Abstract: The technology relates to a method of producing a moulded polyurethane hydrogel, for example a condom. The method involves forming a solution of at least one polyurethane having a molecular weight of between about 40000 to about 500000 in a water:organic polar solvent comprising less than about 40% (v/v) water; applying a layer of the solution to a mould; drying the layer of the first solution to form a polyurethane film on the mould; and contacting the polyurethane film with a swelling agent under conditions such that the film forms a polyurethane hydrogel with a swelling agent content of between about 1% to about 95%.

Abstract: Various exemplary drug delivery devices with multiple drug vials, drug products utilizing the same, and methods of using drug delivery devices with multiple drug vials are provided. In general, a nasal drug delivery device configured to dispense a drug therefrom into a nose and includes two or more vials each containing the drug therein. The drug delivery device is configured to deliver the drug from each of the vials for a total of two or more sprays into the nose. The same drug delivery device may therefore deliver multiple drug sprays to a user. In some embodiments, instead of including two or more vials that collectively contain enough drug therein for more than two drug sprays, the drug delivery device can include a single vial that contains enough drug therein for more than two drug sprays.

Abstract: Technologies for interruptibility analysis and notification are disclosed. In at least one illustrative embodiment, a method may comprise generating a live data stream including activity data received from one or more sensors associated with a worker, repeatedly generating an interruptibility status of the worker as a function of the activity data in the live data stream over a recent time period, and transmitting a signal that causes one of a plurality of status indicators to be displayed, the displayed status indicator corresponding to the current interruptibility status of the worker.

Abstract: The technology relates to a method of producing a moulded polyurethane hydrogel, for example a condom. The method involves forming a solution of at least one polyurethane having a molecular weight of between about 40000 to about 500000 in a water:organic polar solvent comprising less than about 40% (v/v) water; applying a layer of the solution to a mould; drying the layer of the first solution to form a polyurethane film on the mould; and contacting the polyurethane film with a swelling agent under conditions such that the film forms a polyurethane hydrogel with a swelling agent content of between about 1% to about 95%.

Abstract: Technologies for interruptibility analysis and notification are disclosed. In at least one illustrative embodiment, a method may comprise generating a live data stream including activity data received from one or more sensors associated with a worker, repeatedly generating an interruptibility status of the worker as a function of the activity data in the live data stream over a recent time period, and transmitting a signal that causes one of a plurality of status indicators to be displayed, the displayed status indicator corresponding to the current interruptibility status of the worker.

Abstract: Systems and methods are provided for determining performance capacity. One such system includes a wearable device having a biosensor that measures biometrics and a motion sensor that monitors activity. The system also includes a processor coupled to the biosensor and the motion sensor, and a non-transitory computer-readable medium operatively coupled to the processor and storing instructions that, when executed, cause the processor to execute specific functions. The instructions are executed to cause the processor to generate biometric data from the biometrics and activity data from the activity. Further, the instructions are executed to create a response profile based on one or more of a heart rate variability (HRV) score based on the biometric data, a fatigue score based on the activity data, a predicted HRV score based on the biometric and activity data, and a predicted fatigue score based on the biometric data and/or the activity data.

Abstract: Systems, methods, and devices are provided for determining an exertion recommendation for an anticipated exercise session. One such system includes a wearable device comprising a biosensor that monitors biometrics (e.g. heart rate); a motion sensor that monitors activity; a processor operatively coupled to the biosensor, the processor configured to process electronic signals periodically generated by the biosensor and the motion sensor; and a non-transitory computer-readable medium operatively coupled to the processor and storing instructions that, when executed, cause the processor to execute specific functions. In particular, the instructions are executed to cause the processor to generate biometric data from the biometrics (e.g. heart rate information in particular). Further, the instructions are executed to generate an exertion recommendation based on an exertion model created from and representing a relationship between prior exertion measures and prior response profile measures.

Abstract: Systems, methods, and devices are provided for determining an exercise program recommendation for an anticipated exercise session. One such system includes a wearable device comprising a biosensor that monitors biometrics (e.g. heart rate); a motion sensor that monitors activity; a processor operatively coupled to the biosensor, the processor configured to process electronic signals periodically generated by the biosensor and the motion sensor; and a non-transitory computer-readable medium operatively coupled to the processor and storing instructions that, when executed, cause the processor to execute specific functions. In particular, the instructions are executed to cause the processor to generate biometric data from the biometrics (e.g. heart rate information in particular).

Abstract: Systems and methods are provided for using earphones with biometric sensors to identify and present information regarding performance periods. Fatigue level associated with fatigue experienced in response to a stimulus and recovery from such fatigue may be determined based on heart rate variability (HRV) data and learned user characteristics. One or more cycles of fatigue and recovery can be identified as a fitness cycle(s), each fitness cycle encompassing a period of time beginning with the stimulus associated with the fitness-related activity and progressing through recovery from the fatigue experienced in response to the stimulus associated with the fitness-related activity. A performance period may be predicted based on a pre-determined fatigue/recovery level instance within a fitness cycle.

Abstract: Systems and methods for identifying and presenting information regarding performance periods are provided. Fatigue level associated with fatigue experienced in response to a stimulus and recovery from such fatigue may be determined based on heart rate variability (HRV) data and learned user characteristics. One or more cycles of fatigue and recovery can be identified as a fitness cycle(s), each fitness cycle encompassing a period of time beginning with the stimulus associated with the fitness-related activity and progressing through recovery from the fatigue experienced in response to the stimulus associated with the fitness-related activity. A performance period may be predicted based on a pre-determined fatigue/recovery level instance within a fitness cycle.

Abstract: A system for identifying fatigue sources includes a processor and at least one computer program residing on the processor. The computer program is stored on a non-transitory computer readable medium having computer executable code embodied thereon. The computer executable code is configured to detect a fatigue level. The computer executable code is further configured to receive fatigue contribution data. In addition, the computer executable code is configured to identify a fatigue source based on the fatigue level and the fatigue contribution data.

Abstract: Systems, methods, and devices are provided for determining an exercise program recommendation for an anticipated exercise session. One such system includes a wearable device comprising a biosensor that monitors biometrics (e.g. heart rate); a motion sensor that monitors activity; a processor operatively coupled to the biosensor, the processor configured to process electronic signals periodically generated by the biosensor and the motion sensor; and a non-transitory computer-readable medium operatively coupled to the processor and storing instructions that, when executed, cause the processor to execute specific functions. In particular, the instructions are executed to cause the processor to generate biometric data from the biometrics (e.g. heart rate information in particular).

Abstract: Systems, methods, and devices are provided for determining an exertion recommendation for an anticipated exercise session. One such system includes a wearable device comprising a biosensor that monitors biometrics (e.g. heart rate); a motion sensor that monitors activity; a processor operatively coupled to the biosensor, the processor configured to process electronic signals periodically generated by the biosensor and the motion sensor; and a non-transitory computer-readable medium operatively coupled to the processor and storing instructions that, when executed, cause the processor to execute specific functions. In particular, the instructions are executed to cause the processor to generate biometric data from the biometrics (e.g. heart rate information in particular). Further, the instructions are executed to generate an exertion recommendation based on an exertion model created from and representing a relationship between prior exertion measures and prior response profile measures.

Abstract: Systems and methods are provided for determining performance capacity. One such system includes a wearable device having a biosensor that measures biometrics and a motion sensor that monitors activity. The system also includes a processor coupled to the biosensor and the motion sensor, and a non-transitory computer-readable medium operatively coupled to the processor and storing instructions that, when executed, cause the processor to execute specific functions. The instructions are executed to cause the processor to generate biometric data from the biometrics and activity data from the activity. Further, the instructions are executed to create a response profile based on one or more of a heart rate variability (HRV) score based on the biometric data, a fatigue score based on the activity data, a predicted HRV score based on the biometric and activity data, and a predicted fatigue score based on the biometric data and/or the activity data.

Abstract: Systems and methods are disclosed for providing a user a training load schedule for peak performance using earphones with biometric sensors. In one embodiment, the system includes earphones, including: speakers; a processor; a heartrate sensor electrically coupled to the processor; and a motion sensor electrically coupled to the processor. In this embodiment, the system also includes a memory coupled to a processor and having instructions stored that, when executed by the processor: display on a display an initial load schedule stored in a memory to the user; calculate a fatigue level of the user based on signals generated by the heartrate sensor; modify the initial load schedule based on the calculated fatigue level to create a dynamic load schedule for the user; and display on the display the dynamic load schedule to the user.

Abstract: A system for providing a training load schedule for peak performance positioning includes an apparatus for providing a training load schedule for peak performance positioning. The apparatus includes an initial load schedule module that provides an initial load schedule. The apparatus also includes a fatigue level module that detects a fatigue level. In addition, the apparatus includes a dynamic load schedule module that creates and updates a dynamic load schedule by modifying the initial load schedule based on the fatigue level.

Abstract: A sample holder comprises a bottom and one or more arms. The bottom has an initial area for supporting a sample. The one or more arms actuate to move the sample in the initial area to a target area, wherein the one or more arms hold the sample.

Abstract: A sample holder comprises a bottom and one or more arms. The bottom has an initial area for supporting a sample. The one or more arms actuate to move the sample in the initial area to a target area, wherein the one or more arms hold the sample.

Abstract: A system for providing a training load schedule for peak performance positioning includes an apparatus for providing a training load schedule for peak performance positioning. The apparatus includes an initial load schedule module that provides an initial load schedule. The apparatus also includes a fatigue level module that detects a fatigue level. In addition, the apparatus includes a dynamic load schedule module that creates and updates a dynamic load schedule by modifying the initial load schedule based on the fatigue level.

Abstract: A system for providing a training load schedule for peak performance positioning includes an apparatus for providing a training load schedule for peak performance positioning. The apparatus includes an initial load schedule module that provides an initial load schedule. The apparatus also includes a fatigue level module that detects a fatigue level. In addition, the apparatus includes a dynamic load schedule module that creates and updates a dynamic load schedule by modifying the initial load schedule based on the fatigue level.