Abstract: An applicator of a clip system includes an elongated member and a bushing coupled to a distal end of the elongated member and a coupling movably attached to the bushing. A capsule is coupled to the coupling via a coupling member hooked over a hook of the coupling. Proximal ends of clip arms are received within the capsule and a core member received between and connected to the proximal ends of the arms includes a projection and a failure point distal of the projection. The core member is coupled to a control member so that movement of the control member relative to the elongated member opens and closes the arms. The projection is configured so that, when the clip is clipped over tissue, the coupling is drawn into the body and the projection drives the coupling member radially outward off the hook to free the capsule.

Abstract: Computer based systems and methods for estimating a user state are disclosed. In some embodiments, the methods comprise inputting a first input at an intermittent interval and a second input at a frequent interval into a user state estimation model to estimate the user state. In some embodiments, the first inputs are enhanced by injecting a noise input to create a plurality of enhanced first inputs whereby the plurality of enhance first inputs correspond to the plurality of second inputs at the frequent interval. In some embodiments, the first input comprises a self-reported input and the second inputs comprise a physiological input, a performance input or a situational input. In some embodiments, a machine learning algorithm creates the state estimation model. In some embodiments, the state estimation model estimates a future user state. In some embodiments, a computer based system for estimating a user state is provided.

Abstract: Computer based systems and methods for estimating a user state are disclosed. In some embodiments, the methods comprise inputting a first input at an intermittent interval and a second input at a frequent interval into a user state estimation model to estimate the user state. In some embodiments, the first inputs are enhanced by injecting a noise input to create a plurality of enhanced first inputs whereby the plurality of enhance first inputs correspond to the plurality of second inputs at the frequent interval. In some embodiments, the first input comprises a self-reported input and the second inputs comprise a physiological input, a performance input or a situational input. In some embodiments, a machine learning algorithm creates the state estimation model. In some embodiments, the state estimation model estimates a future user state. In some embodiments, a computer based system for estimating a user state is provided.

Abstract: Computer based systems and methods for estimating a user state are disclosed. In some embodiments, the methods comprise inputting a first input at an intermittent interval and a second input at a frequent interval into a user state estimation model to estimate the user state. In some embodiments, the first inputs are enhanced by injecting a noise input to create a plurality of enhanced first inputs whereby the plurality of enhance first inputs correspond to the plurality of second inputs at the frequent interval. In some embodiments, the first input comprises a self-reported input and the second inputs comprise a physiological input, a performance input or a situational input. In some embodiments, a machine learning algorithm creates the state estimation model. In some embodiments, the state estimation model estimates a future user state. In some embodiments, a computer based system for estimating a user state is provided.

Abstract: Computer based systems and methods for estimating a user state are disclosed. In some embodiments, the methods comprise inputting a first input at an intermittent interval and a second input at a frequent interval into a user state estimation model to estimate the user state. In some embodiments, the first inputs are enhanced by injecting a noise input to create a plurality of enhanced first inputs whereby the plurality of enhance first inputs correspond to the plurality of second inputs at the frequent interval. In some embodiments, the first input comprises a self-reported input and the second inputs comprise a physiological input, a performance input or a situational input. In some embodiments, a machine learning algorithm creates the state estimation model. In some embodiments, the state estimation model estimates a future user state. In some embodiments, a computer based system for estimating a user state is provided.