Abstract: A surgical device for examination and treatment of a target area. The surgical device includes a shaft portion that extends along a longitudinal axis and that is configured to be inserted into a patient's body, a surgical tool provided within the outer sheath and configured to be movable along the longitudinal axis, and an optical assembly provided at a distal end of the inner shaft, the optical assembly including a light source and an imaging sensor.

Abstract: A surgical device for examination and treatment of a target area. The surgical device includes a shaft portion that extends along a longitudinal axis and that is configured to be inserted into a patient's body, a surgical tool provided within the outer sheath and configured to be movable along the longitudinal axis, and an optical assembly provided at a distal end of the inner shaft, the optical assembly including a light source and an imaging sensor.

Abstract: A surgical device for examination and treatment of a target area. The surgical device includes a shaft portion that extends along a longitudinal axis and that is configured to be inserted into a patient's body, a surgical tool provided within the outer sheath and configured to be movable along the longitudinal axis, and an optical assembly provided at a distal end of the inner shaft, the optical assembly including a light source and an imaging sensor.

Abstract: A system for predicting and detecting urination events of users is disclosed. The system can include any number of wearable devices, mobile devices, hubs, computing devices, and servers to collect, share, process, and interpret data, as well as to provide stimuli to users and caregivers. Biometric and/or environmental data associated with a user can be collected and applied to a urination model to determine a predicted urination time. The user or a caregiver can be provided with direct or environmental stimuli conveying information about predicted urination times. Ongoing biometric and/or environmental data collection can be used to identify, and provide stimuli warning of, imminent urination events. Voluntary and involuntary feedback of actual urination events, as well as continued biometric and/or environmental data collection, can be used to train individual and collective urination models.

Abstract: A method performed by a computer correlates vesicoelastic pressure data with volume data and calculates vesicoelastic work performed by the bladder, wherein the amount of vesicoelastic work performed by the bladder is determined by calculating an area under said vesicoelastic pressure data when said vesicoelastic pressure data is correlated against the volume data.

Abstract: A method performed by a computer correlates vesicoelastic pressure data (10, 12, 14) with volume data and calculates vesicoelastic work performed by the bladder (20), wherein the amount of vesicoelastic work performed by the bladder (20) is determined by calculating an area under said vesicoelastic pressure data (10, 12, 14) when said vesicoelastic pressure data (10, 12, 14) is correlated against the volume data.

Abstract: A system for predicting and detecting urination events of users is disclosed. The system can include any number of wearable devices, mobile devices, hubs, computing devices, and servers to collect, share, process, and interpret data, as well as to provide stimuli to users and caregivers. Biometric and/or environmental data associated with a user can be collected and applied to a urination model to determine a predicted urination time. The user or a caregiver can be provided with direct or environmental stimuli conveying information about predicted urination times. Ongoing biometric and/or environmental data collection can be used to identify, and provide stimuli warning of, imminent urination events. Voluntary and involuntary feedback of actual urination events, as well as continued biometric and/or environmental data collection, can be used to train individual and collective urination models.

Abstract: An endoscopic biopsy and debulking system is disclosed with a sheath having a distal end, an orifice defined on a lateral surface of the distal end, a handle disposed at a proximal end of the sheath, the handle having a connection on for attaching a hose, a suction source attached to the hose for providing negative pressure at the orifice, a cutting instrument at least partially inside the sheath and movable relative to the sheath between a first position and a cutting position, and the cutting instrument being capable of retracting or cutting tissue through the orifice in the cutting position.

Abstract: An endoscopic system having a shaft, a sheath disposed at least partially inside the shaft having a distal end with a leading surface and an inner surface, the leading surface at the distal end of the sheath having rounded edges so as to be atraumatic, an instrument at least partially inside the sheath and movable relative to the sheath along a longitudinal direction of the sheath, the inner surface being sloped so as to deflect the instrument at a predetermined angle as it is moved into contact with the inner surface and out of the sheath, and the sheath being rotatable relative to the shaft so as to change the direction at which the instrument extends from the sheath.

Abstract: A bedwetting monitoring method implemented by a computer, bladder monitoring device and a patient alert device and includes determining a urination volume of a bladder of a patient at which a patient will urinate, determining a trigger volume of the bladder of the patient representing a volume that is less than the urination volume, monitoring a volume of the bladder of the patient with a bladder monitoring device, and alerting the patient with the patient alert device at the trigger volume to wake the patient prior to urination.

Abstract: A system for predicting and detecting urination events of users is disclosed. The system can include any number of wearable devices, mobile devices, hubs, computing devices, and servers to collect, share, process, and interpret data, as well as to provide stimuli to users and caregivers. Biometric and/or environmental data associated with a user can be collected and applied to a urination model to determine a predicted urination time. The user or a caregiver can be provided with direct or environmental stimuli conveying information about predicted urination times. Ongoing biometric and/or environmental data collection can be used to identify, and provide stimuli warning of, imminent urination events. Voluntary and involuntary feedback of actual urination events, as well as continued biometric and/or environmental data collection, can be used to train individual and collective urination models.

Abstract: A system for predicting and detecting urination events of users is disclosed. The system can include any number of wearable devices, mobile devices, hubs, computing devices, and servers to collect, share, process, and interpret data, as well as to provide stimuli to users and caregivers. Biometric and/or environmental data associated with a user can be collected and applied to a urination model to determine a predicted urination time. The user or a caregiver can be provided with direct or environmental stimuli conveying information about predicted urination times. Ongoing biometric and/or environmental data collection can be used to identify, and provide stimuli warning of, imminent urination events. Voluntary and involuntary feedback of actual urination events, as well as continued biometric and/or environmental data collection, can be used to train individual and collective urination models.

Abstract: A method performed by a computer correlates vesicoelastic pressure data (10, 12, 14) with volume data and calculates vesicoelastic work performed by the bladder (20), wherein the amount of vesicoelastic work performed by the bladder (20) is determined by calculating an area under said vesicoelastic pressure data (10, 12, 14) when said vesicoelastic pressure data (10, 12, 14) is correlated against the volume data.

Abstract: A method performed by a computer correlates vesicoelastic pressure data (10, 12, 14) with volume data and calculates vesicoelastic work performed by the bladder (20), wherein the amount of vesicoelastic work performed by the bladder (20) is determined by calculating an area under said vesicoelastic pressure data (10, 12, 14) when said vesicoelastic pressure data (10, 12, 14) is correlated against the volume data.

Abstract: A system for predicting and detecting urination events of users is disclosed. The system can include any number of wearable devices, mobile devices, hubs, computing devices, and servers to collect, share, process, and interpret data, as well as to provide stimuli to users and caregivers. Biometric and/or environmental data associated with a user can be collected and applied to a urination model to determine a predicted urination time. The user or a caregiver can be provided with direct or environmental stimuli conveying information about predicted urination times. Ongoing biometric and/or environmental data collection can be used to identify, and provide stimuli warning of, imminent urination events. Voluntary and involuntary feedback of actual urination events, as well as continued biometric and/or environmental data collection, can be used to train individual and collective urination models.

Abstract: A bedwetting monitoring method implemented by a computer, bladder monitoring device and a patient alert device and includes determining a urination volume of a bladder of a patient at which a patient will urinate, determining a trigger volume of the bladder of the patient representing a volume that is less than the urination volume, monitoring a volume of the bladder of the patient with a bladder monitoring device, and alerting the patient with the patient alert device at the trigger volume to wake the patient prior to urination.