A method for adjusting the operation of a surgical instrument using machine learning in a surgical suite is disclosed. The method comprises the steps of gathering data during surgical procedures, wherein the surgical procedures include the use of a surgical instrument, analyzing the gathered data to determine an appropriate operational adjustment of the surgical instrument, and adjusting the operation of the surgical instrument to improve the operation of the surgical instrument.

Systems and methods for instrument control include a first actuator for controlling a first mechanical degree of freedom, a second actuator for controlling a second mechanical degree of freedom, and a controller. The controller is configured to command the first actuator to maintain the first actuator at a first position, wherein actuation of the first actuator is subject to a first torque limit; command the second actuator to maintain the second actuator at a second position, wherein actuation of the second actuator is subject to a second torque limit; and in response to detecting that the first actuator cannot be maintained at the first position using actuation subject to the first torque limit and the second actuator can be maintained at the second position using actuation subject to the second torque limit, terminate the command to the first actuator to maintain the first actuator at the first position.

A method for characterising the performance of a joint in a surgical robotic arm, the joint being driven by a drivetrain which transfers power from a drive source to the joint, the method comprising: sending a first command signal to position the robot arm into an initial configuration; sending a second command signal to apply a force to the joint to displace the joint from a steady state; for a plurality of predefined time intervals: receiving a first measurement indicating the configuration of the drive source at a first end of the drivetrain; receiving a second measurement indicating the configuration of the joint at a second end of the drivetrain; calculating a value of elongation using the first and second measurements; and receiving a third measurement indicating the torque experienced by the joint at the second end of the drivetrain; comparing the values of elongation with corresponding values of torque at each of the predefined time intervals; and generating an output from the comparison indicating the performance of the joint.

Techniques of selective joint floating in a computer-assisted system include a computer-assisted device that includes a kinematic chain including a plurality of links coupled by a plurality of joints and a control unit coupled to the kinematic chain. The kinematic chain is configured to support an end effector. The control unit is configured to determine location information for a first operator interaction with the kinematic chain, determine one or more joints to place into a floating state based on one or more parameters, and place the one or more joints into the floating state in response to determining the one or more joints. The one or more parameters being of the first operator interaction or of computer-assisted device. The one or more parameters including the location information. The plurality of joints including the one or more joints.

Co-manipulation robotic systems are described herein that may be used for assisting with laparoscopic surgical procedures. The co-manipulation robotic systems allow a surgeon to use commercially-available surgical tools while providing benefits associated with surgical robotics. Advantageously, the surgical tools may be seamlessly coupled to the robot arms using a disposable coupler while the reusable portions of the robot arm remain in a sterile drape. Further, the co-manipulation robotic system may operate in multiple modes to enhance usability and safety, while allowing the surgeon to position the instrument directly with the instrument handle and further maintain the desired position of the instrument using the robot arm.

A method of estimating bone mineral density according to at least one embodiment of the present disclosure includes receiving one or more images of an anatomical element; generating, based on the one or more images of the anatomical element, a three-dimensional mask for the anatomical element; generating, based on the three-dimensional mask for the anatomical element, a transformed three-dimensional mask for at least a portion of the anatomical element; filtering the one or more images of the anatomical element with the transformed three-dimensional mask for the at least a portion of the anatomical element; and determining, based on the filtering, a bone mineral density for the at least a portion of the anatomical element.

An implantable growing rod assembly adapted to be secured along a length of a spine for treating deformities of the spine. The assembly includes a housing, a fixed rod extending along a longitudinal axis away from the housing, and an expansion rod extendible from the housing along the longitudinal axis. A driver assembly is fixed to the housing and adapted to translate the expansion rod along the longitudinal axis. Examples of the implantable growing rod assembly include a smart growing system, and an autonomous growing rod system.

A carrier tool is proposed that may be used in combination with a dental torque wrench to easily access all dental implants, regardless of their location within the mount. The carrier tool comprises a shaft for extending the reach of the wrench, with a shortened mount attached to an opposing end of the shaft. The shorted mount is used to securely hold the implant measurement device during insertion within the implant. A magnet is disposed within the interior of the mount to secure the implant measurement device (also magnetized) in place as the carrier tool is brought into the proper position with respect to the implant.

To accurately predict a sensor value even in the case where external force is received. A control apparatus according to the present disclosure includes a prediction section that, in an actuator including a torque sensor that detects torque generated at a driving shaft, and an encoder that detects a rotational angle of the driving shaft, predicts a detection value of the encoder on a basis of a detection value of the torque sensor, or predict the detection value of the torque sensor on a basis of the detection value of the encoder, and a trouble determination section that compares a prediction value predicted by the prediction section with an actually measured value of the torque sensor or the encoder to perform trouble determination on the torque sensor or the encoder.

A robotic system includes control circuitry communicatively coupled to a robotic manipulator and configured to cause actuation of one or more actuators of the robotic manipulator. The control circuitry is configured to determine a manual force on the robotic manipulator, and control actuation of the one or more actuators of the robotic manipulator based at least in part on the manual force.