Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Response to Arguments
Claim objection has been withdrawn in view of amendments. Applicant's arguments filed on 07/08/2026 regarding claims 1, 3-9, 11-20 have been fully considered but they are not persuasive or moot. However, a new ground of rejection is provided below.
Claim Rejections - 35 USC § 102
The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention.
Claim(s) 1, 7, 9, 15, 17, and 18 are rejected under 35 U.S.C. 102(a)(1) as being read upon by Brett (P. N. Brett, "Moving on from surgical robotics to robotic micro-tools in surgery," 2007 14th International Conference on Mechatronics and Machine Vision in Practice, Xiamen, China, 2007, pp. 1-5).
Regarding Claim 1, Brett teaches a system, comprising:
a robotic arm having one or more degrees of freedom of control (See at least Figure 3 shows a robotic arm with one or more degrees of freedom of control), wherein the robotic arm includes an instrument interface comprising a tool guide which is configured to interface with a tool which can be manipulated during a collaborative procedure with a user (See at least Figure 3, Page 1 Col 2 Para 3 “Moving on from automatic and master-slave robotic systems in surgery there is a need for sensor-guided robotic devices that interpret or react to tissues in order to control the state of interaction between the tool-point and tissues. This is a complex process for a machine as perception will require automated interpretation of data, consideration of information derived and formation of strategies. These systems could be fully automatic, or automatic as part of a master-slave system to enable precise operation of tool points with respect to tissue targets and interfaces…”, Page 2 Col 1 Para 2 “…the second a micro drilling tool point able to discriminate tissue/ tool-point interaction to automatically identify the state and control the surgical process. The latter example has been deployed recently in the operating room as the first surgical robotic device of its kind.”, Page 3 Col 2 Para 2 “The system monitors force and torque transients of the tool point and interprets these in real-time…”, Page 3 Col 1 Para 3 “…Working under a surgical microscope, the drill unit is aligned by the surgeon in close proximity with the drilling site on the correct trajectory using the support arm, fine adjustment mechanism and the hand-held remote unit…”);
at least one force/torque sensor configured to sense forces applied to or at the instrument interface by the user while interfacing with the instrument (See at least Page 3 Col 2 Para 2 “The system monitors force and torque transients of the tool point and interprets these in real-time. The relationship between the transients can be used to distinguish between different states and phenomena, such as patient or tool movement, the approach to tissue boundaries, tissue hardness and stiffness, and drill breakthrough. …”, Page 3 Col 1 “III. SMART MICRO-DRILLING TOOL POINT … (deploying standard drill bits and accommodating the drill drive system and sensing elements), an anti-backlash support arm that can be attached to the operating table, a hard-wired controller system that also incorporates sensor interpretation functions, a hand held control pendant and a computer screen to provide feedback to the surgeon. The system is shown in figure 3.”);
a robot controller configured to control the robotic arm to move the instrument interface to a determined position and to control at least one robot control parameter (See at least Page 3 Col 2 Para 2 “The system monitors force and torque transients of the tool point and interprets these in real-time. The relationship between the transients can be used to distinguish between different states and phenomena, such as patient or tool movement, the approach to tissue boundaries, tissue hardness and stiffness, and drill breakthrough. Using part of this information it is possible to interpret the critical breakthrough event before it occurs and to automatically control drill tip penetration with minimum protrusion….”); and
a system controller configured to:
receive temporal force/torque data, wherein the temporal force/torque data represents
the forces at the instrument interface over time, sensed by the at least one force/torque sensor during the collaborative procedure with the user (See at least Page 3 Col 2 Para 2 “The system monitors force and torque transients of the tool point and interprets these in real-time. The relationship between the transients can be used to distinguish between different states and phenomena, such as patient or tool movement, the approach to tissue boundaries, tissue hardness and stiffness, and drill breakthrough. Using part of this information it is possible to interpret the critical breakthrough event before it occurs and to automatically control drill tip penetration with minimum protrusion….”),
analyze the temporal force/torque data to determine at least one of a current intention
of the user or a predefined state of the collaborative procedure (See at least Page 3 Col 2 Para 2 “The system monitors force and torque transients of the tool point and interprets these in real-time. The relationship between the transients can be used to distinguish between different states and phenomena, such as patient or tool movement, the approach to tissue boundaries, tissue hardness and stiffness, and drill breakthrough…”, discloses monitoring the force and torque transients can be used to distinguish between different states and phenomena, such as tool movement which is construed as determining current intention of the user),
determine a control mode which is predefined for the determined at least one of the
current intention of the user or the state of the collaborative procedure, wherein the control mode determines the at least one robot control parameter (See at least Page 3 Col 2 Para 2 “The system monitors force and torque transients of the tool point and interprets these in real-time. The relationship between the transients can be used to distinguish between different states and phenomena, such as patient or tool movement, the approach to tissue boundaries, tissue hardness and stiffness, and drill breakthrough. Using part of this information it is possible to interpret the critical breakthrough event before it occurs and to automatically control drill tip penetration with minimum protrusion….”, discloses using information related to force and torque to distinguish between different states and control the robot accordingly which is construed as determining a control mode which is predefined for the determined at least one of the current intention of the user or the state of the collaborative procedure); and
cause the robot controller to control the robotic arm in accordance with the control
mode (See at least Page 3 Col 2 Para 2 “The system monitors force and torque transients of the tool point and interprets these in real-time. The relationship between the transients can be used to distinguish between different states and phenomena, such as patient or tool movement, the approach to tissue boundaries, tissue hardness and stiffness, and drill breakthrough. Using part of this information it is possible to interpret the critical breakthrough event before it occurs and to automatically control drill tip penetration with minimum protrusion….”, discloses using information related to force and torque to distinguish between different states and control the robot accordingly which is construed as causing the robot controller to control the robotic arm in accordance with the control mode); and
wherein the forces comprise at least one of:
forces applied indirectly to the tool guide during user manipulation of the tool;
forces applied directly to the tool guide by the user (See at least Page 3 Col 2 Para 2 “III. SMART MICRO-DRILLING TOOL POINT … The system monitors force and torque transients of the tool point and interprets these in real-time…”, Page 3 Col 1 “(deploying standard drill bits and accommodating the drill drive system and sensing elements), an anti-backlash support arm that can be attached to the operating table, a hard-wired controller system that also incorporates sensor interpretation functions, a hand held control pendant and a computer screen to provide feedback to the surgeon. The system is shown in figure 3.”);
forces from an environment of the robotic arm; and
forces generated by the tool
Regarding Claim 7, modified Brett teaches all the elements of claim 1. Brett further teaches wherein the system provides an alert to the user when the system changes the control mode (See at least Page 3 Col 1 “III. SMART MICRO-DRILLING TOOL POINT … (deploying standard drill bits and accommodating the drill drive system and sensing elements), an anti-backlash support arm that can be attached to the operating table, a hard-wired controller system that also incorporates sensor interpretation functions, a hand held control pendant and a computer screen to provide feedback to the surgeon. The system is shown in figure 3.”).
Regarding Claim 9, Brett teaches a method of operating a robotic arm having one or more degrees of freedom of control (See at least Figure 3 shows a robotic arm with one or more degrees of freedom of control), wherein the robotic arm includes an instrument interface and a force/torque sensor to sense forces at the instrument interface, the instrument interface comprising a tool guide configured to interface with a tool which can be manipulated configured to interface with a tool which can be manipulated during a collaborative procedure with a user (See at least Figure 3, Page 1 Col 2 Para 3 “Moving on from automatic and master-slave robotic systems in surgery there is a need for sensor-guided robotic devices that interpret or react to tissues in order to control the state of interaction between the tool-point and tissues. This is a complex process for a machine as perception will require automated interpretation of data, consideration of information derived and formation of strategies. These systems could be fully automatic, or automatic as part of a master-slave system to enable precise operation of tool points with respect to tissue targets and interfaces…”, Page 2 Col 1 Para 2 “…the second a micro drilling tool point able to discriminate tissue/ tool-point interaction to automatically identify the state and control the surgical process. The latter example has been deployed recently in the operating room as the first surgical robotic device of its kind.”, Page 3 Col 2 Para 2 “The system monitors force and torque transients of the tool point and interprets these in real-time…”, Page 3 Col 1 Para 3 “…Working under a surgical microscope, the drill unit is aligned by the surgeon in close proximity with the drilling site on the correct trajectory using the support arm, fine adjustment mechanism and the hand-held remote unit…”), the method comprising:
receiving temporal force/torque data, wherein the temporal force/torque data represents forces applied to or at the instrument interface over time by the user while interfacing with the instrument, sensed by at least one force/torque sensor during the collaborative procedure with the user (See at least Page 3 Col 2 Para 2 “The system monitors force and torque transients of the tool point and interprets these in real-time. The relationship between the transients can be used to distinguish between different states and phenomena, such as patient or tool movement, the approach to tissue boundaries, tissue hardness and stiffness, and drill breakthrough. …”, Page 3 Col 1 “III. SMART MICRO-DRILLING TOOL POINT … (deploying standard drill bits and accommodating the drill drive system and sensing elements), an anti-backlash support arm that can be attached to the operating table, a hard-wired controller system that also incorporates sensor interpretation functions, a hand held control pendant and a computer screen to provide feedback to the surgeon. The system is shown in figure 3.”);
a robot controller configured to control the robotic arm to move the instrument interface to a determined position and to control at least one robot control parameter (See at least Page 3 Col 2 Para 2 “The system monitors force and torque transients of the tool point and interprets these in real-time. The relationship between the transients can be used to distinguish between different states and phenomena, such as patient or tool movement, the approach to tissue boundaries, tissue hardness and stiffness, and drill breakthrough. Using part of this information it is possible to interpret the critical breakthrough event before it occurs and to automatically control drill tip penetration with minimum protrusion….”); and
a system controller configured to:
receive temporal force/torque data, wherein the temporal force/torque data represents
the forces at the instrument interface over time, sensed by the at least one force/torque sensor during the collaborative procedure with the user (See at least Page 3 Col 2 Para 2 “The system monitors force and torque transients of the tool point and interprets these in real-time. The relationship between the transients can be used to distinguish between different states and phenomena, such as patient or tool movement, the approach to tissue boundaries, tissue hardness and stiffness, and drill breakthrough. Using part of this information it is possible to interpret the critical breakthrough event before it occurs and to automatically control drill tip penetration with minimum protrusion….”), wherein the forces comprise at least one of:
forces applied indirectly to the tool guide during user manipulation of the tool;
forces applied directly to the tool guide by the user (See at least Page 3 Col 2 Para 2 “III. SMART MICRO-DRILLING TOOL POINT … The system monitors force and torque transients of the tool point and interprets these in real-time…”, Page 3 Col 1 “(deploying standard drill bits and accommodating the drill drive system and sensing elements), an anti-backlash support arm that can be attached to the operating table, a hard-wired controller system that also incorporates sensor interpretation functions, a hand held control pendant and a computer screen to provide feedback to the surgeon. The system is shown in figure 3.”);
forces from an environment of the robotic arm; and
forces generated by the tool
analyzing the temporal force/torque data to determine at least one of a current intention
of the user or a predefined state of the collaborative procedure (See at least Page 3 Col 2 Para 2 “The system monitors force and torque transients of the tool point and interprets these in real-time. The relationship between the transients can be used to distinguish between different states and phenomena, such as patient or tool movement, the approach to tissue boundaries, tissue hardness and stiffness, and drill breakthrough…”, discloses monitoring the force and torque transients can be used to distinguish between different states and phenomena, such as tool movement which is construed as determining current intention of the user),
determining a control mode which is predefined for the determined at least one of the
current intention of the user or the state of the collaborative procedure, wherein the control mode determines the at least one robot control parameter (See at least Page 3 Col 2 Para 2 “The system monitors force and torque transients of the tool point and interprets these in real-time. The relationship between the transients can be used to distinguish between different states and phenomena, such as patient or tool movement, the approach to tissue boundaries, tissue hardness and stiffness, and drill breakthrough. Using part of this information it is possible to interpret the critical breakthrough event before it occurs and to automatically control drill tip penetration with minimum protrusion….”, discloses using information related to force and torque to distinguish between different states and control the robot accordingly which is construed as determining a control mode which is predefined for the determined at least one of the current intention of the user or the state of the collaborative procedure); and
controlling the robotic arm in accordance with the control mode (See at least Page 3 Col
2 Para 2 “The system monitors force and torque transients of the tool point and interprets these in real-time. The relationship between the transients can be used to distinguish between different states and phenomena, such as patient or tool movement, the approach to tissue boundaries, tissue hardness and stiffness, and drill breakthrough. Using part of this information it is possible to interpret the critical breakthrough event before it occurs and to automatically control drill tip penetration with minimum protrusion….”, discloses using information related to force and torque to distinguish between different states and control the robot accordingly which is construed as causing the robot controller to control the robotic arm in accordance with the control mode).
Regarding Claim 15, modified Brett teaches all the elements of claim 9. Brett further teaches the method of claim 9, further comprising providing an alert to the user when the control mode is changed (See at least Page 3 Col 1 “III. SMART MICRO-DRILLING TOOL POINT … (deploying standard drill bits and accommodating the drill drive system and sensing elements), an anti-backlash support arm that can be attached to the operating table, a hard-wired controller system that also incorporates sensor interpretation functions, a hand held control pendant and a computer screen to provide feedback to the surgeon. The system is shown in figure 3.”).
Regarding Claim 17, Brett teaches a processing system for controlling a robotic arm having one or more degrees of freedom of control (See at least Figure 3 shows a robotic arm with one or more degrees of freedom of control), wherein the robotic arm includes an instrument interface and a force/torque sensor to sense forces at the instrument interface, the instrument interface comprising a tool guide configured to interface with a tool during a collaborative procedure with a user (See at least Figure 3, Page 1 Col 2 Para 3 “Moving on from automatic and master-slave robotic systems in surgery there is a need for sensor-guided robotic devices that interpret or react to tissues in order to control the state of interaction between the tool-point and tissues. This is a complex process for a machine as perception will require automated interpretation of data, consideration of information derived and formation of strategies. These systems could be fully automatic, or automatic as part of a master-slave system to enable precise operation of tool points with respect to tissue targets and interfaces…”, Page 2 Col 1 Para 2 “…the second a micro drilling tool point able to discriminate tissue/ tool-point interaction to automatically identify the state and control the surgical process. The latter example has been deployed recently in the operating room as the first surgical robotic device of its kind.”, Page 3 Col 2 Para 2 “The system monitors force and torque transients of the tool point and interprets these in real-time…”, Page 3 Col 1 Para 3 “…Working under a surgical microscope, the drill unit is aligned by the surgeon in close proximity with the drilling site on the correct trajectory using the support arm, fine adjustment mechanism and the hand-held remote unit…”), the processing system comprising:
a processor (See at least Page 2 Col 1 Para 2 “…a micro drilling tool point able to discriminate
tissue/ tool-point interaction to automatically identify the state and control the surgical process…”); and
memory having stored therein instructions which, when executed by the processor (See at least
Page 2 Col 1 Para 2 “…a micro drilling tool point able to discriminate tissue/ tool-point interaction to automatically identify the state and control the surgical process…”), cause the
processor to:
receive temporal force/torque data, wherein the temporal force/torque data represents forces applied to or at the instrument interface over time by the user while interfacing with the instrument during the collaborative procedure with the user (See at least Page 3 Col 2 Para 2 “The system monitors force and torque transients of the tool point and interprets these in real-time. The relationship between the transients can be used to distinguish between different states and phenomena, such as patient or tool movement, the approach to tissue boundaries, tissue hardness and stiffness, and drill breakthrough. …”, Page 3 Col 1 “III. SMART MICRO-DRILLING TOOL POINT … (deploying standard drill bits and accommodating the drill drive system and sensing elements), an anti-backlash support arm that can be attached to the operating table, a hard-wired controller system that also incorporates sensor interpretation functions, a hand held control pendant and a computer screen to provide feedback to the surgeon. The system is shown in figure 3.”), wherein the forces comprise at least one of:
forces applied indirectly to the tool guide during user manipulation of the tool;
forces applied directly to the tool guide by the user (See at least Page 3 Col 2 Para 2 “III. SMART MICRO-DRILLING TOOL POINT … The system monitors force and torque transients of the tool point and interprets these in real-time…”, Page 3 Col 1 “(deploying standard drill bits and accommodating the drill drive system and sensing elements), an anti-backlash support arm that can be attached to the operating table, a hard-wired controller system that also incorporates sensor interpretation functions, a hand held control pendant and a computer screen to provide feedback to the surgeon. The system is shown in figure 3.”);
forces from an environment of the robotic arm; and
forces generated by the tool
analyze the temporal force/torque data to determine at least one of a current intention
of the user or a predefined state of the collaborative procedure (See at least Page 3 Col 2 Para 2 “The system monitors force and torque transients of the tool point and interprets these in real-time. The relationship between the transients can be used to distinguish between different states and phenomena, such as patient or tool movement, the approach to tissue boundaries, tissue hardness and stiffness, and drill breakthrough…”, discloses monitoring the force and torque transients can be used to distinguish between different states and phenomena, such as tool movement which is construed as determining current intention of the user),
determine a control mode which is predefined for the determined at least one of the
current intention of the user or the state of the collaborative procedure, wherein the control mode determines the at least one robot control parameter (See at least Page 3 Col 2 Para 2 “The system monitors force and torque transients of the tool point and interprets these in real-time. The relationship between the transients can be used to distinguish between different states and phenomena, such as patient or tool movement, the approach to tissue boundaries, tissue hardness and stiffness, and drill breakthrough. Using part of this information it is possible to interpret the critical breakthrough event before it occurs and to automatically control drill tip penetration with minimum protrusion….”, discloses using information related to force and torque to distinguish between different states and control the robot accordingly which is construed as determining a control mode which is predefined for the determined at least one of the current intention of the user or the state of the collaborative procedure); and
cause the robot controller to control the robotic arm in accordance with the control mode (See
at least Page 3 Col 2 Para 2 “The system monitors force and torque transients of the tool point and interprets these in real-time. The relationship between the transients can be used to distinguish between different states and phenomena, such as patient or tool movement, the approach to tissue boundaries, tissue hardness and stiffness, and drill breakthrough. Using part of this information it is possible to interpret the critical breakthrough event before it occurs and to automatically control drill tip penetration with minimum protrusion….”, discloses using information related to force and torque to distinguish between different states and control the robot accordingly which is construed as causing the robot controller to control the robotic arm in accordance with the control mode).
Regarding Claim 18, modified Brett teaches all the elements of claim 17. Brett further teaches the system of claim 17, wherein the instrument interface comprises a tool guide which is configured to be interfaced with a tool which can be manipulated by the user during the collaborative procedure, and wherein the forces comprise at least one of: (1) forces exerted indirectly on the tool guide by the user during user manipulation of the tool; (2) forces applied directly to the tool guide by the user (See at least Page 3 Col 2 Para 2 “III. SMART MICRO-DRILLING TOOL POINT … The system monitors force and torque transients of the tool point and interprets these in real-time…”, Page 3 Col 1 “(deploying standard drill bits and accommodating the drill drive system and sensing elements), an anti-backlash support arm that can be attached to the operating table, a hard-wired controller system that also incorporates sensor interpretation functions, a hand held control pendant and a computer screen to provide feedback to the surgeon. The system is shown in figure 3.”); (3) forces from an environment of the robot; and (4) forces generated by the tool.
Claim Rejections - 35 USC § 103
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
Claim(s) 3, 4, 8, 11, 12, and 16 are rejected under 35 U.S.C. 103 as being unpatentable over Brett (P. N. Brett, "Moving on from surgical robotics to robotic micro-tools in surgery," 2007 14th International Conference on Mechatronics and Machine Vision in Practice, Xiamen, China, 2007, pp. 1-5).
Regarding Claim 3, Brett teaches all the elements of claim 1.
However, Brett teaches in another sensory guided smart tool wherein the system controller is
configured to apply the temporal force/torque data to a neural network to determine the at least one of the current intention of the user or the state of the collaborative procedure (See at least Page 2 Col 2 Para 3 “…For the surgical glove, strain corresponding with hand or finger gesture is detected at up to 3 points using sensory signals coupled by non-linear functions, with a neural network to interpret the transients in hand or finger gesture…”, Figure 2).
Therefore, it would have been obvious to one of the ordinary skill in the art before the effective filing date of the claimed invention to combine the teachings of using neural network to determine the at least one of the current intention of the user or the state of the collaborative procedure, thereby provide precise robotic control resulting in greater surgical accuracy (See at least “Abstract - … This offers the order of magnitude greater accuracy needed in micro-surgical processes…”).
Regarding Claim 4, modified Brett teaches all the elements of claim 3.
However, Brett teaches in another sensory guided smart tool wherein the neural network is
configured to determine from the temporal force/torque data when the user is drilling with the tool, and is further configured to determine from the temporal force/torque data when the user is hammering with the tool (See at least Page 2 Col 2 Para 3 “…For the surgical glove, strain corresponding with hand or finger gesture is detected at up to 3 points using sensory signals coupled by non-linear functions, with a neural network to interpret the transients in hand or finger gesture…”, Page 2 Col 2 Para 3 “Figure 2, In the laboratory, using phantom devices, the system is able to discriminate a variety of contacting conditions; texture, motion, velocity, force direction, force level, proportion of contact, curvature of the digit and types of contacting features…”).
Therefore, it would have been obvious to one of the ordinary skill in the art before the effective
filing date of the claimed invention to combine the teachings of the neural network being configured to determine from the temporal force/torque data the intention of the user, thereby ensure precise robotic control resulting in greater surgical accuracy (See at least “Abstract - … This offers the order of magnitude greater accuracy needed in micro-surgical processes…”).
Regarding Claim 8, modified Brett teaches all the elements of claim 1.
However, Brett teaches in another sensory guided smart tool wherein the system controller is further configured to receive auxiliary data comprising at least one of video data, image data, audio data, surgical plan data, diagnostic plan data and robot vibration data, and is still further configured to determine the current intention of the user or the state of the collaborative procedure based on the temporal force/torque data and the auxiliary data (See at least Page 2 Para 3 “II. A SYSTEM FOR SMART TOOL POINT FOR MOVING OVER THE SURFACE OF A TISSUE…. Diagnostic methods will benefit from palpation and ultrasound imaging, where a form of tactile perception will enable greater control of the action against the surface. Using these methods, there is then the potential to control needle puncture and penetration of tissues from a point within the body…”, Page 2 Col 2 Para 3 “…. In the laboratory, using phantom devices, the system is able to discriminate a variety of contacting conditions; texture, motion, velocity, force direction, force level, proportion of contact, curvature of the digit and types of contacting features….”).
Therefore, it would have been obvious to one of the ordinary skill in the art before the effective
filing date of the claimed invention to combine the teachings of the system controller being further configured to receive auxiliary data comprising at least image data and is still further configured to determine the current intention of the user or the state of the collaborative procedure based on the temporal force/torque data and the auxiliary data, thereby ensure precise robotic control resulting in greater surgical accuracy (See at least “Abstract - … This offers the order of magnitude greater accuracy needed in micro-surgical processes…”).
Regarding Claim 11, Brett teaches all the elements of claim 9.
However, Brett teaches in another sensory guided smart tool wherein analyzing the temporal
force/torque data to determine the at least one of the current intention of the user or the state of the collaborative procedure comprises applying the temporal force/torque data to a neural network to determine the current intention of the user or the state of the collaborative procedure (See at least Page 2 Col 2 Para 3 “…For the surgical glove, strain corresponding with hand or finger gesture is detected at up to 3 points using sensory signals coupled by non-linear functions, with a neural network to interpret the transients in hand or finger gesture…”, Figure 2).
Therefore, it would have been obvious to one of the ordinary skill in the art before the effective filing date of the claimed invention to combine the teachings of using neural network to determine the at least one of the current intention of the user or the state of the collaborative procedure, thereby provide precise robotic control resulting in greater surgical accuracy (See at least “Abstract - … This offers the order of magnitude greater accuracy needed in micro-surgical processes…”).
Regarding Claim 12, modified Brett teaches all the elements of claim 11.
However, Brett teaches in another sensory guided smart tool wherein the neural network
determines from the temporal force/torque data when the user is drilling with the tool, and further determines from the temporal force/torque data when the user is hammering with the tool (See at least Page 2 Col 2 Para 3 “…For the surgical glove, strain corresponding with hand or finger gesture is detected at up to 3 points using sensory signals coupled by non-linear functions, with a neural network to interpret the transients in hand or finger gesture…”, Page 2 Col 2 Para 3 “Figure 2, In the laboratory, using phantom devices, the system is able to discriminate a variety of contacting conditions; texture, motion, velocity, force direction, force level, proportion of contact, curvature of the digit and types of contacting features…”).
Therefore, it would have been obvious to one of the ordinary skill in the art before the effective
filing date of the claimed invention to combine the teachings of the neural network being configured to determine from the temporal force/torque data the intention of the user, thereby ensure precise robotic control resulting in greater surgical accuracy (See at least “Abstract - … This offers the order of magnitude greater accuracy needed in micro-surgical processes…”).
Regarding Claim 16, modified Brett teaches all the elements of claim 9.
However, Brett teaches in another sensory guided smart tool the method of claim 9, further comprising: receiving auxiliary data comprising at least one of video data, image data, audio data, surgical plan data, diagnostic plan data and robot vibration data; and determining the current intention of the user or the state of the collaborative procedure based on the temporal force/torque data and the auxiliary data (See at least Page 2 Para 3 “II. A SYSTEM FOR SMART TOOL POINT FOR MOVING OVER THE SURFACE OF A TISSUE…. Diagnostic methods will benefit from palpation and ultrasound imaging, where a form of tactile perception will enable greater control of the action against the surface. Using these methods, there is then the potential to control needle puncture and penetration of tissues from a point within the body…”, Page 2 Col 2 Para 3 “…. In the laboratory, using phantom devices, the system is able to discriminate a variety of contacting conditions; texture, motion, velocity, force direction, force level, proportion of contact, curvature of the digit and types of contacting features….”).
Therefore, it would have been obvious to one of the ordinary skill in the art before the effective
filing date of the claimed invention to combine the teachings of the system controller being further configured to receive auxiliary data comprising at least image data and is still further configured to determine the current intention of the user or the state of the collaborative procedure based on the temporal force/torque data and the auxiliary data, thereby ensure precise robotic control resulting in greater surgical accuracy (See at least “Abstract - … This offers the order of magnitude greater accuracy needed in micro-surgical processes…”).
Claim(s) 5, 6, 13, 14, 19, and 20 are rejected under 35 U.S.C. 103 as being unpatentable over Brett (P. N. Brett, "Moving on from surgical robotics to robotic micro-tools in surgery," 2007 14th International Conference on Mechatronics and Machine Vision in Practice, Xiamen, China, 2007, pp. 1-5) in view of Quaid et al. (US 2004/0106916 A1) (Hereinafter Quaid).
Regarding Claim 5, modified Brett teaches all the elements of claim 4.
However, Brett does not explicitly spell out wherein the at least one robot control parameter controls a rendered stiffness of the tool guide against the forces applied in at least one direction.
Quaid teaches wherein the at least one robot control parameter controls a rendered stiffness of the tool guide against the forces applied in at least one direction (See at least Para [0051] “…For example, the computer-aided surgery system may send a command to the haptic device requesting it to enter into a joystick-like input mode with certain stiffness parameters…”).
Therefore, it would have been obvious to one of the ordinary skill in the art before the effective
filing date of the claimed invention to combine Brett with the teachings of Quaid and include the feature of at least one robot control parameter controlling a rendered stiffness of the tool guide against the forces applied in at least one direction, thereby provide greater flexibility to the surgeon during surgery (See at least Para [0087] “A technical advantage of this exemplary embodiment for interactive haptic positioning of a medical device is that by modifying a haptic object based on the haptic interaction forces and/or torques, greater flexibility is provided to the surgeon…”).
Regarding Claim 6, modified Brett teaches all the elements of claim 5.
However, Brett does not explicitly spell out wherein when the neural network determines from
the temporal force/torque data that the user is hammering with the tool, the neural network further determines whether the tool is hammering through bone or is hammering through tissue, wherein when the tool is determined to be hammering through tissue, the control mode is a first stiffness mode wherein the robot controller controls the tool guide to have a first stiffness, and wherein when the tool is determined to be hammering through bone, the control mode is a second stiffness mode wherein the robot controller controls the tool guide to have a second stiffness, wherein the second stiffness is less than the first stiffness.
Quaid teaches wherein when the neural network determines from the temporal force/torque data that the user is hammering with the tool, the neural network further determines whether the tool is hammering through bone or is hammering through tissue, wherein when the tool is determined to be hammering through tissue, the control mode is a first stiffness mode wherein the robot controller controls the tool guide to have a first stiffness, and wherein when the tool is determined to be hammering through bone, the control mode is a second stiffness mode wherein the robot controller controls the tool guide to have a second stiffness, wherein the second stiffness is less than the first stiffness (See at least Para [0052] “…An algorithm which computes the current position of haptic device 113 relative to haptic object 20 may be used to provide information to the surgeon about the location of haptic device 113 relative to haptic object 20. When haptic device 113 comes within a predefined distance of haptic object 20, a stiffness parameter may be changed to make it more difficult to move haptic device 113…”, Para [0117] “The stiffness or damping of the control algorithm may vary in different directions to indicate preferential directions of motion which may be aligned with any direction as described in the previous paragraph. This stiffness variation may include zero stiffness along certain directions or may lock the user to the preferred directions once the deviation from the reference position exceeds some threshold value. This stiffness variation assists with simplifying the planning process by allowing the user to focus their attention on a limited number of degrees of freedom at a time…”, Para [0118] “The stiffness and damping variations can occur automatically depending on the physical interaction of the user with the haptic device…”, Para [0121] “…Thus, haptic device 113 may be used to differentiate between hard and soft bones, healthy and diseases tissues, different types of healthy tissues, boundaries of anatomical structures, etc…”).
Therefore, it would have been obvious to one of the ordinary skill in the art before the effective
filing date of the claimed invention to combine Brett with the teachings of Quaid and include the feature of the neural network determining from the temporal force/torque data that the user is hammering with the tool, the neural network further determines whether the tool is hammering through bone or is hammering through tissue, wherein when the tool is determined to be hammering through tissue, the control mode is a first stiffness mode wherein the robot controller controls the tool guide to have a first stiffness, and wherein when the tool is determined to be hammering through bone, the control mode is a second stiffness mode wherein the robot controller controls the tool guide to have a second stiffness, wherein the second stiffness is less than the first stiffness, thereby provide improved flexibility to the surgeon during surgery (See at least Para [0087] “A technical advantage of this exemplary embodiment for interactive haptic positioning of a medical device is that by modifying a haptic object based on the haptic interaction forces and/or torques, greater flexibility is provided to the surgeon…”).
Regarding Claim 13, modified Brett teaches all the elements of claim 12.
However, Brett does not explicitly spell out wherein the at least one robot control parameter controls a rendered stiffness of the tool guide against the forces applied in at least one direction.
Quaid teaches wherein the at least one robot control parameter controls a rendered stiffness of the tool guide against the forces applied in at least one direction (See at least Para [0051] “…For example, the computer-aided surgery system may send a command to the haptic device requesting it to enter into a joystick-like input mode with certain stiffness parameters…”).
Therefore, it would have been obvious to one of the ordinary skill in the art before the effective
filing date of the claimed invention to combine Brett with the teachings of Quaid and include the feature of at least one robot control parameter controlling a rendered stiffness of the tool guide against the forces applied in at least one direction, thereby provide greater flexibility to the surgeon during surgery (See at least Para [0087] “A technical advantage of this exemplary embodiment for interactive haptic positioning of a medical device is that by modifying a haptic object based on the haptic interaction forces and/or torques, greater flexibility is provided to the surgeon…”).
Regarding Claim 14, modified Brett teaches all the elements of claim 13.
However, Brett does not explicitly spell out wherein when the neural network determines from
the temporal force/torque data that the user is hammering with the tool, the neural network further determines whether the tool is hammering through bone or is hammering through tissue, wherein when the tool is determined to be hammering through tissue, the control mode is a first stiffness mode wherein the tool guide has a first stiffness, and wherein when the tool is determined to be hammering through bone, the control mode is a second stiffness mode wherein the tool guide has a second stiffness, wherein the second stiffness is less than the first stiffness.
Quaid teaches wherein when the neural network determines from the temporal force/torque data that the user is hammering with the tool, the neural network further determines whether the tool is hammering through bone or is hammering through tissue, wherein when the tool is determined to be hammering through tissue, the control mode is a first stiffness mode wherein the tool guide has a first stiffness, and wherein when the tool is determined to be hammering through bone, the control mode is a second stiffness mode wherein the tool guide has a second stiffness, wherein the second stiffness is less than the first stiffness (See at least Para [0052] “…An algorithm which computes the current position of haptic device 113 relative to haptic object 20 may be used to provide information to the surgeon about the location of haptic device 113 relative to haptic object 20. When haptic device 113 comes within a predefined distance of haptic object 20, a stiffness parameter may be changed to make it more difficult to move haptic device 113…”, Para [0117] “The stiffness or damping of the control algorithm may vary in different directions to indicate preferential directions of motion which may be aligned with any direction as described in the previous paragraph. This stiffness variation may include zero stiffness along certain directions or may lock the user to the preferred directions once the deviation from the reference position exceeds some threshold value. This stiffness variation assists with simplifying the planning process by allowing the user to focus their attention on a limited number of degrees of freedom at a time…”, Para [0118] “The stiffness and damping variations can occur automatically depending on the physical interaction of the user with the haptic device…”, Para [0121] “…Thus, haptic device 113 may be used to differentiate between hard and soft bones, healthy and diseases tissues, different types of healthy tissues, boundaries of anatomical structures, etc…”).
Therefore, it would have been obvious to one of the ordinary skill in the art before the effective
filing date of the claimed invention to combine Brett with the teachings of Quaid and include the feature of the neural network determining from the temporal force/torque data that the user is hammering with the tool, the neural network further determines whether the tool is hammering through bone or is hammering through tissue, wherein when the tool is determined to be hammering through tissue, the control mode is a first stiffness mode wherein the robot controller controls the tool guide to have a first stiffness, and wherein when the tool is determined to be hammering through bone, the control mode is a second stiffness mode wherein the robot controller controls the tool guide to have a second stiffness, wherein the second stiffness is less than the first stiffness, thereby provide improved flexibility to the surgeon during surgery (See at least Para [0087] “A technical advantage of this exemplary embodiment for interactive haptic positioning of a medical device is that by modifying a haptic object based on the haptic interaction forces and/or torques, greater flexibility is provided to the surgeon…”).
Regarding Claim 19, modified Brett teaches all the elements of claim 18.
However, Brett does not explicitly spell out wherein the instructions further cause the processor to analyze the temporal force/torque data to identify a command provided by the user to the system to instruct the system to switch the control mode to a predefined mode
Quaid further teaches wherein the instructions further cause the processor to analyze the temporal force/torque data to identify a command provided by the user to the system to instruct the system to switch the control mode to a predefined mode (See at least Para [0122] “FIG. 9 is a flowchart of a representative method 190 for using haptic device 113 as an input device. In step 192, the input mode is initiated. The user may initiate the input mode by any mechanism now known or later developed. For example, the user may use a graphical user interface, a footswitch, a keyboard, a button, and/or the like, to indicate that the user desires to use haptic device 113 as an input device…”).
Therefore, it would have been obvious to one of the ordinary skill in the art before the effective
filing date of the claimed invention to combine Brett with the teachings of Quaid and include the feature of the instructions further causing the processor to analyze the temporal force/torque data to identify a command provided by the user to the system to instruct the system to switch the control mode to a predefined mode thereby provide greater flexibility to the surgeon during surgery (See at least Para [0087] “A technical advantage of this exemplary embodiment for interactive haptic positioning of a medical device is that by modifying a haptic object based on the haptic interaction forces and/or torques, greater flexibility is provided to the surgeon…”).
Regarding Claim 20, modified Brett teaches all the elements of claim 18.
However, Brett does not explicitly spell out wherein the at least one robot control parameter controls a rendered stiffness of the tool guide against the forces applied in at least one direction.
Quaid teaches wherein the at least one robot control parameter controls a rendered stiffness of the tool guide against the forces applied in at least one direction (See at least Para [0051] “…For example, the computer-aided surgery system may send a command to the haptic device requesting it to enter into a joystick-like input mode with certain stiffness parameters…”).
Therefore, it would have been obvious to one of the ordinary skill in the art before the effective
filing date of the claimed invention to combine Brett with the teachings of Quaid and include the feature of at least one robot control parameter controlling a rendered stiffness of the tool guide against the forces applied in at least one direction, thereby provide greater flexibility to the surgeon during surgery (See at least Para [0087] “A technical advantage of this exemplary embodiment for interactive haptic positioning of a medical device is that by modifying a haptic object based on the haptic interaction forces and/or torques, greater flexibility is provided to the surgeon…”).
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure:
Gulhar et al. (US 2016/0144510 A1) teaches method for operating robotic device such as
medical-robotic device e.g. medical-surgical device with kinematic chain of mobile components in medical-surgical and/or medical-diagnostic procedure
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/SHAHEDA HOQUE/Examiner, Art Unit 3658
/Ramon A. Mercado/Supervisory Patent Examiner, Art Unit 3658
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