A method for calibrating respective estimated joint axis directions for each of a pair of body mounted sensors, one of the pair of sensors being located to each side of the joint comprising a joint axis, the sensors each calculating a pitch angle about respective first sensor axes and a roll angle about respective second sensor axes, the first and second sensor axes together with a third sensor axis orthogonal to the first and second sensor axes forming a sensor frame, the method comprising: receiving orientation data for each of the two sensors, the orientation data being associated with at least two different poses of the joint for each of the two sensors and the orientation data comprising the pitch angle and the roll angle of the sensor for each pose; calculating a sensor frame estimated gravity vector for each pose associated with each sensor based on the pitch and roll angles for each pose associated with each sensor and a gravity vector running along a vertical direction; and determining the estimated joint axis directions for the joint axis, relative to the first and second sensor axes, for each sensor that minimise a loss function concerning projections of each sensor frame estimated gravity vector for each pose associated with each sensor on to the estimated joint axis direction for the respective sensor.

A positioning method of functional rotation center of shoulder based on rigid upper arm model includes: step 1: abstracting a human upper arm into a cylinder with FRCS as a center of top surface; step 2: determining a reference axis vector of the cylinder; step 3: determining an axis vector of the cylinder and a displacement from the reference axis vector to the axis vector; step 4: correcting a central axis direction of the cylinder; step 5: determining a height compensation of the cylinder, and positioning the FRCS. The method has higher accuracy for the positioning result of FRCS, the positioning result of FRCS has better stability relative to the upper arm and trunk, and can be used to establish a more accurate human digital dynamic model and predict more accurate human posture.

A method of evaluating a joint includes obtaining test data indicative of movement of the joint during a test of the joint, generating visualization data for a three-dimensional representation of the joint to be rendered via a display, generating plane data for a representation of a plane to be rendered via the display with the three-dimensional representation of the joint, the plane having a position and an orientation fixed relative to a bone of the joint, adjusting the visualization data to animate the three-dimensional representation to depict, via the display, the movement of the joint during the test, and adjusting the plane data to update the position and the orientation of the plane in accordance with the movement of the joint.

Wearable ergonomics improvement systems and related methods are disclosed. An example ergonomics improvement system includes a membrane including a first frame having a plurality of first cutouts defining a first pattern. The system includes a sensor coupled to the membrane and includes a second frame having a plurality of second cutouts defining a second pattern. The first pattern is complementary to the second pattern.

An apparatus comprising at least one sensor to detect the position and/or orientation of a body portion of a subject, the sensor in communication with a computing device to process sensor data and optionally a transmitter to transmit sensor data between the sensor and the computing device and/or one or more computing devices.

A method of a measuring kinematic parameter in a subject is provided. The method includes obtaining a first magnetic resonance (MR) image set of a bone marrow segment of the subject in a first position and obtaining a second MR image set of the bone marrow segment of the subject in a second position where the second position different from the first position. The method further includes registering the first image set with the second image set and measuring a kinematic parameter.

Novel tools and techniques might provide for implementing image-based physiological status determination of users, and, in particular embodiments, for implementing physiological status determination of users based on marker-less motion-capture and generating appropriate remediation plans. In various embodiments, one or more cameras may be used to capture views of a user (e.g., an athlete, a person trying to live a healthy life, or the like) as the user is performing one or more set of motions, and the captured images may be overlaid with a skeletal framework that is compared with similar skeletal framework overlaid images for the same one or more sets of motions. The system can automatically determine a physical condition of the user or a probability that the user will suffer a physical condition based at least in part on an analysis of the comparison, which may be difficult or impossible to observe with the naked human eye.

Methods for evaluating subjects having conditions associated with loss of muscle function (e.g., a motor neuron disease, a neuromuscular disease, or a myopathy) by measuring muscle function (e.g., muscle strength) are disclosed.

The subject invention corresponds to a joint flexion indicator device connecting a first member to a second member, comprising a first housing connected to the first member; a second housing connected to the second member and a sensor arranged between the housings. The sensor detects an alignment between the housings, wherein the housings are aligned facing each other when the joint is extended. The device of the subject invention allows monitoring the relative position between the members articulated by the joint, which is useful for sports training where certain postures are required to achieve an adequate technical performance. For example, in the case of golf, the device of this invention allows monitoring that an arm and forearm joined by an elbow are aligned, thereby achieving superior performance during the swing stroke. The device also allows monitoring the position and alignment of legs, hands, and feet to correct ergonomic or sports postures.

A textile suitable for detecting movement and/or deformation comprises an electrically conductive fabric (8) which can expand in at least two directions, electrodes (12) arranged substantially regularly along the periphery of the fabric (8), a controller (14) designed to control the excitation of the electrodes (12) two by two according to a pattern such that all the electrodes (12) are successively excited, and to measure each time the voltage in the non-excited electrodes (12), and a computer (22) comprising a neural network inference engine and designed to receive the voltage measurements taken attire non-excited electrodes (12) in a given excitation cycle, in order to supply them to the neural network inference engine and to return a characteristic measurement of a movement having caused a deformation of the textile.