DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Claim 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 limitation(s) uses a generic placeholder that is coupled with functional language without reciting sufficient structure to perform the recited function and the generic placeholder is not preceded by a structural modifier. Such claim limitation(s) is/are:
“user recognition unit” to “receive” and “extract” in Claim 1 (and its dependent claims)
The claim is interpreted according to [95] as a software portion of a program executed by a computer with “The method may be recorded on a computer-readable medium including program commands for performing various computer-implemented operations…can be executed by a computer…”) and [39] with “biofeedback-based bruxism alleviating system 100 may include a user recognition unit 110…” The “user recognition unit” is shown as a generic block element of “user recognition unit 110” in “biofeedback-based bruxism alleviating system 100” in Fig. 2.
“data collection unit” to “receive” in Claim 1 (and its dependent claims)
Looking to [15] “…data collection unit may include a first sensor that collects first electromyography data for a preset period of time” and [44] with a first and a second sensor, it is unclear if the data collection unit is lines of program code that are part of an overall program or a processor, or if is intended to be a physical section on board the wearable apparatus that “receives” the electromyography data as a cable, etc. The “data collection unit” is shown as a generic block element of “data collection unit 120” in “biofeedback-based bruxism alleviating system 100” in Fig. 2, which does not clarify if this element is intended to be hardware or software.
“bruxism diagnosis unit” to “diagnose” and “determine” in Claim 1 (and its dependent claims)
The claim is interpreted according to [95] as a software portion of a program executed by a computer with “The method may be recorded on a computer-readable medium including program commands for performing various computer-implemented operations…can be executed by a computer…”) and [39] with “biofeedback-based bruxism alleviating system 100 may include…a bruxism diagnosis unit 130…” The “data collection unit” is shown as a generic block element of “bruxism diagnosis unit 130” in Figure 4.
“biofeedback generation unit” to “apply a vibration” in Claim 1 (and its dependent claims)
It is unclear if the biofeedback generation unit is lines of program code that are part of an overall program, or if it is intended to be a physical section of the wearable apparatus with an attached vibration motor on the person’s body. There is no clear structure disclosed that performs the functions of applying the vibration stimulation to the skins of the user through the vibration motor provided on the wearable device. The “biofeedback generation unit” is shown as a generic block element of “biofeedback generation unit 140” in “biofeedback-based bruxism alleviating system 100” in Fig. 2, which does not clarify if this element is intended to be hardware or software.
“user monitoring unit” to “monitor” in Claim 1 (and its dependent claims)
The claim is interpreted according to [95] as a software portion of a program executed by a computer with “The method may be recorded on a computer-readable medium including program commands for performing various computer-implemented operations…can be executed by a computer…”) and [39] with “biofeedback-based bruxism alleviating system 100 may include… a user monitoring unit 150…” The “user monitoring unit” is shown as a generic block element of “user monitoring unit 150” in “biofeedback-based bruxism alleviating system 100” in Fig. 2.
“sleep state determination unit” to “determine” in Claim 2 (and its dependent claims)
The claim is interpreted according to [95] as a software portion of a program executed by a computer with “The method may be recorded on a computer-readable medium including program commands for performing various computer-implemented operations…can be executed by a computer…”) and [49] with “bruxism diagnosis unit 130 may include… a sleep state determination unit 131…” The “sleep state determination unit is shown as a generic block element of “sleep state determination unit 131” of “bruxism diagnosis unit 130” in Figure 4.
“bruxism occurrence detection unit” to “determine” in Claim 2 (and its dependent claims)
The claim is interpreted according to [95] as a software portion of a program executed by a computer with “The method may be recorded on a computer-readable medium including program commands for performing various computer-implemented operations…can be executed by a computer…”) and [49] with “bruxism diagnosis unit 130 may include… a bruxism occurrent detection unit 132…” The “bruxism occurrence detection unit” is shown as a generic block element of “bruxism occurrence detection unit 132” in “bruxism diagnosis unit 130” in Fig. 4.
“user stimulation providing unit” to “generate vibration stimulation” in Claim 3
Looking to Applicant’s specification at [65] and Fig. 6, It is unclear if the user stimulation providing unit is “if-then” program code as part of an overall program, or if is intended to be a vibrator element or physical element that is controlled by the “biofeedback generation unit 140” that allows for the stimulation level to be adjusted. There is no clear structure disclosed that performs the functions of generating the vibration stimulation. The “user stimulation providing unit” is shown as a generic block element of “user stimulation providing unit 141” in “biofeedback generation unit 140” in Fig. 6.
“user stimulation correction unit” to “correct the vibration stimulation” in Claim 3
Looking to Applicant’s specification at [65] and Fig. 6, It is unclear if the user stimulation correction unit is “if-then” program code as part of an overall program, or if is intended to be a physical switch, spacer, or knob that is controlled by the “biofeedback generation unit 140” that allows for the stimulation level to be adjusted. There is no clear structure disclosed that performs the functions of correcting the vibration stimulation. The “user stimulation correction unit” is shown as a generic block element of “user stimulation correction unit 142” in “biofeedback generation unit 140” in Fig. 6.
“user data generation unit” to “measure” in Claim 5
The claim is interpreted according to [181] with “the user monitoring unit may include a user data generation unit” and [95] as a software portion of a program executed by a computer with “The method may be recorded on a computer-readable medium including program commands for performing various computer-implemented operations…can be executed by a computer…”) and [39] with “the user monitoring unit 150 may include a user data generation unit 151…” The “user data generation unit” is shown as a generic block element of “user data generation unit 151” in “user data generation 150” in Fig.
“bruxism diagnosis learning unit” to “learn” in Claim 5
The claim is interpreted as a software module that includes a generic machine learning according to [84] “a bruxism diagnosis learning unit 152…learns…through a present artificial intelligence learning algorithm.” The “bruxism diagnosis learning unit” is not shown in a figure.
“user data transmission unit” to “transmit” in Claim 5
The “user data transmission unit” is generically described at [84] with “…a user data transmission unit 153 that transmits the daily user data generated by the user data generation unit 151 to the user terminal 20…” It is unclear if the user data transmission unit is “if-then” program code as part of an overall program, or if is intended to be a physical cable or antenna that allows for transmission of information. There is no clear structure disclosed that performs the functions of transmitting the daily user data and receiving a request signal. The “user data transmission unit” is not shown in a figure.
Because this/these claim limitation(s) is/are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, it/they is/are being interpreted to cover the corresponding structure described in the specification as performing the claimed function, and equivalents thereof.
If applicant does not intend to have this/these limitation(s) interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, applicant may: (1) amend the claim limitation(s) to avoid it/them being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph (e.g., by reciting sufficient structure to perform the claimed function); or (2) present a sufficient showing that the claim limitation(s) recite(s) sufficient structure to perform the claimed function so as to avoid it/them being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph.
Claim Rejections - 35 USC § 112
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
Claims 1 – 5 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.
Claim limitation “biofeedback generation unit” in Claim 1 invokes 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. However, the written description fails to disclose the corresponding structure, material, or acts for performing the entire claimed function and to clearly link the structure, material, or acts to the function. It is unclear if the biofeedback generation unit is lines of program code that are part of an overall program, or if it is intended to be a physical section of the wearable apparatus with an attached vibration motor on the person’s body. There is no clear structure disclosed that performs the functions of applying the vibration stimulation to the skins of the user through the vibration motor provided on the wearable device. The “biofeedback generation unit” is shown as a generic block element of “biofeedback generation unit 140” in “biofeedback-based bruxism alleviating system 100” in Fig. 2, which does not clarify if this element is intended to be hardware or software. Therefore, the claim is indefinite and is rejected under 35 U.S.C. 112(b) or pre-AIA 35 U.S.C. 112, second paragraph. Claims 2 – 5 are similarly rejected due to their dependence on Claim 1.
Claim limitation “data collection unit” in Claim 1 invokes 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. However, the written description fails to disclose the corresponding structure, material, or acts for performing the entire claimed function and to clearly link the structure, material, or acts to the function. Looking to [15] “…data collection unit may include a first sensor that collects first electromyography data for a preset period of time” and [44] with a first and a second sensor, it is unclear if the data collection unit is lines of program code that are part of an overall program or a processor, or if is intended to be a physical section on board the wearable apparatus that “receives” the electromyography data as a cable, etc. The “data collection unit” is shown as a generic block element of “data collection unit 120” in “biofeedback-based bruxism alleviating system 100” in Fig. 2, which does not clarify if this element is intended to be hardware or software.
Claim limitation “user stimulation providing unit” in Claim 3 invokes 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. However, the written description fails to disclose the corresponding structure, material, or acts for performing the entire claimed function and to clearly link the structure, material, or acts to the function. Looking to Applicant’s specification at [65] and Fig. 6, It is unclear if the user stimulation providing unit is “if-then” program code as part of an overall program, or if is intended to be a vibrator element or physical element that is controlled by the “biofeedback generation unit 140” that allows for the stimulation level to be adjusted. There is no clear structure disclosed that performs the functions of generating the vibration stimulation. The “user stimulation providing unit” is shown as a generic block element of “user stimulation providing unit 141” in “biofeedback generation unit 140” in Fig. 6.
Claim limitation “user stimulation correction unit” in Claim 3 invokes 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. However, the written description fails to disclose the corresponding structure, material, or acts for performing the entire claimed function and to clearly link the structure, material, or acts to the function. Looking to Applicant’s specification at [65] and Fig. 6, It is unclear if the user stimulation correction unit is “if-then” program code as part of an overall program, or if is intended to be a physical switch, spacer, or knob that is controlled by the “biofeedback generation unit 140” that allows for the stimulation level to be adjusted. There is no clear structure disclosed that performs the functions of correcting the vibration stimulation. The “user stimulation correction unit” is shown as a generic block element of “user stimulation correction unit 142” in “biofeedback generation unit 140” in Fig. 6.
Claim limitation “user data transmission unit” in Claim 5 invokes 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. However, the written description fails to disclose the corresponding structure, material, or acts for performing the entire claimed function and to clearly link the structure, material, or acts to the function. It is unclear if the user data transmission unit is “if-then” program code as part of an overall program, or if is intended to be a physical cable or antenna that allows for transmission of information. There is no clear structure disclosed that performs the functions of transmitting the daily user data and receiving a request signal. Therefore, the claim is indefinite and is rejected under 35 U.S.C. 112(b) or pre-AIA 35 U.S.C. 112, second paragraph.
Applicant may:
(a) Amend the claim so that the claim limitation will no longer be interpreted as a limitation under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph;
(b) Amend the written description of the specification such that it expressly recites what structure, material, or acts perform the entire claimed function, without introducing any new matter (35 U.S.C. 132(a)); or
(c) Amend the written description of the specification such that it clearly links the structure, material, or acts disclosed therein to the function recited in the claim, without introducing any new matter (35 U.S.C. 132(a)).
If applicant is of the opinion that the written description of the specification already implicitly or inherently discloses the corresponding structure, material, or acts and clearly links them to the function so that one of ordinary skill in the art would recognize what structure, material, or acts perform the claimed function, applicant should clarify the record by either:
(a) Amending the written description of the specification such that it expressly recites the corresponding structure, material, or acts for performing the claimed function and clearly links or associates the structure, material, or acts to the claimed function, without introducing any new matter (35 U.S.C. 132(a)); or
(b) Stating on the record what the corresponding structure, material, or acts, which are implicitly or inherently set forth in the written description of the specification, perform the claimed function. For more information, see 37 CFR 1.75(d) and MPEP §§ 608.01(o) and 2181.
Claim 1 (lines 7 – 8) recites the term “calls up user information corresponding to the unique number from a predetermined DB”. It is unclear to what “DB” is intended to refer. The expanded form of “DB” is not defined in the claim set, nor does it appear to be included in the Applicant’s specification. For the first recitation of “DB” in the claims (Claim 1), an accompanying expanded form of the abbreviation is necessary. Looking to [53] of Applicant’s specification in which data is “stored in a pre-designated DB”, the abbreviation DB is interpreted as a database. Claims 2- 5 are similarly rejected due to their dependence on Claim 1.
Claim 3 (line 13), Claim 4 (line 3), and Claim 5 (line 12) each recite the term “from the user terminal”. It is unclear if this is intended to be the same or different than the previously-recited predetermining user terminal. For the purposes of examination, the term “from the user terminal” is deemed to claim “from the predetermined user terminal.”
Claim 3 (line 12) recites the term “within a preset time range after the vibration stimulation”. It is unclear if this is intended to be the same or different than the previously-recited present time in Claim 3. For the purposes of examination, the term “within a preset time range after the vibration stimulation” is deemed to claim “within a second preset time range after the vibration stimulation.” It is suggested to revise the “preset time range” on Claim 3 (line 2) to be “a first preset time range”.
Claim 4 (lines 4 - 5) recites the term “determining a sleep state of the user”. It is unclear if this is intended to be the same or different than the previously-recited sleep state of the user. For the purposes of examination, the term “determining a sleep state of the user” is deemed to claim “determining the sleep state of the user”.
Claim 5 (line 3) recites the term “at least one of the number of bruxism events occurring”. There is insufficient antecedent basis for this limitation in the claim. There is no such previously-recited number of bruxism events. For the purposes of examination, the term “at least one of the number of bruxism events occurring” is deemed to claim “at least one of a number of bruxism events occurring”.
Claim 5 (lines 4 - 5) recites the term “the number of vibration stimulation generation times”. There is insufficient antecedent basis for this limitation in the claim. There is no such previously-recited number of bruxism events. For the purposes of examination, the term “the number of vibration stimulation generation times” is deemed to claim “a number of vibration stimulation generation times”.
Claim 5 (line 10) recites the limitation “derived through the artificial intelligence learning algorithm”. It is unclear if this is intended to be the same or different than the previously-recited preset artificial intelligence learning algorithm. For the purposes of examination, the term “derived through the artificial intelligence learning algorithm” is deemed to claim “derived through the preset artificial intelligence learning algorithm.”
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 – 5 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.
Regarding Claim 1, the claims recite "an act or step, or series of acts or steps" and is therefore a process, which is a statutory category of invention (Step 1). The claims are then analyzed to determine whether it is directed to any judicial exception (Step 2A, Prong 1).
Each of Claims 1 – 5 has been analyzed to determine whether it is directed to any judicial exceptions.
Step 2A, Prong 1
Each of Claims 1 – 5 recites at least one step or instruction for observations, evaluations, judgments, and opinions, which are grouped as a mental process under the 2019 PEG. The claimed invention involves making observations, evaluations, judgments, and opinions, which are concepts performed in the human mind under the 2019 PEG.
Accordingly, each of Claims 1 – 5 recites an abstract idea.
Specifically, Independent Claim 1 recites (underlined are observations, judgements, evaluations, or opinions, which are grouped as a mental process under the 2019 PEG) (additional elements bolded, see Step 2A, prong 2);
Claim 1
A biofeedback-based bruxism alleviating system comprising:
a user recognition unit that receives a bruxism diagnosis request signal generated from at least one of a predetermined user terminal and a wearable device attached to skins of a user, that extracts a unique number assigned to the wearable device included in the bruxism diagnosis request signal, and that calls up user information corresponding to the unique number from a predetermined DB;
a data collection unit that receives electromyography data collected from at least one sensor provided in the wearable device;
a bruxism diagnosis unit that diagnoses occurrence of bruxism by determining whether the electromyography data collected from the data collection unit satisfies a preset condition;
a biofeedback generation unit that applies a vibration stimulation to the skins of the user through a vibration motor provided in the wearable device, when the bruxism diagnosis unit determines the occurrence of the bruxism; and
a user monitoring unit that monitors bruxism symptoms of the user, based on bruxism diagnosis data derived by the bruxism diagnosis unit and vibration stimulation data generated by the biofeedback generation unit.
(observation, judgment or evaluation, which is grouped as a mental process under the 2019 PEG);
These underlined limitations describe a mathematical calculation and/or a mental process, as a skilled practitioner is capable of performing the recited limitations and making a mental assessment thereafter. Examiner notes that nothing from the claims suggests that the limitations cannot be practically performed by a human with the aid of a pen and paper, or by using a generic computer as a tool to perform mathematical calculations and/or mental process steps in real time. Examiner additionally notes that nothing from the claims suggests and undue level of complexity that the mathematical calculations and/or the mental process steps cannot be practically performed by a human with the aid of a pen and paper, or using a generic computer as a tool to perform mathematical calculations and/or mental process steps. For example, in Independent Claim 1, these limitations include:
Observation and judgment of a unique number assigned to the wearable device included in the bruxism diagnosis request signal
Observation and judgment to calls up user information corresponding to the unique number from a predetermined DB;
Observation and judgment to diagnose occurrence of bruxism by Observation and judgment of whether the electromyography data collected from the data collection unit satisfies a preset condition;
Observation and judgment to determine the occurrence of the bruxism
Observation and judgment to monitor bruxism symptoms of the user, based on bruxism diagnosis data derived by the bruxism diagnosis unit and vibration stimulation data generated by the biofeedback generation unit.
Similarly, Dependent Claims 2 – 5 include the following abstract limitations, in addition to the aforementioned limitations in Independent Claim 1 (underlined observation, judgment or evaluation, which is grouped as a mental process under the 2019 PEG):
determines a sleep state of the user by comparing the first electromyography data collected through the first sensor with a preset first reference voltage V_thl
Observation and judgment of a sleep state of the user by Observation and judgment to compare the first electromyography data collected through the first sensor with a preset first reference voltage V_thl
determines occurrence of bruxism events of the user by comparing the second electromyography data collected through the second sensor with a preset second reference voltage Vth2, when the sleep state determination unit determines that the user falls asleep.
Observation and judgment of occurrence of bruxism events of the user by Observation and judgment to compare the second electromyography data collected through the second sensor with a preset second reference voltage Vth2,
determines that the user falls asleep.
Observation and judgment that the user falls asleep.
generates a window mask in a preset time range, superimposes the window mask on the second electromyography data to determine the occurrence of the bruxism events,
Observation and judgment to generate a window mask in a preset time range, Observation and judgment to superimpose the window mask on the second electromyography data to Observe and judge the occurrence of the bruxism events,
determines the occurrence of the bruxism events, based on a time during which the second electromyography data exceeds the preset second reference voltage V_th2 within the window mask,
Observation and judgment of the occurrence of the bruxism events, based on a time during which the second electromyography data exceeds the preset second reference voltage V_th2 within the window mask,
corrects the vibration stimulation having the first pattern, when the bruxism events are detected through the bruxism diagnosis unit within a preset time range after the vibration stimulation having the first pattern is completed,
Observation and judgment to correct the vibration stimulation having the first pattern, when the bruxism events are Observed and judged within a preset time range after the vibration stimulation having the first pattern is completed,
in the first pattern, an initial value of the vibration stimulation is determined based on minimum stimulation intensity set from the user terminal, and intensity of the vibration stimulation is corrected by each one level through the user stimulation correction unit.
in the first pattern, an initial value of the vibration stimulation is Observed and judged based on minimum stimulation intensity set from the user terminal, and intensity of the vibration stimulation is Observed and judged to be corrected by each one level through the user stimulation correction unit.
determines whether to use the electromyography data collected from the first sensor and the second sensor, based on a bruxism diagnosis mode input from the user terminal
Observation and judgment whether to use the electromyography data collected from the first sensor and the second sensor, based on a bruxism diagnosis mode input from the user terminal
determining a sleep state of the user through the sleep state determination unit,
Observation and judgment of a sleep state of the user
determining the occurrence of the bruxism events of the user through the bruxism occurrence detection unit, when it is determined that the user falls asleep,
Observation and judgment of the occurrence of the bruxism events of the user, when it is Observed and judged that the user falls asleep,
counting a preset sleep waiting time, automatically determining that the user falls asleep, when the sleep waiting time is exceeded
Observation and judgment to count a preset sleep waiting time, automatically Observing and judging that the user falls asleep, when the sleep waiting time is exceeded
determining the occurrence of the bruxism events of the user
Observation and judgment of the occurrence of the bruxism events of the user
measures a daily sleep time of the user and generates daily user data including at least one of the number of bruxism events occurring during the daily sleep time, a duration of the bruxism, a degree of the bruxism, the number of vibration stimulation generation times, and maximum intensity of the vibration stimulation,
Observation and judgment to a daily sleep time of the user and Observation and judgment to generate daily user data including at least one of the number of bruxism events occurring during the daily sleep time, a duration of the bruxism, a degree of the bruxism, the number of vibration stimulation generation times, and maximum intensity of the vibration stimulation,
learns the number of the bruxism events occurring during the daily sleep time, the duration of the bruxism, and the maximum intensity of the vibration stimulation included in the daily user data
Observation and judgment of the number of the bruxism events occurring during the daily sleep time, the duration of the bruxism, and the maximum intensity of the vibration stimulation included in the daily user data
optimizes a bruxism diagnosis reference of the bruxism diagnosis unit, based on result data derived through the artificial intelligence learning algorithm,
Observation and judgment to optimize a bruxism diagnosis reference of the bruxism diagnosis unit, based on result data Observed and judged as an output of the artificial intelligence learning algorithm,
all of which are grouped as mental processes or mathematical algorithms under the 2019 PEG.
Accordingly, as indicated above, each of the above-identified claims recite an abstract idea.
Step 2A, Prong 2
The above-identified abstract ideas in each of Independent Claim 1 (and their respective Dependent Claims) are not integrated into a practical application under 2019 PEG because the additional elements (identified in Claims 1 – 5), either alone or in combination, generally link the use of the above-identified abstract ideas to a particular technological environment or field of use. More specifically, the additional elements of:
“user recognition unit”
“wearable device attached to skins of a user”
“data collection unit”
“bruxism diagnosis unit”
“biofeedback generation unit”
“vibration motor”
“user monitoring unit”
“first sensor”/“second sensor”
“sleep state determination unit”
“bruxism occurrence detection unit”
“user stimulation providing unit”/“user stimulation correction unit”
“user terminal”
“user data generation unit”
“bruxism diagnosis learning unit”
“user data transmission unit”
Additional elements recited include “user recognition unit”, “wearable device attached to skins of a user”, “data collection unit”, “bruxism diagnosis unit”, “biofeedback generation unit”, “vibration motor”, “user monitoring unit”, “first sensor”, “second sensor”, “sleep state determination unit”, “bruxism occurrence detection unit”, “user stimulation providing unit”, “user stimulation correction unit”, “user terminal”, “user data generation unit”, “bruxism diagnosis learning unit”, and “user data transmission unit” in Independent Claim 1 (and their respective Dependent Claims). These generic hardware component limitations for “user recognition unit”, “wearable device attached to skins of a user”, “data collection unit”, “bruxism diagnosis unit”, “biofeedback generation unit”, “vibration motor”, “user monitoring unit”, “first sensor”, “second sensor”, “sleep state determination unit”, “bruxism occurrence detection unit”, “user stimulation providing unit”, “user stimulation correction unit”, “user terminal”, “user data generation unit”, “bruxism diagnosis learning unit”, and “user data transmission unit” are no more than mere instructions to apply the exception using generic computer and hardware components. As such, these additional elements do not impose any meaningful limits on practicing the abstract idea.
Further additional elements from Independent Claim 1 includes pre-solution activity limitations, such as:
a user recognition unit that receives a bruxism diagnosis request signal generated from at least one of a predetermined user terminal and a wearable device attached to skins of a user
a data collection unit that receives electromyography data collected from at least one sensor provided in the wearable device;
a biofeedback generation unit that applies a vibration stimulation to the skins of the user through a vibration motor provided in the wearable device,
The dependent claims 2- 5 including further additional elements with are extra-solution activity limitations such as:
wherein the data collection unit includes a first sensor that collects first electromyography data for a preset period of time, and a second sensor provided at a preset interval from the first sensor to collect second electromyography data,
a user stimulation providing unit that generates vibration stimulation having a first pattern at T_winend which is an end time of the window mask, and that provides the vibration stimulation having the first pattern to the user through the wearable device,
a user data transmission unit that transmits the daily user data generated by the user data generation unit to the user terminal, based on a request signal received from the user terminal.
These pre-solution measurement elements are insignificant extra-solution activity, setting up the parameters of the system, and serve as data-gathering for the subsequent steps.
The “user recognition unit”, “wearable device attached to skins of a user”, “data collection unit”, “bruxism diagnosis unit”, “biofeedback generation unit”, “vibration motor”, “user monitoring unit”, “first sensor”, “second sensor”, “sleep state determination unit”, “bruxism occurrence detection unit”, “user stimulation providing unit”, “user stimulation correction unit”, “user terminal”, “user data generation unit”, “bruxism diagnosis learning unit”, and “user data transmission unit” as recited in Independent Claim 1 (and their respective Dependent Claims) are generically recited computer and hardware elements which do not improve the functioning of a computer, or any other technology or technical field. Nor do these above-identified additional elements serve to apply the above-identified abstract idea with, or by use of, a particular machine, effect a transformation or apply or use the above-identified abstract idea in some other meaningful way beyond generally linking the use thereof to a particular technological environment, such that the claim as a whole is more than a drafting effort designed to monopolize the exception. Furthermore, the above-identified additional elements do not add a meaningful limitation to the abstract idea because they amount to simply implementing the abstract idea on a computer. For at least these reasons, the abstract ideas identified above in Independent Claim 1 (and their dependent claims) is not integrated into a practical application under 2019 PEG.
Moreover, the above-identified abstract idea is not integrated into a practical application under 2019 PEG because the claimed method and system merely implements the above-identified abstract idea (e.g., mental process and certain method of organizing human activity) using rules (e.g., computer instructions) executed by a computer processor as claimed. In other words, these claims are merely directed to an abstract idea with additional generic computer elements which do not add a meaningful limitation to the abstract idea because they amount to simply implementing the abstract idea on a computer. Additionally, Applicant’s specification does not include any discussion of how the claimed invention provides a technical improvement realized by these claims over the prior art or any explanation of a technical problem having an unconventional technical solution that is expressed in these claims. That is, like Affinity Labs of Tex. v. DirecTV, LLC, the specification fails to provide sufficient details regarding the manner in which the claimed invention accomplishes any technical improvement or solution. Thus, for these additional reasons, the abstract idea identified above in Independent Claim 1 (and their dependent claims) is not integrated into a practical application under the 2019 PEG.
Accordingly, Independent Claim 1 (and their dependent claims) are each directed to an abstract idea under 2019 PEG.
Step 2B –
None of Claims 1 – 5 include additional elements that are sufficient to amount to significantly more than the abstract idea for at least the following reasons.
These claims require the additional elements of: “user recognition unit”, “wearable device attached to skins of a user”, “data collection unit”, “bruxism diagnosis unit”, “biofeedback generation unit”, “vibration motor”, “user monitoring unit”, “first sensor”, “second sensor”, “sleep state determination unit”, “bruxism occurrence detection unit”, “user stimulation providing unit”, “user stimulation correction unit”, “user terminal”, “user data generation unit”, “bruxism diagnosis learning unit”, and “user data transmission unit” as recited in Independent Claim 1 (and their dependent claims).
The additional elements of the “user recognition unit”, “wearable device attached to skins of a user”, “data collection unit”, “bruxism diagnosis unit”, “biofeedback generation unit”, “vibration motor”, “user monitoring unit”, “first sensor”, “second sensor”, “sleep state determination unit”, “bruxism occurrence detection unit”, “user stimulation providing unit”, “user stimulation correction unit”, “user terminal”, “user data generation unit”, “bruxism diagnosis learning unit”, and “user data transmission unit” in Independent Claim 1 (and their dependent claims), as discussed with respect to Step 2A Prong Two, amounts to no more than mere instructions to apply the exception using generic computer and hardware components. The same analysis applies here in 2B, i.e., mere instructions to apply an exception using a generic computer component cannot integrate a judicial exception into a practical application at Step 2A or provide an inventive concept in Step 2B.
The above-identified additional elements 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.
Per Applicant’s specification, the “wearable device attached to skins of a user” is described generically on [45] with “when the wearable device 10 is provided in a form of being attached to one side of the head of the user, the wearable device 10 may be attached near a temple of the user…” The “body-worn sensor” is shown as what appears to be a patch “wearable device 10” on a person’s temple in Fig. 1.
Per Applicant’s specification and the 112(f) interpretations above, the “user recognition unit”/“bruxism diagnosis unit”/“user monitoring unit”/“sleep state determination unit”/“bruxism occurrence detection unit”/“user data generation unit” are described generically in [39] with “biofeedback-based bruxism alleviating system 100 may include a user recognition unit 110…” and [95]. The “user recognition unit”/“bruxism diagnosis unit”/“user monitoring unit”/“sleep state determination unit”/“bruxism occurrence detection unit”/“user data generation unit” are shown as generic block elements in Fig. 2.
Per Applicant’s specification, the “vibration motor” is described generically as a vibration motor that can provide vibration stimulation to the user in [34], and it is “provided in the wearable device” in [14]. The “vibration motor” is not specifically shown in a figure.
Per Applicant’s specification, the “first sensor” and “second sensor” are described generically at [15] as “…first sensor that collects first electromyography data” and “second sensor provided at a preset interval from the first sensor to collect second electromyography data…”. The “first sensor” and “second sensor” as shown as generic block elements “first sensor 121” and “second sensor 122” in the “data collection unit 120” block in Fig. 3.
Per Applicant’s specification, the “user terminal” is described generically at [36] with “data on the bruxism symptoms of the user which is generated through the biofeedback-based bruxism alleviating system 100 may be transmitted to the user terminal 20 linked with the wearable device 10,” and shown in Fig. 1 as “user terminal 20”, which is what appears to be a generic smart phone.
Per Applicant’s specification, the “data collection unit” is generically described at [15] to include the “first sensor” and “second sensor”, but as described in the 112(f) interpretation and 112(b) rejection above, it is unclear if this is a hardware or software element. The “data collection unit” is shown as a generic block element of “data collection unit 120” in “biofeedback-based bruxism alleviating system 100” in Fig. 2, which does not clarify if this element is intended to be hardware or software.
Per Applicant’s specification, the “biofeedback generation unit” is generically described as part of “biofeedback-based bruxism alleviating system 100” at [39], but as described in the 112(f) interpretation and 112(b) rejection above, it is unclear if this is a hardware or software element. The “biofeedback generation unit” is shown as a generic block element of “biofeedback generation unit 140” in “biofeedback-based bruxism alleviating system 100” in Fig. 2, which does not clarify if this element is intended to be hardware or software.
Per Applicant’s specification, the “user stimulation providing unit” and “user stimulation correction unit” are described generically in [65] and Fig. 6 as providing stimulation in a pattern and “correcting” that stimulation. As described in the 112(f) interpretation and 112(b) rejection above, it is unclear if these are hardware or software elements. The “user stimulation providing unit” and the “user stimulation correction unit” are shown as a generic block element of “user stimulation providing unit 141” and “user stimulation correction unit 142” in “biofeedback generation unit 140” in Fig. 6.
Per Applicant’s specification, the “bruxism diagnosis learning unit” is described generically at [84] “a bruxism diagnosis learning unit 152…learns…through a present artificial intelligence learning algorithm.” It appears to be generically any artificial intelligence learning algorithm that can learn information and prioritize it. The “bruxism diagnosis learning unit” is not shown in a figure.
Per Applicant’s specification, the “user data transmission unit” is generically described at [84] with “…a user data transmission unit 153 that transmits the daily user data generated by the user data generation unit 151 to the user terminal 20…”, but as described in the 112(f) interpretation and 112(b) rejection above, it is unclear if this is a hardware or software element.
Accordingly, in light of Applicant’s specification, the claimed terms “user recognition unit”, “wearable device attached to skins of a user”, “data collection unit”, “bruxism diagnosis unit”, “biofeedback generation unit”, “vibration motor”, “user monitoring unit”, “first sensor”, “second sensor”, “sleep state determination unit”, “bruxism occurrence detection unit”, “user stimulation providing unit”, “user stimulation correction unit”, “user terminal”, “user data generation unit”, “bruxism diagnosis learning unit”, and “user data transmission unit” are reasonably construed as a generic computing and hardware devices. Like SAP America vs Investpic, LLC (Federal Circuit 2018), it is clear, from the claims themselves and the specification, that these limitations require no improved computer resources, just already available computers, with their already available basic functions, to use as tools in executing the claimed process.
Furthermore, Applicant’s specification does not describe any special programming or algorithms required for “user recognition unit”, “wearable device attached to skins of a user”, “data collection unit”, “bruxism diagnosis unit”, “biofeedback generation unit”, “vibration motor”, “user monitoring unit”, “first sensor”, “second sensor”, “sleep state determination unit”, “bruxism occurrence detection unit”, “user stimulation providing unit”, “user stimulation correction unit”, “user terminal”, “user data generation unit”, “bruxism diagnosis learning unit”, and “user data transmission unit” This lack of disclosure is acceptable under 35 U.S.C. §112(a) since this hardware performs non-specialized functions known by those of ordinary skill in the computer arts. By omitting any specialized programming or algorithms, Applicant's specification essentially admits that this hardware is conventional and performs well understood, routine and conventional activities in the computer industry or arts. In other words, Applicant’s specification demonstrates the well-understood, routine, conventional nature of the above-identified additional elements because it describes these additional elements in a manner that indicates that the additional elements are sufficiently well-known that the specification does not need to describe the particulars of such additional elements to satisfy 35 U.S.C. § 112(a) (see Berkheimer memo from April 19, 2018, (III)(A)(1) on page 3). Adding hardware that performs “‘well understood, routine, conventional activit[ies]’ previously known to the industry” will not make claims patent-eligible (TLI Communications).
The recitation of the above-identified additional limitations in Independent Claim 1 (and their dependent claims) amounts to mere instructions to implement the abstract idea on a computer. Simply using a computer or other machinery in its ordinary capacity for economic or other tasks (e.g., to receive, store, or transmit data) or simply adding a general-purpose computer or computer components after the fact to an abstract idea (e.g., a fundamental economic practice or mathematical equation) does not provide significantly more. See Affinity Labs v. DirecTV, 838 F.3d 1253, 1262, 120 USPQ2d 1201, 1207 (Fed. Cir. 2016) (cellular telephone); and TLI Communications LLC v. AV Auto, LLC, 823 F.3d 607, 613, 118 USPQ2d 1744, 1748 (Fed. Cir. 2016) (computer server and telephone unit). Moreover, implementing an abstract idea on a generic computer, does not add significantly more, similar to how the recitation of the computer in the claim in Alice amounted to mere instructions to apply the abstract idea of intermediated settlement on a generic computer.
A claim that purports to improve computer capabilities or to improve an existing technology may provide significantly more. McRO, Inc. v. Bandai Namco Games Am. Inc., 837 F.3d 1299, 1314-15, 120 USPQ2d 1091, 1101-02 (Fed. Cir. 2016); and Enfish, LLC v. Microsoft Corp., 822 F.3d 1327, 1335-36, 118 USPQ2d 1684, 1688-89 (Fed. Cir. 2016). However, a technical explanation as to how to implement the invention should be present in the specification for any assertion that the invention improves upon conventional functioning of a computer, or upon conventional technology or technological processes. That is, the disclosure must provide sufficient details such that one of ordinary skill in the art would recognize the claimed invention as providing an improvement. Here, Applicant’s specification does not include any discussion of how the claimed invention provides a technical improvement realized by these claims over the prior art or any explanation of a technical problem having an unconventional technical solution that is expressed in these claims. Instead, as in Affinity Labs of Tex. v. DirecTV, LLC 838 F.3d 1253, 1263-64, 120 USPQ2d 1201, 1207-08 (Fed. Cir. 2016), the specification fails to provide sufficient details regarding the manner in which the claimed invention accomplishes any technical improvement or solution.
For at least the above reasons, the systems of Claims 1 – 5 are directed to applying an abstract idea as identified above on a general-purpose computer without (i) improving the performance of the computer itself, or (ii) providing a technical solution to a problem in a technical field. None of Claims 1 – 5 provides meaningful limitations to transform the abstract idea into a patent eligible application of the abstract idea such that these claims amount to significantly more than the abstract idea itself.
Taking the additional elements individually and in combination, the additional elements do not provide significantly more. Specifically, when viewed individually, the above-identified additional elements for Step 2A Prong 2 in Independent Claim 1 (and their dependent claims) do not add significantly more because they are simply an attempt to limit the abstract idea to a particular technological environment. That is, 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. When viewed as a combination, these above-identified additional elements 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. As such, there is no inventive concept sufficient to transform the claimed subject matter into a patent-eligible application. 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. Thus, Claims 1 – 5 apply an abstract idea to a computer and do not (i) improve the performance of the computer itself (as in Bascom and Enfish), or (ii) provide a technical solution to a problem in a technical field (as in DDR).
Therefore, none of the Claims 1 – 5 amounts to significantly more than the abstract idea itself. Accordingly, Claims 1 – 5 are not patent eligible and rejected under 35 U.S.C. 101.
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.
This application currently names joint inventors. In considering patentability of the claims the examiner presumes that the subject matter of the various claims was commonly owned as of the effective filing date of the claimed invention(s) absent any evidence to the contrary. Applicant is advised of the obligation under 37 CFR 1.56 to point out the inventor and effective filing dates of each claim that was not commonly owned as of the effective filing date of the later invention in order for the examiner to consider the applicability of 35 U.S.C. 102(b)(2)(C) for any potential 35 U.S.C. 102(a)(2) prior art against the later invention.
Claim 1 is rejected under 35 U.S.C. 103 as being unpatentable over Kim (KR 20220043385A), hereinafter Kim ‘385, in view of Jadidi (US 2012/0203133 A1),
Regarding Claim 1, Kim ‘385 discloses A biofeedback-based bruxism alleviating system ([Summary]) comprising:
a user recognition unit that receives a bruxism diagnosis request signal generated from at least one of a predetermined user terminal and a wearable device attached to skins of a user, that extracts a unique number assigned to the wearable device included in the bruxism diagnosis request signal, and that calls up user information corresponding to the unique number from a predetermined DB ([0098] - [0100] “The user information database (310)…include the user’s name…user terminal information database (320) may include the type of user terminal (200)… the user terminal information database (320) may store information on the unique device assigned to each teeth grinding detection and prevention device (100) used by the user.”; Fig. 10);
a data collection unit ([0049] – [0050] “…sensing unit 130…”) that receives electromyography data collected from at least one sensor provided in the wearable device ([0027] “…a pad unit attached to the skin of the user’s face…detection unit that detects the user's electromyography state through the pad unit…”; [0049] – [0050]);
a bruxism diagnosis unit that diagnoses occurrence of bruxism ([0048] “…The pad portion (120) is attached to the user's skin and used as a medium to detect a teeth grinding state…”; [0053] “…when the control unit (150) determines that the electromyogram state is a teeth grinding state…”; [0075] “..the detection unit determines whether bruxism has occurred…”) by determining whether the electromyography data collected from the data collection unit satisfies a preset condition ([0122] “…whether the detected measurement value is greater than or equal to a preset reference value (S30)… if the measured electromyogram signal value exceeds 40% of the reference signal value, but the electromyogram signal value exceeds the reference signal value for a period of 5 seconds or more and 40 seconds or less, it is determined that bruxism has occurred.”)
a biofeedback generation unit that applies a stimulation to the skins of the user ([0124] “…the control unit (150) causes an electric stimulus to be applied to the user's skin through the operating unit (140) (S40)….”) through a stimulator provided in the wearable device, when the bruxism diagnosis unit determines the occurrence of the bruxism ([0124] “…the control unit (150) causes an electric stimulus to be applied to the user's skin through the operating unit (140) (S40).”; Figure on page 16); and
a user monitoring unit that monitors bruxism symptoms of the user ([0128] “…the management server (400)…information on the user’s bruxism status…”), based on bruxism diagnosis data derived by the bruxism diagnosis unit and stimulation data generated by the biofeedback generation unit ([0123] “…management server (400) extracts bruxism detection information stored in the database according to the transmitted information and learns personalized bruxism detection information”; [0106] “…managing stimulation information for preventing the progression on bruxism…”; [0109]).
Kim ‘385 does not specifically disclose that the stimulus is a vibration stimulus for a biofeedback generation unit that applies a vibration stimulation to the skins of the user through a vibration motor provided in the wearable device and vibration stimulation data generated by the biofeedback generation unit.
Jadidi teaches an apparatus that uses EMG signal measurement on the skin of the face to determine occurrences of bruxism and a vibration motor as a feedback signal stimulus to discourage the detected bruxism grinding ([Abstract]; [0170]; Fig 13, Fig. 25). Specifically for Claim 1, Jadidi teaches a biofeedback generation unit that applies a vibration stimulation to the skins of the user through a vibration motor provided in the wearable device ([0015] “…feedback…a vibrator placed on a location on the body…”; [0170] “…a bio-feedback signal 605 is activated in the form of…vibration…sent to the patient…vibrator module, a bracelet vibrator, or the like…”), and vibration stimulation data generated by the biofeedback generation unit ([0160] “…the stimulation shall be able to be adjusted individually…on the basis of the table it can be ascertained which feedback fits the patient's bruxism pattern, where the feedback (the stimulation) is set regarding duration, intensity and delay…”; [0132] “…The measurements
and the settings are stored in the apparatus…”; [0170])
Jadidi provides a motivation to combine at [0170] with “a bio-feedback signal 605 is activated in the form of sound, vibration and/or other stimuli, which via 606 is sent to the patient,” and [0040] “…the individual user may adjust and set the feedback signal, e.g. a vibration, an electric signal, or another form of stimulus to a level that will be suitable to the user, e.g. a level that will not be uncomfortable to the user but that may clearly be sensed/felt/heard etc.” A person having ordinary skill in the art before the effective filing date of the claimed invention would recognize that a vibration stimulation would be an interchangeable type of stimulus in response to determination of bruxism with an electrical stimulus, and that it can be adjusted to a level that is not uncomfortable to the user but can still be clearly sensed/felt/heard by the user.
Therefore, it would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to combine the bruxism detection device that applies a stimulus in response to determining bruxism has occurred disclosed by Kim ‘385 with the specifically vibration stimulus in response to bruxism detection taught by Jadidi, creating a single bruxism detection and feedback stimulus-providing device that can help mitigate bruxism occurrence by giving a user skin vibration feedback at a comfortable level to be sensed/felt/heard.
Claims 2 and 3 are rejected under 35 U.S.C. 103 as being unpatentable over Kim ‘385 (KR 20220043385A) in view of Jadidi (US 2012/0203133 A1), further in view of Toth, et. al., (US 2023/0147888 A1), further in view of Hwang et. al., (“Sleep/wake estimation using only anterior tibialis electromyography data”, Ref U on PTO-892)
Regarding Claim 2, Kim ‘385 in view of Jadidi discloses as described above, The biofeedback-based bruxism alleviating system of claim 1. For the remainder of Claim 2, Kim ‘385 discloses wherein the data collection unit ([0049] – [0050] “…sensing unit 130…”) includes a first sensor ([0050] “…The tilt sensor, gravity sensor, and gyroscope sensor may be used as sensors to detect tossing and turning for the user's sleep quality…”) that collects first data for a preset period of time ([0033] “…the measurement values and reference values of sleep…”)(Examiner notes that the measurements are broadly during the preset period of time of time that the subject is asleep), and a second sensor provided ([0027] “…a pad unit attached to the skin of the user’s face…detection unit that detects the user's electromyography state through the pad unit…”; [0049] – [0050]) to collect second electromyography data ([0027] “…a pad unit attached to the skin of the user’s face…detection unit that detects the user's electromyography state through the pad unit…”; [0049] – [0050]), and
the bruxism diagnosis unit includes a sleep state determination unit that determines a sleep state of the user ([0128] “…control unit (150) determines whether the user wakes up from sleep based on the detection information from the detection unit (130) (S50).”; [0131] “…if the user continues to grind their teeth without waking up from sleep in step S50 (S60)…”), and
a bruxism occurrence detection unit ([0122] “…the control unit (150)…”) that determines occurrence of bruxism events of the user by comparing the second electromyography data collected through the second sensor with a preset second reference voltage Vth2 ([0122] “…determines whether the detected measurement value is greater than or equal to a preset reference value (S30)…”; Fig. 14), when the sleep state determination unit determines that the user falls asleep ([0128] “…control unit (150) determines whether the user wakes up from sleep based on the detection information from the detection unit (130) (S50).”; [0131] “…if the user continues to grind their teeth without waking up from sleep in step S50 (S60)…”)
Kim ‘385 does not disclose a first sensor that collects first electromyography data for a preset period of time a second sensor provided at a preset interval from the first sensor to collect second electromyography data, and determines a sleep state of the user by comparing the first electromyography data collected through the first sensor with a preset first reference voltage V_thl
Toth teaches a physiologic parameter measuring apparatus that uses two EMG sensors to measure local EMG signals and signals from adjacent tissues to determine incidence of bruxism and sleep state, interacts with the subject based on the measurements using a feedback system (such as a buzzer or tactile actuator), and displays obtained physiologic data with an overlay of when the user was asleep ([Abstract]; [0078] – [0081]; [0157]; [0174]). Specifically for Claim 2, Toth teaches wherein the data collection unit includes a first sensor that collects first electromyography data ([0078] “…an electromyography (EMG)/electrooculography (EOG) device…patch/module pair…to measure local electromyographic…signals…head or neck…”) for a preset period of time (Fig. 14, “physiologic data…physiologic parameters collected from a given set of one or more subjects over a given period of time…”)), and a second sensor provided at a preset interval from the first sensor to collect second electromyography data ([0078] “…an electromyography (EMG)/electrooculography (EOG) device…patch/module pair…to measure local electromyographic…signals from adjacent tissues”, “…head or neck…”), and
determines a sleep state of the user by evaluating the first electromyography data collected through the first sensor ([0078] “…algorithm configured to analyze EMG/EOG signal, to determine the sleep state of the subject…”) and
determines occurrence of bruxism events of the user ([0081] “… the signal analysis function configured to analyze the EMG/EOG signals…to…identify a bruxism event…”) by comparing the second electromyography data collected through the second sensor ([0078] - [0081] including “… the signal analysis function configured to analyze the EMG/EOG signals…to…identify a bruxism event…”) when the sleep state determination unit determines that the user falls asleep ([0078] – [0081] “…algorithm configured to analyze EMG/EOG signal, to determine the sleep state of the subject…”; [0157] “…data visualizations…overlaying a filter showing when the subject was awake/asleep…”; [0174]).
Toth provides a motivation to combine at [0036] with “The modular physiologic monitoring system may include one or more patches, each patch adapted for attachment to the body of the subject…”; patch characteristics at [0040] – [0046] including “Such a configuration may be advantageous for providing a comfortable wearable physiologic monitor for a subject, while reducing material waste and/or cost of goods, preventing contamination or disease spread through uncontrolled re-use, and the like“; and [0078] “…(EMG)/electrooculography (EOG) device (e.g., a patch/module pair…“. A person having ordinary skill in the art before the effective filing date of the claimed invention would recognize that using multiple patches of EMG data to determine bruxism and sleep state would be convenient for attaching the measurement apparatuses directly to the skin with patches that can be comfortably, consistently, and safely worn for long measurement sessions.
Therefore, it would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to combine the bruxism detection device that measures EMG with a sensor and includes multiple sensors to detect signals to determine bruxism and sleep state disclosed by Kim ‘385 with the specifically two EMG sensors each attached at a different location on the user to detect both bruxism and sleep state using EMG signals, creating a single bruxism detection and feedback stimulus-providing device that can use EMG signal processing to determine the occurrence of sleep bruxism using multiple sensors that can be reliably, comfortably, and safely attached to the user with patches for longer data collection sessions.
Toth does not specifically teach determines a sleep state of the user by comparing the first electromyography data collected through the first sensor with a preset first reference voltage V_thl.
Hwang teaches a method of determining sleep state using an EMG sensor and an amplitude threshold of the EMG signal between sleep and awake states ([Abstract]). Specifically for Claim 2, Hwang teaches determines a sleep state of the user by comparing the first electromyography data collected through the first sensor with a preset first reference voltage V_thl ([Page 4, 1st Full Paragraph] “…the EMG signal amplitudes during sleep and wake states were quantified after amplitude normalization…wake states show relatively high…EMG amplitudes compared with those in sleep states… Based on the anterior tibialis EMG amplitude differences between sleep and wake states, we were able to estimate sleep/wake cycles.”; [Page 5, 1st Full Paragraph] “obtain the adaptive amplitude threshold of EMG signals for each epoch…”; Figure 8);
Hwang provides a motivation to combine at ([Page 4, 1st Full Paragraph] with “…the EMG signal amplitudes during sleep and wake states were quantified after amplitude normalization…wake states show relatively high…EMG amplitudes compared with those in sleep states… Based on the anterior tibialis EMG amplitude differences between sleep and wake states, we were able to estimate sleep/wake cycles.” A person having ordinary skill in the art before the effective filing date of the claimed invention would recognize that using a specific threshold in the EMG data to determine sleep state would be useful for having a concrete metric of when sleep occurs during the measurements, permitting more consistent bruxism data reporting.
Therefore, it would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to combine the bruxism detection device that measures EMG with a sensors to determine bruxism and sleep state disclosed by Kim ‘385 in view of Toth with obtaining a comparative specific EMG amplitude threshold for sleep as taught by Hwang, creating a single bruxism detection and feedback stimulus-providing device that can use EMG signal processing to determine the occurrence of sleep bruxism using a specific comparative EMG signal amplitude threshold for consistent data processing for sleep bruxism detection.
Regarding Claim 3, Kim ‘385 in view of Jadidi, Toth, and Hwang discloses as described above, The biofeedback-based bruxism alleviating system of claim 2. For the remainder of Claim 3, Kim ‘385 discloses wherein the bruxism occurrence detection unit ([0075] “..the detection unit determines whether bruxism has occurred…”) generates a window in a preset time range (Figure 14, threshold line drawn over the EMG output as the upper bound of the window mask, with the lower bound at 0; [0122] including “…detected measurement value is greater than or equal to a preset reference value (S30)… desirable to determine that a bruxism phenomenon has occurred when the electromyogram signal value continuously exceeds the reference signal value for a period of 5 seconds or more and 40 seconds or less”, which would be the horizontal time bounds of the window mask.)(Examiner notes that the window is broadly an analysis range of interest, such as a 5 second or 40 second time width window with an upper window threshold of the reference signal value for a bruxism instance), superimposes the window mask on the second electromyography data to determine the occurrence of the bruxism events (Figure 14, threshold line drawn over the EMG output as the upper bound of the window mask, with the lower bound at 0; [0122] including “…detected measurement value is greater than or equal to a preset reference value (S30)… desirable to determine that a bruxism phenomenon has occurred when the electromyogram signal value continuously exceeds the reference signal value for a period of 5 seconds or more and 40 seconds or less”, which would be the horizontal time bounds of the window mask.)( Examiner notes that the range is mathematically superimposed on the second electromyography data, in that the data are screened to determine if there are any intervals that have sections with amplitude greater than the reference signal lasting longer than 5 seconds and less than 40 second to determine if the movement evidence of bruxism.) and determines the occurrence of the bruxism events ([0075] “..the detection unit determines whether bruxism has occurred…”; [0122]), based on a time during which the second electromyography data exceeds the preset second reference voltage V_th2 ([0122] “…determines whether the detected measurement value is greater than or equal to a preset reference value (S30)…”; Fig. 14) within the window mask (Figure 14, threshold line drawn over the EMG output as the upper bound of the window mask, with the lower bound at 0; [0122] including “…detected measurement value is greater than or equal to a preset reference value (S30)… desirable to determine that a bruxism phenomenon has occurred when the electromyogram signal value continuously exceeds the reference signal value for a period of 5 seconds or more and 40 seconds or less”, which would be the horizontal time bounds of the window mask.) and
the biofeedback generation unit ([0124] “…the control unit (150) causes an electric stimulus to be applied to the user's skin through the operating unit (140) (S40)….”) includes a user stimulation providing unit that generates stimulation ([0028] “…stimulation applied at the operating unit…an electrical stimulation through the pad unit”) having a first pattern ([0028] “…at a level within the range of 0.1 to 7 mA…”) at T_winend which is an end time of the window mask ([0122] - [0124] “…When it is determined by the control unit (150) in step S30 that the user's teeth grinding has occurred, the control unit (150) causes an electric stimulus to be applied to the user's skin through the operating unit (140) (S40).”), and that provides the stimulation having the first pattern to the user through the wearable device ([0028] “….an electrical stimulation through the pad unit …at a level within the range of 0.1 to 7 mA…”), and
a user stimulation correction unit that corrects the stimulation having the first pattern, when the bruxism events are detected through the bruxism diagnosis unit within a preset time range after the stimulation having the first pattern is completed ([0131] “…if the user continues to grind their teeth without waking up from sleep in step S50 (S60), the control unit (150) controls the increase in stimulation at the operating unit (140) (S70)…if tossing and turning occurs within 5 seconds after the time of the occurrence of teeth grinding…user has recognized the teeth grinding phenomenon, and if it is outside this range…user has not properly recognized the teeth grinding phenomenon… current value is increased for electrical stimulation or the time for applying electrical stimulation is increased.”; [0127] “…stimulation of gradually increasing intensity…”), and
in the first pattern, an initial value of the stimulation is determined based on minimum stimulation intensity set from the user terminal ([0028] “….an electrical stimulation through the pad unit …at a level within the range of 0.1 to 7 mA…”)(Examiner notes that the minimum intensity set would be 0.1 mA), and intensity of the stimulation is corrected by each one level through the user stimulation correction unit ([0131] “…if the user continues to grind their teeth without waking up from sleep in step S50 (S60), the control unit (150) controls the increase in stimulation at the operating unit (140) (S70)…current value is increased for electrical stimulation or the time for applying electrical stimulation is increased.”; [0127] “…stimulation of gradually increasing intensity…”).
Kim ‘385 does not disclose that the stimulation is specifically vibration stimulation. For the instances of vibration stimulation, Jadidi teaches vibration stimulation ([0015] “…The feedback…form of a vibrator placed on a location on the body.”; [0040] ‘…adjust and set the feedback signal, e.g. a vibration…or another form of stimulus to a level…”)
The motivation for Claim 3 to combine Kim ‘385 with Jadidi is the same as that described in more detail above for Claim 1. In summary, it would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to combine the bruxism detection device that applies a stimulus in response to determining bruxism has occurred disclosed by Kim ‘385 with the specifically vibration stimulus in response to bruxism detection taught by Jadidi, creating a single bruxism detection and feedback stimulus-providing device that can help mitigate bruxism occurrence by giving a user skin vibration feedback at a comfortable level to be sensed/felt/heard.
Claim 4 is rejected under 35 U.S.C. 103 as being unpatentable over Kim ‘385 (KR 20220043385A) in view of Jadidi, Toth, and Hwang, further in view of Kim (KR 102063143B1), hereinafter Kim ‘143, further in view of Klaus et. al., (“Accuracy of a Smartphone Application Measuring Snoring in Adults—How Smart Is It Actually?”, Ref V on PTO-892), as evidenced by Treiman, (“Are You Grinding Your Teeth? Here’s How to Know and How to Stop This Harmful Habit”. Ref W on PTO-892).
Regarding Claim 4, Kim ‘385 in view of Jadidi, Toth, and Hwang discloses as described above, The biofeedback-based bruxism alleviating system of claim 2. For the remainder of Claim 4, Kim ‘385 discloses wherein the bruxism diagnosis unit ([0075] “..the detection unit determines whether bruxism has occurred…”; [0122]), determines whether to use the electromyography data collected from the first sensor and the second sensor, based on a bruxism diagnosis mode input from the user terminal ([0026] “the management server comprises a bruxism information management unit that manages the user's bruxism status information detected by the bruxism detection and prevention device and transmitted through the user terminal…user’s sleep quality status…”; [0128] – 131]), and
the bruxism diagnosis mode ([0026] “the management server comprises a bruxism information management unit that manages the user's bruxism status information detected by the bruxism detection and prevention device and transmitted through the user terminal…user’s sleep quality status…”; [0128] – [0131]), includes
a first diagnosis mode for determining a sleep state of the user through the sleep state determination unit ([0128] “…control unit (150) determines whether the user wakes up from sleep based on the detection information from the detection unit (130) (S50).”; [0131] “…if the user continues to grind their teeth without waking up from sleep in step S50 (S60)…”), and for determining the occurrence of the bruxism events of the user through the bruxism occurrence detection unit, when it is determined that the user falls asleep ([0122]; [0128] “…control unit (150) determines whether the user wakes up from sleep based on the detection information from the detection unit (130) (S50).”; [0131] “…if the user continues to grind their teeth without waking up from sleep in step S50 (S60)…”); and
and determining the occurrence of the bruxism events of the user through the bruxism occurrence detection unit ([0075] “..the detection unit determines whether bruxism has occurred…”).
Kim ‘385 does not disclose a second diagnosis mode for counting a preset sleep waiting time, automatically determining that the user falls asleep, when the sleep waiting time is exceeded.
Kim ‘143 teaches selecting two different modes on a user interface for a bruxism device an “awake” mode and a “sleep” mode ([0093] – [0095]; [0107]; [0114]). Specifically for Claim 4, Kim ‘143 teaches a first diagnosis mode and a second diagnosis mode ([0093] “…the above interface enables the selection of a sleep mode or a wake mode, and in each mode, the electromyography signal…”; [0094] – [0095] “…in the above sleep mode, sleep time information is further detected and stored as the bruxism occurrence information….”; [0114] “…operated in deep sleep mode… The motion sensor measures tossing and turning information in real time and transmits it to the control unit (340)….”); [0107]).
Kim ‘143 provides a motivation to combine at [0093] “…the above interface enables the selection of a sleep mode or a wake mode, and in each mode… The selection of starting or ending the measurement is possible…” A person having ordinary skill in the art before the effective filing date of the claimed invention would recognize that allowing the user to select from multiple modes of use in a user interface would be useful for allowing the user greater agency in deciding what type of data they would like to collect for their purposes and when it is collected.
Therefore, it would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to combine the bruxism detection device that measures EMG with a sensors to determine bruxism with a user interface disclosed by Kim ‘385 with two selectable bruxism detection modes in the user interface as taught by Kim ‘143, creating a single bruxism detection and feedback stimulus-providing device with user-selectable modes for bruxism detection for greater data collection personalization for the user.
Kim ‘143 does not particularly teach a second diagnosis mode for counting a preset sleep waiting time, automatically determining that the user falls asleep, when the sleep waiting time is exceeded.
Klaus teaches research to determine how accurately the commercially-available smartphone application, SnoreLab, is at measuring snoring, wherein the SnoreLab app records data with a delay from when the user selects a sleep mode on the user interface (a smartphone) ([Abstract]; [Page 3]). Specifically for Claim 4, Klaus teaches a diagnosis mode for counting a preset sleep waiting time, automatically determining that the user falls asleep when the sleep waiting time is exceeded ([Page 3, 1st Full Paragraph underneath the bullet points] “…SnoreLab gives the opportunity to select manually how long it usually takes the user to fall asleep...”), and determining the occurrence of the bruxism events of the user through the bruxism occurrence detection unit ([Page 3, Bullet Points] “…starting and ending time of monitoring…time in bed…monitoring time…duration and ratio of quiet sleep, light, loud…”)(Examiner notes that as evidenced by Treiman, “Are You Grinding Your Teeth? Here’s How to Know and How to Stop This Harmful Habit”, [Page 12, Paragraph 2, “SnoreLab”] regarding the SnoreLab app, “Although created to track snoring, “…the program’s sophisticated algorithms can pick up and record bruxism’s telltale cacophony….”, such that SnoreLab can determine the occurrence of the bruxism events of the user through its bruxism occurrence detection unit of algorithms in a smartphone app.)
Klaus provides a motivation to combine at ([Page 3, 1st Full Paragraph underneath the bullet points] with “…SnoreLab gives the opportunity to select manually how long it usually takes the user to fall asleep.” A person having ordinary skill in the art before the effective filing date of the claimed invention would recognize that having the user input a number of minutes delay for categorizing sleep, it would permit the measurement of sleep bruxism without requiring specialized sensors to determine whether or not sleep is actually occurring, which would be less expensive in regard to processing power and sensor requirements. A person having ordinary skill in the art before the effective filing date of the claimed invention would also recognize that a user input for a sleep onset time would be useful as an optional mode in a bruxism detection device with multiple mode selection options, such as that of Kim ‘385 in view of Kim ‘143, for allowing personalized data collection.
Therefore, it would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to combine the bruxism detection device that measures EMG with a sensors to determine bruxism with a user interface having two selectable modes disclosed by Kim ‘385 in view of Kim ‘143 with Klaus’ taught user executing a mode in which they manually enter how long it usually takes them to fall asleep to influence when the sleep noise data recording starts. This would create a single bruxism detection and feedback stimulus-providing device that can use EMG signal processing to determine the occurrence of sleep bruxism using either an automatic detection mode for when the sleep data starts or a user-specified delay to denote the sleep time, for varying levels of data processing requirements.
Claim 5 is rejected under 35 U.S.C. 103 as being unpatentable over Kim ‘385 (KR 20220043385A) in view of Jadidi (US 2012/0203133 A1), further in view of Martini (US 2022/0008243 A1).
Regarding Claim 5, Kim ‘385 in view of Jadidi discloses as described above, The biofeedback-based bruxism alleviating system of claim 1. For the remainder of Claim 5, Kim ‘385 discloses wherein the user monitoring unit ([0128] “…the management server (400)…”) includes
a user data generation unit that measures a sleep time of the user and generates user data including at least one of the number of bruxism events occurring during the sleep time ([0101]; [0136] “…personalized teeth grinding status information may include…the number of teeth grinding occurrences…”) a duration of the bruxism ([0101] “…include information about…the duration of teeth grinding…”), a degree of the bruxism ([0136] “…personalized teeth grinding status information may include…intensity…interval or teeth grinding occurrence…”), the number of stimulation generation times ([0101]; [0025] “…stimulation time for preventing bruxism…”; [0127] “…repeatedly transmit stimulation of the same intensity or transmit stimulation of gradually increasing intensity when transmitting the stimulation signal…”), and maximum intensity of the stimulation ([0101]; [0025] “…information regarding stimulation intensity…”; [0125] – [0126] “…electric stimulation delivered at this time is to be at an intensity of 0.1 to 7 mA…”).
a bruxism diagnosis learning unit ([0106] “…learning unit (460)…”) that learns the number of the bruxism events occurring during the sleep time ([0136] “:…personalized teeth grinding status information learned by the learning unit (460)…personalized teeth grinding status information may include…number of teeth grinding occurrences…”), the duration of the bruxism ([0136] “…may include…duration per occurrent…”) and the maximum intensity of the stimulation included in the user data through a preset artificial intelligence learning algorithm ([0026] “…a learning unit that performs learning to set the stimulation intensity and stimulation time executed in the bruxism detection…”; [0126]; [0125] “…electric stimulation delivered at this time is to be at an intensity of 0.1 to 7 mA…”), and that optimizes a bruxism diagnosis reference of the bruxism diagnosis unit ([0033] “…learning unit…provided as basic values…threshold values for sleep, bruxism, and teeth clenching to be continuously modified…”), based on result data derived through the artificial intelligence learning algorithm ([0109] “…learning unit (460) is provided to provide personalized feedback by applying artificial intelligence feedback to learn not only the user's teeth grinding and clenching…learns the causal relationship between sleep quality and the occurrence of teeth grinding…according to the user's teeth grinding status information managed by the above teeth grinding information management unit (430), sleep quality information management unit (440), and stimulation information management unit (450)…”), and
a user data transmission unit that transmits the user data generated by the user data generation unit to the user terminal ([0027] “…a communication unit that communicates information about the user's bruxism state in real time with the user terminal…”), based on a request signal received from the user terminal ( [0136] “…the user controls the operation of the teeth grinding detection and prevention device (100) according to the output teeth grinding status information”; [0045]; [0047]; [0104])
Kim ‘385 does not specifically disclose that the stimulus is a vibration stimulus or that the collected data is daily collected data for the limitations of:
a user data generation unit that measures a daily sleep time of the user and generates daily user data including at least one of the number of bruxism events occurring during the daily sleep time, and maximum intensity of the vibration stimulation; learns the number of the bruxism events occurring during the daily sleep time, and the maximum intensity of the vibration stimulation included in the daily user data, and transmits the daily user data generated by the user data generation unit to the user terminal.
Martini teaches a systems, apparatuses, software, and methods for monitoring/treating bruxism, including recording daily user data such as sleep time, number of bruxism events, duration of bruxism, etc; a machine learning unit that processes the daily user data to assess the level of bruxism; and “biofeedback by providing information that could trigger behavioral changes on people” ([Abstract]; [0003]; [0008]; [0048] – [0049]; Figs 6 - 9). Specifically for Claim 5, Martini teaches a user data generation unit that measures a daily sleep time of the user ([0008] “…the output comprises…an amount or quality of sleep…”; [0048] – [0049]) and generates daily user data (Fig. 6 and Fig. 7; [0048] – [0049]) including at least one of the number of bruxism events occurring during the daily sleep time (Fig. 6, “Number of episodes”), a duration of the bruxism (Fig. 6, “Average duration”), a degree of the bruxism (Fig. 6, “Average force”)
a bruxism diagnosis learning unit ([0049] “…use machine learning to predict the level of bruxism for a given set of input activities…”) that learns the number of the bruxism events occurring during the daily sleep time (Fig. 6, “Number of episodes”; [0010] “…machine learning classifier…assess the risk of the health condition based on the sensor data…”) the duration of the bruxism (Fig. 6, “Average duration”; [0010] “…machine learning classifier… based on the sensor data…”), included in the daily user data through a preset artificial intelligence learning algorithm ([0049] “…use machine learning to predict the level of bruxism for a given set of input activities…”), and that optimizes a bruxism diagnosis reference of the bruxism diagnosis unit, based on result data derived through the artificial intelligence learning algorithm ([0050] “…web server trains machine learning algorithms using the community results to generate prediction models…”; [0049] “…use machine learning to predict the level of bruxism for a given set of input activities.”; [0010] “…the risk prediction is generated by a machine learning classifier configured to assess the risk of the health condition based on the sensor data…”),
and a user data transmission unit that transmits the daily user data generated by the user data generation unit to the user terminal, based on a request signal received from the user terminal ([0060] “…download data from the server…”; [0033] “Bluetooth module…smartphone…packets…”; Fig. 10, Fig. 11; [0078] “…remote device 1202…configured to communicate with the digital processing device 1201…receive information…”).
Martini provides a motivation to combine at [0048] with “the user is able to view this presented data to determine their current level of a health condition such as bruxism with regards to their historical bruxism patterns and sleep quality…” and [0053] with “machine learning algorithms are used for training prediction models and/or making predictions. In some embodiments, the algorithm predicts a likelihood or probability (e.g., probability of the presence of a health condition such as bruxism, or the probability of a particular treatment being effective for reducing severity or symptoms of bruxism)…” A person having ordinary skill in the art before the effective filing date of the claimed invention would recognize that storing the sensor measurements and settings data (like that obtained by Kim ‘385 in view of Jadidi) on a daily basis would be useful for presenting the user with an ongoing history and progress of their bruxism and potential treatments (such as the vibration stimulation of Kim ‘385 in view of Jadidi). Further, a person having ordinary skill in the art before the effective filing date of the claimed invention would recognize that using the daily information, including treatment information, would be useful to determine if the treatment has been effective for reducing or relieving the bruxism.
Therefore, it would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to combine Kim ‘385 in view of Jadidi’s disclosed bruxism detection device that collects bruxism sensor data and stimulation settings for bruxism-relieving vibration stimulation with machine learning to determining bruxism characteristics and stimulation settings, with Martini’s taught daily user bruxism data gathering from sensors to input into a machine learning to determine the efficacy of treatment for bruxism, creating a single bruxism detection and feedback stimulus-providing device that can use daily user and sensor data to inform bruxism treatment and diagnosis that can be reported to a user over time.
Martini does not disclose maximum intensity of the vibration stimulation and the maximum intensity of the vibration stimulation included in the daily user data
Jadidi teaches maximum intensity of the vibration stimulation ([0040] “…may adjust and set the feedback signal, e.g. a vibration, an electric signal, or another form of stimulus to a level that will be suitable to the user…”; [0132] “…measurements and settings are stored in the apparatus…”) and the maximum intensity of the vibration stimulation included in the daily user data (([0160] “…the stimulation shall be able to be adjusted individually…on the basis of the table it can be ascertained which feedback fits the patient's bruxism pattern, where the feedback (the stimulation) is set regarding duration, intensity and delay…”; [0132] “…The measurements and the settings are stored in the apparatus…”; [0170]; [0218] – [0219] “…the certainty in the detection of nightly bruxism….”, “…7 nights…”)
The motivation for Claim 5 to combine Kim ‘385 and Jadidi is the same as that described in more detail in Claim 1. In summary, it would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to combine the bruxism detection device that applies a stimulus in response to determining bruxism has occurred disclosed by Kim ‘385 with the specifically vibration stimulus in response to bruxism detection taught by Jadidi, creating a single bruxism detection and feedback stimulus-providing device that can help mitigate bruxism occurrence by giving a user skin vibration feedback at a comfortable level to be sensed/felt/heard.
Conclusion
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/MELISSA JO MONTGOMERY/Examiner, Art Unit 3791
/JUSTIN XU/Primary Examiner, Art Unit 3791
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