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.

Various arrangements for sonar-based vital sign monitoring are presented herein. A mobile device may be determined to be stationary. In response, sonar-based movement sensing can be activated. Sonar data can then be captured in response to activating the sonar-based movement sensing. A breathing pattern can be detected in the sonar data and used to collect respiration data about a user.

Methods and devices using measurements of heart electrophysiological activity to guide structural heart disease interventions. In some embodiments, measurements of heart electrophysiological activity are mapped into locations of a heart model defined by one or more additional measurement modalities. In some embodiments, the additional measurement modalities comprise impedance measurements. Locations to map electrophysiological data to, in some embodiments, are determined by non-electrophysiological measurements simultaneous with the electrophysiological data measurement which locate a probe—for example, measurements made by the probe itself, and/or measurements which themselves indicate positioning of the probe.

A system is disclosed herein for providing a kinetic assessment and preparation of a prosthetic joint comprising one or more prosthetic components. The system comprises a prosthetic component including sensors and circuitry configured to measure load, position of load on a curved surface, joint stability, range of motion, and impingement. In one embodiment, the system is for a ball and socket joint of a musculoskeletal system. The system further includes a computer having a display configured to graphical display quantitative measurement data to support rapid assimilation of the information. The kinetic assessment measures joint alignment under loading that will be similar to that of a final joint installation. The kinetic assessment can use trial or permanent prosthetic components. Furthermore, adjustments can be made to the applied load magnitude, position of load, and joint alignment by various means to fine-tune an installation.

Systems and methods for monitoring the status of a joint or limb using color sensing. First and second color sensors are provided to sense first and second color encoded surfaces at first and second locations of a joint or limb, respectively. The color sensing data are processed to obtain the respective motion information of the first and second locations.

A system for contactless monitoring of a person in a chair includes a detector mount positioned adjacent the chair and detached from the chair. A detector is coupled to the detector mount and is configured to detect thermal radiation from a field of view that includes the chair. A controller controls the detector. The controller includes a processor and a nontransitory memory device that includes instructions that are performed by the processor to control the detector.

The differential voltage measuring system has a number of signal measuring circuits, each having a capacitive sensor element for capturing a measurement signal relating to the patient. The differential voltage measuring system further has a signal processing apparatus for determining at least one bioelectrical signal from the measurement signals and a computer unit which is configured to ascertain, on the basis of the at least one bioelectrical signal, and to provide, an item of breathing information, said breathing information indicating a breathing activity of the patient.

A system for monitoring a sleep of a user includes a plurality of patches for placement adjacent to a surface of a body of a user, a processor, and a data communication system. Each patch from the plurality of patches includes at least one sensor. The data communication system transmits positional data generated by the plurality of sensors, including orientation data and motion data, to the processor. The processing of the positional data includes detecting a change in position of the body of the user between a first position and a second position. Based on the first image and the second image, an animation of a movement of the body from the first position to the second position is generated.

A non-fixed shoulder brace is provided comprising: an affected shoulder support which is supported on an affected shoulder of a wearer; a waist support coupled to the wearer's waist; an affected arm mounting part in which the wearer's affected arm is inserted and which is supported by means of an affected shoulder strap member from the affected shoulder support; and an affected upper limb exercise assistance apparatus coupled to both ends of the waist support and disposed between the wearer's waist and the affected arm mounting part.

Embodiments are disclosed for a machine learning (ML) gesture recognition with a framework for adding user-customized gestures. In an embodiment, a method comprises: receiving sensor data indicative of a gesture made by a user, the sensor data obtained from at least one sensor of a wearable device worn on a limb of the user; generating a current encoding of features extracted from the sensor data using a machine learning model with the features as input; generating similarity metrics between the current encoding and each encoding in a set of previously generated encodings for gestures; generating similarity scores based on the similarity metrics; predicting the gesture made by the user based on the similarity scores; and performing an action on the wearable device or other device based on the predicted gesture.