Disclosed are an electronic device for generating workout types and a method of operating the electronic device. According to an embodiment, an electronic device includes: a memory and at least one processor connected to the memory, wherein the at least one processor is configured to: acquire a workout type name in response to a request for adding a workout type, recommend at least one data type based on the workout type name, generate a new workout type corresponding to the workout type name based on a data type selected from among the at least one recommended data type, and acquire workout measurement information corresponding to the selected data type in response to execution of the new workout type.

The present invention provides in part wearable devices for balance control. The wearable devices are capable of non-invasively monitoring and stimulating the wearer's vestibular system such that it produces postural responses. The wearable devices deliver low levels of electrical current to the vestibular system of a user to maintain balance. In one example, the wearable device is in the form of a pair of glasses.

A pulse sensor is capable of measuring a pulse rate of a wearer at a peripheral artery. In an embodiment, the pulse sensor includes a magnet supported to move responsive to an arterial pulse and a magnetometer configured to detect changes in a magnetic field produced by the magnet. The magnet may include a plurality of ferromagnetic particles disposed in or on a flexible substrate configured to be held adjacent to human skin subject to arterial palpation and a magnetic sensor configured to sense movement of the ferromagnetic particles. A system and method may measure hydration includes using a pulse sensor to measure pulse rate and modulation. The wearer is prompted when the pulse rate and pulse modulation indicate a response to dehydration of the wearer.

The present invention relates to a device for measuring grip strength including a basis; a cover coupled to the basis to form an enclosed pressure space separated from the outside; a cap disposed between the basis and the cover and configured to form a sensing space separated from the pressure space; magnets mounted on the cap or the basis to form a magnetic field; and a magnetic sensor for detecting change in the magnetic field. With this configuration, when measuring the grip strength of the user's hand, accuracy or sensitivity may be increased.

A non-contact respiratory monitoring system, method, and sensor are disclosed. The system includes a magnet and a sensor including a coil made of magnetic microwire. The magnetic microwire sensor coil is configured to detect motion of the magnet relative to the magnetic sensor coil. An alternating voltage across the magnetic microwire sensor coil is modified by a change in impedance of the magnetic microwire sensor coil caused by the change in the distance of the magnet from the magnetic microwire sensor coil. The non-contact respiratory monitoring method includes changing a distance of a magnet from a magnetic sensor coil. The sensor includes a coil composed of high quality melt-extracted amorphous microwire.

A system may obtain a set of features characterizing a segment of inertial measurement unit (IMU) data generated by an IMU of an ear-wearable device. The system may apply a machine learning model (MLM) that takes the features characterizing the segment of the IMU data as input. The system may determine, based on output values produced by the MLM, whether a user of the ear-wearable device has potentially been subject to physical abuse. The system may then perform an action in response to determining that the user of the ear-wearable device has potentially been subject to physical abuse.

Augmenting real-time views of a patient with three-dimensional (3D) data. In one embodiment, a method may include identifying 3D data for a patient with the 3D data including an outer layer and multiple inner layers, determining virtual morphometric measurements of the outer layer from the 3D data, registering a real-time position of the outer layer of the patient in a 3D space, determining real-time morphometric measurements of the outer layer of the patient, automatically registering the position of the outer layer from the 3D data to align with the registered real-time position of the outer layer of the patient in the 3D space using the virtual morphometric measurements and using the real-time morphometric measurements, and displaying, in an augmented reality (AR) headset, one of the inner layers from the 3D data projected onto real-time views of the outer layer of the patient.

A medical system is disclosed that includes a medical device having an optical fiber, and an interchangeable connection component configured to provide a fiber optic connection between the medical device and capital equipment. The connection component is configured to facilitate cleaning and/or polishing of fiber optic interfaces include therewith. The connection component is also configured for replacement by a medical technician while the capital equipment is operational. The capital equipment may include one or more of an optical interrogator, a patch cable, a medical probe, an ultrasound machine, a display, a magnet sensor, or an electro-cardiogram (ECG) machine. The medical device may include an elongate member configured for insertion within the patient body, where the optical fiber core extends along a length of the elongate member.

A method and apparatus for reducing magnetic tracking error in the position and orientation determined in a magnetic tracking system having a magnetic field generator. In some embodiments, the measured position and orientation of a sensor is compared to an expected theoretical position and orientation. Any error is assumed to be from “floor distortion,” i.e., eddy currents in the floor caused by the magnetic field generated by the magnetic field transmitter. The floor distortion is modeled as being caused by eddy currents caused by a second magnetic field transmitter that is a reflection of the actual transmitter. An algorithm iteratively searches over a parameter space to minimize the difference between the measured position and orientation and the theoretical position and orientation, and applies a correction to the measured position and orientation. The measurements and corrections of the position and orientation run in real-time with no additional hardware or calibration required.

A method for assessing movement of a body portion includes, via one or more machine learning models, analyzing a sensor signal indicative of movement of the body portion to determine a movement of the body portion; determining a sensor confidence level based, at least in part, on a characteristic of the sensor signal; receiving a series of images indicative of movement of the body portion; measuring an angle of movement of the body portion; determining a vision confidence level based, at least in part, on a quality of an identification the body portion; selecting the sensor signal, the measured angle of movement, or a combination thereof as an input into a machine learning model based on the sensor confidence level and the vision confidence level, respectively; analyzing the input to determine a movement pattern of the body portion; and outputting the movement pattern to a user.