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 .
Continued Examination Under 37 CFR 1.114
A request for continued examination under 37 CFR 1.114, including the fee set forth in 37 CFR 1.17(e), was filed in this application after final rejection. Since this application is eligible for continued examination under 37 CFR 1.114, and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114. Applicant's submission filed on 7/28/2026 has been entered.
Response to Arguments
Applicant’s arguments filed 7/28/2026 have been considered but are moot in view of the new ground(s) of rejection as necessitated by the applicant’s claim amendments.
35 USC § 112 Written Description Rejection
The applicant’s specification amendment now meets the requirements for providing written description for the phrases “anatomical model” in claim 1, 15, and “finite element model” in claim 2 and “by reconstructing internal tissue conductivity based on the EIT measurement, wherein the EIT measurement constitutes a medical image of the limb” in claims 1 and 15. In particular, the specification now properly references and incorporates co-pending application 18/018,453. This application provides written description for the above phrases in [0027], [0033]-[0037], figures 3A-3C and 4A-4B. The 35 USC § 112 written description rejection has been withdrawn.
35 USC §101 Rejection
The rejection under 35 USC §101 has been vacated as the applicant has added the language “calibrating the electrode array based on the estimated one or more spatial alignment variations by modifying operation of the electrode array” to claims 1 and 15 which puts the abstract idea into practical application.
35 USC § 103 Prior Art Rejection
Applicant’s arguments filed 7/28/2026 have been considered but are not persuasive in view of the new ground(s) of rejection as necessitated by the applicant’s claim amendments. In particular, the examiner is now making a rejection under 35 USC § 103 using Barachant in view of Bovermann and Herr as follows:
“Barachant discloses generating, using a processor, an anatomical model of a limb (e.g. see [0053], “computer-based musculoskeletal representation associated with a hand”) but is silent as to generating, using a processor, an anatomical model of the limb by reconstructing internal tissue conductivity based on the EIT measurement, wherein the EIT measurement constitutes a medical image of the limb. Boverman teaches it is known to use such a modification as set forth in [0020]-[0021], [0024]-[0025], figure 2 steps 150-160 (Note: Boverman discloses in [0024]-[0025] the model is a finite element model which is what the applicant discloses in claim 2) to improve the quality of the generated diagnostic image (e.g. see [0016]). It would have been obvious to one having ordinary skill in the art at the time the invention was filed to generate an anatomical model based on the EIT measurement as taught by Bovermann in the system/method of Barachant, since said modification would provide the predictable results of improving the quality of the generated diagnostic image.
Barachant and Bovermann disclose the invention except for the anatomical model identifies, a location of at least one rigid anatomical marker of the limb (Note: Bovermann and the applicant are both use EIT to map internal tissue conductivity. Rigid markers, such as bone as disclosed by the applicant’s specification, are not conductive). Herr teaches it is known to use such a modification as set forth in [0029]-[0030] and [0456] (Note: [0029]-[0030] discloses rigid structures can be mapped using finite element analysis and [0456] discloses tissue impedances can be mapped into the 3-D model) to infer a geometry of a rigid internal structure of the biological body segment based on cross-correlation of the captured images (e.g. see [0029]). It would have been obvious to one having ordinary skill in the art at the time the invention was filed to map the rigid structures in addition to the conductive tissue as taught by Herr in the system/method of Barachant and Bovermann, since said modification would provide the predictable results of inferring a geometry of a rigid internal structure of the biological body segment based on cross-correlation of the captured images.”
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
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, 2, 4, 7, 10-13, 15, 17, and 19-20 is/are rejected under 35 U.S.C. 103 as being unpatentable over Barachant (WO 2020/112986 A1) in view of Boverman et al. (Pub. No.: US 2017/0172451 A1); hereinafter referred to as “Boverman” and Herr et al. (Pub. No.: US 2021/0145608 A1); hereinafter referred to as “Herr”.
Regarding claims 1 and 15, Barachant discloses a method for calibrating an electrode array, the method comprising: receiving an electrical impedance tomography (EIT) measurement receiving an electrical impedance tomography (EIT) measurement obtained by injecting electrical current and sensing voltages using a plurality of electrodes of an electrode array positioned on a limb (e.g. see [0066]); generating, using a processor, an anatomical model of a limb (e.g. see [0053], “computer-based musculoskeletal representation associated with a hand”); determining an alignment of the electrode array relative to anatomical structures represented in the anatomical model based on the EIT measurement (e.g. see [0079], [0081]. [0079] discloses “some embodiments use autocalibration to automatically detect the position of the wearable device on a body part using an autocalibration model”, [0081] discloses “autocalibration model(s) can be used to determine the orientation and/or positioning of the band on the user’s body part, e.g., forearm”); comparing the determined alignment of the electrode array with a reference alignment associated with a reference anatomical model (e.g. see [0054], [0069]); estimating one or more spatial alignment variations of the electrode array relative to the anatomical structures using an alignment variation model (e.g. see [0054], [0069]. Note: [0054] discloses “In certain embodiments, the systems and methods disclosed herein comprise identifying a “virtual” reference electrode and mapping the specific orientation of an armband to an offset value associated with an electrode and the “virtual” reference electrode” while [0069] discloses “in certain embodiments, the armband system can be calibrated via selection of particular inference model(s) such that the system adapts to any rotation and/or arm position offset without interfering with the user experience, also referred to herein as autocalibration. In other embodiments, the detected offset in orientation and/or relative difference in location of the band on the user compared to the orientation and/or positioning of the band used to train one or more inference models can be used to “normalize” the orientation and/or location of the band for input into the inference model(s). A virtual reference electrode (e.g., the“0” electrode) may be defined, and a rotation offset relative to the virtual reference electrode may be used to normalize the orientation and/or location of the band”), and calibrating the electrode array based on the estimated one or more spatial alignment variations by modifying operation of the electrode array (e.g. see [0054], [0069]).
Barachant discloses generating, using a processor, an anatomical model of a limb (e.g. see [0053], “computer-based musculoskeletal representation associated with a hand”) but is silent as to generating, using a processor, an anatomical model of the limb by reconstructing internal tissue conductivity based on the EIT measurement, wherein the EIT measurement constitutes a medical image of the limb. Boverman teaches it is known to use such a modification as set forth in [0020]-[0021], [0024]-[0025], figure 2 steps 150-160 (Note: Boverman discloses in [0024]-[0025] the model is a finite element model which is what the applicant discloses in claim 2) to improve the quality of the generated diagnostic image (e.g. see [0016]). It would have been obvious to one having ordinary skill in the art at the time the invention was filed to generate an anatomical model based on the EIT measurement as taught by Bovermann in the system/method of Barachant, since said modification would provide the predictable results of improving the quality of the generated diagnostic image.
Barachant and Bovermann disclose the invention except for the anatomical model identifies, a location of at least one rigid anatomical marker of the limb (Note: Bovermann and the applicant are both use EIT to map internal tissue conductivity. Rigid markers, such as bone as disclosed by the applicant’s specification, are not conductive). Herr teaches it is known to use such a modification as set forth in [0029]-[0030] and [0456] (Note: [0029]-[0030] discloses rigid structures can be mapped using finite element analysis and [0456] discloses tissue impedances can be mapped into the 3-D model) to infer a geometry of a rigid internal structure of the biological body segment based on cross-correlation of the captured images (e.g. see [0029]). It would have been obvious to one having ordinary skill in the art at the time the invention was filed to map the rigid structures in addition to the conductive tissue as taught by Herr in the system/method of Barachant and Bovermann, since said modification would provide the predictable results of inferring a geometry of a rigid internal structure of the biological body segment based on cross-correlation of the captured images.
Regarding claim 2, Barachant discloses the invention but is silent as to the anatomical model is a finite element model. Boverman teaches it is known to use such a modification as set forth in [0024]-[0025], figure 2 step 156 to improve the quality of the generated diagnostic image (e.g. see [0016]). It would have been obvious to one having ordinary skill in the art at the time the invention was filed to use a finite element model for the anatomical model as taught by Bovermann in the system/method of Barachant, since said modification would provide the predictable results of improving the quality of the generated diagnostic image
Regarding claims 4 and 20, Barachant discloses automatically adjusting a pattern of the electrode array to accommodate the one or more alignment variations using an alignment adjustment function (e.g. see “autocalibration” in [0054], [0069], [0079], [0081]).
Regarding claims 7 and 17, Barachant discloses the limb is a forearm (e.g. see [0054], [0069], [0081]).
Regarding claim 10, Barachant discloses the alignment variation model is a shared response model or a domain adaptation model (e.g. see [0054], [0070], [0075]. The examiner is interpreting the models trained on multiple users as a “shared response model”).
Regarding claim 11, Barachant discloses machine learning is used to improve alignment variation model (e.g. see [0067], [0068], [0070], [0075]).
Regarding claim 12, Barachant discloses the machine learning comprises a deep learning model (e.g. see [0068]).
Regarding claim 13, Barachant discloses the one or more alignment variations comprise one or more of a distal shift or a proximal shift (e.g. see [0069]).
Regarding claim 19, Barachant discloses the electrode array is configured to perform electromyography (e.g. see [0054], [0061]-[0064])
Claim(s) 5-6, 8-9, 14, and 16 is/are rejected under 35 U.S.C. 103 as being unpatentable over Barachant in view of Bovermann and Herr as applied to claims 1, 4, and 15 above, and further in view of Friedenberg et al. (Pub. No.: US 2021/0353942 A1); hereinafter referred to as “Friedenberg” (NOTE: Please see provisional application 63/024,589 for a date that precedes the applicant’s application priority data).
Regarding claim 5, Barachant in view of Bovermann and Herr discloses method and system for calibrating an electrode array as set forth above. Barachant further discloses autocalibration (e.g. see [0054], [0069], [0079], [0081]) but is silent as to automatically adjusting the pattern of the electrode array comprises sending one or more signals to the electrode array to shift a pattern of active electrodes and inactive electrodes. Friedenberg teaches that it is known to use such a modification as set forth in [0045] to provide an iterative calibration process (e.g. see [0014]) that lacks many of the drawbacks of previous calibration techniques (e.g. see [0011]). It would have been obvious to one having ordinary skill in the art at the time the invention was made to shift a pattern of active electrodes and inactive electrodes as taught by Friedenberg in the system/method of Barachant in view of Bovermann and Herr, since said modification would provide the predictable results of an iterative calibration process (e.g. see [0014]) that lacks many of the drawbacks of previous calibration techniques (e.g. see [0011]).
Regarding claim 6, Barachant in view of Bovermann and Herr discloses the one or more alignment variations using an alignment adjustment function (e.g. see “autocalibration” in [0054], [0069], [0079], [0081]) but is silent as to manually adjusting a pattern of active electrodes and inactive electrodes of the electrode array. Friedenberg teaches that it is known to use such a modification as set forth in figure 8, [0074]-[0077] to provide an iterative calibration process (e.g. see [0014]) that lacks many of the drawbacks of previous calibration techniques (e.g. see [0011]). It would have been obvious to one having ordinary skill in the art at the time the invention was made to use manually adjust the electrode pattern as taught by Friedenberg in the system/method of Barachant in view of Bovermann and Herr, since said modification would provide the predictable results of an iterative calibration process (e.g. see [0014]) that lacks many of the drawbacks of previous calibration techniques (e.g. see [0011]).
Regarding claims 8, 9, and 16, Barachant in view of Bovermann and Herr discloses the claimed invention except for the electrode array is located on an internal surface of a garment and the method is performed following a donning of the garment. Friedenberg teaches that it is known to use such a modification as set forth in [0007], [0086] (for the internal surface limitation) and [0078] (for the donning limitation) to provide superior skin contact for the electrodes (e.g. see [0007], [0086]). It would have been obvious to one having ordinary skill in the art at the time the invention was made to use electrodes located on the inside of the garment and performing the method following the donning as taught by Friedenberg in the system/method of Barachant in view of Bovermann and Herr, since said modification would provide the predictable results of superior skin contact for the electrodes (e.g. see [0007], [0086]).
Regarding claim 14, Barachant in view of Bovermann and Herr discloses the claimed invention but is silent as to optimizing the electrode current of the electrode array. Friedenberg teaches that it is known to use such a modification as set forth in figure 2, [0056]-[0057], [0061] to provide reduced discomfort/pain when adjusting current amplitude for choosing the right electrode energization pattern (e.g. see [0061]). It would have been obvious to one having ordinary skill in the art at the time the invention was made to optimize the current of the electrode array as taught by Friedenberg in the system/method of Barachant in view of Bovermann and Herr, since said modification would provide the predictable results of reduced discomfort/pain when adjusting current amplitude for choosing the right electrode energization pattern (e.g. see [0061]).
Claim(s) 18 is/are rejected under 35 U.S.C. 103 as being unpatentable over Barachant in view of Bovermann and Herr as applied to claim 15 above, and further in view of Sharma et al. (Pub. No.: US 2020/0406035 A1); hereinafter referred to as “Sharma”.
Regarding claim 18, Barachant in view of Bovermann and Herr discloses method and system for calibrating an electrode array as set forth above. Barachant further discloses the claimed invention but is silent as to the electrode array is a high-density electrode array. Sharma teaches that it is known to use such a modification as set forth in figure 1, element 12, [0020] to provide an electrode sleeve with high channel density and large coverage area that allows for the classification of more complex hand movements (e.g. see [0045]). It would have been obvious to one having ordinary skill in the art at the time the invention was made to optimize the current of the electrode array as taught by Sharma in the system/method of Barachant in view of Bovermann and Herr, since said modification would provide the predictable results of an electrode sleeve with high channel density and large coverage area that allows for the classification of more complex hand movements (e.g. see [0045]).
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to PHILIP C EDWARDS whose telephone number is (571)270-1804. The examiner can normally be reached Mon-Fri, 9:00-5:00 EST.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Unsu Jung can be reached at 571-272-8506. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/P.C.E/Examiner, Art Unit 3792
/AMANDA L STEINBERG/Examiner, Art Unit 3792
