A system includes a first and second sensor for a first and second body portion, wherein each sensor includes perturbation sensors for determining physical perturbations for each respective body portion in response to a body movement, each sensor includes a processor for determining orientation and velocity data for each respective body portion in response to the physical perturbations, a shape sensing unit coupled to a joint portion between the first and second body portions including an optical fiber configured to bend in response to the body movement, a light source for providing light into the optical fiber, a light sensor for sensing reflected light from the optical fiber in response to being bent, and a processor for determining curvature data associated with the joint portion, and a central processor for determining user movement data in response to the orientation and velocity data for each body portion and the curvature data.

An active suspension orthotic support system is disclosed. The suspension orthotic support system comprises at least one variable resistance beam extending from a heel section to a mid-arch section of the footwear, wherein rotation of the variable resistance beam from a first position to a second position causes a resistance provided by the variable resistance beam to vary between a minimum resistance to a maximum resistance.

A system for assessing laxity of a joint of a patient is disclosed. The system comprises a tensioner tool having a substantially rigid portion that may be inserted within the joint to apply a force against a bone surface thereof. The system further comprises a tensioner sock having a flexible body with an opening to receive the tensioner tool and a sensor array disposed on the flexible body. Each sensor of the sensor array is configured to contact the bone surface and detect a pressure when the force is applied against the bone surface. The system further comprises a processor configured to receive the detected pressure from each sensor and calculate the force applied to the bone surface based on the detected pressures.

An apparatus for predicting an outcome of a patient includes a processor, and a memory storing computer executable instructions, which when executed by the processor cause the processor to perform operations comprising obtaining patient kinematic data of the patient; deriving one or more patient kinematic features from the patient kinematic data; and determining the outcome based on the one or more patient kinematic features and at least one additional data element of the patient using an outcome model trained on a training set of kinematic features of the same type as the patient kinematic features and the at least one additional data element.

An exercise form analysis and feedback system (EFAF) including at least one sensor, at least one local movement data receiver, an analysis and feedback processing unit (AFPU) and a feedback display. The EFAF system of the present invention obtains lift movement data through the one or more sensors as lift movements are performed. This lift movement data may, in turn, be transmitted to one or more local movement data receivers such that the AFPU may operate on the lift movement data to provide real-time or near real-time form/technique feedback to the user via a feedback display. The system of the presentation invention uses machine learning techniques to provide feedback on lift quality aspects based on data associated with previous lifts and external data as applicable.

The present invention teaches an articular fracture rehabilitation process measuring device. The measuring device comprises a base plate, a positioning tube, and an electronic angle gauge; the positioning tube and the electronic angle gauge are fixed separately on the base plate. The electronic angle gauge comprises a distance sensor, a rotation angle sensor, a data processor, and a digital display; the data processor is connected to the distance sensor and the rotation angle sensor; the digital display is connected with the data processor.

The present disclosure provides methods of identifying a loosened joint implant by analyzing acoustic emissions from the implant. The present disclosure further provides apparatuses for measuring acoustic data and analyzing acoustic emissions from a joint implant.

A computer system provides patient monitoring and treatment using implanted biosensors. Data associated with a target joint of a patient is collected via one or more implanted biosensors. A plurality of feature values are extracted from the data. The plurality of feature values are processed using a trained classification model to select a recommendation. The recommendation is provided to mitigate hemophilia-related injury to the target joint. Embodiments of the present invention further include a method and program product for providing patient monitoring and treatment using implanted biosensors in substantially the same manner described above.

A method for determining the flexion or extension of a joint of a human or animal subject, comprising: applying a plurality of strain gauges to the joint in a known configuration; applying a first inertial measurement unit, IMU, to each strain gauge; receiving strain data from each of the strain gauges; receiving motion data from each of the IMUs; and calculating the flexion or extension of the joint in dependence on the received strain data, motion data and the configuration of the strain gauges.

A system for treating dysfunctional SI joints that includes a multi-function bone structure prosthesis adapted to be delivered to and inserted into a dysfunctional SI joint via a posterior approach, the multi-function bone structure prosthesis, when disposed in a dysfunctional SI joint, being adapted to (i) stabilize the dysfunctional SI joint, (ii) induce proliferation, and/or growth and/or remodeling and/or regeneration of osseous tissue and, thereby, healing and arthrodesis of the dysfunctional SI joint, (iii) attenuate pain associated with the dysfunctional SI joint via neurostimulation, and (iv) monitor physiological and/or biomechanical parameters associated with the dysfunctional SI joint via one or more sensor systems.