skeletal system to be measured. In one embodiment, the sensors of a sensor array can be elastically compressible capacitors. A load plate can underlie the sensor array. Similarly, a load plate can overlie the load plate. Load plates are rigid structures for distributing a force, pressure, or load. The measurement device can include an articular surface for allowing movement of the muscular-skeletal system. A remote system can be in proximity to the measurement device. The remote system can receive, process, and display data from the measurement module in real-time.