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 .
Response to Amendment
The amendment filed January 2, 2026 has been entered. Claims 1-22 remain pending in the application. Applicant’s amendments to the claims necessitate new grounds of rejection, as described in the Response to Arguments, 101, and 102 Rejections below.
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 do not use the word “means,” but are nonetheless being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, because the claim limitations use 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 limitations are: “range setting portion” and “arithmetic portion” in claim 1; “index value calculator” in claim 2; “range setting portion” and “arithmetic portion” in claim 9; “total activity level calculator”, range setting portion”, and “arithmetic portion” in claim 10; “a plurality of identification devices” and “a determination portion” in claim 15; and “an application execution portion” in claim 21.
Because these claim limitations are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, they are being interpreted to cover the corresponding structure described in the specification as performing the claimed function, and equivalents thereof.
If applicant does not intend to have these limitations interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, applicant may: (1) amend the claim limitations to avoid 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 limitations recite 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 § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claims 1-9 are rejected under 35 U.S.C. 101 because the claimed invention is directed to a judicial exception (i.e., a law of nature, a natural phenomenon, or an abstract idea) without significantly more. Claims 1-9 are directed to an apparatus for detecting a motion of a user using a computational algorithm, which is an abstract idea. Claims 1-9 do not include additional elements that integrate the exception into a practical application or that are sufficient to amount to significantly more than the judicial exception for the reasons provided below which are in line with the 2014 Interim Guidance on Patent Subject Matter Eligibility (Federal Register, Vol. 79, No. 241, p 74618, December 16, 2014), the July 2015 Update on Subject Matter Eligibility (Federal Register, Vol. 80, No. 146, p. 45429, July 30, 2015), the May 2016 Subject Matter Eligibility Update (Federal Register, Vol. 81, No. 88, p. 27381, May 6, 2016), and the 2019 Revised Patent Subject Matter Eligibility Guidance (Federal Register, Vol. 84, No. 4, page 50, January 7, 2019).
The analysis of claim 1 is as follows:
Step 1: Claim 1 is drawn to a machine.
Step 2A – Prong One: Claim 1 recites an abstract idea. In particular, claim 1 recites the following limitations:
[A1] – “a range setting portion configured to set an operation learning time range”; and
[B1] – “an arithmetic portion configured to learn an operation”.
These elements [A1]-[B1] of claim 1 are drawn to an abstract idea since they involve mathematical concepts in the form of mathematical relationships, mathematical formulas or equations, and/or mathematical calculations and they involve a mental process that can be practically performed in the human mind including observation, evaluation, judgment, and opinion and using pen and paper.
Step 2A – Prong Two: Claim 1 recites the following limitations that are beyond the judicial exception:
[A2] – “a plurality of sensors configured to be worn on a wrist and to output a sensor signal based on a displacement of a body surface of the wrist”;
[B2] – “the sensor signal of the plurality of sensors”;
[C2] – “the plurality of sensors in the operation learning time range”; and
[D2] – “wherein the arithmetic portion is configured to obtain a normative signal based on a plurality of different conditions from the sensor signal and further configured to identify, based on the normative signal, the operation as relating to at least one finger of a hand extending from the wrist on which the plurality of sensors are worn”.
These elements [A2]-[D2] of claim 1 do not integrate the exception into a practical application of the exception. In particular, the elements [A2] are merely adding insignificant extra-solution activity to the judicial exception, i.e., mere data gathering at a higher level of generality - see MPEP 2106.04(d) and MPEP 2106.05(g). Also, the elements [B2-D2] merely add the words “apply it” (or an equivalent) with the judicial exception.
Step 2B: Claim 1 does not recite additional elements that amount to significantly more than the judicial exception itself. In particular, the recitation “a plurality of sensors configured to be worn on a wrist and to output a sensor signal based on a displacement of a body surface of the wrist” does not qualify as significantly more because this limitation merely describes a generic sensor configured to be worn on the wrist, which is not a particular machine, as part of the claimed invention. Also, this limitation is merely insignificant extra-solution activity to the judicial exception, e.g., mere data gathering in conjunction with the abstract idea that uses conventional, routine, and well known elements. In particular, the sensor is nothing more than a wrist-worn sensor capable of detecting displacement/motion. Such sensors are conventional as evidenced by:
U.S. Patent Application Publication No. US 20180317852 A1 (MacDonald et al.) discloses that devices including motion sensors worn on the wrist of a user are conventional [0028].
Claims 2-8 depend from claim 1, and recite the same abstract idea as claim 1. Furthermore, these claims only contain recitations that further limit the abstract idea (that is, the claims only recite limitations that further limit the algorithm).
In view of the above, the additional elements individually do not integrate the exception into a practical application and do not amount to significantly more than the above-judicial exception (the abstract idea). Looking at the limitations of each claim as an ordered combination in conjunction with the claims from which they depend (that is, as a whole) adds nothing that is not already present when looking at the elements taken individually. There is no indication that the combination of elements improves the functioning of a computer, for example, or improves any other technology. There is no indication that the combination of elements permits automation of specific tasks that previously could not be automated. There is no indication that the combination of elements includes a particular solution to a computer-based problem or a particular way to achieve a desired computer-based outcome. Rather, the collective functions of the claimed invention merely provide conventional computer implementation, i.e., the computer is simply a tool to perform the process.
The analysis of claim 9 is as follows:
Step 1: Claim 9 is drawn to a machine.
Step 2A – Prong One: Claim 9 recites an abstract idea. In particular, claim 9 recites the following limitations:
[A1] – “a range setting portion configured to set an operation estimating time range”
[B1] – “an arithmetic portion configured to learn an operation”
These elements [A1]-[B1] of claim 9 are drawn to an abstract idea since they involve mathematical concepts in the form of mathematical relationships, mathematical formulas or equations, and/or mathematical calculations and they involve a mental process that can be practically performed in the human mind including observation, evaluation, judgment, and opinion and using pen and paper.
Step 2A – Prong Two: Claim 9 recites the following limitations that are beyond the judicial exception:
[A2] – “a plurality of sensors configured to be worn on a wrist and to output a sensor signal based on a displacement of a body surface of the wrist”;
[B2] – “the sensor signal of the plurality of sensors”;
[C2] – “the plurality of sensors in the operation learning time range”; and
[D2] – “wherein the arithmetic portion is configured to obtain a normative signal based on a plurality of different conditions from the sensor signal and further configured to identify, based on the normative signal, the operation as relating to at least one finger of a hand extending from the wrist on which the plurality of sensors are worn”.
These elements [A2]-[D2] of claim 9 do not integrate the exception into a practical application of the exception. In particular, the element [A2] is merely adding insignificant extra-solution activity to the judicial exception, i.e., mere data gathering at a higher level of generality - see MPEP 2106.04(d) and MPEP 2106.05(g). Also, the elements [B2-D2] merely add the words “apply it” (or an equivalent) with the judicial exception.
Step 2B: Claim 9 does not recite additional elements that amount to significantly more than the judicial exception itself. In particular, the recitation “a plurality of sensors configured to be worn on a wrist and to output a sensor signal based on a displacement of a body surface of the wrist” does not qualify as significantly more because this limitation merely describes a generic sensor configured to be worn on the wrist, which is not a particular machine, as part of the claimed invention. Also, this limitation is merely insignificant extra-solution activity to the judicial exception, e.g., mere data gathering in conjunction with the abstract idea that uses conventional, routine, and well known elements. In particular, the sensor is nothing more than a wrist-worn sensor capable of detecting displacement/motion. Such sensors are conventional as evidenced by MacDonald et al., as described in the analysis of claim 1.
In view of the above, the additional elements individually do not integrate the exception into a practical application and do not amount to significantly more than the above-judicial exception (the abstract idea). Looking at the limitations of each claim as an ordered combination in conjunction with the claims from which they depend (that is, as a whole) adds nothing that is not already present when looking at the elements taken individually. There is no indication that the combination of elements improves the functioning of a computer, for example, or improves any other technology. There is no indication that the combination of elements permits automation of specific tasks that previously could not be automated. There is no indication that the combination of elements includes a particular solution to a computer-based problem or a particular way to achieve a desired computer-based outcome. Rather, the collective functions of the claimed invention merely provide conventional computer implementation, i.e., the computer is simply a tool to perform the process.
Claim Rejections - 35 USC § 102
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 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.
Claims 1-7, 9-16, 18, and 20-22 are rejected under 35 U.S.C. 102(a)(1) as being anticipated by US 20190094979 A1 (Hall et al.).
Regarding claim 1, Hall teaches an operation apparatus comprising:
a plurality of sensors configured to be worn on a wrist and to output a sensor signal based on a displacement of a body surface of the wrist ([0017] “the device 105 is a wrist-worn wearable device that includes a sensor array 110”; [0018] “The sensor array 110 includes one or more sensors to observe the user. In an example, the sensor array 110 includes an accelerometer. In an example, the sensor array 110 includes a gyroscope”);
a range setting portion configured to set an operation learning time range that includes a time of a feature point of the sensor signal of the plurality of sensors ([0022] “the components of the second sensor composition include at least one of an average, maximum, minimum, standard deviation, or absolute value average values for one or more of the x, y, or z axes of the gyroscope. In an example, these values are calculated over a predetermined time window. In an example, the time window is half a second long. In an example, the time window begins after a pose is detected (e.g., by the filter 125).”); and
an arithmetic portion configured to learn an operation based on the sensor signal of the plurality of sensors in the operation learning time range ([0029] “using a learning technique (e.g., the clustering) involves the ease with which a user may train a new gesture”; [0038-0039] “depending on the number of features selected for each axis, there may between nine and twenty one features analyzed for the motion classification.” … “If a pose is detected, for a short duration of time (e.g., about 0.5 seconds) after the sensor starts moving again, machine learning features are computed from the gyroscope (e.g., operations 425)”),
wherein the arithmetic portion is configured to obtain a normative signal based on a plurality of different conditions from the sensor signal and further configured to identify, based on the normative signal, the operation as relating to at least one finger of a hand extending from the wrist on which the plurality of sensors are worn ([0010]; [0033] “FIGS. 2A-2C illustrate an example of motion for a gesture, according to an embodiment. As illustrated, a single gesture, as measured from the device 205, is finally determined using the pose-stop-gesture technique described above”; Figs. 2A-2C depicts a gesture of a pointing finger on a hand extending from the wrist wearing the sensor.; [0016-0017] The poses and gestures determined by the system are based on conditions captured by a sensor array).
Regarding claim 2, Hall teaches the operation apparatus according to claim 1, further comprising:
an index value calculator configured to calculate a range setting index, by using a magnitude of the sensor signal of the plurality of sensors ([0036] “whether the sensor is in a pose is measured by taking the average value of recent accelerometer reading on the x, y, and z axes and classifying the reading using a clustering algorithm”),
wherein the range setting portion is further configured to set the operation learning time range, with a feature point of the range setting index, as the feature point of the sensor signal ([0022] “components of the second sensor composition include at least one of an average, maximum, minimum, standard deviation, or absolute value average values for one or more of the x, y, or z axes of the gyroscope. In an example, these values are calculated over a predetermined time window. In an example, the time window is half a second long. In an example, the time window begins after a pose is detected (e.g., by the filter 125).”).
Regarding claim 3, Hall teaches the operation apparatus according to claim 2, wherein the index value calculator is further configured to calculate the range setting index as a total value of the magnitude of the sensor signal of the plurality of sensors ([0022]; [0064] “the accumulator includes: a buffer to store an acceleration average; and a calculator to: accept an additional accelerometer sample; and update the acceleration average in the buffer with the additional accelerometer sample.”).
Regarding claim 4, Hall teaches the operation apparatus according to claim 2, wherein the range setting portion is further configured to detect the feature point from time characteristics of the range setting index ([0020] “To perform the average, the calculator may sum samples received over a period of time and divide by the number of samples. Thus, the calculator may store a count of the number of samples and a running total of the sum as well as a timing metric.”).
Regarding claim 5, Hall teaches the operation apparatus according to claim 4, wherein the range setting portion is further configured to set the feature point as a detected peak value of the range setting index ([0020] “calculations that may be stored as part of the sensor composition include a maximum value”; [0022]).
Regarding claim 6, Hall teaches the operation apparatus according to claim 2, wherein the range setting portion is further configured to set the operation learning time range as a predetermined time range that includes the time of the feature point ([0022] “these values are calculated over a predetermined time window. In an example, the time window is half a second long. In an example, the time window begins after a pose is detected (e.g., by the filter 125).”).
Regarding claim 7, Hall teaches the operation apparatus according to claim 6, wherein the range setting portion is further configured to set the predetermined time range including the time of the feature point, by spread of the time characteristics of the range setting index ([0020] “the calculator may sum samples received over a period of time and divide by the number of samples. Thus, the calculator may store a count of the number of samples and a running total of the sum as well as a timing metric.”; [[0022-0023] “a timer (e.g., defining sample periods)”).
Regarding claim 9, Hall teaches an operation apparatus comprising:
a plurality of sensors configured to be worn on a wrist and to output a sensor signal based on a displacement of a body surface of the wrist ([0017] “the device 105 is a wrist-worn wearable device that includes a sensor array 110”; [0018] “The sensor array 110 includes one or more sensors to observe the user. In an example, the sensor array 110 includes an accelerometer. In an example, the sensor array 110 includes a gyroscope”);
a range setting portion configured to set an operation estimating time range that includes time of a feature point of the sensor signal of the plurality of sensors ([0020] “the calculator may instead employ a running average calculation or estimation”; [0022] “the components of the second sensor composition include at least one of an average, maximum, minimum, standard deviation, or absolute value average values for one or more of the x, y, or z axes of the gyroscope. In an example, these values are calculated over a predetermined time window. In an example, the time window is half a second long. In an example, the time window begins after a pose is detected (e.g., by the filter 125).”); and
an arithmetic portion configured to estimate an operation based on the sensor signal of the plurality of sensors in the operation estimating time range ([0029] “using a learning technique (e.g., the clustering) involves the ease with which a user may train a new gesture”; [0038-0039] “depending on the number of features selected for each axis, there may between nine and twenty one features analyzed for the motion classification.” … “If a pose is detected, for a short duration of time (e.g., about 0.5 seconds) after the sensor starts moving again, machine learning features are computed from the gyroscope (e.g., operations 425)”),
wherein the arithmetic portion is configured to obtain a normative signal based on a plurality of different conditions from the sensor signal and further configured to identify, based on the normative signal, the operation as relating to at least one finger of a hand extending from the wrist on which the plurality of sensors are worn ([0010]; [0033] “FIGS. 2A-2C illustrate an example of motion for a gesture, according to an embodiment. As illustrated, a single gesture, as measured from the device 205, is finally determined using the pose-stop-gesture technique described above”; Figs. 2A-2C depicts a gesture of a pointing finger on a hand extending from the wrist wearing the sensor.; [0016-0017] The poses and gestures determined by the system are based on conditions captured by a sensor array).
Regarding claim 10, Hall teaches an operation apparatus comprising:
a plurality of sensors configured to be worn on a wrist and to output a sensor signal based on a displacement of a body surface of the wrist ([0017] “the device 105 is a wrist-worn wearable device that includes a sensor array 110”; [0018] “The sensor array 110 includes one or more sensors to observe the user. In an example, the sensor array 110 includes an accelerometer. In an example, the sensor array 110 includes a gyroscope”);
a total activity level calculator configured to calculate a total activity level obtained from a total of intensity that is calculated from an amplitude of each sensor signal of the plurality of sensors ([0015] “motion data may be captured, the motion data both indicating an orientation of an object (e.g., a hand) and movement (e.g., whether or not the hand is stationary”; [0020] “The accumulator 115 or the calculator may employ this same technique to create a portion of a sensor composition from accelerometer data as well. Other calculations that may be stored as part of the sensor composition include a maximum value, a minimum value, a median, a standard deviation, average of absolute values, or other metrics that characterize the sensor data.”; [0022]; [0038] “If a pose is detected, for a short duration of time (e.g., about 0.5 seconds) after the sensor starts moving again, machine learning features are computed from the gyroscope (e.g., operations 425) for example. In an example, a small number of features (e.g., between three and seven) are computed along the x, y, and z gyroscope axes. Example features may include maximum speed, minimum speed, absolute sum (e.g., sum of absolute values), among others.”);
a range setting portion configured to set a time window for operation estimation ([0022] “the components of the second sensor composition include at least one of an average, maximum, minimum, standard deviation, or absolute value average values for one or more of the x, y, or z axes of the gyroscope. In an example, these values are calculated over a predetermined time window. In an example, the time window is half a second long. In an example, the time window begins after a pose is detected (e.g., by the filter 125).”); and
an arithmetic portion configured to estimate an operation based on the total activity level in the time window and the sensor signal ([0020] “the calculator may instead employ a running average calculation or estimation”; [0029] “using a learning technique (e.g., the clustering) involves the ease with which a user may train a new gesture”; [0038-0039] “depending on the number of features selected for each axis, there may between nine and twenty one features analyzed for the motion classification.”; “If a pose is detected, for a short duration of time (e.g., about 0.5 seconds) after the sensor starts moving again, machine learning features are computed from the gyroscope (e.g., operations 425)”).
Regarding claim 11, Hall teaches the operation apparatus according to claim 10, wherein the arithmetic portion is further configured to estimate the operation based on a magnitude of the total activity level in a plurality of time periods in the time window and an identification result of the operation by the sensor signal ([0015] “If the hand is stationary, the orientation data may be used to determine a pose among several poses. After the pose is determined, the motion data may be cleared and additional motion data captured. The Additional motion data may be combined with the pose determination to ultimately determine a user gesture.”; [0022]; [0064] “the accumulator includes: a buffer to store an acceleration average; and a calculator to: accept an additional accelerometer sample; and update the acceleration average in the buffer with the additional accelerometer sample.”).
Regarding claim 12, Hall teaches the operation apparatus according to claim 11, wherein the arithmetic portion is further configured to determine the identification result as the operation in the time window when the total activity level for all the time periods in the time window is equal to or greater than a threshold value for action detection and all the time periods have a same identification result ([0036] “whether the sensor is stationary is determined by measuring the average recent angular velocity and comparing with a threshold (e.g., if the average is below the threshold the device is stationary and moving otherwise).”; [0039] “If the features are measured to be sufficiently similar to a pre-learned canonical set of gesture parameters, the motion is classified as the corresponding gesture”; [0045] “comparing the running average against a threshold—the method being stationary if the running average is below the threshold and not stationary otherwise.”).
Regarding claim 13, Hall teaches the operation apparatus according to claim 11, wherein the arithmetic portion is further configured to retain the identification result in a first time window in the plurality
of consecutive time windows and to discard the identification result in other time windows when the same identification result of the operation is determined in a plurality of consecutive time windows ([0019] “When the filter 125 finds a pose, the accumulator 110 clears its values to create the second sensor composition for the classifier 135. In this way, hardware of the accumulator 115 (e.g., memory) is reduced, saving costs in both manufacture and power consumption.”).
Regarding claim 14, Hall teaches the operation apparatus according to claim 13, wherein the arithmetic portion, in a retention time period of the identification result in the plurality of time windows, is further configured to keep the identification result in a last time window and to discard the identification result in other time windows when the same identification result of the operation is determined in a plurality of inconsecutive time windows ([0023] “the accumulator 115 produces the same data for both the first sensor composition and the second sensor composition, clearing the data after a signal from the filter 125, a timer (e.g., defining sample periods), or other triggering event.”).
Regarding claim 15, Hall teaches the operation apparatus according to claim 10, wherein the arithmetic portion includes:
a plurality of identification devices that are each configured to identify an operation on different conditions to each sensor signal of the plurality of sensors ([0045] “accelerometer samples of the first sensor composition are used to identify that the device is stationary in the pose status”; [0046] “a second representation of the sensor array may be collected into a second sensor composition. In an example, the second sensor composition is derived entirely from gyroscope samples”); and
a determination portion configured to determine the operation based on a result identified by the plurality of identification devices ([0015] “If the hand is stationary, the orientation data may be used to determine a pose among several poses. After the pose is determined, the motion data may be cleared and additional motion data captured. The Additional motion data may be combined with the pose determination to ultimately determine a user gesture.”; [0016] “specific pose serves as a trigger and a following motion readings are used to identify the gesture.”).
Regarding claim 16, Hall teaches the operation apparatus according to claim 15, wherein the plurality of identification devices are configured identify the operation based on a relationship between previously learned operation content and the sensor signal of the plurality of sensors ([0039] “If the features are measured to be sufficiently similar to a pre-learned canonical set of gesture parameters, the motion is classified as the corresponding gesture (e.g., illustrated gestures G1-GM), if not, the motion is rejected as not being a gesture. This prevents false positives even after the gesture classifier is triggered. That is, each pose has a different set of machine learned gestures associated with them”).
Regarding claim 18, Hall teaches the operation apparatus according to claim 10, wherein the plurality of sensors are configured to output the sensor signal based on the displacement of the body surface of the wrist that occurs by a motion of at least one of a hand and a finger ([0015] “For example, motion data may be captured, the motion data both indicating an orientation of an object (e.g., a hand) and movement (e.g., whether or not the hand is stationary)”).
Regarding claim 20, Hall teaches the operation apparatus according to claim 10, further comprising a display configured to display an estimation result of the operation ([0047] “The results of the fit measurement, (e.g., selecting a specific gesture) is provided to a gesture consumer.”; [0049] ‘In an example, the machine 600 may act as a peer machine in peer-to-peer (P2P) (or other distributed) network environment. The machine 600 may be a personal computer (PC), a tablet PC, a set-top box (STB), a personal digital assistant (PDA), a mobile telephone, a web appliance, a network router, switch or bridge, or any machine capable of executing instructions (sequential or otherwise) that specify actions to be taken by that machine”; [0051]).
Regarding claim 21, Hall teaches the operation apparatus according to claim 10, further comprising an application execution portion configured to execute an application based on the estimation result of the operation ([0040] “The training may be performed using an app written to a smartphone, tablet, or other device with basic connectivity to the device.”; [0047] “([0047] “The results of the fit measurement, (e.g., selecting a specific gesture) is provided to a gesture consumer.”).
Regarding claim 22, Hall teaches the operation apparatus according to claim 10, further comprising a communication portion configured to send the estimation result of the operation to an external operation target device ([0051] “The machine 600 may include an output controller 628, such as a serial (e.g., universal serial bus (USB), parallel, or other wired or wireless (e.g., infrared (IR), near field communication (NFC), etc.) connection to communicate or control one or more peripheral devices (e.g., a printer, card reader, etc.).”).
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 8 is rejected under 35 U.S.C. 103 as being unpatentable over US 20190094979 A1 (Hall et al.). in view of US 20180099182 A1 (Miettinen et al.).
Regarding claim 8, Hall teaches the operation apparatus according to claim 2, wherein the range setting portion is configured to:
perform a fitting on the time characteristics of the range setting index ([0027] “The pattern is arranged to fit the second sensor composition to a model from the model library 140.”; [0047] “The results of the fit measurement, (e.g., selecting a specific gesture) is provided to a gesture consumer.”),
detect the feature point ([0047] “, the model is a collection of cluster points, and wherein measuring the fit of the second sensor composition to the model includes comparing pieces of the second sensor composition to the cluster points”), and
set the operation learning time range ([0022] “the time window begins after a pose is detected (e.g., by the filter 125).”).
Hall does not explicitly teach a fitting based on a normal distribution.
However,
Miettinnen teaches a fitting based on a normal distribution ([0032] “the performance data is categorized and compared with the normal distribution of performances”).
It would have been obvious for one of ordinary skill in the art before the effective filing date of the invention to have modified the apparatus taught by Hall to including fitting to a normal distribution. One would have been motivated to make this modification because this enables the device to store activities as a new activity if the detected event is outside the normal range and is not a previously identified activity by the wristwatch, as suggested by Miettinen [0032].
Claim 17 is rejected under 35 U.S.C. 103 as being unpatentable over US 20190094979 A1 (Hall et al.). in view of US 20160091980 A1 (Baranski et al.).
Regarding claim 17, Hall teaches the operation apparatus according to claim 10.
Hall does not explicitly teach wherein the plurality of sensors include: a front side sensor group configured to be worn on a front side of the wrist; and a back side sensor group configured to be worn on a back side of the wrist.
However,
Baranski teaches wherein the plurality of sensors include:
a front side sensor group configured to be worn on a front side of the wrist (Fig. 8 electrodes 806; [0049] “Device 800 can include one or more myoelectric sensors or electrodes 806 and 816.); and
a back side sensor group configured to be worn on a back side of the wrist (Fig. 8 electrodes 816; [0049] “Device 800 can include one or more myoelectric sensors or electrodes 806 and 816.).
It would have been obvious for one of ordinary skill in the art before the effective filing date of the invention to have modified the apparatus taught by Hall to include sensors configured to be worn on the front and back of the wrist. One would have been motivated to make this modification because the sensors being positioned in locations around the tension, muscles, and bones allows the device to determine a corresponding motion or gesture of the user, as suggested by Baranski [0030, 0049].
Claim 19 is rejected under 35 U.S.C. 103 as being unpatentable over US 20190094979 A1 (Hall et al.) in view of US 20150269825 A1 (Tran, Bao).
Regarding claim 19, Hall teaches the operation apparatus according to claim 10.
Hall does not explicitly teach wherein the plurality of sensors are piezoelectric sensors having an electrode disposed on a piezoelectric film with flexibility.
However,
Tran teaches wherein the plurality of sensors are piezoelectric sensors having an electrode disposed on a piezoelectric film with flexibility ([0047]; [0241] “piezoelectric accelerometers designed to give qualitative assessment of limb movement”; [0224]; [0252] “a piezo film sensor element is placed on the wristwatch band”).
It would have been obvious for one of ordinary skill in the art before the effective filing date of the invention to have modified the apparatus taught by Hall to include piezoelectric sensors with an electrode. One would have been motivated to make this modification because including piezoelectric sensors and an electrode on a piezoelectric film allows the for sensing that is sensitive to low level mechanical movements, as suggested by Tran [0252].
Response to Arguments
Applicant's arguments filed January 2, 2026 have been fully considered. With respect to the 112(f) Claim Interpretations (See Page 7 of Applicant’s Response “Claim Interpretation”), Applicant states that claims are intended to be interpreted based on the structure in the specification, and therefore the claims will remain interpreted under 112(f) as described above.
With respect to the 101 Rejections in the Non-Final Office Action (See Page 7-11 of Applicant’s Response “Claim Rejections – 35 U.S.C. § 101”), Applicant argues that claims 1 and 9 are directed to a concrete wrist-worn operation apparatus. Applicant states that the amended limitation describing that the arithmetic portion is configured to obtain “a normative signal based on a plurality of different conditions from the sensor signal” and to identify an operation relating to at least one finger of the hand that extends from the wrist cannot be performed in the human mind. Applicant points to [0082] in the present specification for proof that the process cannot be performed mentally, and argues that claims 1 and 9 are not directed to a mental process. Additionally, Applicant argues that the wrist-based finger-operation sensing and input integrate the concept into practical application that improves a specific technical field, and points to [0155] of the present specification. Applicant argues that the claimed invention uses the characteristics of tendon-induced wrist-surface displacement to increase separability of finger-specific signatures. Applicant states that independent claims 1 and 9 recite a specific combination of claim limitations relating to multi-channel displacement signals, Gaussian time-window fitting around feature points, category-specific normative-signals learning, multi-category identification, and a collective determination of the particular finger which improves the system’s accuracy and reliability. Applicant also states that the particular combination of claimed elements materially improves the wearable system’s ability to identify finger operations.
With respect to the 102 Rejections in the Non-Final Office Action (See Page 11-12 of Applicant’s Response “Claim Rejections – 35 U.S.C. § 102”), Applicant argues that Hall fails to disclose or suggest the amended limitation to “obtain a normative signal based on a plurality of different conditions from the sensor signal and further configured to identify, based on the normative signal, the operation as relating to at least one finger of a hand”. Applicant also argues that Hall does not teach calculating a total activity based on individual amplitudes of the measurement signals.
With respect to the 102 Rejections in the Non-Final Office Action (See Page 11-12 of Applicant’s Response “Claim Rejections – 35 U.S.C. § 102”), Applicant argues that Miettinen, Baranski, and Tran fail to cure the deficiencies in Hall.
MPEP § 2111 discusses proper claim interpretation, including giving claims their broadest reasonable interpretation in light of the specification during examination. Under broadest reasonable interpretation (BRI), the words of a claim must be given their plain meaning unless such meaning is inconsistent with the specification, and it is improper to import claim limitations from the specification into the claim. The requirements for anticipation are discussed in MPEP § 2131.
Under BRI, the apparatus of claims 1 and 9 is a device comprising wrist-worn sensors. The sensors are not specified in the claim, and wrist-worn sensors are generic as described above by MacDonald. Applicant’s arguments pointing to [0082] and [0155] in the specification cannot be imported into the claim interpretation, and therefore, Applicant’s arguments regarding a practical application being claimed are not persuasive. The amended claim limitation to “identify, based on the normative signal, the operation as relating to at least one finger of a hand extending from the wrist on which the plurality of sensors are worn” is not a practical application of the operation apparatus, as the limitation may be interpreted under BRI to mean that a signal is obtained through mere data gathering to identify that the operation is related to at least one finger of a hand extending form the wrist on which generic sensors are worn. The term “related to” can be interpreted as any type of relationship between the operation and the finger. Since the at least one finger is described as being located on a hand on the wrist, an operation detected by the sensor is inherently related to a finger on a hand extending from the wrist by means of the fingers’ physical connection to the wrist. Therefore, the step to “identify” in the claims could be performed by the human mind given data from the generic sensors and not implemented into any type of application (e.g. what is the identification of the finger used to do?). The claim does not make it clear how the identification is determined, other than that it is “based on” the signals from the generic sensors. Additionally, the “normative signal” is not defined by the claim and can be interpreted to be any signal based on any conditions from the sensor. Therefore, as written, claims 1-9 are directed to performing a mental process without a clear practical application using generic computer components and sensors under BRI.
There are new grounds of claim rejections that were necessitated by the claim amendments.
The amended elements of claims 1, 9, and 10 are taught by Hall, as described in the 102 rejections above. The limitations of claims 1 and 9 to identify the operation as relating to at least one finger is taught by Hall in at least [0033] and Figs. 2A-2C which depict finger pointing gestures being identifies based on signals from the wrist-worn sensor. Therefore, Hall reads on the amended limitations of claims 1 and 9 under BRI. The limitations of claim 10 to calculate a total activity level obtained from a total intensity that is calculated from an amplitude of each sensor signal is taught in at least [0020-0022] and [0038], which describe calculating maximum values based on the movement and speed of the wrist-worn sensor. Under BRI, the total activity level and total of intensity can be any measure of activity or intensity of movement of the user of the wrist-worn device. Therefore, Hall teaches the limitations of claim 10 under BRI.
Claims 2-8 and 11-22 are rejected because the rejection of claims 1, 9, and 10 are proper and the prior art teaches or suggests all the features of these claims for the reasons described in the 102 and 103 Rejections.
Conclusion
THIS ACTION IS MADE FINAL. Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
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/EVELYN GRACE PARK/Examiner, Art Unit 3791
/TSE W CHEN/Supervisory Patent Examiner, Art Unit 3791
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