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 .
Claim Objections
Claim 1 is objected to because of the following informalities: Claim 1 recites “the one or more control signal” in line 15, which appears to be referring to – the one or more control signals – as recited earlier in the claim. Appropriate correction is required.
Claim Rejections - 35 USC § 112
The following is a quotation of 35 U.S.C. 112(d):
(d) REFERENCE IN DEPENDENT FORMS.—Subject to subsection (e), a claim in dependent form shall contain a reference to a claim previously set forth and then specify a further limitation of the subject matter claimed. A claim in dependent form shall be construed to incorporate by reference all the limitations of the claim to which it refers.
The following is a quotation of pre-AIA 35 U.S.C. 112, fourth paragraph:
Subject to the following paragraph [i.e., the fifth paragraph of pre-AIA 35 U.S.C. 112], a claim in dependent form shall contain a reference to a claim previously set forth and then specify a further limitation of the subject matter claimed. A claim in dependent form shall be construed to incorporate by reference all the limitations of the claim to which it refers.
Claims 13 and 14 are rejected under 35 U.S.C. 112(d) or pre-AIA 35 U.S.C. 112, 4th paragraph, as being of improper dependent form for failing to further limit the subject matter of the claim upon which it depends, or for failing to include all the limitations of the claim upon which it depends. Claims 13 and 14 are each directed only toward the robotic arm in the system of claim 8 and therefore fail to include all the limitations of the claim upon which it depends (the system of claim 8). Applicant may cancel the claim(s), amend the claim(s) to place the claim(s) in proper dependent form, rewrite the claim(s) in independent form, or present a sufficient showing that the dependent claim(s) complies with the statutory requirements.
Claim Interpretation
The following is a quotation of 35 U.S.C. 112(f):
(f) Element in Claim for a Combination. – An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
The following is a quotation of pre-AIA 35 U.S.C. 112, sixth paragraph:
An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
The claims in this application are given their broadest reasonable interpretation using the plain meaning of the claim language in light of the specification as it would be understood by one of ordinary skill in the art. The broadest reasonable interpretation of a claim element (also commonly referred to as a claim limitation) is limited by the description in the specification when 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is invoked.
As explained in MPEP § 2181, subsection I, claim limitations that meet the following three-prong test will be interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph:
(A) the claim limitation uses the term “means” or “step” or a term used as a substitute for “means” that is a generic placeholder (also called a nonce term or a non-structural term having no specific structural meaning) for performing the claimed function;
(B) the term “means” or “step” or the generic placeholder is modified by functional language, typically, but not always linked by the transition word “for” (e.g., “means for”) or another linking word or phrase, such as “configured to” or “so that”; and
(C) the term “means” or “step” or the generic placeholder is not modified by sufficient structure, material, or acts for performing the claimed function.
Use of the word “means” (or “step”) in a claim with functional language creates a rebuttable presumption that the claim limitation is to be treated in accordance with 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. The presumption that the claim limitation is interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is rebutted when the claim limitation recites sufficient structure, material, or acts to entirely perform the recited function.
Absence of the word “means” (or “step”) in a claim creates a rebuttable presumption that the claim limitation is not to be treated in accordance with 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. The presumption that the claim limitation is not interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is rebutted when the claim limitation recites function without reciting sufficient structure, material or acts to entirely perform the recited function.
Claim limitations in this application that use the word “means” (or “step”) are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, except as otherwise indicated in an Office action. Conversely, claim limitations in this application that do not use the word “means” (or “step”) are not being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, except as otherwise indicated in an Office action.
This application includes one or more claim limitations that use the word “means,” and are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, because the claim limitation(s) uses a generic placeholder that is coupled with functional language without reciting sufficient structure to perform the recited function and the generic placeholder is not preceded by a structural modifier. Such claim limitation(s) is/are: classifying means, detecting means, and analyzing means in claim 8.
Because this/these claim limitation(s) is/are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, it/they is/are being interpreted to cover the corresponding structure described in the specification as performing the claimed function, and equivalents thereof: classification unit, detection unit, and analyzing unit, respectively.
If applicant does not intend to have this/these limitation(s) interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, applicant may: (1) amend the claim limitation(s) to avoid it/them being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph (e.g., by reciting sufficient structure to perform the claimed function); or (2) present a sufficient showing that the claim limitation(s) recite(s) sufficient structure to perform the claimed function so as to avoid it/them being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph.
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) 1-5 and 8-12 is/are rejected under 35 U.S.C. 103 as being unpatentable over US Patent No. 8,457,705 B2 to Shoureshi et al. (Shoureshi).
Regarding at least claim 1
Shoureshi discloses methods and systems for controlling a prosthesis using a brain imager that images a localized portion of the brain (abstract). Shoureshi meets the limitations of a method of controlling a robotic arm (col. 13, lines 11-36 discloses controlling an artificial limb for the wrist and col. 14, lines 15-17 discloses that the methods and systems may be applied to various robotic and/or prosthetics which may be used in place of an artificial limb) based on brain activities (col. 13, lines 31-36 discloses control of the robotic arm using EMG and brain imaging data and developing algorithms developed by a neural network), comprising: measuring a hyperbaric oxygen (HbO) level (col. 7, lines 29-34 discloses recording the oxygen level changes with time via tracking of the neural activity) of a subject at target brain areas during a wrist movement (col. 13, lines 19-30 discloses use of a brain imager that is placed over the portion of a user’s motor cortex that controls the wrist) using a functional near-infrared spectroscopy (fNIRS) device having light sources and detectors (the abstract discloses that the brain imager uses near infrared light and detects spectral changes of the NIR light as it passes through the brain; fig. 3 shows light sources and detectors); detecting one or more brain activities of the subject through said detectors based on the HbO level of the non-disabled subject during the wrist movement (col. 10, lines 1-9 and 22-28 disclose detecting brain activities through the detectors based on the oxygen level during wrist movement); classifying the one or more brain activities corresponding to the wrist movement using one or more classification algorithms and generating a training data set (col. 13, lines 19-31 discloses placing the brain imager over the portion of a user’s motor cortex that controls the wrist and capturing data during the wrist motion such that data sets are then provided to a control system such as a neural network, which develops algorithms to control the artificial limb/robotic arm); generating one or more control signals based on the one or more brain activities for the robotic arm to perform the wrist movement (col. 14, lines 50-56 discloses that the neural network generates control signals for the prosthesis/robotic arm); detecting one or more brain activities of a disabled subject at the target brain areas based on the HbO level using the fNIRS device (col. 13, lines 19-30 discloses detecting brain activation data at target brain areas based on the oxygen/HbO level using the brain imager/fNIRS on a disabled subject that is in need of a prosthetic); analyzing the one or more brain activities of the disabled subject based on the training data set (col. 15, lines 14-22 discloses analyzing with the neural network the brain imaging data to determine levels of oxygen that correspond to the brain activity obtained during the training, to determine corresponding muscular outputs); and generating the one or more control signal for the robotic arm to perform the wrist movement based on the analyzed brain activity of the disabled subject (col. 15, lines 14-22 discloses that the determined muscular outputs are then used to operate or control a prosthesis/robotic artificial limb to perform the wrist movement based on the brain imager data of subject in need of the prosthetic/robotic artificial limb).
Shoureshi also teaches obtaining the desired data with the brain imager in patients who have already had a limb removed because activation of the brain in the areas that correspond with the muscle groups of the missing limb still occurs – therefore, the brain of the disabled subject would provide the same data as a non-disabled subject (col. 14, lines 57-67 through col. 15, lines 1-3). However, Shoureshi does not explicitly teach that the subject in which the hyperbaric oxygen (HbO) level is measured and the one or more brain activities are detected is non-disabled.
It would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to substitute the disabled subject in which the hyperbaric oxygen (HbO) level is measured and the one or more brain activities are detected of Shoureshi for a subject that is non-disabled, since the data provided would be the same and this substitution would therefore yield predictable results.
Regarding at least claim 2
Shoureshi teaches the method of claim 1. Shoureshi also teaches wherein the wrist movement includes at least one selected from the group consisting of wrist extension, wrist flexion, ulnar deviation, and radial deviation of the non-disabled subject (col. 13, lines 11-21 discloses wrist extension and flexion).
Regarding at least claim 3
Shoureshi teaches the method of claim 1. Shoureshi also teaches wherein the one or more classification algorithms is an Artificial Neural Network (ANN), K-Nearest Neighbor (KNN) or Support Vector Machine (SVM) (col. 13, lines 33-3 teaches that the algorithms are developed by a neural network).
Regarding at least claim 8
Shoureshi meets the limitations of a system of provisioning control of a robotic arm based on brain activities, comprising: a robotic arm (col. 13, lines 11-36 discloses controlling an artificial limb for the wrist and col. 14, lines 15-17 discloses that the methods and systems may be applied to various robotic and/or prosthetics which may be used in place of an artificial limb); a functional near-infrared spectroscopy (fNIRS) device with one or more light sources and one or more detectors (the abstract discloses that the brain imager uses near infrared light and detects spectral changes of the NIR light as it passes through the brain; fig. 3 shows light sources and detectors) for measuring a hyperbaric oxygen (HbO) level (col. 7, lines 29-34 discloses recording the oxygen level changes with time via tracking of the neural activity) of at least one subject at target brain areas during a wrist movement (col. 13, lines 19-30 discloses use of a brain imager that is placed over the portion of a user’s motor cortex that controls the wrist); wherein the one or more detectors detects one or more brain activities of the subject based on the HbO level of the subject during the wrist movement (col. 10, lines 1-9 and 22-28 disclose detecting brain activities through the detectors based on the oxygen level during wrist movement); a classifying means for classifying the one or more brain activities corresponding to wrist movement using one or more classification algorithms(col. 13, lines 19-31 discloses placing the brain imager over the portion of a user’s motor cortex that controls the wrist and capturing data during the wrist motion such that data sets are then provided to a control system such as a neural network, which develops algorithms to control the artificial limb/robotic arm) and generating a training data set (col. 3, lines 1-10 discloses generating a training data set); a brain-control interface (BCI) generates one or more control signals based on the classified brain activities for the robotic arm to perform the wrist movement (col. 14, lines 50-56 discloses that the neural network generates control signals for the prosthesis/robotic arm based on the classified brain activities via the neural network and col. 15, lines 46-57 discloses that the techniques, blocks, steps, and means disclosed may be implemented in hardware, software, or a combination and are construed to be a brain-control interface as claimed); a detecting means for detecting one or more brain activities of a disabled subject at the target brain areas based on the HbO level using the fNIRS device (col. 13, lines 19-30 discloses detecting brain activation data at target brain areas based on the oxygen/HbO level using the brain imager/fNIRS on a subject that is in need of a prosthetic); and an analyzing means for analyzing the one or more brain activities of the disabled subject based on the training data set (col. 15, lines 14-22 discloses use of the neural network which based on the brain imaging data to determine levels of oxygen that correspond to the brain activity obtained during the training and determine corresponding muscular outputs); wherein, the BCI generates the control signal for the robotic arm to perform the wrist movement based on the analyzed brain activity of the disabled subject (col. 15, lines 14-22 and lines 46-57 discloses that the determined muscular outputs are then used to operate or control a prosthesis/robotic artificial limb to perform the wrist movement based on the brain imager data of subject in need of the prosthetic/robotic artificial limb via the BCI).
Shoureshi also teaches obtaining the desired data with the brain imager in patients who have already had a limb removed because activation of the brain in the areas that correspond with the muscle groups of the missing limb still occurs– therefore, the brain of the disabled subject would provide the same data as a non-disabled subject (col. 14, lines 57-67 through col. 15, lines 1-3). However, Shoureshi does not explicitly teach that the subject in which the hyperbaric oxygen (HbO) level is measured and the one or more brain activities are detected is non-disabled.
It would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to substitute the disabled subject in which the hyperbaric oxygen (HbO) level is measured and the one or more brain activities are detected of Shoureshi for a subject that is non-disabled, since the data provided would be the same and this substitution would therefore yield predictable results.
Regarding at least claim 9
Shoureshi teaches the system of claim 8, wherein the wrist movement includes at least one selected from the group consisting of wrist extension, wrist flexion, ulnar deviation, and radial deviation of the non-disabled subject (col. 13, lines 11-21 discloses wrist extension and flexion).
Regarding at least claim 10
Shoureshi teaches the system of claim 8, wherein the one or more classification algorithms an Artificial Neural Network (ANN), K-Nearest Neighbor (KNN) or Support Vector Machine (SVM) (col. 13, lines 33-3 teaches that the algorithms are developed by a neural network).
Regarding at least claims 4 and 11
Shoureshi teaches the method of claims 1 and 8. Shoureshi also teaches that the brain imager may include one or more light detectors, such as photodiodes, that detect light transmitted into the brain by the light source, for the purpose of generating enough power to provide a sufficient signal back from the brain (col. 8, lines 49-59). However, Shoureshi does not appear to teach wherein the fNIRS device includes eight light sources and eight detectors.
There is no evidence of record that establishes that changing the amount of detectors and light sources would result in a difference in function of the Shoureshi device. Further, a person having ordinary skill in the art, being faced with modifying the amount of detectors and light sources of Shoureshi, would have a reasonable expectation of success in making such a modification and it appears the device would function as intended being given the claimed eight detectors and eight light sources. Lastly, applicant has not disclosed that the claimed amount solves any stated problem, indicating that the system “may” include eight light sources and eight detectors, and offering other acceptable ranges (e.g., one or more of each, specification at the last paragraph on page 9) and therefore there appears to be no criticality placed on the amount as claimed such that it produces an unexpected result.
Therefore, it would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to modify the one or more light sources and detectors of the fNIRS of Shoureshi to include eight light sources and eight detectors as an obvious matter of design choice within the skill of the art, depending on the amount of power required to provide a sufficient signal back from the individual patient’s brain.
Regarding at least claims 5 and 12
Shoureshi teaches the method of claims 1 and 8, wherein the light sources emit light at a first peak emission of 735 nm and at a second peak emission of 850 nm (which meets the limitation of being of 850 ± 10 nm (col. 8, lines 47-49)). However, Shoureshi does not explicitly teach a first peak emission of 760 ± 10 nm.
It would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to modify the first peak emission of Shoureshi from 735 nm to 760 ± 10 nm as applicant appears to have placed no criticality on the claimed range (see last paragraph on page 9 indicating the first peak emission “may” be within the claimed range) and since it has been held that “[i]n the case where the claimed ranges ‘overlap or lie inside ranges disclosed by the prior art’ a prima facie case of obviousness exists.” In re Wertheim, 541 F.2d 257, 191 USPQ 90 (CCPA 1976); In re Woodruff, 919 F.2d 1575, 16 USPQ2d 1934 (Fed. Cir. 1990).
Claim(s) 6, 7, 13, and 14 is/are rejected under 35 U.S.C. 103 as being unpatentable over Shoureshi in view of US Patent Application Publication No. 2012/0186383 A1 to Schvalb et al. (Schvalb).
Regarding at least claim 6
Shoureshi meets the limitations of a robotic arm to execute the method of claim 1. However, Shoureshi does not explicitly teach that the robotic arm, comprises: a pin finger, a first finger, and a proximal finger connected together with a joint pin in a palm section of the robotic arm, wherein the palm section comprises a palm; a wrist connector and a hand connector connecting the palm section to a forearm section through a wrist joint; and wherein the forearm section comprises an actuator base mounted on a circuit holder to control a movement of the robotic arm.
Schvalb teaches a mechanical arm (figs. 1B and 4A) that includes a pin finger, a first finger, and a proximal finger connected together with a joint pin in a palm section (18) of the robotic arm (see annotated fig. 1B below), wherein the palm section comprises a palm (18); a wrist connector (58) and a hand connector (46) connecting the palm section to a forearm section through a wrist joint (56) (fig. 3A); and wherein the forearm section comprises an actuator base (60) mounted on a circuit holder (62/68) to control a movement of the robotic arm (paragraphs 0140-0141), for the purpose of resembling human hands having at least two articulated digits that may be brought together to grasp an object (paragraph 0003).
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It would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to modify the robotic arm of Shoureshi to specify that the arm comprises a pin finger, a first finger, and a proximal finger connected together with a joint pin in a palm section of the robotic arm, wherein the palm section comprises a palm; a wrist connector and a hand connector connecting the palm section to a forearm section through a wrist joint; and wherein the forearm section comprises an actuator base mounted on a circuit holder to control a movement of the robotic arm, in order to resemble human hands having at least two articulated digits that may be brought together to grasp an object, as taught by Schvalb.
Regarding at least claim 7
Shoureshi in view of Schvalb teaches the robotic arm of claim 6. Shoureshi also teaches wherein the robotic arm is configured to perform four wrist movements including wrist extension, wrist flexion, ulnar deviation, and radial deviation (col. 13, lines 11-21 discloses wrist extension and flexion).
Regarding at least claim 13
Shoureshi teaches the robotic arm in the system of claim 8. However, Shoureshi does not explicitly teach that the robotic arm, comprises: a pin finger, a first finger, and a proximal finger connected together with a joint pin in a palm section of the robotic arm, wherein the palm section comprises a palm; a wrist connector and a hand connector connecting the palm section to a forearm section through a wrist joint; and wherein the forearm section comprises an actuator base mounted on a circuit holder to control a movement of the robotic arm.
Schvalb teaches a mechanical arm (figs. 1B and 4A) that includes a pin finger, a first finger, and a proximal finger connected together with a joint pin in a palm section (18) of the robotic arm (see annotated fig. 1B below), wherein the palm section comprises a palm (18); a wrist connector (58) and a hand connector (46) connecting the palm section to a forearm section through a wrist joint (56) (fig. 3A); and wherein the forearm section comprises an actuator base (60) mounted on a circuit holder (62/68) to control a movement of the robotic arm (paragraphs 0140-0141), for the purpose of resembling human hands having at least two articulated digits that may be brought together to grasp an object (paragraph 0003).
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It would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to modify the robotic arm of Shoureshi to specify that the arm comprises a pin finger, a first finger, and a proximal finger connected together with a joint pin in a palm section of the robotic arm, wherein the palm section comprises a palm; a wrist connector and a hand connector connecting the palm section to a forearm section through a wrist joint; and wherein the forearm section comprises an actuator base mounted on a circuit holder to control a movement of the robotic arm, in order to resemble human hands having at least two articulated digits that may be brought together to grasp an object, as taught by Schvalb.
Regarding at least claim 14
Shoureshi in view of Schvalb teaches the robotic arm of claim 13. Shoureshi also teaches wherein the robotic arm is configured to perform four wrist movements including wrist extension, wrist flexion, ulnar deviation, and radial deviation (col. 13, lines 11-21 discloses wrist extension and flexion).
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to MELISSA A HOBAN whose telephone number is (571)270-5785. The examiner can normally be reached Monday-Friday 8:00AM-5:00PM.
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/M.A.H/Examiner, Art Unit 3774
/MELANIE R TYSON/Supervisory Patent Examiner, Art Unit 3774