DETAILED ACTION
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 .
Priority
Receipt is acknowledged of certified copies of papers required by 37 CFR 1.55.
Claim Rejections - 35 USC § 112
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
Claim 2-5 rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention.
Claim 2 and 3 recites the distance difference as 2a. It is unclear what the variable “a” mean. Applicant is suggested to define the variable “a”. In prior art, Examiner considers the distance between two anchor points which are in fixed point from the tag points have 2a distance difference.
Claim 2 recites “small-scale and large-scale” positioning system. It is unclear which or what type of system is considered to be a small or large-scale positioning system. Examiner considers any positioning system be a small or a large scale.
Claim 2 recites “substituting screened TDOA measurement values with small errors into the standard EKF filtering algorithm, so as to obtain a final position coordinate of the surgical instrument. It is unclear which values are to be considered with small errors.
Applicant is suggested to either remove or define the unclear terms in the claim limitations.
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.
Claim(s) 1-5 is/are rejected under 35 U.S.C. 103 as being unpatentable over Mahfouz US 20170143494 A1 in view of Rui et al. "Design of a TDOA Location Engine and Development of a Location System Based on Chirp Spread Spectrum." International Journal of Distributed Sensor Networks, vol. 12, no. 12, 2016, pp. 1–12. doi:10.1177/1550147716682734” herein after “Rui”.
Regarding claim 1, Mahfouz teaches a chip-level positioning method for orthopedic surgery navigation based on an Ultra-wide Bandwidth (UWB) (para [0003] The present disclosure includes a surgical navigation system using a self-reference hybrid navigation system based on the UltraWide Band (UWB)), comprising:
S1, laying a positioning base station and arranging a UWB wireless positioning module on a surgical instrument (Fig. 189. [0557] During the acetabular cup preparation, in one configuration of this hybrid system, a central unit is attached to the iliac crest of a patient's pelvis as a reference. A peripheral unit is attached to an acetabular reamer (see FIG. 209). In another alternate exemplary configuration of this invention, a central unit is positioned adjacent to the operating table.,
From Fig. 189 and Fig 209 examiner views the inertial tracking system with a base (i.e. positioning base station) and UWB antenna are positioned on an acetabular reamer (i.e., a surgical instrument).
wherein the positioning base station and the UWB wireless positioning module arranged on the surgical instrument use a same UWB module unit (0518] Referring to FIGS. 189-212, an exemplary hybrid navigation and tracking system is disclosed. This exemplary hybrid system makes use of ultrawide band (UWB) and inertial measurement units (IMUs) and comprises at least one central unit (i.e., a core unit) and one peripheral unit (i.e., a satellite unit). Each central unit comprises, in exemplary form, at least one microcomputer, at least one tri-axial accelerometer, at least one tri-axial gyroscope, at least three tri-axial magnetometers, at least one communication module, at least one UWB transceiver, at least one multiplexer, and at least four UWB antennas (see FIG. 189).
From Fig. 189 and Fig 209 examiner views the inertial tracking system with a base (i.e. positioning base station) and UWB antenna are positioned on an acetabular reamer (i.e., a surgical instrument) using same UWB module unit.
S2, real-time positioning (para [0011] In a more detailed embodiment, the primary processor is operative to utilize data from the inertial measurement unit to reposition the three dimensional virtual model of the surgical tool with respect to a three dimensional virtual model of the anatomical feature in real-time.):
Mahfouz does not explicitly teach first, substituting an original Time Difference of Arrival (TDOA) value into a Chan algorithm to calculate and acquire a preliminary positioning coordinate of a UWB positioning tag, thereafter, calculating a residual sum of squares to set a threshold and eliminating TDOA measurement values with errors higher than the threshold, and substituting the screened TDOA measurement values that meet requirements into a standard Extended Kalman Filter (EKF) filtering algorithm, so as to obtain a final position coordinate of the surgical instrument.
Rui teaches first, substituting an original Time Difference of Arrival (TDOA) value into a Chan algorithm to calculate and acquire a preliminary positioning coordinate of a UWB positioning tag, thereafter, calculating a residual sum of squares to set a threshold (page 2, Background, first paragraph, In recent years, wireless localization technology has become very popular in industrial,… Notable examples include global positioning systems (GPS), WiFi, ZigBee, ultrasound, ultra-wide bands (UWB))
page 8. First paragraph. Chan TDOA algorithms can be utilized to linearize TDOA hyperbolic equations and conduct dual weighted least squares (WLS) to obtain useful results; this yields relatively high accuracy if the noise error is in Gaussian distribution.
Second paragraph. Per the proposed method, the measured data (smoothed by a Kalman filter) is read first and initial results (X1, Y1) are obtained via Chan algorithm. The residual square sum of the Chan algorithm (Reschan) are compared with the first threshold.
Page 16, last paragraph, Tag was placed in six different positions and six sets of ranging data were gathered. Chan, Taylor, Kalman, Compared Taylor Method, and method in this paper were respectively used.),
Here examiner views the Chan TDOA algorithm is used for substation of the initial (original) TDOA value and determine an initial position of Tags. Then a residual square sum of the Chan algorithm (Reschan) is calculated and compared to set a threshold.
and eliminating TDOA measurement values with errors higher than the threshold, and substituting the screened TDOA measurement values that meet requirements into a standard Extended Kalman Filter (EKF) filtering algorithm, so as to obtain a final position coordinate of the surgical instrument (page 8, First pargraph, line 5. The EKF lends the Kalman-based TDOA algorithm better dynamic performance.
Page 9, third paragraph, Third, there are two necessary conditions remaining for the 𝑅𝑒𝑠𝑡𝑎𝑦𝑙𝑜𝑟). Whether the Kalman algorithm has been initialized, and whether the interval time is below threshold. If both are satisfied, (X2, Y2) will be the input parameter of the Kalman algorithm to obtain another result (X3,Y3), or the estimated results (𝑥2, 𝑦2) will be the initial value of the Kalman algorithm and become the final result. Then, provided there is sufficiently small measurement error, the location results of Taylor and Kalman are close to each other based on these characteristics. (The larger the error, the larger the deviation). Another two thresholds, 𝛿3 and 𝛿4, are adopted to judge two types of inequality and further determine whether the measurement error is too large (Eq. 5). If both threshold conditions are not met, the process returns to the first step to read the measurement and gives up the current step…. And the measured values must be re-read. Otherwise, the residual square sum ResKalman of the Kalman algorithm is calculated and the residual weighted method is applied to obtain location result (X4, Y4).
Examiner views Kalman-based TDOA algorithm is used for eliminating TDOA measurement values with errors higher than the threshold, and substituting the selected or screened TDOA measurement values that meet requirements into a standard Extended Kalman Filter (EKF) filtering algorithm, so as to obtain a final position (X4, Y4) coordinate. The applicant uses Chan and Kalman algorithm for locating the surgical instrument.
Accordingly, it would have been obvious to one of ordinary skill in the art before the effective filing of the invention to have incorporated Rui et al into Mahfouz for the purpose of using Chan and Kalman algorithm to reduce the error in determining a position of tags, so that an accurate final position can be determined for a surgical instrument.
Regarding claim 2 the combination of Mahfouz and Rui teach The chip-level positioning method for orthopedic surgery navigation based on the UWB according to claim 1, Rui teaches wherein Step S2 comprises:
S21, TDOA positioning; by using a TDOA algorithm, measuring a time difference between moments of two reference base stations receiving broadcast signals sent by a target node (page 5, line 5, Again, the TDOA model measures the differences in times at which signals from the Tag directly or indirectly arrive at multiple Anchors…), thus calculating a distance difference between distances from the target node to the two reference base stations by multiplying a wave velocity by the time difference (page 5, line 13 TOA obtains measurements as the signal propagation time between Tagand the ith Anchor, then the distance rth between the Tag and the ith Anchor can be calculated asfollows: ri=tv, where v represents the speed of light. )
Examiner views the TDOA method measures a signal propagation time (i.e., receiving broadcast signal) by the Anchor node (or reference base station) sent by target or tag node, the distance between the target node and the reference nodes or base station is determined by multiplying the signal or wave propagation time (i.e., time difference) by wave propagation velocity.
obtaining a hyperbolic equation by taking the two reference base stations as focuses of a curve (page 5, line 11, Measurements are then used to establish a hyperbolic model and to estimate the Tag coordinates. The hyperbolic model of TDOA is more complex than the circle model of TOA, accordingly, asdepicted in Figs. 2 and 3.) and taking the distance difference as 2a (page 5, line 7, Anchors are devices placed at fixed sites with known coordinate values,), wherein one hyperbolic equation is incapable of determining the target node, and at least three base stations are used to solve two hyperbolic equations, and an intersection point of two hyperbolas determined by the two hyperbolic equations is a target node (page 5 line 20, Figures 2 and 3 show where the TOA model obtains the Tags location by finding n(n>3 or n=3)circles intersections, then the TDOA model obtains the hyperbolas intersection);
From above paragraph and Fig. 2, 3, examiner views the anchors (i.e., reference base stations) are in fixed or equal distances (a) from the tag or target node where distance difference is viewed 2a. a single hyperbola from the reference station is not capable of determining the target node coordinate therefore three base stations hyperbola were used and their intersection (at least two hyperbola) is used to determine the target node.
S22, the Chan algorithm for positioning based on TDOA technology (page 8, first paragraph, Cooperative localization based on Chan, Kalman, and Taylor:);
using a two-step Weighted Least Square (WLS) method to locate and calculate a target position, which is suitable for both small-scale and large-scale positioning systems, wherein during the calculating, a nonlinear TDOA equations are first processed and converted into linear equations, and then an initial solution is estimated through WLS (page 8, first paragraph, Chan TDOA algorithms can be utilized to linearize TDOA hyperbolic equations and conduct dual weighted least squares (WLS) to obtain useful results; this yields relatively high accuracy if the noise error is in Gaussian distribution.); and thereafter, the initial solution is calculated through the WLS for a second time to further estimate coordinate of the positioning tag (page 8, last paragraph Per the proposed method, the measured data (smoothed by a Kalman filter) is read first and initial results (X1, Y1) are obtained via Chan algorithm. The residual sum of squares of the Chan algorithm are then compared with the first threshold), wherein equation conditions used in the first WLS calculation are a same as those used in the second WLS calculation (page 9, line 4, If the first result of the Chan algorithm is less than the first threshold, it serves as the initial value of the Taylor algorithm to obtain a second result. Then, the second threshold is set for judging the (residual sum of squares) of, as mentioned above)
From above paragraphs and a software program in page 10, examiner views the Chan TDOA algorithms first uses linearization of hyperbolic equation (i.e., non linear curve) and second determine weighted least square (WLS). After determining WLS the position coordinates (X2, Y2), (X3, Y3) for tags are determined where the condition for the first coordinates is same as the second coordinate by repeating the step 2 (see in page 10).
S23, the EKF algorithm for positioning based on TDOA technology (page, 7 first paragraph Smoothing method based on Kalman filter for TDOA measurements);
in a UWB positioning system based on TDOA technology, considering that the TDOA equations are nonlinear equations, using an EKF to solve a nonlinear problem, wherein the idea of the EKF is that for a nonlinear system, the system is discretized by means of numerical analysis (page 7 line 6, As discussed in detail below, some results are disturbed severely by NLOS. When this occurs, the state estimated values of Pk (assuming at time) will be given up and previous estimated values Pk-1 will be reused in the subsequent iteration. Because the Kalman filter as a linear optimal filtering algorithm can effectively utilize historical data, it also smooths the measurements and effectively reduces error.)
Here examiner views Kalman filters or solves the nonlinear problems and outputs a linear results in time discrete form, and Taylor expansion is carried out in a neighborhood of calculation points, terms above quadratic terms are deleted, and only primary terms are reserved, and thus the Kalman filter is applied to the nonlinear system (page 8, line 3, Taylor TDOA algorithms are recursive, and require an initial estimated value to expand the Taylor series and linearize nonlinear equations, so the calculation load is high (and the results divergent) when there are large initial errors. The EKF lends the Kalman-based TDOA algorithm better dynamic performance.);
Examiner views a Taylor series exapansion and EKF is performed on the points to linearize the non linear or remove quadratic equations, holding the original terms in linear results.
S24, estimation of the position coordinate of the positioning tag; substituting screened TDOA measurement values with small errors into the standard EKF filtering algorithm, so as to obtain a final position coordinate of the surgical instrument (page 9, line 7, Third, there are two necessary conditions remaining for the Restaylor: Whether the Kalman algorithm has been initialized, and whether the interval time is below threshold. If both are satisfied (x2,y2), will be the input parameter of the Kalman algorithm to obtain another result (x3,y3), or the estimated results (x2,y2) will be the initial value of the Kalman algorithm and become the final result. Then, provided there is sufficiently small measurement error, the location results of Taylor and Kalman are close to each other based on these characteristics.)
Examiner views when the substituted TDOA measurements in Kalman filter have small error, the resulting position is a final position of the tag associated with a device (i.e., surgical instrument).
Accordingly, it would have been obvious to one of ordinary skill in the art before the effective filing of the invention to have incorporated Rui et al into Mahfouz for the purpose of using Chan, Taylor and Kalman algorithm to reduce the error in determining a position of tags, so that an accurate final position can be determined for a surgical instrument.
Regarding claim 3 the combination of Mahfouz and Rui teach The chip-level positioning method for orthopedic surgery navigation based on the UWB according to claim 2, Mahfouz teaches wherein a specific linear equation of TDOA positioning in Step S21 is as follows: coordinates of base stations are set to (x1, y1), (x2, y2), and (x3, y3), clockwise from the BS1 and a tag coordinate to be solved is (x, y), a time for a measure signal traveling from a node to be tested to BS1 is t1 (i=2,3) (see in Fig. 197, the base stations (BS) or anchor are in clockwise from BS1), and tag the middle where a time for signal traveling from node to the tested BS to be determined.)
Rui teaches BS1 and BSi are deemed as focuses, a hyperbolic equation is drawn with Di,1=di−d1=2a, and a distance relationship between the node to be tested and the base station i is obtained by a distance formula between two points Di= √((xi -x)2) - √((yi -y)2)
(in Fig. 2 and 3 examiner views the hyperparabola with fixed anchor position as focuses in fixed distant from tag, the distance between two points is determined using distance formula in equation 2, 3.
a relationship between a distance difference between the distance from the node to be tested to a main positioning base station BS1 and the distance Di from the node to be tested to other base stations and the time difference is as follows
Di= Di-D1=cti,1 = √((xi -x)2 + (yi -y)2) - √((x1 -x)2 + (y1-y)2)
c indicates a propagation velocity of an electromagnetic wave emitted by the target in the medium (please see equation 1, 2, where v represents the speed of light ):, and more than two base stations besides the main base station are needed to complete the determination of the target node, from which following hyperbolic nonlinear equations are obtained (page 6, The Anchors coordinates are known, represents the ith Anchors location, and represents the Tags coordinate which which can be calculated via Eq. (3).please see equation 3 in page 6.):
D2,1= D2 – D1 = √((x2 -x)2 + (y2 -y)2) - √((x1 -x)2 + (y1-y)2)
D3,1= D3 – D1 = √((x3 -x)2 + (y3 -y)2) - √((x1 -x)2 + (y1-y)2)
X and y are solved using Chan algorithm to obtain the tag coordinate (please see software code in page 10 where the x, y coordinates for tag are solved or calculated using Chang algorithm).
Accordingly, it would have been obvious to one of ordinary skill in the art before the effective filing of the invention to have incorporated Rui et al into Mahfouz for the purpose of using Chan, Taylor and Kalman algorithm to reduce the error in determining a position of tags, so that an accurate final position can be determined for a surgical instrument.
Regarding claim 4 the combination of Mahfouz and Rui teach The chip-level positioning method for orthopedic surgery navigation based on the UWB according to claim 2, Mahfouz teaches wherein a specific linear equation of the EKF algorithm based on TDOA technology positioning in Step S23 is as follows (para [0541] The basic Kalman filter can be separated into 2 major sets of equations, which are the time update equations and the measurement update equations. The time update equations predict the priori estimates at time k with the knowledge of the current states and error covariance at time k−1 in equation (13) respectively): assuming that the nonlinear system is (para [0544] There are multiple different implementations of a Kalman filter that tackles the linear and Gaussian assumptions such as an extended Kalman filter that linearize the system, as well as Sigma point and Unscented Kalman filters that provide non-linear transformation of the system.): Since Kalman filter linearize a nonlinear system, examiner views the applicant recited nonlinear equation can also be linearized by the prior art Kalman filter.
Xk = f (Xk-1, Uk-1, Wk-1),
Zk = h (Xk,, Vk)
time update equation is: (please see equation 13 and 14 in paragraph [0541] for time updated equation for below equations)
X-^k =f^ (Xk-1, Uk-1, Wk-1),
Pk-= ϕPk-1 ϕT + Q,
an updated measurement equation is: (para [0542] The measurements update equations use the measurements acquired with the priori estimates to calculate the posteriori estimates.) Please see equations 15-18 for equations listed below.
Kk= Pk- HKT (HK Pk- HKT +R)-1
Xˆk = Xˆk-1 + Kk (Zk- h (Xˆk-1, Vk)
Pk= (I-Kk Hk) Pk-
in the above process, φ is a state transition matrix (para [0541] A is the state transition matrix); H is a Jacobian matrix calculated by h function for the state (examiner views Jacobian is calculated using observation function for a state quantity x);
T is a sampling time, in which ϕ=I+F×T (T is the sampling time)
where f is a state equation; h is an observation equation; x is a state quantity; u is an input quantity; w and v are a process noise and an observation noise; P is an error covariance matrix; K is a Kalman gain. (examiner views where f is a state equation; h is an observation equation; x is a state quantity; u is an input quantity; w and v are a process and observation noise, P is an error covariance matrix K is a Kalman gain from equations 15-18)
Regarding claim 5 the combination of Mahfouz and Rui teach the chip-level positioning method for orthopedic surgery navigation based on the UWB according to claim 2, Rui teaches wherein estimating the position coordinate of the positioning tag in Step S24 comprises: first, the original TDOA value is substituted into the Chan algorithm to calculate and acquire initial positioning coordinates of the UWB positioning tag, and then the residual sum of squares is calculated, in which calculation formula is as follows (please see equation 4 in page 9 of Rui for the residual square sum of estimation using Chan algorithm by substituting the original TDOA value):
eliminated, the residuals are used to measure proximity between a set of TDOA values and corresponding positioning results, when errors of the UWB positioning system mainly comes from Non Line of Sight (NLOS) errors, in response to increasing of an influence of the NLOS errors on a set of measurement values, calculated residual value increases (page 10, first paragraph, the values of the thresholds and are highly influenced by the accuracy of the historical data and the precision of the location device; when they are appropriate, they reduce the interference of NLOS and improve the location accuracy overall. We conducted several experiments yielding a large amount of measured data which were used to get location results by the three algorithms (Chan, Taylor, and Kalman). first determined by the residual sum of squares of the location results of Chan and Taylor separately. and first determined by the difference value between the mean value of the residual sum of squares of the location results of Taylor and Kalman. Then adjusted the threshold values according to the actual effect;
Here examiner views the error in determining position of device is implemented using NLOS errors, the threshold values are adjusted based on the residual sum of square values (i.e., increase).
therefore, a threshold value is set as Rws ≤ Δ, and compared with the residual value; in response to the residual value being greater than the threshold value, corresponding TDOA measurement values are eliminated (page 10, first paragraph, Finally, the thresholds were set by the following principles iteratively and verified according to the accuracy of the location results. (1) is set as large as possible to filter the measurements with large error and reduce the calculation amount of the Taylor algorithm. (2) is set carefully to discard the measurements which suffer from excessive);
In response to the residual value being determined to be greater than the threshold value, corresponding TDOA measurement values are eliminated or discarded.
in response to the residual value being less than or equal to the threshold value, corresponding measurement values are retained (page 9, line 7 Third, there are two necessary conditions remaining for the Residual Sum of Squares: Whether the Kalman algorithm has been initialized, and whether the interval time is below threshold. If both are satisfied, will be the input parameter of the Kalman algorithm to obtain another result, or the estimated results will be the initial value of the Kalman algorithm and become the final result.);
Examiner views if the residual value is less than the required threshold value, the initial measurement value is used as the final position value, also see in software program in page 10.
finally, the position coordinates of the positioning tag are estimated, and the retained TDOA measurement values are substituted into the standard EKF filtering algorithm, so that the final position coordinate of the surgical instrument is obtained (see above in page 9, line7. The applicant uses Rui technique in locating the final position of surgical instrument.).
Accordingly, it would have been obvious to one of ordinary skill in the art before the effective filing of the invention to have incorporated Rui et al into Mahfouz for the purpose of using Chan, Taylor and Kalman algorithm to reduce the error in determining a position of tags, so that an accurate final position can be determined for a surgical instrument.
Claim(s) 6, is/are rejected under 35 U.S.C. 103 as being unpatentable over The combination of Mahfouz and Rui in view of Rofougaran US 20040102161 A1.
Regarding claim 6 the combination of Mahfouz and Rui teach the chip-level positioning method for orthopedic surgery navigation based on the UWB according to claim 1 (para [0009] The current UWB and IMU hybrid tracking system, as disclosed in more detail hereafter, addresses these deficiencies and allows for precise tracking and surgical navigation.), wherein the UWB module unit comprises a main control chip (see fig. 193, 194 microcontroller), a signal processing chip, a radio frequency power amplifier circuit (see Fig. 193, 194 power amplifier, radio antenna) and a power supply unit which are electrically connected in sequence (para [0380], power supply 1024), and
The combination does not teach the radio frequency power amplifier circuit is also electrically connected with a tri-state power buffer.
Rofougaran teaches the radio frequency power amplifier circuit is also electrically connected with a tri-state power buffer (Fig. 4, para [0044] In a 1.sup.st configuration of the transmitter section 82, the transmitter switch module 124, which may be a multiplexer, high frequency switching network, or tri-state buffering network, provides the 1.sup.st outbound RF signal 130 to the 2.sup.nd transmitter IF stage 122 and provides the output of the 2.sup.nd transmitter IF stage 122 to the power amplifier 126.)
From Fig. 4 and above paragraph examiner views the radio frequency power amplifier 126 is electrically connected with tristate buffer 124.
Accordingly, it would have been obvious to one of ordinary skill in the art before the effective filing of the invention to have incorporated Rofougaran et al into Mahfouz for the purpose of using power amplifier and tristate buffer so that the RF signal can be boosted with amplifier and share signal to multiple devices without any interruption using tristate buffer.
Claim(s) 7 is/are rejected under 35 U.S.C. 103 as being unpatentable over the combination of Mahfouz, Rui and Rofougaran in view of Nguyen et al US 20200069358 A1 herein after “Nguyen”.
Regarding claim 7 the combination of Mahfouz, Rui and Rofougaran teach the chip-level positioning method for orthopedic surgery navigation based on the UWB according to claim 6, the combination does not teach wherein electrical connection method between the main control chip and the signal processing chip is bidirectional electrical connection
Nguyen et al US 20200069358 A1 teaches wherein electrical connection method between the main control chip and the signal processing chip is bidirectional electrical connection (Fig. 9,para [0030] The feedback system in various embodiments collects its voltage and current measurements simultaneously from the RF amplifier and digitizes the measurements through analog to digital converters (ADC). The feedback system is configured to process the digitized values, to derive real and imaginary components of the voltage and current RF output, and to supply the real and imaginary components to the primary microcontroller.)
From Fig. 9 and above paragraph, examiner views the primary or main microcontroller and feedback system (i.e., signal processor) is bidirectionally electrical connected to each other.
Accordingly, it would have been obvious to one of ordinary skill in the art before the effective filing of the invention to have incorporated Nguyen et al into Mahfouz for the purpose of connecting primary microcontroller and the signal processor in a bidirectional system, so that the information like position and direction related to the surgical device can be accurately analyzed and controlled.
Claim(s) 8 is/are rejected under 35 U.S.C. 103 as being unpatentable over the The combination of Mahfouz, Rui and Rofougaran in view of Wang et al US 20230152096 A1 herein after “Wang”, Feng CN 2023287676 U, Armitage US 20200333307 A1 and Fisher et al US 20200266967 A1 herein after “Fisher”
Regarding claim 8, the combination of Mahfouz, Rui and Rofougaran teach the chip-level positioning method for orthopedic surgery navigation based on the UWB according to claim 6, the combination does not teach wherein a model of the main control chip is STM32F407, a model of the signal processing chip is DW100, a model of the power supply unit is TPS61240, and a model of the tri-state power buffer is SN74LV1T125.
Wang teaches wherein a model of the main control chip is STM32F407 (para [0023] the control system exists in the form of a digital control algorithm in a control chip, for example, C language programming in the control chip microcontroller STM32F407).
Accordingly, it would have been obvious to one of ordinary skill in the art before the effective filing of the invention to have incorporated Wang into Mahfouz for the purpose of using main control chip with model STM32F407, so the surgical navigation device can be properly controller.
the combination of Mahfouz, Rui, Rofougaran and Wang do not teach a model of the signal processing chip is DW100, a model of the power supply unit is TPS61240, a model of the tri-state power buffer is SN74LV1T125.
Feng teaches a model of the signal processing chip is DW100 (para [0041] DW100 graphics wall controller further comprises video processing channel and RGB processing channels, can be window displaying video and RGB signal.),
Accordingly, it would have been obvious to one of ordinary skill in the art before the effective filing of the invention to have incorporated Feng into Mahfouz for the purpose of using signal processing chip DW100, so the surgical navigation device can be properly controller with processed signals.
the combination of Mahfouz, Rui, Rofougaran, Wang and Feng do not teach a model of the power supply unit is TPS61240, a model of the tri-state power buffer is SN74LV1T125.
Armitage teaches a model of the power supply unit is TPS61240 (para [0103] On example of a boost converter 290 is Texas Instrument's TPS61240.), and
Accordingly, it would have been obvious to one of ordinary skill in the art before the effective filing of the invention to have incorporated Armitage into Mahfouz for the purpose of using power supply unit TPS61240, so the surgical navigation device can be accurately powered.
the combination of Mahfouz, Rui, Rofougaran, Wang, Feng and Armitage do not teach a model of the tri-state power buffer is SN74LV1T125.
Fisher teaches a model of the tri-state power buffer is SN74LV1T125 (para [0030] Example implementations of level shifter 214 include Texas Instruments SN74LV1T125 or Nexperia 74LV1T125.).
Accordingly, it would have been obvious to one of ordinary skill in the art before the effective filing of the invention to have incorporated Fisher into Mahfouz for the purpose of using tri-state power buffer SN74LV1T125, so the components in a surgical navigation device can be accurately powered without any interruptions.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Zimmerman et al US 20070179626 A1 discuss navigation in joint arthroplasty.
Vesely et al Us 6246898 B1 discuss medical procedure suing navigation and imaging system.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to SHARAD TIMILSINA whose telephone number is (571)272-7104. The examiner can normally be reached Monday-Friday 9:00-5:00.
Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Catherine Rastovski can be reached at 571-270-0349. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/SHARAD TIMILSINA/Examiner, Art Unit 2857
/Catherine T. Rastovski/Supervisory Primary Examiner, Art Unit 2857
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