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 .
Status of Claims
This Action is in response to the amendment filed on August 3, 2026.
As directed by the amendment: Claims 1, 9-11, and 19-20 were amended. Claims 1-20 are pending and currently under consideration for patentability under 37 CFR 1.104.
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.
Claim Objections
Claims 11 and 18 are objected to because of the following informalities:
Claim 11, line 3 recites “a wearable device” and the Examiner suggests –the wearable device—to clarify the antecedent basis from line 2.
Claim 18, line 3 recites “the multichannel waveform output” and the Examiner suggests –the multichannel waveform—to clarify the antecedent basis with line 2, which recites “a multichannel waveform.”
Appropriate correction is required.
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
Claim(s) 1-7 and 11-17 are rejected under 35 U.S.C. 103 as being unpatentable over Moaddeb et al. (2021/0330547) in view of Ong et al. (12,295,724).
Regarding claim 1, Moaddeb discloses a wearable device for vibratory stimulation (wearable tremor control system 100, Fig. 8), comprising:
a sensor (sensing elements 132, 134, Fig. 8) configured to receive data (configured to sense physiological signals indicative of tremor, see lines 8-14 of [0040]) and generate sensor output (“signals are received from one or more of the sensing elements 132, 134 that are in a range that is indicative to active tremor” see para. [0040]);
a processor (circuit board 190 with controller 192, Fig. 15) in communication with the sensor (“controller 192 and/or the App 189 may be configured (via software or firmware) to receive one or more signals from the sensing elements 132, 134, and to automatically adjust the vibration mode, either turning it on or off, or adjusting it between low, medium, and high vibration” see [0047]);
a memory (memory unit 197, Fig. 15; see App 189, Fig. 18, which comprises “a computer program embodied in a non-transitory computer readable medium” see lines 30-32 of [0046]) communicatively connected to the processor (“memory unit 197 which is configured to store data, such as patient data, calibration data, treatment programs, treatment data, … and measurement algorithms” see lines 19-24 of [0046]; see also the App 189, Fig. 18, that “allows the users to control and modify the operation of the wearable tremor control system. The application may comprise a computer program embodied in a non-transitory computer readable medium, that when executing on one or more computers … provides one or more operation instructions to the wearable tremor control system 100” see para. [0046]), the memory containing instructions configuring the processor to:
receive the sensor output (“controller 192 and/or the App 189 may be configured (via software or firmware) to receive one or more signals from the sensing elements 132, 134” see lines 12-15 of [0047]);
determine a symptom of a movement disorder of a user based on the sensor output (tremor frequency, “a derived function of the dominant tremor frequency that is measured or calculated by the sensing elements 132, 134” see the last sentence of [0047]);
calculate a waveform output based on the symptom of the movement disorder (the vibration waveform is calculated as a derived function of the dominant tremor frequency, “vibration elements 136, 138 may be configured to operate at a derived function of the dominant tremor frequency that is measured or calculated by the sensing elements 132, 134” see the last sentence of [0047]); and
command a transducer (the vibration element(s) 136, 138, Fig. 15) in communication with the processor to apply the waveform output (the vibration(s)) to the user to reduce the symptom of the movement disorder (“the vibration elements 136, 138 are caused to activate in a manner which is proportional to or matches in some way the reduction or increase in amplitude, intensity and/or prevalence of tremor.” See lines 17-22 of [0047]. The vibration operates at frequencies between 1-30 Hz which “can be very effective at dampening the shaking of a patient’s limb … configured to abate or completely stop the shaking caused by one or more forms of tremor” see lines 18-24 of [0040]).
Moaddeb is silent regarding categorizing the sensor output to one or more categories of symptoms of the movement disorder.
Ong teaches a related wearable tremor mitigation device (glove in Fig. 5) having one or more sensors (such as an accelerometer that produces a motion signal 234, see col. 9, lines 3-16) to produce a sensor output (motion signal 234, Fig. 1). Ong has a processor (tremor analysis system 110, which includes a severity module 111, Fig. 1) that determines a symptom (tremor) of a movement disorder of a user based on the sensor output (234) by categorizing the sensor output (motion signal 234; see col. 5, lines 55-64) to one or more categories of symptoms (at least two categories: 1) high severity tremor and 2) low severity tremor) of the movement disorder (“severity module 111 configured to determine the severity of a tremor based on the motion signal 234 … For example, for a strong tremor, or a high severity tremor, the motion signal will have higher frequency and/or amplitude than a mild tremor (or a low severity tremor)” see col. 5, lines 55-64). Ong provides stimulation to the limb (via tremor mitigating glove of Fig. 5, which includes a tremor mitigation device: “any device that is suitable for reducing tremor of a patient … [i.e.,] providing mechanical dampening, a device providing vibrostimulation and/or a device providing electrical stimulation” see col. 5, lines 34-48) and the severity of the tremor is used to control the stimulation provided (“the severity module controls the tremor mitigation device based on the motion signal, physiological data, a factor and user lifestyle information” see col. 7, lines 44-46). This provides an expected result that higher/stronger severity tremors that exhibit higher tremor frequency and/or amplitude will be treated with different stimulation parameters compared to lower/milder severity tremors that exhibit lower tremor frequency and/or amplitude, and thus a more tailored treatment is provided.
Therefore, it would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to modify the processor of Moaddeb to further determine the symptom of the movement disorder based on the sensor output by categorizing the sensor output to one or more categories of symptoms of the movement disorder, such as high severity tremor and low severity tremor based upon motion data frequency and amplitude, as taught by Ong so the higher/stronger severity tremors that exhibit higher tremor frequency and/or amplitude will be treated with different stimulation parameters compared to lower/milder severity tremors that exhibit lower tremor frequency and/or amplitude, and thus a more tailored treatment is provided.
Regarding claim 2, the modified Moaddeb/Ong device discloses wherein the symptom of a movement disorder is one of stiffness, rigidity, freezing, paralysis, paresis, dyskinesia, or a combination thereof (the symptom is a tremor frequency and/or amplitude, and a tremor is an involuntary movement, i.e., dyskinesia).
Regarding claim 3, the modified Moaddeb/Ong device discloses wherein the transducer (vibration element(s) 136, 138, Fig. 15 of Moaddeb) is further configured to apply the waveform output (vibration output) to a proprioceptive nerve of the user (configured to apply vibrations to the wrist/forearm area of the user as seen in Fig. 5 of Moaddeb. There are a plurality of proprioceptive nerves in this area).
Regarding claim 4, the modified Moaddeb/Ong device discloses wherein the proprioceptive nerve is in a proprioceptive tissue of one of flexor carpi radialis, flexor carpi ulnaris, extensor carpi radialis, extensor carpi ulnaris, or a combination thereof (these tissues are generally in the forearm and wrist area, which is where the vibration is applied as seen in Fig. 5 of Moaddeb).
Regarding claim 5, the modified Moaddeb/Ong device discloses wherein the transducer (vibration element(s) 136, 138, Fig. 15 of Moaddeb) is positioned to apply the waveform output (vibration) to one of a C5, C6, C7, C8, or T1 dermatomes (the wrist area, such as in Fig. 5 of Moaddeb, corresponds to dermatomes C6-C8).
Regarding claim 6, the modified Moaddeb/Ong device as currently combined is silent regarding wherein the processor is further configured to determine extraneous movement of the user by processing the sensor output to remove noise unrelated to the extraneous movement of the user.
However, Ong additionally teaches that its processor is configured to determine extraneous movement (non-tremor movement) of the user by processing the sensor output to remove noise unrelated to the extraneous movement of the user (“pre-processor 831 may apply one or more filters to filter out noise and non-tremor movement data, such as, e.g., low-pass filter high-pass filter band-pass filter band-stop filter or band-reject filter notch filter comb all-pass filter, or other linear and non-linear filters. For example, the pre-processor 831 may employ, e.g., a band-pass filter to extract tremor-related accelerometer data while filtering out non-tremor-related accelerometer data, thus producing a tremor signal representing Euler angles related to tremors.” See col. 22, lines 46-55).
Therefore, it would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to modify the processor of Moaddeb/Ong to additionally determine extraneous movement of the user by processing the sensor output to remove noise unrelated to the extraneous movement of the user as taught by Ong because this will allow the sensor to more accurately detect tremors, and disregard non-tremor related accelerometer data.
Regarding claim 7, the modified Moaddeb/Ong device discloses wherein the processor is further configured to: calculate a frequency of the waveform output that reduces an amplitude of the extraneous movement (the vibration waveform is calculated as a derived function of the dominant tremor frequency, “vibration elements 136, 138 may be configured to operate at a derived function of the dominant tremor frequency that is measured or calculated by the sensing elements 132, 134” see the last sentence of [0047] of Moaddeb. The vibration is intended to reduce tremor, which will reduce an amplitude of the tremor); and apply the frequency of the waveform output to reduce the amplitude of the extraneous movement (the vibration elements 136, 138 are caused to activate in a manner which is proportional to or matches in some way the reduction or increase in amplitude, intensity and/or prevalence of tremor.” See lines 17-22 of [0047] of Moaddeb. The vibration operates at frequencies between 1-30 Hz which “can be very effective at dampening the shaking of a patient’s limb … configured to abate or completely stop the shaking caused by one or more forms of tremor” see lines 18-24 of [0040] of Moaddeb).
Regarding claim 11, Moaddeb discloses a method of reducing symptoms of a movement disorder through a wearable device (wearable tremor control system 100, Fig. 8), comprising:
receiving, through a sensor of a wearable device (sensing elements 132, 134, are part of wearable tremor control system 100, see Fig. 8), data of a user (configured to sense physiological signals indicative of tremor, see lines 8-14 of [0040]);
generating sensor output based on the data of the user (“signals are received from one or more of the sensing elements 132, 134 that are in a range that is indicative to active tremor” see para. [0040]);
communicating the sensor output to a processor (circuit board 190 with controller 192, Fig. 15; “controller 192 and/or the App 189 may be configured (via software or firmware) to receive one or more signals from the sensing elements 132, 134, and to automatically adjust the vibration mode, either turning it on or off, or adjusting it between low, medium, and high vibration” see [0047]) of the wearable device (100, Fig. 15);
determining, a symptom of a movement disorder based on the sensor output (tremor frequency, “a derived function of the dominant tremor frequency that is measured or calculated by the sensing elements 132, 134” see the last sentence of [0047]);
calculating, at the processor (“controller 192 and/or the App 189 may be configured (via software or firmware) to receive one or more signals from the sensing elements 132, 134, and to automatically adjust the vibration mode, either turning it on or off, or adjusting it between low, medium, and high vibration” see [0047]), a waveform output (vibration waveform) based on the symptom of the movement disorder (the vibration waveform is calculated as a derived function of the dominant tremor frequency, “vibration elements 136, 138 may be configured to operate at a derived function of the dominant tremor frequency that is measured or calculated by the sensing elements 132, 134” see the last sentence of [0047]); and
commanding a transducer (the vibration element(s) 136, 138, Fig. 15) in communication with the processor to apply the waveform output (the vibration(s)) to the user (“the vibration elements 136, 138 are caused to activate in a manner which is proportional to or matches in some way the reduction or increase in amplitude, intensity and/or prevalence of tremor.” See lines 17-22 of [0047]).
Moaddeb is silent regarding categorizing the sensor output to one or more categories of symptoms of the movement disorder; and Moaddeb does not specifically state the symptom of the movement disorder is determined at the processor. However, utilizing a processor to evaluate sensor output is well known in the art.
For example, Ong teaches a related wearable tremor mitigation device (glove in Fig. 5) having one or more sensors (such as an accelerometer that produces a motion signal 234, see col. 9, lines 3-16) to produce a sensor output (motion signal 234, Fig. 1). Ong has a processor (tremor analysis system 110, which includes a severity module 111, Fig. 1) that determines, at the processor (via severity module 111), a symptom (tremor) of a movement disorder of a user based on the sensor output (234) by categorizing the sensor output (motion signal 234; see col. 5, lines 55-64) to one or more categories of symptoms (at least two categories: 1) high severity tremor and 2) low severity tremor) of the movement disorder (“severity module 111 configured to determine the severity of a tremor based on the motion signal 234 … For example, for a strong tremor, or a high severity tremor, the motion signal will have higher frequency and/or amplitude than a mild tremor (or a low severity tremor)” see col. 5, lines 55-64). Ong provides stimulation to the limb (via tremor mitigating glove of Fig. 5, which includes a tremor mitigation device: “any device that is suitable for reducing tremor of a patient … [i.e.,] providing mechanical dampening, a device providing vibrostimulation and/or a device providing electrical stimulation” see col. 5, lines 34-48) and the severity of the tremor is used to control the stimulation provided (“the severity module controls the tremor mitigation device based on the motion signal, physiological data, a factor and user lifestyle information” see col. 7, lines 44-46). This provides an expected result that higher/stronger severity tremors that exhibit higher tremor frequency and/or amplitude will be treated with different stimulation parameters compared to lower/milder severity tremors that exhibit lower tremor frequency and/or amplitude, and thus a more tailored treatment is provided.
Therefore, it would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to modify the processor of Moaddeb to further determine, at the processor, the symptom of the movement disorder based on the sensor output by categorizing the sensor output to one or more categories of symptoms of the movement disorder, such as high severity tremor and low severity tremor based upon motion data frequency and amplitude, as taught by Ong so the higher/stronger severity tremors that exhibit higher tremor frequency and/or amplitude will be treated with different stimulation parameters compared to lower/milder severity tremors that exhibit lower tremor frequency and/or amplitude, and thus a more tailored treatment is provided.
Regarding claim 12, the modified Moaddeb/Ong method discloses wherein the symptom of a movement disorder is one of stiffness, rigidity, freezing, paralysis, paresis, dyskinesia, or a combination thereof (the symptom is a tremor frequency and/or amplitude, and a tremor is an involuntary movement, i.e., dyskinesia).
Regarding claim 13, the modified Moaddeb/Ong method discloses further comprising applying the waveform output (vibration output) to a proprioceptive nerve of the user (configured to apply vibrations to the wrist/forearm area of the user as seen in Fig. 5 of Moaddeb. There are a plurality of proprioceptive nerves in this area).
Regarding claim 14, the modified Moaddeb/Ong method discloses wherein the proprioceptive nerve is in a proprioceptive tissue of one of flexor carpi radialis, flexor carpi ulnaris, extensor carpi radialis, extensor carpi ulnaris, or a combination thereof (these tissues are generally in the forearm and wrist area, which is where the vibration is applied as seen in Fig. 5 of Moaddeb).
Regarding claim 15, the modified Moaddeb/Ong method discloses wherein the transducer (vibration element(s) 136, 138, Fig. 15 of Moaddeb) is positioned within the wearable device to apply the waveform output (vibration) to one of a C5, C6, C7, C8, or T1 dermatomes (the wrist area, such as in Fig. 5 of Moaddeb, corresponds to dermatomes C6-C8).
Regarding claim 16, the modified Moaddeb/Ong method as currently combined is silent regarding determining, by the processor, extraneous movement of the user by processing the sensor output to remove noise unrelated to the extraneous movement of the user.
However, Ong additionally teaches that its processor is configured to determine extraneous movement (non-tremor movement) of the user by processing the sensor output to remove noise unrelated to the extraneous movement of the user (“pre-processor 831 may apply one or more filters to filter out noise and non-tremor movement data, such as, e.g., low-pass filter high-pass filter band-pass filter band-stop filter or band-reject filter notch filter comb all-pass filter, or other linear and non-linear filters. For example, the pre-processor 831 may employ, e.g., a band-pass filter to extract tremor-related accelerometer data while filtering out non-tremor-related accelerometer data, thus producing a tremor signal representing Euler angles related to tremors.” See col. 22, lines 46-55).
Therefore, it would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to modify the processor of Moaddeb/Ong to additionally determine extraneous movement of the user by processing the sensor output to remove noise unrelated to the extraneous movement of the user as taught by Ong because this will allow the sensor to more accurately detect tremors, and disregard non-tremor related accelerometer data.
Regarding claim 17, the modified Moaddeb/Ong method discloses further comprising calculating, by the processor, a frequency of the waveform output that reduces an amplitude of the extraneous movement (the vibration waveform is calculated as a derived function of the dominant tremor frequency, “vibration elements 136, 138 may be configured to operate at a derived function of the dominant tremor frequency that is measured or calculated by the sensing elements 132, 134” see the last sentence of [0047] of Moaddeb. The vibration is intended to reduce tremor, which will reduce an amplitude of the tremor); and apply the frequency of the waveform output to reduce the amplitude of the extraneous movement (the vibration elements 136, 138 are caused to activate in a manner which is proportional to or matches in some way the reduction or increase in amplitude, intensity and/or prevalence of tremor.” See lines 17-22 of [0047] of Moaddeb. The vibration operates at frequencies between 1-30 Hz which “can be very effective at dampening the shaking of a patient’s limb … configured to abate or completely stop the shaking caused by one or more forms of tremor” see lines 18-24 of [0040] of Moaddeb).
Claim(s) 8-9 and 18-19 are rejected under 35 U.S.C. 103 as being unpatentable over Moaddeb et al. (2021/0330547) in view of Ong et al. (12,295,724) as applied to claim 1 and claim 11 above, and further in view of Tass (2021/0401664).
Regarding claim 8, the modified Moaddeb/Ong device is silent regarding wherein the processor is further configured to generate a multichannel waveform output and apply the multichannel waveform output to the user through the transducer.
Tass teaches a related wearable vibrotactile stimulation device (Fig. 12A, Figs. 15-16) for treating brain disorders (treatment of Parkinson’s and movement disorders such as essential tremor and dystonia, see para. [0007]). Tass includes a processor (controller 10, Figs. 15-16) configured to generate a multichannel waveform output and apply the multichannel waveform output to the user (“Burst-like vibrotactile multi-channel stimulation with both high-frequency and low-frequency vibratory bursts can be delivered via 3 or more channels (e.g., fingertips).” See the last two sentences of [0070]) through one or more transducers (vibratory stimulators 11-14, Figs. 15-16). The multichannel stimulation helps “disrupt abnormal neuronal synchrony” to provide long-lasting relief of symptoms (see all of para. [0005]). Although Tass’ transducers shown on various fingertips, Tass additionally states the “multi-channel stimulation … can also be applied to other parts of a hand and, in general, to other parts of the body” (see the last two sentences of [0005]). Thus, one of ordinary skill in the art would recognize that the burst multi-channel stimulation would similarly disrupt abnormal neuronal synchrony at the wrist transducer locations of Moaddeb.
Therefore, it would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to modify the processor and transducer(s) of Moaddeb/Ong to be further configured to generate a multichannel waveform output and apply the multichannel output to the user through the transducer as taught by Tass because the multi-channel stimulation helps disrupt abnormal neuronal synchrony, which is beneficial in providing long-lasting relief of symptoms related to brain and/or movement disorders.
Regarding claim 9, the modified Moaddeb/Ong/Tass device discloses wherein each channel of the multichannel waveform is calculated (“Burst-like vibrotactile multi-channel stimulation with both high-frequency and low-frequency vibratory bursts can be delivered via 3 or more channels (e.g., fingertips).” See the last two sentences of [0070] of Tass) to target specific proprioceptive channels of the wrist of the user (in the modified device, the vibrating transducers 136, 138, Fig. 8 of Moaddeb are configured to target specific proprioceptive channels of the wrist based upon their location(s) on either side of the band 104, as seen in Fig. 8. This would target specific proprioceptive channels of the wrist such as the C8 and C6 dermatomes, which are known to be on the lateral sides of the wrist, in a similar manner as disclosed by the applicant. The instant specification states “vibratory stimulation 13 may be applied around a circumference of a user's wrist which may allow for stimulation of five distinct somatosensory channels via the C5-T1 dermatomes” see para. [0042] of the instant publication).
Regarding claim 18, the modified Moaddeb/Ong method is silent regarding generating, by the processor, a multichannel waveform; and applying the multichannel waveform output to the user through the transducer.
Tass teaches a related wearable vibrotactile stimulation device (Fig. 12A, Figs. 15-16) for treating brain disorders (treatment of Parkinson’s and movement disorders such as essential tremor and dystonia, see para. [0007]). Tass includes generating, by the processor (controller 10, Figs. 15-16), a multichannel waveform and applying the multichannel waveform output to the user (“Burst-like vibrotactile multi-channel stimulation with both high-frequency and low-frequency vibratory bursts can be delivered via 3 or more channels (e.g., fingertips).” See the last two sentences of [0070]) through one or more transducers (vibratory stimulators 11-14, Figs. 15-16). The multichannel stimulation helps “disrupt abnormal neuronal synchrony” to provide long-lasting relief of symptoms (see all of para. [0005]). Although Tass’ transducers shown on various fingertips, Tass additionally states the “multi-channel stimulation … can also be applied to other parts of a hand and, in general, to other parts of the body” (see the last two sentences of [0005]). Thus, one of ordinary skill in the art would recognize that the burst multi-channel stimulation would similarly disrupt abnormal neuronal synchrony at the wrist transducer locations of Moaddeb. Therefore, it would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to modify the processor and transducer(s) of Moaddeb/Ong to generate, by the processor, a multichannel waveform; and applying the multichannel waveform output to the user through the transducer as taught by Tass because the multi-channel stimulation helps disrupt abnormal neuronal synchrony, which is beneficial in providing long-lasting relief of symptoms related to brain and/or movement disorders.
Regarding claim 19, the modified Moaddeb/Ong/Tass method discloses wherein generating the multichannel waveform comprises generating a plurality of channels of waveform (for the plurality of transducers, see Figs. 15-16 of Tass), where each channel of the multichannel waveform is calculated (“Burst-like vibrotactile multi-channel stimulation with both high-frequency and low-frequency vibratory bursts can be delivered via 3 or more channels (e.g., fingertips).” See the last two sentences of [0070] of Tass) to target specific proprioceptive channels of the user (Each channel of the multichannel waveform will target specific proprioceptive channels based upon where the transducer(s) are located. In the modified device, the vibrating transducers 136, 138, Fig. 8 of Moaddeb are configured to target specific proprioceptive channels of the wrist based upon their location(s) on either side of the band 104, as seen in Fig. 8. This would target specific proprioceptive channels of the wrist such as the C8 and C6 dermatomes, which are known to be on the lateral sides of the wrist, in a similar manner as disclosed by the applicant. The instant specification states “vibratory stimulation 13 may be applied around a circumference of a user's wrist which may allow for stimulation of five distinct somatosensory channels via the C5-T1 dermatomes” see para. [0042] of the instant publication).
Claims 10 and 20 are rejected under 35 U.S.C. 103 as being unpatentable over Moaddeb et al. (2021/0330547) in view of Ong et al. (12,295,724) as applied to claims 1 and 11 above, and further in view of Heldman et al. (2014/0074179).
Regarding claim 10, the modified Moaddeb/Ong device discloses that stimulation parameters including frequency may be adjusted (“Parameters that may be adjusted, randomly, or non-randomly, by the controller 192 include: time of application of energy (mechanical, electrical, etc.), length of interval of time between application of energy, number of repetitions of application of energy, particular operational frequency of a non-static mode of energy (e.g., applying ultrasound at varying pulse rates), amplitude of the applied energy, timing of particular combinations of more than one element of a particular type of energy, or of two or more different types of energy. Any of these parameters can be increased or decreased.” see [0059] of Moaddeb), but is silent regarding wherein the processor is further configured to provide a train of waveform outputs through the transducer, wherein each waveform output of the train of waveform outputs has a frequency greater than a previous waveform output until the waveform output reaches a frequency with an output-to-input ratio that results in a suppressed output of extraneous movement.
Heldman teaches a related wearable device for movement disorder therapy (Fig. 1), wherein the processor (“micro-controller or processor” described in para. [0086]) configured to provide a train (series) of waveform outputs through a transducer (electrical stimulation electrodes, such as for deep brain stimulation, see para. [0005]), wherein each waveform output of the train of waveform outputs has a frequency greater than a previous waveform output until the waveform output reaches a frequency with an output-to-input ratio that results in a suppressed output of extraneous movement (see the trained tuning algorithm in Fig. 16, there is an initial set of stimulation parameters 200 that are increased incrementally at 202, and then it is determined whether there are any side effects 204 or if symptoms improve 206, and the parameters continue to increase until they reach their maximum setting or until symptoms are not improving. See para. [0190]: “If, however, the depicted algorithm determines that a) the subject's symptoms did improve under the provided therapy parameters or settings 206; b) symptoms did not improve and fewer than eight parameters/settings or groups thereof have been tested 214; or c) at least eight parameters/settings or group have been tested, but there has been some improvement within the last four iterations 216, then the algorithm next determines whether the therapy parameters or settings are being provided at a maximum value for one of those parameters or settings 208--in the depicted case pulse amplitude. Pre-determined parameter or settings limits may be defined to keep the therapy device operating within safe limits in order to protect the subject. If the specific parameter or setting that is being tested (in the depicted case, pulse amplitude) has not reached its maximum value, then the algorithm may again increase the value of that parameter or setting 202 and repeat the process. If the maximum value has already been reached for the particular parameter or setting, then that variable cannot be increased any further, and the algorithm determines whether another individual parameter or setting is at its maximum level 210--in the depicted case frequency. If the frequency has not reached its maximum value yet, then the algorithm reduces the amplitude to zero, increases the frequency 220 and then again begins the iterative process by initially increasing the amplitude 202 to provide therapy to the subject at the new levels of parameters or settings” and see para. [0191]: “This decision process is repeated by the intelligent algorithm until it determines that the best combination of contact(s) and parameters or settings has been achieved, resulting in an optimized therapy that takes into account the subject's side effects, symptoms, and/or other constraints”). Although Heldman is adjusting a parameter (frequency) of deep brain stimulation, one of ordinary skill in the art would have recognized that this guess-and-check type of optimization algorithm would be equally applicable to other stimulation modalities, including vibration frequency. Based upon Moaddeb, the symptom that would be intended to be reduced is the tremor frequency and/or amplitude.
Therefore, it would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to modify the processor of Moaddeb/Ong to provide a train of waveform outputs through the transducer, wherein each waveform output of the train of waveform outputs has a frequency greater than a previous waveform output until the waveform output reaches a frequency with an output-to-input ratio that results in a suppressed output of extraneous movement as generally taught by Heldman because this algorithm helps determine the particular stimulation parameters that are best suited to reduce symptoms while taking into account possible side effects.
Regarding claim 20, the modified Moaddeb/Ong method discloses that stimulation parameters including frequency may be adjusted (“Parameters that may be adjusted, randomly, or non-randomly, by the controller 192 include: time of application of energy (mechanical, electrical, etc.), length of interval of time between application of energy, number of repetitions of application of energy, particular operational frequency of a non-static mode of energy (e.g., applying ultrasound at varying pulse rates), amplitude of the applied energy, timing of particular combinations of more than one element of a particular type of energy, or of two or more different types of energy. Any of these parameters can be increased or decreased.” see [0059]), but is silent regarding providing, through the transducer, a train of waveform outputs, wherein each waveform output of the train of waveform outputs has a frequency greater than a previous waveform output until the waveform output reaches a frequency with an output-to-input ratio that results in a suppressed output of extraneous movement.
Heldman teaches a related wearable device for movement disorder therapy (Fig. 1), wherein the processor (“micro-controller or processor” described in para. [0086]) configured to provide a train (series) of waveform outputs through a transducer (electrical stimulation electrodes, such as for deep brain stimulation, see para. [0005]), wherein each waveform output of the train of waveform outputs has a frequency greater than a previous waveform output until the waveform output reaches a frequency with an output-to-input ratio that results in a suppressed output of extraneous movement (see the trained tuning algorithm in Fig. 16, there is an initial set of stimulation parameters 200 that are increased incrementally at 202, and then it is determined whether there are any side effects 204 or if symptoms improve 206, and the parameters continue to increase until they reach their maximum setting or until symptoms are not improving. See para. [0190]: “If, however, the depicted algorithm determines that a) the subject's symptoms did improve under the provided therapy parameters or settings 206; b) symptoms did not improve and fewer than eight parameters/settings or groups thereof have been tested 214; or c) at least eight parameters/settings or group have been tested, but there has been some improvement within the last four iterations 216, then the algorithm next determines whether the therapy parameters or settings are being provided at a maximum value for one of those parameters or settings 208--in the depicted case pulse amplitude. Pre-determined parameter or settings limits may be defined to keep the therapy device operating within safe limits in order to protect the subject. If the specific parameter or setting that is being tested (in the depicted case, pulse amplitude) has not reached its maximum value, then the algorithm may again increase the value of that parameter or setting 202 and repeat the process. If the maximum value has already been reached for the particular parameter or setting, then that variable cannot be increased any further, and the algorithm determines whether another individual parameter or setting is at its maximum level 210--in the depicted case frequency. If the frequency has not reached its maximum value yet, then the algorithm reduces the amplitude to zero, increases the frequency 220 and then again begins the iterative process by initially increasing the amplitude 202 to provide therapy to the subject at the new levels of parameters or settings” and see para. [0191]: “This decision process is repeated by the intelligent algorithm until it determines that the best combination of contact(s) and parameters or settings has been achieved, resulting in an optimized therapy that takes into account the subject's side effects, symptoms, and/or other constraints”). Although Heldman is adjusting a parameter (frequency) of deep brain stimulation, one of ordinary skill in the art would have recognized that this guess-and-check type of optimization algorithm would be equally applicable to other stimulation modalities, including vibration frequency. Based upon Moaddeb, the symptom that would be intended to be reduced is the tremor frequency and/or amplitude.
Therefore, it would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to modify the processor of Moaddeb/Ong to provide a train of waveform outputs through the transducer, wherein each waveform output of the train of waveform outputs has a frequency greater than a previous waveform output until the waveform output reaches a frequency with an output-to-input ratio that results in a suppressed output of extraneous movement as generally taught by Heldman because this algorithm helps determine the particular stimulation parameters that are best suited to reduce symptoms while taking into account possible side effects.
Response to Arguments
Applicant's arguments filed August 3, 2026, have been fully considered but they are not persuasive.
Regarding the argument that the claim 1 rejection is overcome because Moaddeb does not disclose the processor configured to perform the categorization step of “determine a symptom of a movement disorder of a user based on the sensor output by categorizing the sensor output to one or more categories of symptoms of the movement disorder” as required by amended claim 1 (see the penultimate paragraph of page 6 of the Remarks, through the second paragraph of page 7), this argument is partially persuasive.
The Examiner agrees that Moaddeb is silent regarding the categorization limitation and thus the 35 USC 102 rejection(s) are withdrawn. However, Ong et al. (12,295,724) has now been relied upon to teach the argued limitation. Claim 1 is now rejected under 35 USC 103 as being unpatentable over Moaddeb et al. (2021/0330547) in view of Ong et al. (12,295,724).
Regarding the argument that claims 6-7 depend from claim 1 and thus are patentable over Moaddeb by virtue of their dependency from claim 1, and Rosenbluth fails to cure the deficiencies of Moaddeb with respect to the categorization limitation (see the last paragraph of page 7 of the Remarks), this argument has been considered, but it is moot because Rosenbluth is not relied upon in any of the current rejection(s).
Instead, Ong et al. (12,295,724) has now been relied upon to teach the argued limitation. Claim 1 is now rejected under 35 USC 103 as being unpatentable over Moaddeb et al. (2021/0330547) in view of Ong et al. (12,295,724). Thus, claims 6-7 are not allowable based on their dependency from claim 1.
Regarding the argument that claims 8-9 depend from claim 1 and thus are patentable over Moaddeb by virtue of their dependency from claim 1, and Tass fails to cure the deficiencies of Moaddeb with respect to the categorization limitation (see the third full paragraph of page 8 of the Remarks), this argument is partially persuasive.
The Examiner agrees that Moaddeb is silent regarding the categorization limitation. However, Ong et al. (12,295,724) has now been relied upon to teach the argued limitation. Claim 1 is now rejected under 35 USC 103 as being unpatentable over Moaddeb et al. (2021/0330547) in view of Ong et al. (12,295,724). Thus, claims 8-9 are not allowable based on their dependency from claim 1.
Regarding the argument that claim 9 is not rendered obvious by Tass because Tass assigns channels to fingertips and does not disclose that each channel of the multichannel waveform output is calculated to target specific proprioceptive channels of the wrist of the user (see the last two paragraphs of page 8 of the Remarks), this argument is not persuasive.
Although Tass’ transducers shown on various fingertips, Tass additionally states the “multi-channel stimulation … can also be applied to other parts of a hand and, in general, to other parts of the body” (see the last two sentences of [0005]). Thus, one of ordinary skill in the art would recognize that the burst multi-channel stimulation would similarly disrupt abnormal neuronal synchrony at the wrist transducer locations of Moaddeb.
In the modified Moaddeb/Ong/Tass device, the vibrating transducers (136, 138, Fig. 8 of Moaddeb) are configured to target specific proprioceptive channels of the wrist based upon their location(s) on either side of the band (104, as seen in Fig. 8). This would target specific proprioceptive channels of the wrist such as the C8 and C6 dermatomes, which are known to be on the lateral sides of the wrist, in a similar manner as disclosed by the applicant. The instant specification states “vibratory stimulation 13 may be applied around a circumference of a user's wrist which may allow for stimulation of five distinct somatosensory channels via the C5-T1 dermatomes” (see para. [0042] of the instant publication).
Regarding the argument that claim 10 depends from claim 1 and thus is patentable over Moaddeb by virtue of its dependency from claim 1, and Heldman fails to cure the deficiencies of Moaddeb with respect to the categorization limitation (see the first three paragraphs of page 9 of the Remarks), this argument is partially persuasive.
The Examiner agrees that Moaddeb is silent regarding the categorization limitation. However, Ong et al. (12,295,724) has now been relied upon to teach the argued limitation. Claim 1 is now rejected under 35 USC 103 as being unpatentable over Moaddeb et al. (2021/0330547) in view of Ong et al. (12,295,724). Thus, claim 10 is not allowable based on its dependency from claim 1.
Regarding the argument that independent claim 11 is amended to recite “determining, at the processor, a symptom of a movement disorder based on the sensor output by categorizing the sensor output to one or more categories of symptoms of the movement disorder” which is substantively identical to amended claim 1, and thus Moaddeb fails to disclose this limitation for the same reasons discussed above with respect to claim 1 (see the penultimate paragraph of page 9 of the Remarks), this argument is partially persuasive.
The Examiner agrees that Moaddeb is silent regarding the categorization limitation. However, Ong et al. (12,295,724) has now been relied upon to teach the argued limitation. Claim 11 is now rejected under 35 USC 103 as being unpatentable over Moaddeb et al. (2021/0330547) in view of Ong et al. (12,295,724).
Regarding the argument that Ross does not cure the deficiencies of Moaddeb with respect to the categorization limitation (see the last paragraph of page 9 of the Remarks, through the first two paragraphs of page 10 of the Remarks), this argument has been considered, but it is moot because Ross is not relied upon in any of the current rejection(s).
Regarding the argument that claim 11 is patentable over Moaddeb and Ross, and claims 12-15 each depend from claim 11, and accordingly are patentable over Moaddeb and Ross (see the second paragraph of page 10 of the Remarks), this argument is not persuasive.
Claims 11-15 are now rejected under 35 USC 103 as being unpatentable over Moaddeb et al. (2021/0330547) in view of Ong et al. (12,295,724) based upon the amendment.
Regarding the argument that claims 16-17 depend from claim 11 and thus are patentable over Moaddeb and Ross by virtue of their dependency from claim 11, and Rosenbluth fails to cure the deficiencies of Moaddeb with respect to the categorization limitation (see the last paragraph of page 10 of the Remarks through the first paragraph of page 11), this argument has been considered, but it is moot because neither Ross nor Rosenbluth are relied upon in any of the current rejection(s).
Instead, Ong et al. (12,295,724) has now been relied upon to teach the argued limitation. Claim 11 is now rejected under 35 USC 103 as being unpatentable over Moaddeb et al. (2021/0330547) in view of Ong et al. (12,295,724). Thus, claims 16-17 are not allowable based on their dependency from claim 11.
Regarding the argument that claims 18-19 depend from claim 11 and thus are patentable over Moaddeb and Ross by virtue of their dependency from claim 11, and Tass fails to cure the deficiencies of Moaddeb with respect to the categorization limitation (see the penultimate paragraph of page 11 of the Remarks), this argument is partially persuasive.
The Examiner agrees that Moaddeb is silent regarding the categorization limitation. However, Ong et al. (12,295,724) has now been relied upon to teach the argued limitation. Claim 11 is now rejected under 35 USC 103 as being unpatentable over Moaddeb et al. (2021/0330547) in view of Ong et al. (12,295,724). Thus, claims 18-19 are not allowable based on their dependency from claim 11.
Regarding the argument that claim 20 depends from claim 11 and thus is patentable over Moaddeb by virtue of its dependency from claim 11, and Heldman fails to cure the deficiencies of Moaddeb with respect to the categorization limitation (see all of page 12 of the Remarks), this argument is partially persuasive.
The Examiner agrees that Moaddeb is silent regarding the categorization limitation. However, Ong et al. (12,295,724) has now been relied upon to teach the argued limitation. Claim 11 is now rejected under 35 USC 103 as being unpatentable over Moaddeb et al. (2021/0330547) in view of Ong et al. (12,295,724). Thus, claim 20 is not allowable based on its dependency from claim 11.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure. Kim et al. (2015/0182160) discloses a related wearable tremor sensing device that classified tremors into a rest tremor and an action tremor according to whether significant muscle action occurs. Klapper (2005/0234309) discloses a related apparatus for classification of movement states in Parkinson’s Disease, that automatically classified movement from accelerometer data into different states.
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
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/CHRISTOPHER E MILLER/ Examiner, Art Unit 3785
