Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: Devices, systems, and methods for monitoring health parameters of an individual, including circumferential changes to a portion of the individual's body, are provided herein. A monitoring device includes: a stretchable component configured to fit securely around a body portion, and a sensor module coupled thereto. The sensor module is configured to obtain and transmit a circumference measurement of the body portion. The sensor module may be further configured to obtain and transmit measurements of one or more additional parameters. A related monitoring system includes the described monitoring device and a mobile computing device. The mobile computing device is configured, at least in part, to: process the body circumference measurements to identify and analyze any change in circumference of the body portion, and generate a relevant alert output. Methods performed by the various devices and systems are also provided.

Abstract: Devices, systems, and methods for monitoring health parameters of an individual, including circumferential changes to a portion of the individual's body, are provided herein. A monitoring device includes: a stretchable component configured to fit securely around a body portion, and a sensor module coupled thereto. The sensor module is configured to obtain and transmit a circumference measurement of the body portion. The sensor module may be further configured to obtain and transmit measurements of one or more additional parameters. A related monitoring system includes the described monitoring device and a mobile computing device. The mobile computing device is configured, at least in part, to: process the circumference measurements to identify and analyze any change in circumference of the body portion, and generate a relevant alert output. Methods performed by the various devices and systems are also provided.