The present disclosure provides systems and methods for preparing a spinal rod that enable the digital mapping of rod contours to produce spinal rods that conform to an ideal rod trajectory, which reduces spinal rod to screw head misalignment. Reducing spinal rod to screw head misalignment helps reduce a failure rate of spinal rods in patients. In invasive spinal fusion surgeries, a digital three-dimensional representation may be generated of a flexible rod formed to align with screws installed in the patient. In minimally invasive surgeries, a digital three-dimensional representation may be generated using pointers. A surgeon may adjust the digital three-dimensional representation via a graphical user interface. Bending instructions may be generated from the digital three-dimensional representation that direct how a spinal rod should be bent using a bending tool. The final spinal rod accounts for the anatomical environment around the screws installed in the patient.

A method for adjusting the operation of a surgical instrument using machine learning in a surgical suite is disclosed.

There is provided an information processing device including an information acquisition unit that acquires information from an information providing device that provides the information related to quantitative numerical values to be grasped by the medical practitioner involved with a medical practice, an image data generation unit that generates image data related to the acquired information, and a control unit that controls an installation position of a light source irradiating drawing light having illuminance visually recognizable under a shadowless lamp or an operation state of an optical system that scans an irradiation position of the drawing light so as to draw the image data.

A support system, a support method, and a support program in the form of a non-transitory computer readable medium are disclosed that support a medical action during an operation. The support system includes a data acquisition unit configured to acquire, during an operation, use state data on a use state of a medical device during the operation, and target lesion data on a target lesion of a patient during the operation, a learning unit configured to perform machine learning using the use state data and the target lesion data, and a presentation unit configured to present a recommended operation policy based on a result of the machine learning.

Methods for guiding a surgical procedure include accessing information relating to a surgical procedure, accessing at least one image of a surgical site captured by an endoscope during the surgical procedure, identifying a tool captured in the at least one image by a machine learning system, determining whether the tool should be changed based on comparing the information relating to the surgical procedure and the tool identified by the machine learning system, and providing an indication when the determining indicates that the tool should be changed.

A surgical robot includes a controller configured or programmed to control a display to superimpose guide information indicating a moving direction of a medical cart based on a steering angle of a steering device on an image captured by an imaging device and display the guide information.

Methods, non-transitory computer readable media, interface adapter devices, and surgical computing devices and systems that detect and analyze connectivity of an end effector to a robotic arm are disclosed. With this technology, an interface adapter device of a robotic arm includes a connectivity sensor that determines when an end effector is disconnected from the robotic arm to be used as a handpiece by a surgeon to carry out particular surgical task(s) associated with a surgical procedure. The interface adapter device can instruct the robotic arm to automatically enter an inactive state defined in a surgical plan for the surgical procedure upon detection of the disconnection. Upon reconnection of the handpiece, or installation of a different handpiece, the interface adapter device automatically facilitates readjustment of the robotic arm based on an active state (e.g., automated resumption of the surgical procedure) defined in a surgical plan for the surgical procedure.

A use instrument predicting device includes a motion recognizing module that recognizes a motion of a surgeon during a surgical operation based on motion detection data that is obtained by detecting the surgeon's motion, a situation recognizing module that recognizes a surgery situation based on the motion recognized result of the motion recognizing module, and a predicting module that predicts at least one kind of surgical instrument to be used next by the surgeon out of a plurality of kinds of surgical instruments given beforehand, based on the situation recognized result of the situation recognizing module.

In a robotic surgical system, an operation unit includes a drive to assist an operation of an operator. A controller is configured or programmed to control the drive to exert a braking force when the operation on the operation unit is decelerated and/or accelerated.

A system and device (110) for determining bone laxity. For example, the system includes a tracked probe (300) comprising at least one probe marker (310) and a computer assisted surgical (CAS) system (100). The CAS system includes a navigation system (130) and a processing device (110) operably connected to the navigation system and a computer readable medium configured to store one or more instructions that, when executed, cause the processing device to receive location information from the navigation system, generate (820) a surgical plan comprising a post-operative laxity assumption (720), collect (850) first motion information related to movement of the joint through a first range of motion, collect (860) second motion information related to movement of the joint through a second range of motion, determine (870) a post-operative laxity (710), and compare the post-operative laxity and the post-operative laxity assumption to determine laxity results.