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 .
Election/Restrictions
Applicant's election with traverse of Claims 1-30 in the reply filed on 09/29/2025 is acknowledged. The traversal is on the grounds that “applicant respectfully submits that the search and examination of all currently pending claims would not pose an undue burden on the Examiner. MPEP §803 states that ‘[I]f the search and examination of an entire application can be made without serious burden, the examiner must examine it on the merits, even though it includes claims to independent or distinct inventions.’ In view of the above, applicant respectfully requests examination of all currently pending claims.” This is not found persuasive because each group of claims contains a different scope. As mentioned in the previous office action:
Group I: Claims 1-30, drawn to an apparatus comprised of a plurality of sensors to monitor musculoskeletal loading on a back segment of the user;
Group II: Claims 31-47, drawn to a method comprised of a plurality of sensors which is temporally and/or spatially synchronized to each other to monitor musculoskeletal loading on a back segment of the user;
Group III: Claim 48, drawn to a non-transitory computer-readable medium storing computer to operate a wearable device for monitoring musculoskeletal loading on a back segment of a user.
The requirement is still deemed proper and is therefore made FINAL.
Claim Rejections - 35 USC § 112
Claims 6, 8, 15, 22, and 23 are rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention.
In Claim 6, the claim limitation “the lumbar extension moment” renders the claim indefinite because the limitation is unclear. It is unclear whether the lumbar extension moment is the same as lumbar movement or they are two different limitations. For purposes of examination, the claim limitation is interpreted as the lumbar movement.
In Claim 8, the claim limitation “the user handles” renders the claim indefinite because the limitation lacks proper antecedent basis. For purposes of examination, the indefinite limitation interpreted as “a user handles.”
In Claim 15, the claim limitation “lab-based sensors” renders the claim indefinite because the limitation is unclear. It is unclear the difference between lab-based sensors and plurality of sensors. For purposes of examination, the claim limitation is interpreted as plurality of sensors.
In Claim 22, the claim limitation “additional sensors” renders the claim indefinite because the limitation is unclear. It is unclear the difference between additional sensors and plurality of sensors. For purposes of examination, the claim limitation is interpreted as plurality of sensors.
In Claim 23, the claim limitation “load metrics” renders the claim indefinite because the limitation is unclear. It is unclear what the scope is for “load metrics.” What elements are included and excluded from “load metrics?” For purposes of examination, “load metric” is interpreted as the signals measured from the plurality of sensors.
In Claim 25, the claim limitation “the moment from exoskeleton” renders the claim indefinite because the limitation lacks proper antecedent basis. For purposes of examination, the indefinite limitation interpreted as “a moment from exoskeleton.”
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 1-30 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. Each of Claims 1-20 has been analyzed to determine whether it is directed to any judicial exceptions.
Step 2A, Prong 1
Each of Claims 1-20 recites at least one step or instruction for monitoring musculoskeletal loading on a back segment of the user, which is grouped as a mental process under the 2019 PEG or a certain method of organizing human activity under the 2019 PEG. Accordingly, each of Claims 1-20 recites an abstract idea.
Specifically, Claim 1 recite:
Claim 1 | “A wearable device operably worn by a user for monitoring musculoskeletal loading on a back segment of the user, comprising: a plurality of sensors, each sensor operably attached at a predetermined location of the user and configured to detect information about a biomechanical activity of a musculoskeletal system (Observation), wherein the plurality of sensors comprises at least one motion/orientation sensor; and a processing unit in communication with the plurality of sensors and configured to process the detected information (Observation) by the plurality of sensors to estimate the musculoskeletal loading and/or damage and/or injury risk (Evaluation/Opinion), and communicate the estimated musculoskeletal loading and/or damage and/or injury risk to the user and/or a party of interest (Judgement).”
Regarding the dependent claims, the following dependent claims are directed to steps that are also abstract or organizing human activity:
Claims 8, 25, 27, and 28 include steps that are also abstract as a mental process through additional data gathering or analysis.
Claims 2, 3, 15, 20, 24, and 26 contain additional elements.
Claims 4-7, 9-14, 16-19, 21-23, 29, and 30 contains additional limitations to define the characteristics of said additional elements (i.e. plurality of sensors, processing unit, biofeedback unit, state machine) and other limitations within the claims (i.e. musculoskeletal system, musculoskeletal loading, separate system, statistical modeling, reference data, user input, information, and damage).
Although the dependent claims are further limiting, they do not recite significantly more than the abstract idea. A narrowing idea is still an abstract idea and an abstract idea with additional well-known equipment/functions are not significantly more than the abstract idea.
Accordingly, as indicated above, each of the above-identified claims recites an abstract idea.
Step 2A, Prong 2
Regarding Claim 1 (and their respective dependent Claims 2-30) meets Step 2A, Prong 2 because the above-identified abstract idea in each of independent claims are not integrated into a practical application. The above-identified abstract ideas do not improve the following: function of a particular machine, manufacture or other technology; treatment or prophylaxis for a disease or medical condition; or transforming or reducing of a particular article to a different state or thing (MPEP 2106.04(d)).
Step 2B
Lastly, the claims as a whole are analyzed to determine whether any elements, or in combination, to ensure that they amount to significantly more than the judicial exception itself. However, these claims do not appear to recite additional elements that amount to significantly more than the judicial exception.
The recited additional elements, more specifically plurality of sensors, motion/orientation sensor, pressure-sensing insole, an inertial measurement unit (IMU), wearable device, exoskeleton, exosuit, and smart clothing are not significantly more because US Reference US 20210236020 A1 provides evidence within Paragraphs 0143, 0201, and 0249 that they are well-known, routine, and conventional.
The above-identified additional elements, more specifically the processing unit, computer, a smartphone, a smartwatch, a tablet, cloud storage system, computer readable memory, database, cloud-storage system, biofeedback unit, and state machine, are generically claimed computer components which enable the above-identified abstract idea(s) to be conducted by performing the basic functions of automating mental tasks. The courts have recognized such computer functions as well understood, routine, and conventional functions when claimed in a merely generic manner (e.g., at a high level of generality) or as insignificant extra-solution activity. See, Versata Dev. Group, Inc. v. SAP Am., Inc. , 793 F.3d 1306, 1334, 115 USPQ2d 1681, 1701 (Fed. Cir. 2015); and OIP Techs., 788 F.3d at 1363, 115 USPQ2d at 1092-93.
Taking the additional elements individually and in combination, the additional elements do not provide significantly more. When viewed individually or in combination, neither the general computer elements nor any other additional element adds meaningful limitations to the abstract idea because these additional elements represent insignificant extra-solution activity, and simply instruct the practitioner to implement the claimed functions with well-understood, routine and conventional activity specified at a high level of generality in a particular technological environment. When viewed as whole, the above-identified additional elements do not provide meaningful limitations to transform the abstract idea into a patent eligible application of the abstract idea such that the claims amount to significantly more than the abstract idea itself.
Therefore, none of the Claims 1-30 amounts to significantly more than the abstract idea itself. Accordingly, Claims 1-30 are not patent eligible and rejected under 35 U.S.C. 101.
Claim Rejections - 35 USC § 102
The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention.
(a)(2) the claimed invention was described in a patent issued under section 151, or in an application for patent published or deemed published under section 122(b), in which the patent or application, as the case may be, names another inventor and was effectively filed before the effective filing date of the claimed invention.
Claims 1-7, 10-12, 16, 17, 22-24, 26-29 are rejected under 35 U.S.C. 102(a)(1) and 102(a)(2) as being anticipated by Galiana Bujanda et al. (US 20210007874 A1).
Regarding Claim 1, Galiana Bujanda discloses a wearable device (wearable device – element 100) operably worn by a user for monitoring musculoskeletal loading on a back segment of the user (Abstract; Figures 2A-2C), comprising:
a plurality of sensors, each sensor operably attached at a predetermined location of the user and configured to detect information about a biomechanical activity of a musculoskeletal system (Sensors – element 230; Paragraph 0112), wherein the plurality of sensors comprises at least one motion/orientation sensor (IMU – element 230); and
a processing unit in communication with the plurality of sensors and configured to process the detected information by the plurality of sensors to estimate the musculoskeletal loading and/or damage and/or injury risk, and communicate the estimated musculoskeletal loading and/or damage and/or injury risk to the user and/or a party of interest (Paragraph 0018).
Regarding Claim 2, Galiana Bujanda discloses the wearable device of claim 1, wherein the plurality of sensors further comprises at least one pressure-sensing insole operably worn on at least one foot of the user (Paragraph 0104, Example wearable sensors 230 include one or a combination of an inertial measurement unit (IMU), a joint angle sensor 230, a force or pressure sensor 230, a torque sensor 230, a metabolic energy measurement device, a muscle activity measurement device (EMG), a ground reaction force sensor 230, a heart rate sensor 230, and an insole force or pressure sensor 230, amongst others. These sensors 230 may be integrated into apparel components).
Regarding Claim 3, Galiana Bujanda discloses the wearable device of claim 1, wherein the at least one motion/orientation sensor comprises an inertial measurement unit (IMU) operably attached to the trunk, pelvis, thighs, or shanks of the user (IMU – element 230; Paragraphs 0105, 0112; Figure 9).
Regarding Claim 4, Galiana Bujanda discloses the wearable device of claim 1, wherein the biomechanical activity of the musculoskeletal system comprises a segment orientation, a velocity or acceleration, and segmental load, wherein the segmental load comprises a location and/or magnitude of force or moment applied to the body segment (Paragraph 0112, motion sensors 230 may be used to estimate joint angles and dynamics (angular speed, acceleration) by positioning a motion sensor on each segment of the body, for instance an IMU on the back may be used to know torso angle when doing activities such as lifting, bending over, holding a static pose, sit-to-stand, etc. the relative angle between the torso and the thighs may be used to define whether a person is walking (cyclic motion of both legs) or squatting to lift an object (both legs bending), the relative angle between an IMU on the shoulder and an IMU on the forearm may be used to detect when a user is doing overhead tasks which may require further assistance by a shoulder assistive device, etc. an IMU on both sides of the knee joint may be used to estimate the knee angle, speed or acceleration to know when a person is in a crouched position that may require assistance by a knee assistive device).
Regarding Claim 5 Galiana Bujanda discloses the wearable device of claim 1, wherein the musculoskeletal loading comprises a lumbar moment, a lumbar spine (Paragraph 0112, motion sensors 230 may be used to estimate joint angles and dynamics (angular speed, acceleration) by positioning a motion sensor on each segment of the body, for instance an IMU on the back may be used to know torso angle when doing activities such as lifting, bending over, holding a static pose, sit-to-stand, etc. the relative angle between the torso and the thighs may be used to define whether a person is walking (cyclic motion of both legs) or squatting to lift an object (both legs bending), the relative angle between an IMU on the shoulder and an IMU on the forearm may be used to detect when a user is doing overhead tasks which may require further assistance by a shoulder assistive device, etc. an IMU on both sides of the knee joint may be used to estimate the knee angle, speed or acceleration to know when a person is in a crouched position that may require assistance by a knee assistive device) or disc force, and/or a muscle, muscle group, tendon or ligament force [Examiner’s note, the claim comprises multiple limitations; however, only one of the alternatives needs to be supported by the prior art.].
Regarding Claim 6, Galiana Bujanda discloses the wearable device of claim 5, wherein the lumbar extension moment is used as a target musculoskeletal loading metric for estimating cumulative tissue damage (Paragraph 0104, 0134-0135, 0187; [Examiner’s note, the data collected from the sensors are analyzed by the optimization algorithm. The results from the algorithm estimate cumulative tissue in order to minimize the muscle contraction/strain and tendon strain.]) and/or injury risk to the low back using a fatigue failure and/or finite element analysis [Examiner’s note, the claim comprises multiple limitations; however, only one of the alternatives needs to be supported by the prior art.].
Regarding Claim 7, Galiana Bujanda discloses the wearable device of claim 1, wherein the detected information by the plurality of sensors further includes information about the trunk or lumbar orientation/angles, or velocities, or accelerations, or frequency of lifting or bending movements (Paragraph 0112), which are estimated or tracked, and then combined with or used in conjunction with the musculoskeletal loading estimates to estimate damage or assess injury risk (Paragraph 0104, 0134-0135, 0187).
Regarding Claim 10, Galiana Bujanda discloses the wearable device of claim 8, wherein the separate system comprises a force-sensing crate handle or glove worn by the user that detects the force applied to each object of which the user handles (Figure 32; Paragraphs 0048, 0354).
Regarding Claim 11, Galiana Bujanda discloses the wearable device of claim 1, wherein the detected information by the plurality of sensors is processed by statistical modeling (Paragraph 0130, the onboard sensors 230 may be used for a classification algorithm (e.g. neural network, linear classifiers, nearest neighbor, decision trees, etc.) to detect which activity the motion falls into).
Regarding Claim 12, Galiana Bujanda discloses the wearable device of claim 11, wherein the statistical modeling comprises decision trees or neural networks (Paragraph 0130, the onboard sensors 230 may be used for a classification algorithm (e.g. neural network, linear classifiers, nearest neighbor, decision trees, etc.) to detect which activity the motion falls into), and/or other data-driven machine learning or sensor fusion algorithms, supervised model-based linear regression [Examiner’s note, the claim comprises multiple limitations; however, only one of the alternatives needs to be supported by the prior art.].
Regarding Claim 16, Galiana Bujanda discloses the wearable device of claim 1, wherein the processing unit is further configured to alert the user, via audio, visual or haptic feedback, when the musculoskeletal loading, damage, or injury risk is greater than a threshold that is predetermined or a threshold that is calibrated for a specific user (Paragraph 0258, 0273, 0475).
Regarding Claim 17, Galiana Bujanda discloses the wearable device of claim 16, wherein the processing unit is further configured to advise the user on when and how to adjust their movements, actions or physical activity type and duration so as to reduce injury risks (Paragraph 0475).
Regarding Claim 22, Galiana Bujanda discloses the wearable device of claim 1, wherein the information further comprises data acquired from additional sensors that monitor heart rate (Paragraph 0104), sleep patterns, heart rate variability, rest time between physical activity or other markers of tissue rest or remodeling, or physiological recovery [Examiner’s note, the claim comprises multiple limitations; however, only one of the alternatives needs to be supported by the prior art.].
Regarding Claim 23, Galiana Bujanda discloses wearable device of claim 1. As disclosed above, the detected information comprises: the musculoskeletal loading and/or damage and/or injury risk, and communicate the estimated musculoskeletal loading and/or damage and/or injury risk to the user and/or a party of interest; damage is an alternative limitation. Therefore, Galiana anticipates this claim because the claim language is further limiting an alternative not relied upon in the independent claim.
Regarding Claim 24, Galiana Bujanda discloses the wearable device of claim 1, wherein the plurality of sensors is combined with or integrated into an exoskeleton, exosuit, smart clothing, or other wearable assistance device (Figures 2A-2C; Paragraph 0134).
Regarding Claim 26, Galiana Bujanda discloses the wearable device of claim 24, wherein the musculoskeletal loading is used for control or evaluation of the exoskeleton, exosuit, smart clothing or other wearable assistance device (Paragraphs 0164).
Regarding Claim 27, Galiana Bujanda discloses the wearable device of claim 26, wherein a reinforcement learning algorithm incrementally learns optimal control of the exoskeleton, exosuit, smart clothing or other wearable assistive device from wearable sensor inputs based on real-time feedback from the user and previously observed motion trajectories (Figures 6, 8; Paragraphs 0135, 0223).
Regarding Claim 28, Galiana Bujanda discloses the wearable device of claim 1, wherein a state machine is used to identify specific activities, and then different algorithms are used to process information and to estimate the musculoskeletal loading and/or damage and/or injury risk depending on the current state (Paragraphs 0274-0278; [Examiner’s note, the controller utilizes the classification algorithm and optimization algorithm to mitigate risk of injury for the user]).
Regarding Claim 29, Galiana Bujanda discloses the wearable device of claim 1, wherein the estimates of the musculoskeletal loading and/or damage and/or injury risk are computed via real-time or near-real-time estimation algorithms (Paragraphs 0280, 0321-0322).
Claim Rejections - 35 USC § 103
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
Claims 9, 14, 15, 18-21, and 30 are rejected under 35 U.S.C. 103 as being unpatentable over Galiana Bujanda et al. (US 20210007874 A1) in view of Ong et al. (US 20220031194 A1).
Regarding Claim 9, Galiana Bujanda discloses the wearable device of claim 8. Galiana Bujanda discloses the controller to measure the weight, size, or location of each object of which the user handles, but does not explicitly disclose an inventory management system that tracks that data;
Ong teaches an inventory management system (Ong | Machine Learning Environment – element 404; Paragraphs 0078-0080; [Examiner’s note, the machine learning environment tracks data received from the tremor management device.]). One having an ordinary skill in the art the time the invention was filed would have found it obvious to modify the wearable device of Galiana Bujanda to incorporate the teachings of the machine learning environment of Ong because the machine learning environment analyzes the device data to anticipate tremors, automatically delivering relief before symptoms even begin (Ong | Paragraph 0077).
Regarding Claim 14, Galiana Bujanda discloses the wearable device of claim 1, wherein the processing unit is further configured to estimate the musculoskeletal loading (Galiana Bujanda | Paragraph 0018). However, Galiana Bujanda does not explicitly disclose reference data for calibrating or establishing a processing algorithm, wherein the reference data are either stored on data storage means in communication with the processing unit, or collected or inputted from a specific user;
Ong teaches reference data for calibrating or establishing a processing algorithm, wherein the reference data are either stored on data storage means in communication with the processing unit, or collected or inputted from a specific user (Ong | Paragraphs 0043, 0045; [Examiner’s note, the processing algorithm is the severity module. The severity module is calibrated by the data inputted by the user (i.e. food, beverages consumed, medication taken, activities performed, sleep estimates, and behavioral information) through a user interface.]).
One having an ordinary skill in the art the time the invention was filed would have found it obvious to modify the wearable device of Galiana Bujanda to incorporate the teachings of a severity module from Ong because it allows for a personalized modeling system to provide an accurate the prediction that is specific to the user (Ong | Paragraph 0045).
Regarding Claim 15, Galiana Bujanda in view of Ong teaches the wearable device of claim 14, wherein the reference data are obtained by lab-based sensors (Galiana Bujanda | Sensors – element 230). However, Galiana Bujanda is silent on the data storage means comprises a database, a cloud storage system, and/or a computer readable memory;
Ong teaches the data storage means comprises a database, a cloud storage system, (Ong | Paragraph 0128) and/or a computer readable memory [Examiner’s note, the claim comprises multiple limitations; however, only one of the alternatives needs to be supported by the prior art.]. One having an ordinary skill in the art the time the invention was filed would have found it obvious to modify the wearable device of Galiana Bujanda to incorporate the teachings of cloud storage from Ong because it streamlines data sharing between the user and their physician (Paragraph 0160, as part of the Cloud capability, journal data shall be shared and made viewable to the user and healthcare provider).
Regarding Claim 18, Galiana Bujanda discloses the wearable device of claim 1, wherein the processing unit is further configured to communicate inputting user inputs (Galiana Bujanda | Paragraph 0017, the controller is configured to receive input from the wearer for selecting a peak tensile force for assist different movements, and wherein the controller is configured to scale the impedance of or the force provided by the wearable device to have a maximum peak tensile force corresponding to the selected peak tensile force value), and outputting at least one of the estimated musculoskeletal loading (Galiana Bujanda | Paragraph 0018), alert and advice (Galiana Bujanda | Paragraph 0273), estimates of damage or damage accumulation, and/or probability of fracture or injury risk [Examiner’s note, the claim comprises multiple limitations; however, only one of the alternatives needs to be supported by the prior art.].
Galiana Bujanda discloses inputting data and outputting data, but does not explicitly disclose communicating output data to a computer, a smartphone, a smartwatch, a tablet or other user feedback or data acquisition device and storing said output data;
Ong teaches communicating to a computer, a smartphone, a smartwatch, (Ong | Paragraph 0151) a tablet or other user feedback or data acquisition device [Examiner’s note, the claim comprises multiple limitations; however, only one of the alternatives needs to be supported by the prior art.], and storing output data (Ong | Paragraph 0128).
One having an ordinary skill in the art the time the invention was filed would have found it obvious to modify the wearable device of Galiana Bujanda to incorporate the teachings of a communication device and storing output data from Ong because it allows for a collection of longitudinal data that can be view by the user and physician (Ong | Paragraph 0150-0151, 0158).
Regarding Claim 19, Galiana Bujanda discloses the wearable device of claim 1, further comprising the processing unit for outputting and/or displaying at least one of the estimated musculoskeletal loading (Galiana Bujanda | Paragraph 0018), alert and advice (Galiana Bujanda | Paragraph 0273), estimates of damage or damage accumulation, and/or probability of fracture or injury risk using audible, visual, tactile, haptic, thermal, electrical or other biofeedback means [Examiner’s note, the claim comprises multiple limitations; however, only one of the alternatives needs to be supported by the prior art.].
Galiana Bujanda discloses outputting data, but does not explicitly disclose a biofeedback unit and storing said output data;
Ong teaches a biofeedback unit (Ong | Output Device – element 720; Paragraph 0168, provide anticipatory tremor mitigation signals to modulate the tremor management hardware 11, or to warn a user via the output device 720, such as, e.g., by a means of display/sound/haptic feedback found on the device itself or user or caregiver's personal computing device e.g. phone, tablet etc. with the means to generate this sort of feedback) and storing output data (Ong | Paragraph 0128). One having an ordinary skill in the art the time the invention was filed would have found it obvious to modify the wearable device of Galiana Bujanda to incorporate the teachings of a user interface and storing output data from Ong because it allows for a collection of longitudinal data that can be view by the user and physician (Ong | Paragraph 0150-0151, 0158).
Regarding Claim 20, Galiana Bujanda in view of Ong teaches the wearable device of claim 19. Galiana Bujanda is silent in teaching the biofeedback unit comprises a user interface device for user inputs;
Ong teaches the biofeedback unit comprises a user interface device for user inputs (Figure 10B, 10D; Paragraph 0019). One having an ordinary skill in the art the time the invention was filed would have found it obvious to modify the wearable device of Galiana Bujanda to incorporate the teachings of a user interface from Ong because it allows for a collection of longitudinal data that can be view by the user and physician (Ong | Paragraph 0158).
Regarding Claim 21, Galiana Bujanda in view of Ong teaches the wearable device of claim 20. Galiana Bujanda is silent in teaching the user inputs comprise GPS position, altitude of the user, other personal health or demographic data, height, weight, body mass index, age, gender, diet, training schedule, subjective pain/fatigue, bone cross- sectional area, bone geometry, bone density, and/or bone composition;
Ong teaches the user inputs comprise GPS position, altitude of the user, other personal health or demographic data (Ong | Paragraphs 0042-0043, 0045), height, weight, body mass index, age, gender, diet, training schedule, subjective pain/fatigue, bone cross- sectional area, bone geometry, bone density, and/or bone composition [Examiner’s note, the claim comprises multiple limitations; however, only one of the alternatives needs to be supported by the prior art.].
One having an ordinary skill in the art the time the invention was filed would have found it obvious to modify the wearable device of Galiana Bujanda to incorporate the teachings of user inputs from Ong because it allows for a personalized modeling system to provide an accurate the prediction that is specific to the user (Ong | Paragraph 0045).
Regarding Claim 30, Galiana Bujanda discloses the wearable device of claim 1, wherein the estimated musculoskeletal loading and/or damage and/or injury risk is communicated to the user and/or a party of interest, either in real-time, near-real-time or at a later time (Paragraphs 0280, 0321-0322).
Galiana Bujanda does not explicitly disclose the estimated results are communicated via one or more wireless or wired communication interfaces;
---Ong teaches the estimated results are communicated via one or more wireless or wired communication interfaces (Ong | Paragraph 0180). One having an ordinary skill in the art the time the invention was filed would have found it obvious to the wearable device of Galiana Bujanda to incorporate the teachings of a communication device and storing output data from Ong because it allows for a collection of longitudinal data that can be view by the user and physician (Ong | Paragraph 0158).
Claim 13 is rejected under 35 U.S.C. 103 as being unpatentable over Galiana Bujanda et al. (US 20210007874 A1) in view of Diaz-Arias et al. (US 20220386942 A1).
Regarding Claim 13, Galiana Bujanda discloses the wearable device of claim 12, and statistical modeling. Galiana Bujanda does not explicitly disclose that statistical modeling comprises a gradient boosted decision tree algorithm;
Diaz-Arias teaches a gradient boosted decision tree algorithm (Diaz-Arias | Paragraph 0057). One having an ordinary skill in the art the time the invention was filed would have found it obvious to modify the wearable device of Galiana Bujanda to incorporate the teachings of a gradient boosted decision tree from Diaz-Arias because it improves real-time user intent detection and gait phase detection (Diaz-Arias | Paragraphs 0057-0058).
Allowable Subject Matter
Claims 8 and 25 are objected to as being dependent upon a rejected base claim, but would be allowable if rewritten in independent form including all of the limitations of the base claim and any intervening claims.
Double Patenting
The nonstatutory double patenting rejection is based on a judicially created doctrine grounded in public policy (a policy reflected in the statute) so as to prevent the unjustified or improper timewise extension of the “right to exclude” granted by a patent and to prevent possible harassment by multiple assignees. A nonstatutory double patenting rejection is appropriate where the conflicting claims are not identical, but at least one examined application claim is not patentably distinct from the reference claim(s) because the examined application claim is either anticipated by, or would have been obvious over, the reference claim(s). See, e.g., In re Berg, 140 F.3d 1428, 46 USPQ2d 1226 (Fed. Cir. 1998); In re Goodman, 11 F.3d 1046, 29 USPQ2d 2010 (Fed. Cir. 1993); In re Longi, 759 F.2d 887, 225 USPQ 645 (Fed. Cir. 1985); In re Van Ornum, 686 F.2d 937, 214 USPQ 761 (CCPA 1982); In re Vogel, 422 F.2d 438, 164 USPQ 619 (CCPA 1970); In re Thorington, 418 F.2d 528, 163 USPQ 644 (CCPA 1969).
A timely filed terminal disclaimer in compliance with 37 CFR 1.321(c) or 1.321(d) may be used to overcome an actual or provisional rejection based on nonstatutory double patenting provided the reference application or patent either is shown to be commonly owned with the examined application, or claims an invention made as a result of activities undertaken within the scope of a joint research agreement. See MPEP § 717.02 for applications subject to examination under the first inventor to file provisions of the AIA as explained in MPEP § 2159. See MPEP § 2146 et seq. for applications not subject to examination under the first inventor to file provisions of the AIA . A terminal disclaimer must be signed in compliance with 37 CFR 1.321(b).
The filing of a terminal disclaimer by itself is not a complete reply to a nonstatutory double patenting (NSDP) rejection. A complete reply requires that the terminal disclaimer be accompanied by a reply requesting reconsideration of the prior Office action. Even where the NSDP rejection is provisional the reply must be complete. See MPEP § 804, subsection I.B.1. For a reply to a non-final Office action, see 37 CFR 1.111(a). For a reply to final Office action, see 37 CFR 1.113(c). A request for reconsideration while not provided for in 37 CFR 1.113(c) may be filed after final for consideration. See MPEP §§ 706.07(e) and 714.13.
The USPTO Internet website contains terminal disclaimer forms which may be used. Please visit www.uspto.gov/patent/patents-forms. The actual filing date of the application in which the form is filed determines what form (e.g., PTO/SB/25, PTO/SB/26, PTO/AIA /25, or PTO/AIA /26) should be used. A web-based eTerminal Disclaimer may be filled out completely online using web-screens. An eTerminal Disclaimer that meets all requirements is auto-processed and approved immediately upon submission. For more information about eTerminal Disclaimers, refer to www.uspto.gov/patents/apply/applying-online/eterminal-disclaimer.
Claims 1, 3, 11, 12, and 15-22 are rejected on the ground of nonstatutory double patenting as being unpatentable over claims 1, 2, 4, 8, 9, 12-19, and 23 of U.S. Patent No. 12/011,257 (reference application) in view of Galiana Bujanda et al. (US 20210007874 A1).
Although the claims at issue are not identical, they are not patentably distinct from each other because both inventions claim a wearable device worn by a user for monitoring musculoskeletal loading. Examiner’s note, all the bolded text are what is identical between the instant application and reference application.
Clm
Instant Application 18/017,877
[US 20230270352 A1]
Clm
Reference Application
[US 12011257 B2]
1
A wearable device operably worn by a user for monitoring musculoskeletal loading on a back segment of the user, comprising:
a plurality of sensors, each sensor operably attached at a predetermined location of the user and configured to detect information about a biomechanical activity of a musculoskeletal system, wherein the plurality of sensors comprises at least one motion/orientation sensor; and
a processing unit in communication with the plurality of sensors and configured to process the detected information by the plurality of sensors to estimate the musculoskeletal loading and/or damage and/or injury risk, and communicate the estimated musculoskeletal loading and/or damage and/or injury risk to the user and/or a party of interest.
1
A wearable device operably worn by a user for monitoring musculoskeletal loading on a body structure of the user, comprising:
a plurality of sensors, each sensor operably worn by the user at a predetermined location and configured to detect information about a biomechanical activity of musculoskeletal tissues, a limb segment orientation, and/or a loading magnitude or location thereon; and
a processing unit in communication with the plurality of sensors and configured to process the detected information by the plurality of sensors to estimate the musculoskeletal loading and/or microdamage, and communicate the estimated musculoskeletal loading to the user and/or a party of interest.
1
2
The wearable device of claim 1, wherein the plurality of sensors comprises one or more motion/orientation sensors, and one or more force/muscle sensors.
3
The wearable device of claim 1, wherein the at least one motion/orientation sensor comprises an inertial measurement unit (IMU) operably attached to the trunk, pelvis, thighs, or shanks of the user.
4
The wearable device of claim 2, wherein the one or more motion/orientation sensors comprise inertial measurement units (IMUs), flex sensors, goniometers, or a combination thereof
11
The wearable device of claim 1, wherein the detected information by the plurality of sensors is processed by statistical modeling
8
The wearable device of claim 1, wherein the detected information by the plurality of sensors is processed by statistical modeling combined with biomechanical algorithms
12
The wearable device of claim 11, wherein the statistical modeling comprises supervised model-based linear regression, decision trees or neural networks, and/or other data-driven machine learning or sensor fusion algorithms
9
The wearable device of claim 8, wherein the statistical modeling comprises linear regression and/or other sensor fusion algorithms
14
The wearable device of claim 1, wherein the processing unit is further configured to estimate the musculoskeletal loading using reference data for calibrating or establishing a processing algorithm, wherein the reference data are either stored on data storage means in communication with the processing unit, or collected or inputted from a specific user
12
The wearable device of claim 1, wherein the processing unit is further configured to estimate musculoskeletal loading using reference data that is either stored on data storage means in communication with the processing unit or reference data that has been collected or inputted from the specific user and used to calibrate or establish the processing algorithm
15
The wearable device of claim 14, wherein the reference data are obtained by lab-based sensors, and the data storage means comprises a database, a cloud storage system, and/or a computer readable memory
13
The wearable device of claim 12, wherein the reference data are obtained by lab-based sensors, and the data storage means comprises a database, a cloud storage system, and/or a computer readable memory
16
The wearable device of claim 1, wherein the processing unit is further configured to alert the user, via audio, visual or haptic feedback, when the musculoskeletal loading, damage, or injury risk is greater than a threshold that is predetermined or a threshold that is calibrated for a specific user.
14
The wearable device of claim 12, wherein the processing unit is further configured to alert the user when the musculoskeletal loading is greater than a threshold that has been predetermined or a threshold that has been calibrated for the specific user.
17
The wearable device of claim 16, wherein the processing unit is further configured to advise the user on when and how to adjust their movements, actions or physical activity type and duration so as to reduce injury risks
15
The wearable device of claim 14, wherein the processing unit is further configured to advise the user on when and how to adjust their movement, actions or physical activity type and duration so as to reduce injury risks.
18
The wearable device of claim 1, wherein the processing unit is further configured to communicate to a computer, a smartphone, a smartwatch, a tablet or other user feedback or data acquisition device for inputting user inputs, and outputting at least one of the estimated musculoskeletal loading, alert and advice, estimates of damage or damage accumulation, and/or probability of fracture or injury risk, and storing the estimated musculoskeletal loading, alert and advice, estimates of damage or damage accumulation, and/or probability of fracture or injury risk
16
The wearable device of claim 15, wherein the processing unit is further configured to communicate to a computer, a smartphone, a smartwatch, a tablet or other user feedback or data acquisition device for outputting at least one of the following: estimated musculoskeletal loading, alert and advice, estimates of microdamage or microdamage accumulation, and/or probability of fracture, and storing the estimated musculoskeletal loading, alert and advice, estimates of microdamage or microdamage accumulation, and/or probability of fracture, and inputting user inputs
19
The wearable device of claim 1, further comprising a biofeedback unit in communication with the processing unit for outputting and/or displaying at least one of the estimated musculoskeletal loading, alert and advice, estimates of damage or damage accumulation, and/or probability of fracture or injury risk using audible, visual, tactile, haptic, thermal, electrical or other biofeedback means, and storing the estimated musculoskeletal loading, alert and advice, estimates of damage accumulation, and/or probability of fracture or injury risk
17
The wearable device of claim 15, further comprising a biofeedback unit in communication with the processing unit for outputting or displaying at least one of the estimated musculoskeletal loading, alert and advice, estimates of microdamage or microdamage accumulation, and/or probability of fracture using audible, visual, tactile, haptic, thermal, electrical or other biofeedback means, and storing the estimated musculoskeletal loading, alert and advice, estimates of damage accumulation, and/or probability of fracture
20
The wearable device of claim 19, wherein the biofeedback unit comprises a user interface device for user inputs
18
The wearable device of claim 17, wherein the biofeedback unit comprises a user interface device for user inputs
21
The wearable device of claim 20, wherein the user inputs comprise height, weight, body mass index, age, gender, diet, training schedule, subjective pain/fatigue, bone cross- sectional area, bone geometry, bone density, bone composition, GPS position, altitude of the user and/or other personal health or demographic data.
19
The wearable device of claim 18, wherein the user inputs comprise height, weight, body mass index, age, gender, diet, training schedule, subjective pain/fatigue, bone cross- sectional area, bone geometry, bone density, bone composition, GPS position, altitude of the user and/or other personal health or demographic data.
22
The wearable device of claim 1, wherein the information further comprises data acquired from additional sensors that monitor sleep patterns, heart rate, heart rate variability, rest time between physical activity or other markers of tissue rest or remodeling, or physiological recovery
23
The wearable device of claim 23, wherein the bio-information further comprises data acquired from additional sensors that monitor sleep patterns, rest time between physical activity or other markers of tissue rest or remodeling
The reference application is silent in disclosing the wearable device on the back segment of the user; IMUs attached to the trunk, pelvis, thighs, or shanks of the user, and the alert being via audio, visual or haptic feedback;
Galiana Bujanda discloses a wearable device (wearable device – element 100) on a back segment of the user (Abstract; Figures 2A-2C); IMUs attached to the trunk, pelvis, thighs, or shanks of the user (IMU – element 230; Paragraphs 0105, 0112; Figure 9); alert the user, via audio, visual or haptic feedback (Paragraph 0273; [Examiner’s note, the claim comprises multiple limitations; however, only one of the alternatives needs to be supported by the prior art. The art from Galiana Bujanda teaches an alert being haptic feedback.]).
One having ordinary skill in the art the time the invention was filed would have found it obvious to modify the wearable device of the reference application to incorporate the teachings of the wearable device on the back segment of the user; IMUs attached to the trunk, pelvis, thighs, or shanks of the user, and the alert being via audio, visual or haptic feedback from Galiana Bujanda. Doing so would allow the wearable device to protect and provide an early detection against musculoskeletal injuries on the back segment of the user (Galiana Bujanda | Abstract; Paragraph 0273).
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to SRISTI DIVINA GOMES whose telephone number is (571)272-1356. The examiner can normally be reached Monday-Friday: 9AM to 5PM EST.
Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Robert Chen can be reached at 571-272-3672. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
Information regarding the status of published or unpublished applications may be obtained from Patent Center. Unpublished application information in Patent Center is available to registered users. To file and manage patent submissions in Patent Center, visit: https://patentcenter.uspto.gov. Visit https://www.uspto.gov/patents/apply/patent-center for more information about Patent Center and https://www.uspto.gov/patents/docx for information about filing in DOCX format. For additional questions, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000.
/SRISTI DIVINA GOMES/Examiner, Art Unit 3791
/DANIEL L CERIONI/Primary Examiner, Art Unit 3791
Prosecution Insights