A verification signal transmission unit transmits a verification signal including time information indicating a current time to a server apparatus via a relay apparatus. The verification signal relay unit receives the verification signal from the medical device and transmits the verification signal to the server apparatus. The verification signal reception unit receives the verification signal, and the offset determination unit compares the time information included in the verification signal with a current time on the server apparatus in UTC time and determines whether the medical device includes a UTC offset in the time information. A determination result transmission unit transmits a result of determination related to a UTC offset to the relay apparatus or the medical device. A determination result reception unit receives the result of determination. A registration unit registers information related to the result of determination in a device information recording unit, mapping the information to device identification information identifying the medical device.

Novel tools and techniques are provided for implementing intelligent assistance (“IA”) or extended intelligence (“EI”) ecosystem for pulmonary procedures. In various embodiments, a computing system might analyze received one or more first layer input data (i.e., room content-based data) and received one or more second layer input data (i.e., patient and/or tool-based data), and might generate one or more recommendations for guiding a medical professional in guiding a surgical device(s) toward and within a lung of the patient to perform a pulmonary procedure, based at least in part on the analysis, the generated one or more recommendations comprising 3D or 4D mapped guides toward, in, and around the lung of the patient. The computing system might then generate one or more XR images, based at least in part on the generated one or more recommendations, and might present the generated one or more XR images using a UX device.

A waveguide apparatus includes a planar waveguide and at least one optical diffraction element (DOE) that provides a plurality of optical paths between an exterior and interior of the planar waveguide. A phase profile of the DOE may combine a linear diffraction grating with a circular lens, to shape a wave front and produce beams with desired focus. Waveguide apparati may be assembled to create multiple focal planes. The DOE may have a low diffraction efficiency, and planar waveguides may be transparent when viewed normally, allowing passage of light from an ambient environment (e.g., real world) useful in AR systems. Light may be returned for temporally sequentially passes through the planar waveguide. The DOE(s) may be fixed or may have dynamically adjustable characteristics. An optical coupler system may couple images to the waveguide apparatus from a projector, for instance a biaxially scanning cantilevered optical fiber tip.

A waveguide apparatus includes a planar waveguide and at least one optical diffraction element (DOE) that provides a plurality of optical paths between an exterior and interior of the planar waveguide. A phase profile of the DOE may combine a linear diffraction grating with a circular lens, to shape a wave front and produce beams with desired focus. Waveguide apparati may be assembled to create multiple focal planes. The DOE may have a low diffraction efficiency, and planar waveguides may be transparent when viewed normally, allowing passage of light from an ambient environment (e.g., real world) useful in AR systems. Light may be returned for temporally sequentially passes through the planar waveguide. The DOE(s) may be fixed or may have dynamically adjustable characteristics. An optical coupler system may couple images to the waveguide apparatus from a projector, for instance a biaxially scanning cantilevered optical fiber tip.

A method for adjusting the operation of a surgical suturing instrument using machine learning in a surgical suite is disclosed. The method comprises gathering data during surgical procedures, wherein the surgical procedures include the use of a surgical suturing instrument comprising a suturing needle configured to be mechanically advanced through a suturing stroke, analyzing the gathered data to determine an appropriate operational adjustment of the surgical suturing instrument, and adjusting the operation of the surgical suturing instrument to improve the operation of the surgical suturing instrument.

A method for adjusting the operation of a surgical suturing instrument using machine learning in a surgical suite is disclosed. The method comprises gathering data during surgical procedures, wherein the surgical procedures include the use of a surgical suturing instrument comprising a suturing needle configured to be mechanically advanced through a suturing stroke, analyzing the gathered data to determine an appropriate operational adjustment of the surgical suturing instrument, and adjusting the operation of the surgical suturing instrument to improve the operation of the surgical suturing instrument.

Systems and methods are disclosed for processing sensor data collected by a drug delivery device with an external computing device. The drug delivery device may include a reservoir and a delivery cannula having a proximal end in fluid communication with the reservoir and a distal end to be received within a patient. The drug delivery device may further include one or more sensors configured to generate sensor data representative of a condition and/or operational state of the drug delivery device, and a communication module configured to transmit information to the external computing device. The external computing device may process the information received from the drug delivery device according to information stored in a memory of the external computing device to determine the condition or the operational state of the drug delivery device and/or generate instructional or informational prompts to be displayed to a user or patient.

Systems and methods are disclosed for processing sensor data collected by a drug delivery device with an external computing device. The drug delivery device may include a reservoir and a delivery cannula having a proximal end in fluid communication with the reservoir and a distal end to be received within a patient. The drug delivery device may further include one or more sensors configured to generate sensor data representative of a condition and/or operational state of the drug delivery device, and a communication module configured to transmit information to the external computing device. The external computing device may process the information received from the drug delivery device according to information stored in a memory of the external computing device to determine the condition or the operational state of the drug delivery device and/or generate instructional or informational prompts to be displayed to a user or patient.

A secure dispensing unit includes a housing comprising a first end and a second end and a number of storage assemblies. The number of storage assemblies are arranged in parallel with one another within the housing. Each storage assembly includes a number of compartments arranged linearly along an axis of the housing with each of the compartments being configured to store an item. A cover is coupled with the housing and extends between the first end and the second end such that the cover is positioned over the compartments. An actuator is coupled with the cover, the actuator being configured to retract the cover to draw a distal end of the cover from the first end toward the second end to expose a selected number of compartments.

Disclosed are methods and systems for diagnosing, staging, stratifying, prognosing, and/or treating bladder cancer. In particular, the invention relates to methods and systems for classifying Stage T1 bladder cancer. The disclosed methods may include generating an mRNA expression profile for a sample of Stage T1 bladder cancer and classifying the sample based on the expression profile.