Provided herein are methods and devices configured to detect the heart rate of a user. The method includes receiving at least one input signal, separating the input signal into signal components, receiving a motion signal from the user, and applying a Bayesian filter to the signal components and the motion signal to estimate the heart rate of the user. The method further includes calculating a combination of at least two reflected light signals from at least two different wavelengths. The device includes a photodetector configured to detect at least one reflected light signal resulting from the emitted at least two different wavelengths and a motion detector for detecting a motion signal. The device also includes a processing component configured to calculate a combination of the reflected light signals, separate the combination of detected light signals into signal components, and apply a Bayesian filter to the signals.

A contactless detection method with noise elimination is applied to measuring the information of physiological and physical activities. It includes following steps: sensing a human body to generate an image by an image sensor; capturing a physiological signal from the image; tracing a feature point of the human body in the image to generate a physical activity signal; and calculating information of physical activities covering step count, speed and calories according to the physical activity signal and the physiological signal. In particular, the contactless detection method treats the physiological signal cooperated with the physical activity signal to separate a noise from the physiological signal, so as to generate an ideal physiological signal. Therefore, the physiological information is calculated more accurately according to the ideal physiological signal.

Devices, systems, and methods for monitoring musculoskeletal (MSK) health conditions of an individual, including joint flexibility, strength, and endurance as part of their overall care plan are described here. The overall system includes: a sensor that can be worn anywhere on the human body, an engaging app on a mobile-computing device, and software-based analytics and care management engine running on a cloud-computing infrastructure. The sensor is tuned to measure any human joint movement in any direction or axis as well as elevation and temperature. Methods performed by the various devices and systems and how it improves MSK health are provided.

The present invention provides a novel system and device for wearables for humans and animals that capture and store kinematic and kinetic data and movement during training, rehabilitation, real-time events, and the like, analyze such data and movement in real-time during and after such activities, and provide output, feedback, assessment, and actionable biomechanical data and information about the wearer.

Detecting group activities is disclosed, including: receiving a plurality of GPS recorded activities uploaded by a plurality of athletes, wherein the plurality of athletes comprises a first athlete and a second athlete; receiving a request to determine a set of group activities that includes the first athlete and the second athlete; determining the set of group activities based at least in part on a set of time criteria and a set of space criteria used to compare a first GPS recorded activity associated with the first athlete and a second GPS recorded activity associated with the second athlete; and outputting at least some of the set of group activities.

A probe tip of an oximeter device includes first and second printed circuit boards (PCBs) that are coupled to the ends of optical fibers that transmit light between the PCBs and into patient tissue that is to be measured by the oximeter device. The PCBs are oriented at an angle between zero and ninety degrees so that the fibers have a curved shape between the locations at which the fibers are coupled to the first and second PCBs. The angular orientation of the PCBs and curved shape of the fibers allows the fibers to have a longer length than if the fibers were straight and allows for light transmitted through the fibers to have a uniform distribution across a cross-section of the fibers as the light is emitted from the fibers into patient tissue. The uniform distribution of light transmitted into patient tissue allows for reliable oximetry measurements.

Among other things, embodiments of the present disclosure can detect a movement impairment within one of at least one critical phase or frame and/or instance in time of body movement, based at least on movement analysis data obtained by data captured via a camera coupled to a computer system or input into the computer system. The movement analysis data may include at least one critical phase or frame and/or instance in time of body movement. Information related to the detected movement impairment is displayed by the computer system on the display screen.

A computer-implemented method or system for generating health data is provided. The method includes receiving a sensor data set measured by one or more sensors of a wearable device over an interval of time, the sensor data set indicating a time series profile of a body parameter of a user of the wearable device over the interval of time. The method also includes determining an activity type of the user matching the time series profile; and calculating a value associated with a health metric, wherein the value is calculated based on the activity type.

A device for measuring physical activity of a user during swimming is provided, which includes the following: a sensor unit adapted and dimensioned to be coupled with swimming goggles, wherein the sensor unit includes a motion circuitry configured to measure physical motion of the user; an optical cardiac activity circuitry configured to be placed at least partially against a body tissue of the user and to measure cardiac activity of the user; and a wireless communication circuitry configured to transfer data between the device and at least one external device, wherein the wireless communication circuitry is configured to transfer physical activity data of the user to the at least one external device, and the physical activity data includes at least one of motion data obtained using the motion circuitry, cardiac activity data obtained using the cardiac activity circuitry.

A method and program product includes assigning a first location of at least one embedded device. The embedded device includes at least one sensor and is associated with a one joint capable of movement. The first location is captured by the sensor. A second location of the at least one embedded device is assigned. The second location being captured by observation of the embedded device by at least one external sensor. A pose correspondence between the first location and the second location is established using a model of the joint. The sensor is calibrated by tracking a change in a pose captured by the external sensor and a change in a pose captured by the one sensor as the joint moves.