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: 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: 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 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 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.

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 at are also provided.

Abstract: A network device receives battery status signals for multiple mobile devices and receives a notification of an incoming call from a calling device to a particular mobile device. The network device determines if a battery status, from the battery status signals, is available for the particular mobile device and provides, to the calling device, a challenge to solicit a categorization of the incoming call as important or not important when a battery status is available for the particular mobile device. The network device receives, from the calling device, a response to the challenge, wherein the response includes the categorization of the incoming call. The network device connects the incoming call from the calling device to the particular mobile device when the categorization of the incoming call is important.

Abstract: A network device receives battery status signals for multiple mobile devices and receives a notification of an incoming call from a calling device to a particular mobile device. The network device determines if a battery status, from the battery status signals, is available for the particular mobile device and provides, to the calling device, a challenge to solicit a categorization of the incoming call as important or not important when a battery status is available for the particular mobile device. The network device receives, from the calling device, a response to the challenge, wherein the response includes the categorization of the incoming call. The network device connects the incoming call from the calling device to the particular mobile device when the categorization of the incoming call is important.

Abstract: A method, a device, and a non-transitory storage medium to output a program during a program session; monitor trick play inputs during the outputting of the program; receive a trick play input during the outputting of the program; capture trick play data and time data based on a receipt of the trick play input; store the trick play data and the time data as behavioral data; and use the stored behavioral data to govern a subsequent outputting of the program during another program session.

Abstract: Method, device, and storage medium for receiving a request to change a state of one or multiple elements of an automation system; changing the state of the one or multiple elements based on the request; storing usage activity data of the one or multiple elements; analyzing the usage activity data using a pattern recognition metric; determining whether a usage pattern exits based on the pattern recognition metric; creating a user activity mode in response to determining that the usage pattern exists; and operating the automation system in accordance with the user activity mode.