CN116710019A - Safety mechanism for robot bone cutting - Google Patents
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Abstract
Methods and systems for providing a safety mechanism for robotically controlled surgical tools. Embodiments of these methods use sensors to detect parameters that vary with the tissue traversed by the surgical tool. The sensor detects signals generated by the interaction of the surgical tool with the tissue and provides this information to the robotic controller. For example, during drilling, the sensor may measure power, vibration, acoustic frequency, mechanical load, electrical impedance, and distance traversed from pre-operative measurements of a three-dimensional image set for planning tool trajectories. By comparing the detected output with the output predicted for the planned trajectory based tool position, the identified output difference will indicate that the tool has been diverted from the planned trajectory. The robotic controller may then alter the tool trajectory, alter the speed of the tool, or interrupt power to the tool, thereby preventing damage to the underlying tissue.
Description
Technical Field
The present disclosure describes techniques related to the field of robotic orthopedic surgery, and more particularly to safety mechanisms when robotically cutting or drilling bone.
Background
In hand or robotically performed orthopedic procedures, cutting or drilling tools, whether conventional or ultrasonic blades, are used. Ultrasonic power tools have become the tool of choice for many orthopedic procedures, particularly for delicate work in sensitive areas such as the spine. One of the important challenges in such procedures is the need to apply multiple security layers to the system to prevent damage to the underlying or surrounding tissue. This requirement is important in robotically performed procedures because if tissue experiences unexpected positional changes during the procedure, the dependence on the expected position of the anatomical feature based on the initial registration of the intra-operative robot coordinate system with the pre-operative three-dimensional image may be compromised. For example, when the cutting tool is operated with a large force in bone adjacent to soft tissue, the soft tissue may be accidentally displaced or compressed beyond a desired extent, and thus the force used in cutting or sawing bone tissue should be avoided as much as possible. However, such care cannot be maintained in all cases, and thus the problem arises how to avoid compromising the system registration due to soft tissue movement. In addition, when cutting or otherwise operating on bone tissue, the risk of damage to the surrounding area of bone tissue should be minimized.
Reference is made to the following documents which describe the characteristics of such bone cutting operations:
"Use of an ultrasonic osteotome device in Spine surgery: experience from the first 128 components (use of ultrasonic osteotome device in spinal surgery: experience from the first 128 patients)", hu X, ohnmeiss DD and Lieberman IH, eur Spine J.2013, month 12; 22 (12):2845-2849.
"Sound analysis in drilling, frequency, and time domains (sound analysis in drilling, frequency and time domains)"; parsian A, magnevall M, beno T and Eynian M.Procepia CIRP 58 (2017) 411-415.
234786 1PWCN
US 2014/0276849"Method for ultrasonic tissue excision with tissue selectivity (ultrasound tissue ablation method with tissue selectivity) to Voic D, published at 18/9/2014 and assigned to Misonix corporation.
The disclosure of each of the publications mentioned in this section and in the other sections of this specification is incorporated herein by reference in its entirety.
Disclosure of Invention
The present disclosure describes a new exemplary system for a safety mechanism to prevent collateral damage to tissue by drilling, milling tools, or sawing through bone. Embodiments of the disclosed system utilize at least one of the plurality of sensors to give feedback to the system regarding the characteristics of the tissue being traversed by the tool.
In robotically controlled surgery, the preoperative planning for execution by the surgical robotic system is typically based on a three-dimensional preoperative image set of the surgical field. A planned trajectory of the surgical tool is calculated based on the images. In surgery, the actual trajectory of the tool is typically achieved by locating the tool tip from the preoperative image using a registration procedure as described below. In spinal surgery, known measurements of vertebral bodies, pedicles, and other anatomical features of interest may be used to provide information to the system or to a human operator regarding the position of the tool tip in three dimensions. Such registration between the preoperative image of the operative area and the intraoperative anatomy of the subject allows for determination of the progress of the tool, including, for example, the distance remaining until the edge of the saw or the tip of the operative tool reaches a position where it would pose a hazard to the patient.
However, even if the procedure is performed according to a surgical plan based on pre-operative images registered with the robotically positioned tool tip, small displacements of deeper tissue relative to the surface may introduce small but significant changes in the position of the anatomical feature relative to the actual position of the tool. In other words, the tissue through which the tool passes may not be the tissue in which the tool should be in accordance with the original surgical plan calculation by the system, whether due to lateral displacement or displacement of the depth of the encountered tissue. Even in those procedures that calculate a surgical plan and tool trajectory based on intraoperative CT images (which may reflect updated positions of bone and surrounding tissue), movement of bone and tissue may still occur intraoperatively due to various surgical procedures even in accordance with the intraoperatively generated surgical plan, and such movement may then cause a discrepancy between the actual tissue on which the tool is operating and the tissue expected at that position.
Thus, one of the challenges in automated robotic surgery, particularly in procedures such as bone cutting, milling or drilling, is the need for a reliable safety mechanism to provide the following warnings: the position of the surgical tool has been calculated relative to the tissue in which the surgical tool is operating has changed or the tool is approaching or invading tissue in which the tool is operating would be dangerous. In particular, the following warnings should be provided: surgical tools have been accidentally or soon transferred from bone tissue to surrounding soft tissue or organs. In addition, the transmission from cortical bone to cancellous bone or from cancellous bone to cortical bone may also require a warning or at least notification to the operator. Furthermore, even when navigational tracking is used to directly track the pose of a bone on which a surgical procedure is being performed by the tool so that bone movement may be considered, the possibility of inadvertent blockage of the line of sight of the optical tracking beam may require an additional non-dependent protective layer for safe execution of the procedure.
The present disclosure describes new exemplary security mechanisms that reduce the likelihood of such errors. Such methods and systems are based on using sensors to detect parameters that vary according to the tissue in which the surgical tool is operating. Not only are different tissues of different density and characteristics, but also the outer regions of some tissues (especially bony tissues) may have different characteristics than the inner regions. Thus, the information collected by the sensor should provide an indication of whether the surgical tool has entered the following tissue in its planned path: the organization has characteristics that are different than those expected for the planned path. Furthermore, this information should also preferably give an indication as to whether the surgical tool is approaching the following tissue: according to the surgical plan, the tool is not intended to traverse the tissue even before the tool reaches the boundary.
The information collected by the sensor may include at least some of the following:
(i) Sound emitted by the drilling or cutting process.
(ii) Electrical power drawn by the surgical tool or by the robot.
(iii) The sound emitted by the tool motor during its progress.
(iv) When the surgical tool performs its task, the surgical tool experiences mechanical forces through the reaction of the surgical tool with tissue, particularly with bone.
(v) Mechanical vibrations experienced by the tool as it travels through the bone.
(vi) An electrical impedance sensed between the surgical tool tip and the subject's body.
The above information collected by the sensors may be used to help determine the characteristics of the tissue in which the surgical tool is operating. The above-described system may include a database storing the type and/or level of sensor responses expected for each relevant sensor device as the surgical tool passes through cortical bone, cancellous bone, and various soft tissues. The above-described system is configured to identify a location of the tool relative to tissue through which it passes based on registration with the preoperative image. Thus, the system may compare the actual sensor output generated with the data stored in the database for the projected sensor output of the planned tool path, thereby providing information identifying the tissue in which the surgical tool is actually operating, and providing a warning if the tool has deviated significantly from its projected trajectory. Such a deviation may be determined in the event that the actual measured sensor output does not coincide with an output predicted from the interaction of the surgical tool with the tissue in which the surgical tool is supposed to be located, as determined by the known position of the surgical tool in its robot trajectory. This lack of consistency may be manifested in a variety of ways, most commonly by the level or magnitude of the measured effect, but may also be manifested by other effects, such as by the frequency of the measured effect, or by any other measured inconsistency that suggests a lack of match or difference between the predicted effect and the actual measured effect.
Tissue characteristics not only vary between tissue types (such as between bone tissue and soft tissue), but may also vary based on other factors (such as the age of the surgical personnel). For example, a difference between the density of cortical bone and the density of cancellous bone in an 80 year old osteoporotic woman is expected to be less than a 30 year old man. The above-described system may advantageously use machine learning and big data to calculate predicted sensor responses at different locations within a patient by analyzing data collected from various sources. These sources may include at least some of the following: clinical history of the patient, information collected from pre-operative images and other imaging modalities such as bone density scans, clinical and post-operative outcome data collected from other patients who have previously undergone similar surgery. The actual sensor response recorded during operation is then compared to the predicted response to provide an indication of the nature of the tissue through which the tool is traveling.
Artificial intelligence may be employed during surgery to analyze specific patterns and behaviors of sensor output as different surgical tools traverse different tissues. Thus, the system may learn to identify when the tool traverses unexpected anatomy or even anatomy at an unexpected location or depth that deviates from the location or depth indicated in the original surgical plan. Thus, the presently disclosed methods provide for application of artificial intelligence methods to analyze sensor output parameters related to tool movement (related to tool position) to provide a safety mechanism for robotic operation of the tool even without direct visual or sensory feedback regarding the tool position itself.
An additional or alternative way of using a database of expected sensor output values to give an indication of the transition of the tool between one tissue and another is to configure the system to respond if the sensor output values change by more than a predetermined amount, thereby indicating a hazard to the subject. The quantity may be an absolute cut-off value of a parameter measured by the sensor, or a relative increase or decrease, or a change in the rate of increase or decrease. A significant change in the sensor output value indicates that the tool has transitioned or is transitioning to tissue having different tissue characteristics than the tissue characteristics of the previous operation of the tool. Such variations are acceptable where desired; however, if the detected tissue position of the tool is different than the tissue position calculated by the surgical plan for that point of the planned trajectory, the above-described system may trigger a warning or response from the system. The main purpose of the safety mechanism is to: monitoring and ensuring the position of the tool tip within the tissue in which the tool should operate; and to prevent accidental ingress from the tissue (such as bone) into adjacent, delicate tissue.
Using the sensor output, the system may be capable of providing information about the depth of penetration of the tool through tissue. This situation exists when the sensor output provides a different output depending on the distance from the outer edge of the currently monitored tissue. Thus, if the surgical tool is erroneously advanced toward the edge of the allowed area beyond which the surgical tool will impinge on an area where the tool is prohibited from operating, such as a spinal canal or soft tissue, an advance warning should be provided to the surgeon or robotic controller that the boundary is approaching.
In addition to the basic purpose of the above system to avoid accidental disengagement of the surgical tool from the bone and damage to sensitive soft tissue, an additional advantage of the above system is the use of sensor output to enable more utilization of the bone depth of the subject than originally planned. For example, one example is the ability to insert pedicle screws to greater depths. In addition to or in addition to the sensors detecting access to the exclusion zone, these sensors may also be used to detect that the distance from the exclusion zone is still maintained, allowing the drill to penetrate further into the bone and use the entire available expansion zone of the bone.
Drilling of pedicle screw holes may be used as an example of the criticality and need of the presently disclosed system. The pedicle is a narrow bone bridge between the vertebral body and the spinous process, and the margin of error with respect to the alignment drill is narrow at this point, such that small errors may have serious consequences. In particular for robotic performed procedures, the system needs to be configured with an additional layer of security in addition to the instruction set supplied to the robot by the surgical plan based on the preoperative three-dimensional image. Because robots lack sensory feedback that human operators can feel, additional safety mechanisms are needed to prevent inadvertent damage to neural tissue within the spinal canal, paraspinal muscles on the outside of the vertebrae, or peripheral nerves and blood vessels.
If or when the system senses that the saw, drill or milling tool is approaching impact on the forbidden area, or that the saw, drill or milling tool deviates from the planned trajectory by more than a certain amount, the system may employ a number of options to avoid tissue damage or to prevent the tool from entering areas where it is not allowed. The controller may turn off power to the tool or slow the speed of the tool; or the controller may change the trajectory of the tool by robotic control; or the controller may choose to shut down the robot so that the tool progress can be checked.
Current bone cutters or saws employ ultrasonic vibration of a blade to effect cutting. Such tools have an inherent safety mechanism due to the different cutting capabilities in tissues with different densities. It is known that ultrasonic cutting blades are capable of making initial contact with soft tissue without coupling energy levels into the tissue that could result in cutting the tissue. Instead, the tool will deflect the soft tissue quite simply. This is in contrast to the contact of the same blade with hard tissue, which would result in a cutting action, with the same power. However, a greater positive pressure on the soft tissue typically results in damage to the soft tissue. Thus, it would be advantageous to add another security layer, as anatomical features in the surgical field may shift or slide with respect to the surface level where registration has been performed during surgery.
The presently disclosed methods provide for the application of artificial intelligence methods to analyze sensor output parameters related to tool movement (related to tool position) to provide a safety mechanism for robotic operation of the tool even without direct visual or sensory feedback regarding the tool position itself.
Accordingly, there is provided, in accordance with an exemplary embodiment of the apparatus described in the present disclosure, a robotic surgical system comprising:
(a) A controller configured to control a position of the surgical tool according to the planned trajectory,
the planned trajectory passes through different organizations, and
(b) At least one sensor adapted to output a signal based on the interaction of the surgical tool with the tissue on which the surgical tool is operating,
wherein the controller is further configured to:
(i) A predicted tissue corresponding to a known position of the surgical tool in the planned trajectory is determined,
(ii) Identifying an expected signal output from the at least one sensor from a dataset comprising tissue-specific sensor output signals, the expected signal output resulting from an interaction of the surgical tool with the expected tissue,
(iii) Comparing the predicted signal output from the at least one sensor with a measured signal output from the at least one sensor, the measured signal output resulting from interaction of the surgical tool with tissue on which the surgical tool is operating, and
(iv) If the measured signal output does not coincide with the predicted signal output from the predicted tissue on which the surgical tool is operating, it is concluded that the surgical tool is not following its planned trajectory.
In the robotic surgical system described above, the at least one sensor may be adapted to sense any one of:
(i) The sound made by the surgical procedure is transmitted,
(ii) The electrical power drawn by the surgical tool or by the robot,
(iii) The sound emitted by the motor of the surgical tool during its progress,
(iv) The mechanical forces experienced by the reaction of the surgical tool to the tissue,
(v) Mechanical vibrations experienced by the surgical tool as it travels through tissue, and
(vi) Electrical impedance of tissue in which the tool is operating.
Further, in such robotic surgical systems, if it is determined that the surgical tool does not follow its planned trajectory, the controller may be configured to instruct at least one of:
(i) The movement of the tool along the planned trajectory is stopped,
(ii) The advancing speed of the surgical tool is reduced,
(iii) The processing capacity of the surgical tool is reduced,
(iv) Turning off the power to the surgical tool, and
(v) A warning is issued to the operator of the system.
In addition, in any of the robotic surgical systems described above, the surgical tool may be adapted to perform at least one of cutting, milling, drilling, and sawing of bone tissue. Further, the known location of the surgical tool may include a distance along the tool path of the planned trajectory. Further, the planned trajectory may include a procedure in bone tissue, and deviations from the planned trajectory may thus include the surgical tool exiting from the bone tissue.
In any of the robotic surgical systems described above, if it is determined that the surgical tool does not follow its planned trajectory, the controller may be further configured to prevent the surgical tool from entering tissue that does not conform to the planned trajectory. In such cases, the controller may be further adapted to determine a remaining depth of the procedure within the bone tissue using the output of the at least one sensor. Then, if it is determined that the depth remaining in the bone tissue is greater than the depth predicted from the planned trajectory, the controller may be further adapted to instruct the operation in the bone tissue to proceed to a depth deeper than the depth indicated by the planned trajectory.
According to further embodiments of the robotic surgical system of the present disclosure, the signal output predicted from any of the at least one sensor may be adjusted to reflect at least one of: bone density, age, sex, skeletal muscle condition, osteoporosis measured by z-score, and any concomitant disease in a subject. Additionally, the actions performed by the controller may include maintaining controlled movement of the robotic arm of the surgical tool. Further, the data set of tissue specific sensor output signals may include expected values of sensor output signals generated by a surgical tool through any of cortical bone, cancellous bone, and different types of soft tissue.
There is further provided in accordance with another embodiment described in the present disclosure a method for monitoring the progress of a robotically guided surgical tool along a predetermined path through different tissues, the method comprising:
(i) Determining tissue the surgical tool is expected to traverse from a known location of the surgical tool along the predetermined path,
(ii) At least one sensor output resulting from interaction of the surgical tool with tissue traversed by the surgical tool is detected,
(iii) Comparing the at least one sensor output with an expected sensor output from interaction of the surgical tool with tissue the surgical tool is expected to traverse, and
(iv) If the comparison reveals that the at least one sensor output is meaningfully different from the predicted sensor output, then it is determined that the surgical tool is deviating from the predetermined path.
In such methods, the at least one sensor may detect at least one of:
(i) The sound made by the surgical procedure is transmitted,
(ii) The electrical power drawn by the surgical tool or by the robot,
(iii) The sound emitted by the motor of the surgical tool during its progress,
(iv) The mechanical forces experienced by the surgical tool through its reaction to the tissue,
(v) Mechanical vibrations experienced by the surgical tool as it travels through tissue, and
(vi) Electrical impedance of the tissue being traversed by the tool.
Further, in any of these methods, if the surgical tool is found to deviate from the predetermined path, at least one of the following is performed:
(i) The movement of the tool along the planned trajectory is stopped,
(ii) The advancing speed of the surgical tool is reduced,
(iii) The processing capacity of the surgical tool is reduced,
(iv) Turning off the power to the surgical tool, and
(v) A warning is issued to the operator of the system.
In any of the above methods, the predetermined path through the different tissue may comprise a surgery in bone tissue, and the deviation from the predetermined path may comprise the surgical tool exiting from the bone tissue. The methods may further include analyzing, using artificial intelligence, whether the at least one sensor output falls outside a predetermined normal range of expected sensor outputs. Further, if it is determined that the tool is deviating from the predetermined path, the method may instruct at least one of: disabling power to the tool, reducing power to the tool, or changing the trajectory of the tool.
Finally, according to a further embodiment of the system described in the present application, a robotic surgical system is presented, comprising:
(i) A controller configured to control movement of the robotically controlled surgical tool according to a surgical plan, and
(ii) At least one sensor, each of the at least one sensor being adapted to detect an output resulting from interaction of the tool with tissue of the subject, and to communicate the detected tool-tissue interaction output to the controller,
wherein if at least one of the tool-tissue interaction outputs deviates from the tool-tissue interaction output predicted from tissue interacting with the surgical tool according to the surgical plan by more than a predetermined normal range, it is concluded that the surgical tool has deviated from the surgical plan.
In such systems, the tool-tissue interaction output may include at least one of:
(i) The sound made by the surgical procedure is transmitted,
(ii) The electrical power drawn by the surgical tool or by the robot,
(iii) The sound emitted by the motor of the surgical tool during its progress,
(iv) As the surgical tool performs its task, the mechanical forces experienced by the surgical tool through its reaction to the tissue,
(v) Mechanical vibrations experienced by the surgical tool as it travels through tissue, and
(vi) An electrical impedance sensed between the surgical tool tip and tissue of the subject.
In any of the above systems, the tool-tissue interaction output predicted from tissue interacting with the surgical tool may be obtained from a database of predicted tool-tissue interaction outputs for a range of tissues and for a range of surgical tool conditions. In addition, at least one of the tool-tissue interaction outputs may include a plurality of tool-tissue interaction outputs that match the at least one tissue type. Further, in these systems, the controller may be adapted to use sound emanating from the surgical procedure in bone tissue to provide an indication of the depth to which the surgical tool is positioned within the bone tissue. Furthermore, if the sound emitted by the surgical procedure is experiencing an increase in pitch, the system may be configured to identify this as an indication that the surgical tool is approaching an end boundary of bone tissue. In these systems, the sound detected by the at least one sensor may include either or both of frequency and volume resulting from interaction of the tool with the tissue of the subject.
According to further embodiments of such systems, at least one of the following may be used to provide an indication of at least one of softness or density of the tissue being traversed by the surgical tool:
(i) The power drawn by the motor of the surgical tool,
(ii) The tone of the sound wave generated by the motor of the surgical tool,
(iii) Mechanical vibrations experienced by the surgical tool as it travels through tissue, and
(iv) The mechanical force required by the surgical tool to traverse the tissue.
Additionally, in any of these systems, the controller may be adapted to perform at least one of: (i) terminate power to the tool, (ii) reduce power to the tool, (iii) change the trajectory of the tool, or (iv) alert the system operator if at least one tool-tissue interaction output deviates from an output expected from tissue expected to be traversed by the tool according to the surgical plan by more than a predetermined limit.
Another exemplary embodiment described in the present disclosure relates to a safety system for performing a surgical procedure on a subject with a robotically controlled surgical tool, the system comprising:
(a) A controller configured to control movement of the robotically controlled surgical tool according to the planned trajectory, and
(b) At least one sensor adapted to output a signal based on the interaction of the surgical tool with the tissue on which the surgical tool is operating,
Wherein the controller is further configured to:
(i) An anatomical feature estimated to be the surgical tool being operated upon is determined from the planned trajectory,
(ii) Receiving an output signal transmitted by the at least one sensor, and
(iii) Providing an indication that the surgical tool has deviated from the planned trajectory if at least one of the following occurs:
(c) As the tool traverses the tissue on which the surgical tool is operating, the at least one sensor signal is outside of a predetermined range expected for the sensor signal,
(d) A behavior pattern of sensor signals received from at least one sensor, the behavior pattern differing by more than a predetermined degree from a pattern expected by the tool traversing the planned trajectory, or
(e) Each of the at least two sensor signals is outside a predetermined range within which each sensor signal is expected to be a result of the tool traversing the planned trajectory.
Another embodiment of the method of the present application is a safety mechanism for a bone working tool under robotic control, the safety mechanism comprising:
(i) Using at least one sensor to detect a change in at least one quantifiable parameter when the bone working tool is moved by robotic control, the at least one quantifiable parameter changing when the bone working tool is moved through bone when compared to soft tissue adjacent to the bone, and
(ii) Based on the change in the at least one quantifiable parameter, instructions are sent to the robotic control to take action to provide protection to soft tissue adjacent the bone.
In the method described above, the action taken by the robotic control to protect soft tissue adjacent to the bone may include at least one of:
(i) The movement of the bone working tool is stopped,
(ii) The advancing speed of the bone working tool is reduced,
(iii) The working capacity of the bone working tool is reduced,
(iv) Turning off the power to the bone working tool, and
(v) An alert is issued to an operator of the system using the bone working tool.
In the method, the quantifiable parameter may include at least one of:
(i) The sound emitted by the operation of the bone working tool,
(ii) The electrical power drawn by the bone working tool,
(iii) The sound emitted by the motor of the bone working tool during its movement,
(iv) The bone working tool experiences mechanical forces through its reaction to bone or adjacent tissue,
(v) Mechanical vibration experienced by the bone working tool while the robot controls the movement of the bone working tool, and
(vi) Electrical impedance of the tissue being traversed by the bone working tool.
Definition of the definition
In the context of the present application, segment tracking is used in surgery for real-time imaging, such as ultrasound, to measure the position of a tool relative to a tissue feature.
Edge learning is a process of learning using a tool tip; in surgery, this is accomplished by contacting different tissues and recording information from the tissues.
Drawings
The present invention will be more fully understood and appreciated from the following detailed description, taken in conjunction with the accompanying drawings, in which:
FIG. 1 illustrates an exemplary surgical robotic system using sensors for detecting the type of tissue through which a surgical tool is passing;
FIGS. 2A-2D illustrate the operation of the safety mechanism by measuring various sensed outputs associated with an operating surgical drill;
FIGS. 3A and 3B illustrate the use of an ultrasonic bone cutting blade for craniotomy;
FIGS. 4 and 5 are flowcharts outlining steps performed in two alternative illustrative embodiments of methods that may be used with the system of FIG. 1; and is also provided with
Fig. 6 illustrates structural components of an exemplary block diagram of a controller coupled to a system for implementing a safety mechanism.
Detailed Description
Referring now to fig. 1, an exemplary surgical robotic system having a controller 101 and at least one robotically controlled arm 104 is schematically illustrated. The controller is typically supplied with or calculates a surgical plan for the patient, which may be based on information collected from pre-or intra-operative images. The coordinate system of the robot should be registered to the image used to generate the surgical plan so that when the controller provides instructions to the robot 104 to enable the robot to perform the surgical plan using one or more surgical tools 105, the predicted position of the surgical tool tip 105 relative to the position of the patient's anatomy may be calculated by or known to the controller.
In typical embodiments, the surgical tool 105 may be a saw, drill, or milling head, any of which may be conventional, or may be an ultrasonic cutting tool capable of penetrating bone tissue. In the case of the exemplary procedure shown in fig. 1, the surgical procedure illustrated is a spinal fusion procedure, and the tool is a drill designed to form a hole for inserting a pedicle screw into vertebra 108. During operation of the system, robotic arm 104 operated by controller 101 moves surgical tool 105 to perform the steps of the procedure; in this exemplary case, a hole is drilled from the posterior aspect of the vertebra into the pedicle.
To confirm that the surgical tool 105 follows the trajectory indicated by the surgical plan, as indicated by the coordinates recorded by the controller, and to ensure that the surgical tool is not approaching or entering an unintended area, a plurality of sensors 107A, 107B, 107C, 107D, and 107E provide information to the controller 101 regarding characteristics of the tissue in which the surgical tool 105 is moving, each sensor detecting such characteristics. For clarity of the drawing, fig. 1 does not show all paths of sensor information to the controller.
Based on the characteristics of the tissue, the controller may determine whether the surgical tool 105 is approaching or has entered an unintended area, such as soft tissue. In one embodiment of the system, the response of the sensors 107A-E is used to determine whether the surgical tool is operating in tissue predicted by the trajectory depicted by the surgical plan. If not, the controller 101 uses at least some of these sensor outputs to adjust the robotic action, typically by stopping the forward motion of the tool, or by stopping the cutting action, and by providing a warning to the surgeon, as discussed further below.
For examples of operating on bone, the sensor may include any one or a combination of the following:
(i) A sound sensor 107E adapted to collect data concerning the frequency and intensity of the sound emitted by the surgical procedure itself.
(ii) A power sensor 107B adapted to collect data regarding the amount of electrical power consumed by the motor of the surgical tool.
(iii) A sensor 107C adapted to collect data concerning the frequency and intensity of vibrations emitted by the tool motor during its progress.
(iv) A force sensor 107D adapted to detect mechanical forces encountered by the tool as it travels through the bone.
(v) A mechanical vibration sensor 107A adapted to collect data concerning the mechanical vibrations emitted by the tool as it travels through tissue.
(vi) An electrode 107F adapted to collect data about the electrical impedance of tissue in the region of the tool tip, as sensed between the surgical tool tip and the body of the subject.
The sensors all provide their output signals to the controller 101, the processor of which analyzes the output and calculates any inconsistent data from the data predicted from the surgical plan trajectory and procedure. If such deviations of the experience data from the predicted data are experienced, the robotic system should adjust the robotic actions accordingly and at the same time alert the attending surgeon who can then check the surgical situation to ensure that the robotic actions are corrected in a safe manner or that the progress of the robotic actions is aborted.
In fig. 1, the relative position of each sensor has been schematically shown, but it will be appreciated that each sensor will be in a position where the sensor is able to detect the particular parameter it is intended to measure. Thus, for example, the power sensor 107B may be located in the system controller 101, rather than on circuitry within the robot itself, and the tool machine vibration sensor 107A may preferably be located close to the tool holder.
The vibration sensor 107A is adapted to detect mechanical vibrations experienced by the drill or other surgical tool 105 as it travels through tissue. Different materials will cause different vibrations, as softness, density and other tissue properties may cause the drilling tool to vibrate differently in different materials.
The power used by the drill motor to insert the drill bit through the harder or denser tissue is significantly greater than the mechanical load or force required to advance the drill bit through the softer or less dense tissue. Thus, the power sensor 107B may be used to measure the amount of power drawn by the motor of the surgical tool 105, and the force sensor 107D positioned in line with the drilling tool may be used to measure the force required to advance the drilling tool through tissue.
An indirect measurement of the power used by the drill may be obtained by the pitch of the sound waves generated by the drill motor. Thus, a frequency sensor 107C adapted to measure the frequency of the sound emitted by the drill motor may be used to give an indication of the density and softness of the tissue being drilled.
Measurement of vibration of tissue while drilled or otherwise worked by a surgical tool may provide additional means of detecting tissue characteristics. Different tissues emit sounds with different frequencies because the vibrations produced by drilling are different for drilling through different materials. Perhaps even more useful, such sounds may give an indication of tissue thickness because the thicker the material being drilled, sawn or contacted, the lower the frequency of the sounds produced by contact of the surgical tool with the tissue. Thus, not only can the acoustic sensor 107E give an indication of the type of tissue being drilled, but the tone detected by the sensor for a given material can also indicate where in the tissue the surgical tool is positioned. For example, as the tool tip approaches the edge of the bone, the emitted sound is expected to experience an increase in tone even before the tool tip penetrates.
In some embodiments, the system uses the sensor output to enable pedicle screws to be inserted to depths deeper than predicted by the surgical plan. The sensor may detect that the tool has not been approaching a forbidden area, as opposed to what would be expected from a preoperative surgical plan, and additional bone is available for advancement of the tool. This allows for further penetration of the tool, as well as the use of the entire available expansion area of the bone, thereby expanding the utility and accuracy of the original surgical plan.
Electrical impedance is a property of tissue and is different in cortical bone than in cancellous bone and is different in bone than in fluid-filled or empty space (such as a spinal canal), or is different in cortical bone than in muscle. Each tissue has a different electrical impedance determined by its composition. Some materials have a high electrical impedance, while others have a low electrical impedance. Thus, measuring tissue impedance at the tip site of the drilling tool via the electrode 107F positioned in the tissue may be used to determine the type of tissue and, in some cases, the location of the drilling tool within the tissue.
With the exception of the last-mentioned impedance sensor, each of these parameters is affected by the operation of the saw or drill, and the signal changes as the tool progresses from one tissue type to another. The ideal parameters are those that begin to change before the saw or drill reaches the edge of the bone or other dangerous area, or those that warn of impending danger before the drill bit transitions from one tissue to another. Each of these parameters is discussed in more detail below.
Although not all sensors are used for each system or each surgical procedure, the output of one or more sensors 107A-107F employed is input into control system 101, which analyzes the output signal of each monitored sensor. The controller is additionally supplied with expected values for specific parameters of the anatomy, wherein the controller calculates or estimates that the surgical tool 105 is operating according to the surgical plan. These expected sensor output values may be stored in a database accessible to the controller 101. If the controller receives a sensor output that varies by more than a predetermined amount from the predicted sensor output, the controller may provide a signal to the robotically controlled arm 104 to slow the rate of tool advancement, cut power to the tool, temporarily stop the movement of the tool from progressing, or change the tool trajectory to avoid damage to surrounding tissue. Additionally or alternatively, the controller may issue a warning to a human operator.
A security mechanism using a combination of some or all of the above-described controller responses may have a good potential to prevent collateral damage. The system may be configured to allow any single parameter to be used to provide a warning signal to a human operator, to change the speed or trajectory of the tool, or to disconnect power to the surgical tool. The selected one or more controller safety responses may be selected by the system based on a given tool, surgical or patient characteristic. This flexibility provides the greatest safety margin by personalizing the proximity for a given situation. Preferably, the system may be configured to use a combination of sensor outputs in accordance with both intrinsic characteristics and tissue characteristics of the surgical tool, and to compare intra-operative actual distance and angle measurements with corresponding measurements taken from pre-operative imaging studies to provide a higher level of safety to the drilling process.
In an alternative embodiment, the controller does not use a database of expected sensor outputs to determine if the surgical tool is approaching a forbidden area. Instead, detection of a sudden increase or decrease in sensor output intensity is an indication that the surgical tool is transitioning or has transitioned between tissues, prompting the controller to take one of the actions described above.
Drilling of pedicle screw holes may be used as an example of the criticality and need of the presently disclosed system. Because the pedicle is a narrow bone bridge between the vertebral body and the spinous process, and the accuracy required to align the drilling tool is very high, small errors can have serious consequences. In particular for robotically performed procedures, the system needs to be configured with an additional layer of security in addition to the instructions provided to the robot by the preoperative three-dimensional image based surgical plan. The system must provide sensory feedback that a human operator will feel and be a robotic system that can provide a further safety mechanism to prevent inadvertent damage to neural tissue within the spinal canal, paraspinal muscles outside the vertebrae, or peripheral nerves and blood vessels.
If or when the system senses through any of the system sensor outputs 107A-107F that the saw, drill, or milling tool is approaching impact on the forbidden area, or if the sensor is detecting from the sensor the type of tissue on which the tool is operating suggests that the tool has deviated from the planned trajectory by more than a certain amount, the system may employ a number of options to avoid tissue damage or to prevent the tool from entering an area where it is not allowed.
The proposed solution is applicable to the most common methods of surgical bone cutting and milling using conventional drills or saws or high power ultrasonic surgical blades. Different sensors may be used for different surgical procedures, and the type of sensor used may be tailored to the surgical procedure. For drilling applications, where conventional mechanical rotational action may be used, some of the desired sensor output parameters may be different from those used during ultrasonic cutting.
Referring now to fig. 2A-2D, it is illustrated how the safety mechanism depicted in fig. 1 is designed to protect a patient's tissue from damage by giving an indication as to whether the surgical plan is being followed as expected. In fig. 2A, an example of a surgical tool intended to follow a trajectory 209 depicted in a surgical plan, which in the exemplary illustration of fig. 2A is a trajectory that traverses a spinal plate and a pedicle into the vertebral body 206. On the right side of the vertebrae shown in fig. 2A are two examples of unintended trajectories that the surgical tool may take if the coordinate system of the surgical tool tip is not properly aligned with the map of the patient's anatomy. Drill bit 201A follows trajectory 211A, entering the vertebra at an angle inboard of the pedicle, causing the drill bit to penetrate into spinal canal 208. The drill bit 201B follows the trajectory 211B, causing the drill to enter the adjacent paraspinal muscle 207. Taking into account the small difference in the angle of the surgical tool between the correct trajectory 209 and the incorrect trajectories 201A, 201B, a safety mechanism is required to ensure the correct insertion of the tool.
Referring now to fig. 2B, there is shown the variation of the measured parameters as the drill bit is advanced through the vertebrae along the correct trajectory 209, denoted along the x-axis as cortical bone 205, cancellous bone 206, and if the path continues, through the cortical bone 205 again. Two exemplary parameters represented by traces 220 and 221 are measured, the relative intensities of each of which are shown on the y-axis. These parameters are for illustrative purposes only and may be any of the parameters discussed above in fig. 1, which vary as the drill bit passes through various anatomies. The intensity of the sensor output trace is marked on the ordinate of the graph so that the exemplary graph of fig. 2B shows how the intensity of the sensor output is affected on trace 209 shown on the x-axis.
Trace 220 shows the sensor output that would be obtained by, for example, sound level or vibration of the drilling tool or power drawn as the drilling tool travels along trace 209. As the drill tip enters the cortical bone, the sensor output rises sharply, with the drill traveling through the cortical bone thickness, because the friction on the rotating drill increases, the sensor output drops when cancellous bone is encountered, and rises again in the opposite cortical bone layer. This behavior is expected from the rotating drill, while the behavior of the ultrasonic cutting tool is slightly different. Trace 221 in fig. 2A shows another representative parameter that increases more gradually as the drill enters the bone, but decreases more sharply as the drill leaves the bone. Each parameter may follow a different and unique curve, some of which show a path that is opposite to the other, such as decreasing upon entry into the bone. Each of these parameters varies with the drilling tool. If allowed, then passes through anatomical structures 205 and 206 and passes through anatomical structure 205 again. In a typical embodiment, the control system receives sensor outputs such as 220 and 221 and analyzes the output signals. A sudden increase or decrease in either of these parameter values 220 and 221 may indicate to the controller that the drilling tool has passed the tissue boundary or interface, and that the controller should use its preprogrammed routine to determine what action, if any, to take.
For the part of the patient anatomy where the controller calculates the surgical tool to be operated, the controller may additionally be supplied with the expected value of the sensor output. These expected sensor output values may be stored in a database accessible to the controller. The expected threshold for each tissue parameter may vary based on the bone density, age, sex, skeletal muscle condition of a given patient, osteoporosis measured by z-score, and any concomitant disease that may affect the safety threshold for the measured parameter. In addition, the sensor outputs expected for different tissues may vary depending on the angle of the surgical tool 105, the rate of entry of the surgical tool 105, and the depth of the surgical tool 105 within the patient's tissue or from the skin. Thus, the actual sensor output may provide a reflection of the movement of the tool, and thus the spatial position of the tool, relative to or within a given tissue. Algorithms and methods of artificial intelligence (such as deep learning and machine learning) can be used to analyze this information in space and time to develop an accurate map of the expected sensor output for a particular tool in a given organization.
One such way in which the system may use artificial intelligence and/or machine learning to fine tune the sensor feedback system is to utilize experimental studies or actual sensor output of previous surgical procedures to analyze how the sensor output is affected as different surgical tools traverse different tissues. Thus, as the tool traverses a given anatomy, the system can learn to recognize the particular pattern and behavior of the sensor response output. For example, a reduction in sound intensity and vibration, and possibly frequency, such as that emitted by a surgical procedure, combined with a reduction in power and force required to pass through a given bone feature, may be used to provide an indication that the tool is transitioning from cortical bone to cancellous bone or has transitioned to cancellous bone. As illustrated in exemplary fig. 2B, such as the reduction in the vibration intensity of the drilling tool 201B and the force applied by the drilling tool occurs as the drilling tool passes from cortical bone 205 to cancellous bone 206. Once the drill has been translated into movement through cancellous bone 206, there is an overall drop in both, for example, vibration of the drill and the force applied by the drill. The analysis and other relevant clinical information may be entered into a database and/or stored as a dataset in which different sensor output patterns are marked to indicate different tissues to help define the predicted parameter measurements as the tool traverses a given anatomical feature. Thus, the specificity of the measurement allows for greater definition of the predicted measurement of a given parameter at a given depth or location of a particular tool operating on a particular anatomical feature (such as a vertebra).
Another advantage of using a database of expected sensor output values may be that artificial intelligence can distinguish subtle differences in sensor output behavior as the tool is operated in and passed between soft tissue types such as muscle, ligament, and loose connective tissue. The system may also employ edge learning by contacting the tool with different tissues to learn the characteristics of each tissue in that particular patient. Such techniques are particularly useful for ultrasonic power tools.
Additionally and alternatively, artificial intelligence analysis of the stored data may be used during surgery to provide positional information to the system or surgeon based on measured parameters. During the operation itself, the system may incorporate real-time measurements of parameters defining tool positions relative to other tissue features. Such segment tracking provides an additional source of information related to the location of the tool in the tissue and may be integrated with the changing parameters to enhance the accuracy of the security mechanism.
In fig. 2C, an exemplary power trace 222C is shown as the drill bit travels along trace 211A through cortical bone 205, cancellous bone 206, again through cortical bone 205, and finally into spinal canal 208 if not stopped. In fig. 2D, a trace 223 of another incorrect trajectory 211B is shown, except that the drilling tool enters musculature 207 having a relatively greater density than the potential space of spinal canal 208, which may be discerned as a different level of measured parameters of curve 223 in region 207 than region 208 of fig. 2C. These examples are for illustration only, as activation of the safety mechanism is designed to prevent the drill bit from penetrating beyond the second portion of cortical bone. The use of a combination of parameters to form a combination of sensors provides a higher level of security than the measurement of a single parameter.
Referring now to fig. 3A and 3B, another exemplary embodiment of the disclosed method is illustrated that provides a safety mechanism for an ultrasonic bone cutter used in a skull operation. In fig. 3A, a bone cutter 301 is used to create a bone flap 302 in the skull. Ultrasonic cutting of bone is accomplished by amplifying and converting electrical signals into ultrasonic vibrations of the blunt blade, the frequency of which is on the order of tens of kHz, 22,500kHz being a common frequency; repeated impacts break up the crystalline bone structure while more compliant adjacent soft tissue is less affected by the ultrasonic oscillations. Referring to fig. 3B, due to the different tissue densities between bone 303 and the underlying dura 304 overlying neural tissue 305, the ultrasonic cutter may depress the dura bone while contacting the dura, but does not penetrate the dura bone under normal operating conditions. Such ultrasonic powered cutting tools are therefore particularly useful for performing operations in bone adjacent to neural tissue, such as tools for cutting the skull in the case of fig. 3A and 3B, or for forming osteotomies in vertebrae in operations where preservation of facial neural tissue is critical. However, this approach may result in thermal damage and tearing of the meninges; thus, additional safety mechanisms are needed to prevent tissue damage.
By robotic control of the preoperative three-dimensional image-based procedure, the ultrasonic blade can be precisely inserted to the depth of the vertebrae, skull, or other bone to make cuts in any given location. However, even though prior registration may be performed between the position of the surgical tool 301 and the anatomy of the patient, small anatomical displacements in the tissue plane relative to the surface may introduce small but significant changes in the actual position of the tool. Thus, the additional security measures and information provided by the various sensor embodiments of the present application are very important in helping to ensure a secure operating program.
Referring now to FIG. 4, a flowchart illustrating steps involved in an embodiment of an exemplary method that may be used with the system of FIG. 1 is shown. In step 401, a surgical plan is established that defines a path of the robotic arm 104 to guide the surgical tool 105 along a planned trajectory. In step 402, the predicted change in tissue density that the tool is predicted to experience along the path defined in step 401 is determined using knowledge of the interactions of the tool with the various types of tissue and knowledge of the path to be followed. In step 403, the robotic controller 101 provides guidance to the robotic arm 104 operating the surgical tool 105. In step 404, the interaction of tool 105 with the various tissues through which the tool passes produces outputs from at least some of sensors 107A-107F, and these outputs are input into controller 101. The sensor output is related to tool operation such that the sensor output provides information about the type of tissue through which the tool is moving. In step 405, the system analyzes these outputs of the sensor with respect to the expected sensor outputs expected from step 402. The analysis may be a simple comparison between the actual sensor values measured by the sensors 107A-107F compared to the expected sensor output of a given tissue being traversed by the surgical tool 105 as calculated by the system. However, as depicted in fig. 2B, the system may additionally employ artificial intelligence to give an indication of whether the tissue being operated on has predicted tissue characteristics by analyzing patterns and behavior of changes in sensor output as the procedure progresses. In step 406 of the illustrated exemplary procedure, the system uses the results of the analysis performed in step 405 to determine whether the tool trajectory has been diverted from the planned path, such as due to tissue movement, and from the history of the trajectory, whether the deviation is greater than an allowable distance, or whether the tool has entered tissue of an area in which the tool is prohibited from operating, or whether the system has determined from a particular sensor output that the tool is about to enter a prohibited area. If no such diversion from the surgical plan is found, the sensors 107A-107F continue in step 404 to measure the parameter(s) of interest as the surgery proceeds according to the surgical plan.
On the other hand, if a deviation from the surgical plan is found, then in step 408, the system determines which action to take. The system may have a default response built-in so that the system responds if any, or if the combination of sensor output values exceeds a predetermined threshold. Alternatively, the system may run algorithms that may incorporate machine learning, deep learning, or other techniques of artificial intelligence to determine which action to take. The decision may be based on the particular sensor output received by the control system and the analysis performed in step 405. The system may respond using any of the following steps:
(i) Step 409a: the power to the tool is turned off.
(ii) Step 409b: reducing the speed of rotation of the drill, the frequency of ultrasonic vibrations, or other aspects of tool operation.
(iii) Step 409c: the trajectory of the tool 105 is changed by the robotic control 104.
(iv) Step 409d: the robot is turned off.
In addition, in either step, a warning may be issued to the operator.
Referring now to fig. 5, there is a flow chart showing the steps involved in an alternative exemplary implementation of the method related to the system of fig. 1. In step 501, data regarding predicted patterns of sensor outputs for various sensors that react to various anatomical features is supplied to a controller. The data may be from a known external database or from a database derived from previously performed experiments to obtain the desired response from the particular surgical tool setup being used in the robotic system being used. In step 502, a robotic surgical tool is provided with a planned surgical path to follow from a known starting position of the surgical tool to a desired final target position. In step 503, the robotic controller 101 instructs the robotic arm 104 to begin performing 502 a surgical path. In step 504, the sensors 107A-107F provide outputs to the controller when the surgical path is implemented. In step 505, the controller analyzes the sensor output using the tag data of step 501. In step 506 of the illustrated exemplary procedure, the system uses the results of the analysis performed in step 505 to determine whether the sensor output received by the controller in 504 indicates that the surgical tool is traversing the surgical path determined in step 502. If the tool is traveling along the planned path within the predetermined deviation limits, then in step 507 the system determines if the tool has completed traversing the surgical path, and if so, then in step 508 the method ends. On the other hand, if it is determined in step 506 that the tool is not on the intended path, then in step 509 the system aborts the current path of the surgical tool and returns to step 502 to recalculate the tool position and the new surgical path and resume its implementation.
If it is determined that the deviation from the expected path is due to a shift of tissue in the surgical field, the controller may issue instructions to perform intra-operative imaging to determine the current tissue deployment before planning a new surgical path and then continue from the point where the original path stopped, or resume implementation of the new surgical path, along the modified path, taking into account the tissue shift.
Referring now to FIG. 6, components of an illustrative system for performing representative embodiments of the disclosed methods are illustrated. The control system 600 includes a memory unit 601, a processor 602, a user interface 603, one or more databases 504, one or more measurement devices 605, and a network interface 606. Memory (RAM) 501 is used to store at least some of the following: (i) preoperative planning 607, (ii) real-time measurements 608 obtained by the measurement device 605, and (iii) predetermined cut-off values 609 for the measured parameters. The processor 602 includes a controller for executing optional algorithms for artificial intelligence such as machine learning and deep learning. The system 600 communicates with a surgical robotic system 610 comprising the components schematically shown in fig. 1, which includes a controller 101 that operates at least one robotically controlled arm 104 that holds and controls a surgical tool 105.
In this disclosure, the term system may refer to, be part of, or include the following: an Application Specific Integrated Circuit (ASIC); digital, analog, or hybrid analog/digital discrete circuits; digital, analog, or hybrid analog/digital integrated circuits; a combinational logic circuit; a Field Programmable Gate Array (FPGA); a processor (shared, dedicated, or group) that executes code; a memory (shared, dedicated, or group) storing code for execution by the processor; other suitable hardware components that provide the described functionality, such as optical, magnetic or solid state disks; or a combination of some or all of the above, such as in a system-on-chip. As described above, the term code may include software, firmware, and/or microcode, and may refer to programs, routines, functions, classes, and/or objects. The term shared processor encompasses a single processor that executes some or all code from multiple modules. The term clustered processor encompasses processors that execute some or all code from one or more modules in conjunction with another processor. The term shared memory encompasses a single memory that stores some or all code from multiple modules. The term banked memory encompasses memory that stores some or all code from one or more modules in combination with additional memory. The term memory may be a subset of the term computer readable medium. The term computer-readable medium does not encompass transitory electrical and electromagnetic signals propagating through the medium, and thus may be considered tangible and non-transitory. Non-limiting examples of the non-transitory tangible computer readable medium include nonvolatile memory, volatile memory, magnetic storage, and optical storage.
The apparatus and methods described in this disclosure may be implemented, in part or in whole, by one or more computer programs executed by one or more processors. The computer program includes processor-executable instructions stored on at least one non-transitory tangible computer-readable medium. The computer program may also include and/or be dependent on stored data.
The exemplary embodiments are provided so that this disclosure will be thorough, and will fully convey the scope of the disclosure to those skilled in the art. Numerous specific details are set forth, such as examples of specific components, devices, and methods, in order to provide a thorough understanding of embodiments of the present disclosure. It will be apparent to one skilled in the art that the exemplary embodiments may be embodied in many different forms without the use of specific details and should not be construed as limiting the scope of the disclosure.
It will be appreciated by persons skilled in the art that the present invention is not limited to what has been particularly shown and described hereinabove. Rather, the scope of the present invention includes both combinations and sub-combinations of the various features described hereinabove as well as variations and modifications thereof which would occur to persons skilled in the art upon reading the foregoing description and which are not in the prior art.
Claims (31)
1. A robotic surgical system, the robotic surgical system comprising:
a controller configured to control a position of a surgical tool according to a planned trajectory, the planned trajectory passing through different tissues; and
at least one sensor adapted to output a signal according to an interaction of the surgical tool with tissue on which the surgical tool is operating;
wherein the controller is further configured to:
(i) Determining predicted tissue corresponding to a known position of the surgical tool in the planned trajectory;
(ii) Identifying an expected signal output from at least one sensor from a dataset comprising tissue-specific sensor output signals, the expected signal output resulting from interaction of the surgical tool with the expected tissue;
(iii) Comparing the predicted signal output from the at least one sensor with a measured signal output from the at least one sensor, the measured signal output resulting from interaction of the surgical tool with the tissue on which the surgical tool is operating; and
(iv) If the measured signal output is inconsistent with the predicted signal output from the predicted tissue in which the surgical tool is operating, it is concluded that the surgical tool is not following its planned trajectory.
2. The robotic surgical system according to claim 1, wherein the at least one sensor is adapted to sense any one of:
(i) Sounds made by the surgical procedure;
(ii) Electrical power drawn by the surgical tool or by the robot;
(iii) Sounds emitted by the motor of the surgical tool during its progress;
(iv) Mechanical forces experienced by the reaction of the surgical tool to the tissue;
(v) Mechanical vibrations to which the surgical tool is subjected as it travels through the tissue; and
(vi) An electrical impedance of the tissue in which the tool is operating.
234786 1PWCN
3. The robotic surgical system according to any one of the preceding claims, wherein if the controller determines that the surgical tool does not follow its planned trajectory, the controller is configured to instruct at least one of:
(i) Stopping movement of the tool along the planned trajectory;
(ii) Reducing the advancement speed of the surgical tool;
(iii) Reducing the processing capacity of the surgical tool;
(iv) Closing the power to the surgical tool; and
(v) A warning is issued to an operator of the system.
4. The robotic surgical system according to any one of the preceding claims, wherein the surgical tool is adapted to perform at least one of cutting, milling, drilling and sawing of bone tissue.
5. The robotic surgical system according to any one of the preceding claims, wherein the known position of the surgical tool includes a distance along a tool path of the planned trajectory.
6. The robotic surgical system according to any one of the preceding claims, wherein the planned trajectory includes a procedure in bone tissue and deviation from the planned trajectory includes the surgical tool exiting from the bone tissue.
7. The robotic surgical system according to any one of the preceding claims, wherein if it is determined that the surgical tool does not follow its planned trajectory, the controller is further configured to prevent the surgical tool from entering tissue that does not conform to the planned trajectory.
8. The robotic surgical system according to claim 6, wherein the controller is further adapted to determine a remaining depth of the procedure within the bone tissue using an output of at least one sensor.
9. The robotic surgical system according to claim 8, wherein the controller is further adapted to: if it is determined that the remaining depth within the bone tissue is greater than the depth predicted from the planned trajectory, then the procedure is indicated to continue in the bone tissue to a depth greater than the depth indicated by the planned trajectory.
10. The robotic surgical system according to any one of the preceding claims, wherein the signal output predicted from any one of the at least one sensor is adjusted to reflect at least one of: bone density, age, sex, skeletal muscle condition, osteoporosis measured by z-score, and any concomitant disease in a subject.
11. The robotic surgical system according to any one of the preceding claims, wherein the action performed by the controller includes maintaining a controlled movement of a robotic arm of the surgical tool.
12. The robotic surgical system according to any one of the preceding claims, wherein the data set includes expected values of sensor output signals generated by the surgical tool through any one of cortical bone, cancellous bone, and different types of soft tissue.
13. A method for monitoring the progress of a robotically guided surgical tool through different tissues along a predetermined path, the method comprising:
(a) Determining tissue the surgical tool is expected to traverse from a known location of the surgical tool along the predetermined path;
(b) Detecting at least one sensor output resulting from interaction of the surgical tool with the tissue traversed by the surgical tool;
(c) Comparing the at least one sensor output to an expected sensor output from interaction of the surgical tool with the tissue the surgical tool is expected to traverse; and
(d) If the comparison reveals that the at least one sensor output is meaningfully different from the predicted sensor output, then it is determined that the surgical tool is deviating from the predetermined path.
14. The method of claim 13, wherein the at least one sensor detects at least one of:
(i) Sounds made by the surgical procedure;
(ii) Electrical power drawn by the surgical tool or by the robot;
(iii) Sounds emitted by the motor of the surgical tool during its progress;
(iv) Mechanical forces experienced by the surgical tool through reaction of the surgical tool with the tissue;
(v) Mechanical vibrations to which the surgical tool is subjected as it travels through the tissue; and
(vi) An electrical impedance of the tissue being traversed by the tool.
15. The method according to any one of claims 13 and 14, wherein if the surgical tool is found to deviate from the predetermined path, at least one of:
(i) Stopping movement of the tool along the planned trajectory;
(ii) Reducing the advancement speed of the surgical tool;
(iii) Reducing the processing capacity of the surgical tool;
(iv) Closing the power to the surgical tool; and
(v) A warning is issued to an operator of the system.
16. The method of any one of claims 13 to 15, wherein the predetermined path through different tissue comprises a procedure in bone tissue and the deviation from the predetermined path comprises the surgical tool exiting from the bone tissue.
17. The method of any of claims 13 to 16, further comprising using artificial intelligence to analyze whether the at least one sensor output falls outside a predetermined normal range of the expected sensor output.
18. The method of any of claims 13 to 17, wherein if it is determined that the tool is deviating from the predetermined path, at least one of: disabling power to the tool, reducing power to the tool, or changing the trajectory of the tool.
19. A robotic surgical system, the robotic surgical system comprising:
a controller configured to control movement of the robotically controlled surgical tool according to a surgical plan; and
At least one sensor, each of the at least one sensor being adapted to detect an output resulting from interaction of the tool with tissue of the subject and to communicate the detected tool-tissue interaction output to the controller,
wherein if at least one of the tool-tissue interaction outputs deviates from a tool-tissue interaction output predicted from the tissue interacting with the surgical tool according to a surgical plan by more than a predetermined normal range, it is concluded that the surgical tool has deviated from the surgical plan.
20. The robotic surgical system according to claim 19, wherein the tool-tissue interaction output includes at least one of:
(i) Sounds made by the surgical procedure;
(ii) Electrical power drawn by the surgical tool or by the robot;
(iii) Sounds emitted by the motor of the surgical tool during its progress;
(iv) When the surgical tool performs its task, the surgical tool experiences mechanical forces through the reaction of the surgical tool with the tissue;
(v) Mechanical vibrations to which the surgical tool is subjected as it travels through the tissue; and
(vi) An electrical impedance sensed between the surgical tool tip and tissue of the subject.
21. The system of any of claims 19 and 20, wherein the tool-tissue interaction output predicted from the tissue interacting with the surgical tool is obtained from a database of predicted tool-tissue interaction outputs for a range of tissues and for a range of surgical tool conditions.
22. The system of any of claims 19 to 21, wherein at least one of the tool-tissue interaction outputs comprises a plurality of tool-tissue interaction outputs that match at least one tissue type.
23. The system of any one of claims 19 to 22, wherein the controller is adapted to provide an indication of the depth to which the surgical tool is positioned within bone tissue using sound emitted by the surgical procedure in bone tissue.
24. The system of claim 23, wherein the sound emitted by the surgical procedure undergoing tone augmentation provides an indication that the surgical tool is approaching an end boundary of the bone tissue.
25. The system of any one of claims 20 to 24, wherein the sound detected by the at least one sensor comprises at least one of: (i) Frequency and (ii) volume, the sound being generated by interaction of the tool with tissue of the subject.
26. The system of any one of claims 19 to 25, wherein at least one of the following is used to provide an indication of at least one of softness or density of the tissue being traversed by the surgical tool:
(i) Power drawn by a motor of the surgical tool;
(ii) A tone of sound waves generated by a motor of the surgical tool;
(iii) Mechanical vibrations to which the surgical tool is subjected as it travels through the tissue; and
(iv) The mechanical force required by the surgical tool to traverse the tissue.
27. The system of any one of claims 19 to 26, wherein the controller is adapted to perform at least one of: (i) terminating power to the tool, (ii) reducing power to the tool, (iii) changing the trajectory of the tool, or (iv) alerting the system operator if at least one tool-tissue interaction output deviates from an output expected from the tissue expected to be traversed by the tool according to the surgical plan by more than a predetermined limit.
28. A safety system for performing a surgical procedure on a subject with a robotically controlled surgical tool, the system comprising:
a controller configured to control movement of the robotically controlled surgical tool according to a planned trajectory; and
at least one sensor adapted to output a signal according to an interaction of the surgical tool with tissue on which the surgical tool is operating;
wherein the controller is further configured to:
(i) Determining from the planned trajectory an anatomical feature in which the surgical tool is estimated to operate;
(ii) Receiving an output signal transmitted by at least one sensor; and
(iii) Providing an indication that the surgical tool has deviated from the planned trajectory if at least one of:
(a) At least one sensor signal being outside a predetermined range expected for a sensor signal as the tool traverses the tissue on which the surgical tool is operating;
(b) Receiving a pattern of behavior of sensor signals from at least one sensor, the pattern of behavior differing by more than a predetermined extent from a pattern expected by the tool traversing the planned trajectory; or alternatively
(c) Each of the at least two sensor signals is outside a predetermined range within which each sensor signal is expected to be a result of the tool traversing the planned trajectory.
29. A method for providing a safety mechanism for a bone working tool under robotic control, the method comprising:
using at least one sensor to detect a change in at least one quantifiable parameter as the bone working tool is moved by the robotic control, the at least one quantifiable parameter changing as the bone working tool is moved through the bone as compared to soft tissue adjacent to the bone, and
based on the change in the at least one quantifiable parameter, instructions are sent to the robotic control to take action to provide protection to the soft tissue adjacent to the bone.
30. The method of claim 29, wherein the action taken by the robotic control to protect the soft tissue adjacent the bone comprises at least one of:
(i) Stopping movement of the bone working tool;
(ii) Reducing the travel speed of the bone working tool;
(iii) Reducing the working capacity of the bone working tool;
(iv) Turning off power to the bone working tool; and
(v) An alert is issued to an operator of a system using the bone working tool.
31. The method of claim 29 or 30, wherein the quantifiable parameters include at least one of:
(i) Sounds emitted by operation of the bone working tool;
(ii) Electrical power drawn by the bone working tool;
(iii) Sound emitted by a motor of the bone working tool during movement thereof;
(iv) The mechanical forces experienced by the bone working tool through its reaction to the bone or adjacent tissue;
(v) Mechanical vibrations experienced by the bone working tool as the robotic control moves the bone working tool; and
(vi) An electrical impedance of the tissue being traversed by the bone working tool.
Applications Claiming Priority (4)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| US63/136,010 | 2021-01-11 | ||
| US17/569,957 | 2022-01-06 | ||
| US17/569,957 US20220218421A1 (en) | 2021-01-11 | 2022-01-06 | Safety mechanism for robotic bone cutting |
| PCT/IL2022/050029 WO2022149139A1 (en) | 2021-01-11 | 2022-01-09 | Safety mechanism for robotic bone cutting |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN116710019A true CN116710019A (en) | 2023-09-05 |
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ID=87824401
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202280009402.0A Pending CN116710019A (en) | 2021-01-11 | 2022-01-09 | Safety mechanism for robot bone cutting |
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| Country | Link |
|---|---|
| CN (1) | CN116710019A (en) |
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2022
- 2022-01-09 CN CN202280009402.0A patent/CN116710019A/en active Pending
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