DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Response to Amendment
The Office Action is responsive to amendments filed for application 17/544,749 filed on 10/27/2025. Please note claims 1, 3-15, 17-25 remain in the application.
In response to the amendments filed to claim 22, the previous rejections under 35 U.S.C 112(b) has been withdrawn.
Response to Arguments
Applicant's arguments filed 10/27/2025, page 16, with regards to the rejection of claim 21, have been fully considered but they are not persuasive.
In response to applicant's arguments against the references individually, one cannot show nonobviousness by attacking references individually where the rejections are based on combinations of references. See In re Keller, 642 F.2d 413, 208 USPQ 871 (CCPA 1981); In re Merck & Co., 800 F.2d 1091, 231 USPQ 375 (Fed. Cir. 1986).
In the previous rejection of claim 21 (and current rejection of amended claim 1, detailed later in this action), Litvak (now Melman) are used as primary references, each teaching wherein a tinnitus masking sound may be automatically adjusted by a processor in response to sensor signals.
Whether or not Dragicevic teaches automatically adjust a tinnitus filtering signal, it does teach using a deep neural network to determine presence and improvement of tinnitus in a user (¶[0074], lines 1-8). Given this, and the analogous nature of the cited references, it would have been obvious to apply the known technique of Dragicevic (specifically, use of a deep neural network) to a known device (The machine learning algorithm of Litvak or the control circuitry of Melman) ready for improvement to yield predictable results.
Applicant’s remaining arguments with respect to claims 1, 3-15, and 17-22 have been considered but are moot because the new ground of rejection does not rely on any reference applied in the prior rejection of record for any teaching or matter specifically challenged in the argument.
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, 3-15, and 17-22 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 1 recites the term "the controller” in lines 9 and 15, and “a controller” in line 12. It is unclear if the recitation in line 15 is to refer to the controller of line 9 or 12.
For examination purposes the term “the controller” of line 9 will be read as “a controller” and the term “a controller” of line 12 will be read as “wherein the controller is.”
Claims 3-15, and 17-22 are rejected as they are dependent upon claim 1.
Claim Rejections - 35 USC § 102
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention.
Claims 23-25 are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Dragicevic et al (hereinafter Dragicevic), US-PG-PUB No. 2019/0122125 (previously cited).
Regarding claim 23, Dragicevic discloses a method implemented by an ear-wearable electronic device (A wireless earpiece.....¶[0036], lines 2-3) worn by a wearer (The earpiece is wearable.....¶[0034], lines 3-4) configured for deployment in, an ear of a wearer (Shown in Fig. 1, the earpieces depicted are clearly configured for deployment in the ear), comprising:
measuring (The wireless earpieces measure biometrics and environmental context.....¶[0026], lines 2-4) using a physiologic sensor arrangement (The sensors include biometric (physiologic) sensors, which are both arranged within the device housing.....¶[0026], lines 2-4) of the device (Shown in Fig. 2, the sensors (32) are provided to the housing (12) of the device (60)), a plurality (Examiner notes that “a plurality of one or both of physiologic parameters and physiologic conditions” as recited in lines 3-4 of the claim is interpreted to mean either at least two parameters, at least two conditions, or at least one parameter and one condition) of physiologic parameters (Blood pressure and brainwave activity (via an EEG sensor).....¶[0036], lines 15-16) of the wearer;
producing, by the physiologic sensor arrangement, physiologic sensor signals (Sensor data (a type of signal) is produced to be used by an AI framework.....¶[0035], lines 8-10) in response to the physiologic sensor measurements (The data is reflective of sensor measurements.....¶[0026], lines 2-4); and
detecting (The device may determine (detect) via an AI framework if a user suffers from tinnitus.....¶[0074], lines 1-2), using a controller of the device (The AI framework is part of a processor (controller) of the device.....¶[0035], lines 7-8) presence of tinnitus of the wearer (The device may determine (detect) if a user (wearer) suffers from tinnitus.....¶[0074], lines 1-2) using the physiologic sensor signals (The AI framework detects the wearer’s physical state and well-being (including the presence of tinnitus disclosed in ¶[0074]) based on the sensor data.....¶[0035], lines 12-16).
Regarding claim 24, Dragicevic discloses the method of claim 23, as explained above.
Dragicevic additionally discloses measuring (The wireless earpieces measure biometrics and environmental context.....¶[0026], lines 2-4), using a non-physiologic sensor arrangement of the device (The sensors include environmental (non-physiologic) sensors, which are arranged within the device housing.....¶[0026], lines 2-4), at least one non-physiologic parameter (inertial sensors for measuring acceleration.....¶[0036], lines 3-4); producing, by the non-physiologic sensor arrangement, non-physiologic sensor signals (Sensor data (a type of signal) is produced to be used by an AI framework.....¶[0035], lines 8-10) in response to the non-physiologic sensor measurement (The data is reflective of sensor measurements.....¶[0026], lines 2-4); and detecting (The device may determine (detect) via an AI framework if a user suffers from tinnitus.....¶[0074], lines 1-2), using the controller (The AI framework is part of a processor (controller) of the device.....¶[0035], lines 7-8), presence of tinnitus of the wearer (The device may determine (detect) if a user (wearer) suffers from tinnitus.....¶[0074], lines 1-2) using the physiologic sensor signals and the non-physiologic sensor signals (The AI framework detects the wearer’s physical state and well-being (including the presence of tinnitus disclosed in ¶[0074]) based on all sensor data, including physiologic and non-physiologic.....¶[0035], lines 12-16).
Regarding claim 25, Dragicevic discloses the method of claim 24, as explained above.
Dragicevic additionally discloses receiving, from an external electronic device (Wireless earpieces couple with peripheral (external) devices via a network.....¶[0045], lines 1-3), contextual factor data (Data from network devices may include weather data (contextual factor data).....¶[0069], lines 9-13) indicative of one or more factors impacting a current context of the wearer (The data provides context…..¶[0069], lines 11-12); and detecting (The device may determine (detect) via an AI framework if a user suffers from tinnitus.....¶[0074], lines 1-2), using the controller (The AI framework is part of a processor (controller) of the device.....¶[0035], lines 7-8), the presence of tinnitus of the wearer (The device may determine (detect) if a user (wearer) suffers from tinnitus.....¶[0074], lines 1-2) using the physiologic sensor signals, the non-physiologic sensor signals, and the contextual factor data (The AI framework detects the wearer’s physical state and well-being (including the presence of tinnitus disclosed in ¶[0074]) based on the sensor data, as well as contextual awareness (utilizing contextual factor data, which it itself (at least in the case of weather) is provided by sensors of external devices).....¶[0035], lines 12-16, ¶[0027], lines 3-4).
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.
Claims 1, 3, 8, 10, 12-15, and 17 are rejected under 35 U.S.C. 103 as being unpatentable over in view of Melman, US-PG-PUB No. 2022/0117518 in view of Dragicevic et al (hereinafter Dragicevic), US-PG-PUB No. 2019/0122125 (previously cited), in further view of Eder, US-PG-PUB No. 2021/0260377.
Regarding claim 1, Melman discloses an ear-wearable electronic device (An apparatus embodied as a hearing aid system.....¶[0030], lines 1, 8, 18-20), comprising:
a sound generator (Signal processing circuitry generates data (sound) signals to drive the actuator of an auditory prosthesis, producing sound heard by a wearer.....¶[0031], lines 10-14) disposed in the housing (Shown in Fig. 2, control circuitry (210) is provided to apparatus (200) and configured to produce at least a tinnitus masking sound (The control circuitry tailors (produces) masking signals (sounds) to counteract tinnitus.....¶[0032], lines 4-8);
a physiologic sensor arrangement (Biological monitor which provides physiologic sensor signals.....¶[0031], lines 4-5) connected to the electronic device (The control circuitry receives sensor signals from the biological monitor.....¶[0031], lines 1-2) and configured to measure a plurality of physiologic parameters (Biomarkers, such as EEG results, blood oxygenation, and MMN response.....¶[0031], lines 5-6, ¶[0061], lines 1-4, 20-24) of the wearer, the physiologic sensor arrangement configured to produce physiologic sensor signals in response to the physiologic sensor measurements (The biological monitor produces sensor signals indicative of biological (physiologic) response.....¶[0031], lines 3-5);
a microphone arrangement (One or more microphones.....¶[0033], lines 2-4) coupled to a controller (Shown in Fig. 2B, the control circuity (210) and microphone (250) are coupled within the apparatus (200)), the microphone arrangement comprising one or more microphones (¶[0033], lines 2-4) configured to generate a microphone signal (Transducer signal (252).....¶[0033], line 6) indicative of sound within the wearer's current acoustic environment (Microphone signals are indicative of a recipient’s (wearer’s) sound (acoustic) environment.....¶[0050], lines 6-8); and wherein
the controller (Shown in Fig. 2B, Control Circuitry (210)) is operatively coupled to the sound generator and the physiologic sensor arrangement (Shown in Fig. 2B, the control circuitry receives biological signals (222) from the physiological sensor arrangement (220) and sends control signals (212) to the sound generator (230)), the controller configured to detect the presence of tinnitus of the wearer (Tinnitus analysis circuitry of the controller (Shown in Fig. 2B, (270)) determines (detects) whether the recipient is perceiving tinnitus.....¶[0039], lines 13-15) using the physiologic sensor signals (Presence is determined via sensor signals (222).....¶[0039], lines 13-15);
wherein the controller is configured to:
classify the acoustic environment of the wearer (Monitoring circuitry (260) of the controller (210) detects the type of acoustic environment of the wearer.....¶[0037], lines 18-22) as a specified one of a plurality of disparate acoustic environments (Environments may be classified as “sufficiently loud” and “sufficiently quiet”.....¶[0037], lines 20-24); and
process the physiologic sensor signals (The physiologic sensor signals (222) are compared (processed).....¶[0032], lines 1-4) to adjust the tinnitus masking sound produced by the sound generator (Adjusts masking stimulus (sounds).....¶[0020], lines 1-3, ¶[0019], lines 3-4) using one or more of the physiologic sensor signals (By monitoring biomarkers (physiologic sensor signals).....¶[0020], lines 9-10) and parameter values associated with the specified acoustic environment (Characteristics (parameter values) of the auditory environment are also monitored to determine how to apply the masking sound.....¶[0037], lines 11-13).
Melman fails to explicitly disclose wherein the electronic device comprises a housing configured to be worn about the ear of the wearer and wherein the physiological sensors and microphone are supported by the housing, and additionally fails to disclose wherein the controller comprises a processor configured to classify the environment and process the sensor signals via separate deep neural networks.
However, Dragicevic teaches an analogous hearing device (A wireless earpiece embodied as a hearing device.....¶[0073], lines 4-6), comprising of a housing configured to be worn about the ear of the wearer (¶[0075], lines 1-2), a physiologic sensor arrangement (Physiologic/biometric sensors (32A, 32B).....¶[0029], lines 1-3) disposed in or supported by the housing (Shown in Figs. 1 the sensors (32A, 32B) are disposed in the housings (12A, 12B).....¶[0028], lines 4-7), a microphone arrangement supported by the housing (The sensors may also include microphones.....¶[0026], line 4) and coupled to a controller (Shown in Fig. 2, sensors (32) are coupled to processor (controller) (30).....¶[0023], lines 3-5),
wherein the controller comprises, or is operatively coupled to, a processor (The controller is a processor) configured with instructions (Shown in Fig. 2, processor (30) receives instructions from memory (40).....¶[0041], lines 1-3) to process the physiologic sensor signals (Both biological and environmental sensor data may be processed via an artificial intelligence framework.....¶[0029], lines 14-18) via a deep neural network (The artificial intelligence framework may be a deep neural network.....¶[0035], lines 16-20), to alert a user to adjust a tinnitus therapy sound (Based on detection of tinnitus based on the AI framework and sensors, the device prompts a user to identify a tinnitus frequency, which is then used to adjust the filtered audio played by the device.....¶[0074], lines 1-4, 6-8).
Therefore, it would have been obvious to someone of ordinary skill in the art before the effective filing date of the claimed invention to have modified the disclosure of Melman to incorporate the teachings of Dragicevic, and provide wherein the electronic device comprises a housing configured to be worn about the ear of the wearer, wherein the physiological sensors and microphone are supported by the housing, and wherein the controller comprises a processor configured to process the physiological sensor signals via a deep neural networks. This would provide the benefit of a tinnitus masking device with improved portability (Dragicevic, ¶[0041], lines 16-17), as well as improved context awareness when making determinations regarding a wearer condition (Dragicevic, ¶[0027], lines 8-13).
This further combination still fails to teach wherein the processor is configured to classify the acoustic environment of the wearer via a deep neural network.
However, Eder teaches an electronic hearing device (A hearing implant.....¶[0021], line 3) wherein a controller comprises a processor (Signal processing system.....¶[0035], lines 1-2) configured with instructions (¶[0064], lines 3-4) to: classify (Classifier.....¶[0034], lines 1-2), via a deep neural network (A convolutional neural network comprising multiple layers (deep neural network).....¶[0038], lines 4-6), the acoustic environment of the wearer (Sound captured by a microphone of a user device.....¶[0105], lines 5) as a specified one of a plurality of disparate acoustic environments (Music, traffic, and worksite environments.....¶[0105], lines 10-12);
Therefore, it would have been obvious to someone of ordinary skill in the art before the effective filing date of the claimed invention to have modified the combination of Melman and Dragicevic to incorporate the teachings of Eder, and provide wherein the processor is configured to classify the acoustic environment of the wearer via a deep neural network separate from the deep neural network used to adjust the tinnitus masking sound. This would provide the benefit of a device which provides enhanced sound clarity over systems not using a deep neural network (Eder, ¶[0106], lines 1-4).
Regarding claim 3, the combination of Melman, Dragicevic, and Eder, as explained above, teach the device of claim 1.
Melman additionally teaches wherein: the physiologic sensor arrangement comprises a sensor configured to produce an electroencephalography (EEG) signal (Cortical monitor for EEG measurement.....¶[0040], lines 2-3); and the controller is configured to: produce EEG spectral power data (Electrical activity of the brain.....¶[0040], line 13) using the EEG signal; and detect presence of tinnitus (¶[0041], lines 2-3) of the wearer using the EEG spectral power data (¶[0041], line 2).
Regarding claim 8, the combination of Melman, Dragicevic, and Eder, as explained above, teach the device of claim 1, but fail to teach wherein the sensor arrangement comprises a biochemical sensor configured to sense changes in blood glucose levels of the wearer.
Dragicevic teaches a biochemical sensor configured to sense changes in blood glucose levels of the wearer (An earpiece sensor package may contain a glucose sensor (¶ [0036], lines 11-13), used to alert a user with deteriorating (changing) blood sugar levels…..¶ [0071], lines 1-6).
Therefore, it would have been obvious to someone of ordinary skill in the art before the effective filing date of the claimed invention to have modified the teachings of Melman, Dragicevic, and Eder to further incorporate the teachings of Dragicevic and provide wherein the physiologic sensor arrangement comprises a biochemical sensor configured to sense changes in the blood glucose levels of the wearer. This would provide a system that may alert a user to deteriorating physical conditions (Dragicevic, ¶ [0071], lines 1-3).
Regarding claim 10, the combination of Melman, Dragicevic, and Eder, as explained above, teach the device of claim 1.
Dragicevic teaches wherein a non-physiological sensor may be optical sensor (Optical sensor.....¶[0084], line 30) configured to generate an optical sensor signal indicative of ambient light intensity (Optical sensor measures light.....¶[0084], line 34), and wherein a controller is configured to detect presence of tinnitus of the wearer using the optical sensor signal (Tinnitus is detected based on the AI framework and sensors.....¶[0074], lines 1-4).
Therefore, it would have been obvious to someone of ordinary skill in the art before the effective filing date of the claimed invention to have modified the combination of Melman, Dragicevic, and Eder to further incorporate the teachings of Dragicevic, and provide wherein the non-physiological sensor supported by the housing and coupled to the controller is an optical sensor, indicative of ambient light intensity, wherein the controller is configured to detect one or more of absence, presence, and severity of tinnitus of the wearer using the optical sensor signal. This would provide a system with improved context awareness when making determinations regarding a wearer condition (Dragicevic, ¶[0027], lines 8-13).
Regarding claim 12, the combination of Melman, Dragicevic, and Eder, as explained above, teach the device of claim 1.
Dragicevic teaches wherein a non-physiological sensor may be barometric pressure sensor (Barometer.....¶[0036], line 21) configured to generate a pressure sensor signal indicative of ambient barometric pressure (The function of a barometer), and wherein a controller is configured to detect presence of tinnitus of the wearer using the optical sensor signal (Tinnitus is detected based on the AI framework and sensors.....¶[0074], lines 1-4).
Therefore, it would have been obvious to someone of ordinary skill in the art before the effective filing date of the claimed invention to have modified the combination of Melman, Dragicevic, and Eder to further incorporate the teachings of Dragicevic, and provide wherein the non-physiological sensor supported by the housing and coupled to the controller is a barometric pressure sensor, configured to generate a pressure sensor signal indicative of ambient barometric pressure; and wherein the controller is configured to detect one or more of absence, presence, and severity of tinnitus of the wearer using the pressure sensor signal. This would provide a system with improved context awareness when making determinations regarding a wearer condition (Dragicevic, ¶[0027], lines 8-13).
Regarding claim 13, the combination of Melman, Dragicevic, and Eder, as explained above, teach the device of claim 1.
Melman additionally teaches wherein the controller is configured to adjust the tinnitus masking sound (¶[0020], line 13) produced by the sound generator by producing a tinnitus masking sound that substantially matches the wearer's tinnitus (The masking stimulus may be set at a level to just suppress the auditory phantom (tinnitus), thus matching it’s level.....¶[0020], lines 16-19).
Regarding claim 14, the combination of Melman, Dragicevic, and Eder, as explained above, teach the device of claim 1.
Melman additionally discloses wherein: the controller is configured to adjust the tinnitus masking sound produced by the sound generator (¶[0020], line 13) using the physiologic sensor signals (Presence is determined via sensor signals (222).....¶[0039], lines 13-15); and the physiologic sensor signals are produced by an EEG sensor and a biochemical sensor (Sensor signals include EEG sensor data and blood oxygenation (a biochemical measure) sensor data.....¶[0031], lines 5-6, ¶[0061], lines 1-4, 20-24).
Regarding claim 15, the combination of Melman, Dragicevic, and Eder, as explained above, teach the device of claim 1.
Melman additionally teaches wherein the controller is configured to adjust a loudness level (Adjust a magnitude (loudness level) of the masking stimulus.....¶[0020], lines 5-6) of the tinnitus masking sound produced by the sound generator (¶[0020], lines 1-6).
Regarding claim 17, the combination of Melman, Dragicevic, and Eder, as explained above, teach the device of claim 1.
Melman additionally teaches a non-physiologic sensor arrangement (The microphone arrangement of claim 1) comprising one or more non-physiologic sensors (The microphones of claim 1) configured to sense a least one non-physiologic parameter (ambient sound) impacting a current context of the wearer (Monitoring circuitry (260) of the controller (210) detects the type of acoustic environment of the wearer.....¶[0037], lines 18-22), the non-physiologic sensor arrangement configured to produce non-physiologic sensor signals (Transducer signal (252).....¶[0033], line 6) in response to the non-physiologic sensor measurement (Microphone signals are indicative of a recipient’s (wearer’s) sound (acoustic) environment.....¶[0050], lines 6-8); and wherein the controller is configured to detect presence of tinnitus of the wearer (Masking sounds are enabled/disabled, implying a detection of the presence of tinnitus.....¶[0020], lines 6-7, ¶[0019], lines 3-4) using the physiologic sensor signals (By monitoring biomarkers (physiologic sensor signals).....¶[0020], lines 9-10) and the non-physiologic sensor signals (Characteristics (parameter values) of the auditory environment are also monitored to determine how to apply the masking sound.....¶[0037], lines 11-13).
Claim 4 is rejected under 35 U.S.C. 103 as being unpatentable over in view of Melman in view of Dragicevic and Eder, in further view of Cho, US-PG-PUB 2022/0408205 (previously cited).
Regarding claim 4, the combination of Melman, Dragicevic, and Eder, as explained above, teach the device of claim 1, but fail to teach wherein the physiologic sensor arrangement comprises a sensor configured to produce an electrocardiogram (ECG) signal; and the controller is configured to detect tinnitus of the wearer using the heart rate variability data derived from the ECG signal.
Cho teaches a tinnitus treatment system wherein a physiologic sensor arrangement comprises a sensor configured to produce an electrocardiogram (ECG) signal (A biometric (physiologic) acquisition sensor may acquire ECG information…..¶ [0107], lines 1-5); and a controller configured to: produce heart rate variability data (A tinnitus treatment program providing unit (controller) acquires (produces) HRV information…..¶ [0096], lines 1-5) using the ECG signal (Biometric information (ECG, as stated above) may be used to provide HRV data for stress analysis…..¶ [0164], lines 1-5); and detect the severity of tinnitus of the wearer using the heart rate variability data (Heart rate variability data is correlated with user stress levels, which correspond to the intensity of tinnitus treatment, establishing a correlation between stress levels and the severity of user tinnitus…..¶ [0164], lines 1-11).
Therefore, it would have been obvious to someone of ordinary skill in the art before the effective filing date of the claimed invention to have modified the teachings of Melman, Dragicevic, and Eder to incorporate the teachings of Cho and provide wherein: the physiologic sensor arrangement comprises a sensor configured to produce an ECG signal; and the controller is configured to: produce heart rate variability data using the ECG signal; and detect severity of tinnitus of the wearer using the heart rate variability data. This would provide the benefit of a system which can match intensity of treatment to the intensity of user symptoms (Cho, ¶ [0164], lines 1-3).
Claim 5 is rejected under 35 U.S.C. 103 as being unpatentable over in view of Melman in view of Dragicevic and Eder, in further view of Cho and Hu et al (hereinafter Hu), US-PG-PUB 2010/0274144 (previously cited).
Regarding claim 5, the combination of Melman, Dragicevic, and Eder, as explained above, teach the device of claim 1, but fail to teach a photoplethysmography (PPG) sensor producing a PPG signal; and the controller is configured to: produce heart rate variability data using the PPG signal; and identify tinnitus of the wearer using the heart rate variability data.
Cho teaches detecting the severity of tinnitus of the wearer using heart rate variability data (Heart rate variability data is correlated with user stress levels, which correspond to the intensity of tinnitus treatment, implying a further correlation between stress levels and the severity of user tinnitus…..¶ [0164], lines 1-11).
Therefore, it would have been obvious to someone of ordinary skill in the art before the effective filing date of the claimed invention to have modified the teachings of Melman, Dragicevic, and Eder to incorporate the teachings of Cho and provide detecting the severity of tinnitus of the wearer using the heart rate variability data. This would provide a system which can match intensity of treatment to the intensity of user symptoms (Cho, ¶ [0164], lines 1-3).
However, the combination of Melman, Dragicevic, and Eder, and Cho do not teach wherein: the physiologic sensor arrangement comprises a sensor configured to produce a photoplethysmography (PPG) signal; and the controller is configured to: produce heart rate variability data using the PPG signal.
Hu teaches an earpiece comprising a sensor configured to produce a photoplethysmography (PPG) signal (An earpiece accommodates a measurement unit for PPG signal…..¶ [0025], lines 10-12); and a controller (A control and processing unit (controller)…..¶ [0030], lines 1-3) configured to: produce heart rate variability data using the PPG signal (The controller analyzes PPG signal and outputs a heart rate variability signal…..¶ [0030], lines 1-6).
Therefore, it would have been obvious to someone of ordinary skill in the art before the effective filing date of the claimed invention to have modified the teachings of Melman, Dragicevic, Eder, and Cho and incorporate the teachings of Hu to provide wherein the physiologic sensor arrangement comprises a sensor configured to produce a photoplethysmography (PPG) signal; and the controller is configured to: produce heart rate variability data using the PPG signal. This would provide a system that provides HRV measurement data utilizing compact and cheap-to-produce methods (Hu, ¶ [0014], lines 1-6).
Claim 6 is rejected under 35 U.S.C. 103 as being unpatentable over in view of Melman in view of Dragicevic and Eder, in further view of Popelka et al (hereinafter Popelka), US-PG-PUB 2019/0201657 (previously cited).
Regarding claim 6, the combination of Melman, Dragicevic, and Eder, as explained above, teach the device of claim 1, but fail to teach wherein the physiologic sensor arrangement comprises an EMG sensor.
Popelka teaches a sensor configured to produce an electromyography (EMG) signal (Neural activity is evaluated via a noninvasive EMG sensor…..¶ [0165], lines 1-4).
Therefore, it would have been obvious to someone of ordinary skill in the art before the effective filing date of the claimed invention to have modified the teachings of Melman, Dragicevic, and Eder to incorporate the teachings of Popelka and provide wherein the physiologic sensor arrangement comprises a sensor configured to produce an electromyography (EMG) signal. This would provide a system which can evaluate the effectiveness of tinnitus therapy (Popelka, ¶ [0164], lines 3-10).
Claims 7, 9, 11, 18-22 are rejected under 35 U.S.C. 103 as being unpatentable over in view of Melman in view of Dragicevic and Eder, in further view of Litvak et al (hereinafter Litvak), US-PG-PUB No. 2023/0173271 (previously cited).
Regarding claim 7, the combination of Melman, Dragicevic, and Eder, as explained above, teach the device of claim 1, but fail to teach wherein the physiologic sensors include an electrodermal activity sensor.
Litvak teaches a tinnitus treatment device wherein a physiologic sensor arrangement comprises a sensor configured to produce an electrodermal activity signal (The sensors may measure skin conductance level (electrodermal activity)…..¶ [0016], lines 6-10).
Therefore, it would have been obvious to someone of ordinary skill in the art before the effective filing date of the claimed invention to have modified the disclosures of Melman, Dragicevic, and Eder to incorporate the teachings of Litvak and provide wherein the physiologic sensor arrangement comprises a sensor configured to produce an electrodermal activity signal. This would provide the benefit of a system that is able to use combinations of sensor readings to evaluate a user’s tinnitus (Litvak, ¶ [0023], lines 20-25).
Regarding claim 9, the combination of Melman, Dragicevic, and Eder, as explained above, teach the device of claim 1, but fail to teach a motion sensor supported by the housing and coupled to the controller, configured to generate a signal indicative of wearer motion; and wherein the controller is configured to detect the tinnitus of the wearer using the signal.
However, Litvak teaches a tinnitus treatment device wherein a motion sensor (An external sensor package may include a movement sensor.....¶[0016], lines 1-7, 13) supported by the housing and coupled to the controller (External sensors communicate with the stimulator (housing) by way of the controller.....¶[0013], lines 5-10), the motion sensor configured to generate a motion sensor signal indicative of wearer motion (Sensors may output data representing (indicating) measured properties.....¶[0013], lines 4-6); wherein a controller (Controller connected to implanted and external sensors…..¶ [0013], lines 2-10) is configured to detect the severity of tinnitus of the wearer using a motion sensor signal (Measured properties of implanted and external sensors are used with user input and machine learning algorithms to correlate sensor readings with the change in severity of user tinnitus…..¶ [0025], lines 10-16, ¶ [0024], lines 1-6).
Therefore, it would have been obvious to someone of ordinary skill in the art before the effective filing date of the claimed invention to have modified the disclosures of Melman, Dragicevic, and Eder to incorporate the teachings of Litvak and provide wherein the physiologic sensor arrangement comprises a motion sensor disposed in or supported by the housing and coupled to the controller, the motion sensor configured to generate a motion sensor signal indicative of wearer motion; wherein the controller is configured to detect one or more of absence, presence, and severity of tinnitus of the wearer using the motion sensor signal. This would provide the benefit of a system that is able to use combinations of sensor readings to evaluate a user’s tinnitus (Litvak, ¶ [0023], lines 20-25).
Regarding claim 11, the combination of Melman, Dragicevic, and Eder, as explained above, teach the device of claim 1, but fail to explicitly teach wherein the controller is configured to detect tinnitus of the wearer using the microphone signal.
However, Litvak teaches a tinnitus treatment device wherein a controller is configured to detect severity of tinnitus of the wearer (The external sensors may be used to detect improvement (relative severity) of tinnitus based on measured properties of external sensors…..¶ [0025], lines 10-16, ¶ [0024], lines 1-6) using a microphone signal (An external sensor package may include a microphone.....¶[0019], lines 1-3).
Therefore, it would have been obvious to someone of ordinary skill in the art before the effective filing date of the claimed invention to have modified the disclosures of Melman, Dragicevic, and Eder to incorporate the teachings of Litvak and provide wherein the controller is configured to detect tinnitus of the wearer using the microphone signal. This would provide the benefit of a system that is able to use combinations of sensor readings to evaluate a user’s tinnitus (Litvak, ¶ [0023], lines 20-25).
Regarding claim 18, the combination of Melman, Dragicevic, and Eder, as described above teach the device of claim 17, but fail to teach wherein tinnitus is detected using additional contextual factor data received from an external device in wireless communication with the first device.
Litvak teaches a tinnitus therapy device comprising a communication device supported by a housing (A cochlear implant may wirelessly communicate with an external computing device, requiring a wireless transceiver.....¶[0052], lines 6-10), configured to wirelessly communicate with an external electronic device (The implant may receive external sensor data from a phone.....¶[0019], lines 4-6) and receive contextual factor data indicative of one or more factors impacting a current context of the wearer (The external sensor may also provide stress levels (contextual factor data).....¶[0016], lines 6-8); wherein the controller is configured to detect the severity of tinnitus of the wearer (Measured properties of implanted and external sensors are used with user input and machine learning algorithms to correlate sensor readings with the change in severity of user tinnitus…..¶ [0025], lines 10-16, ¶ [0024], lines 1-6) using physiologic sensor signals (A sensor for detecting wearer heart rate…..¶ [0016], lines 6-9), the non-physiologic sensor signals (An accelerometer for detecting wearer movement…..¶ [0025], lines 16-21), and contextual factor data (The stress level of a wearer…..¶ [0015], lines 6-10).
Therefore, it would have been obvious to someone of ordinary skill in the art before the effective filing date of the claimed invention to have modified the disclosures of Melman, Dragicevic, and Eder to incorporate the teachings of Litvak and provide wherein tinnitus is detected using additional contextual factor data received from an external device in wireless communication with the first device. This would provide the benefit of a system that is able to use combinations of sensor readings to evaluate a user’s tinnitus (Litvak, ¶ [0023], lines 20-25).
Regarding claim 19, the combination of Melman, Dragicevic, Eder, and Litvak, as explained above, teach the device of claim 18.
Dragicevic additionally teaches wherein contextual factor data used in AI determinations comprises local weather data (Current weather conditions…..¶[0045], line 13).
Therefore, it would have been obvious to someone of ordinary skill in the art before the effective filing date of the claimed invention to have modified the combination of Melman, Dragicevic, Eder, and Litvak to further incorporate the teachings of Dragicevic, and provide wherein the contextual factor data comprises local weather data. This would provide a system with improved context awareness when making determinations regarding a wearer condition (Dragicevic, ¶[0027], lines 8-13).
Regarding claim 20, the combination of Melman, Dragicevic, Eder, and Litvak, as explained above, teach the device of claim 18.
Litvak additionally teaches wherein a processor (¶ [0036], lines 1-3) is configured with instructions to process the physiologic sensor signals (The processor is enabled to perform the functions of the device…..¶ [0038], lines 3-5) via a machine learning algorithm to adjust a tinnitus treatment signal (Physiologic sensor data of implantable sensors, the detection of tinnitus severity, and user input are jointly evaluated by a machine learning algorithm to predictively apply changes to the tinnitus treatment…..¶ [0025], lines 1-17, ¶ [0024], lines 1-6).
Therefore, it would have been obvious to someone of ordinary skill in the art before the effective filing date of the claimed invention to have modified the combination of Melman, Dragicevic, Eder, and Litvak to further incorporate the teachings of Litvak and provide wherein the processor is further configured with instructions to process one or more of the physiologic sensor signals, non-physiologic sensor signals, and the contextual factor data via a machine learning algorithm to adjust the tinnitus masking sound produced by the sound generator. This would provide the benefit of a system wherein the masking sound may be adjusted by the controller without the recipient indicating that the tinnitus has changed (Litvak, ¶[0024], lines 18-20).
Regarding claim 21, the combination of Melman, Dragicevic, Eder, and Litvak teach the device of claim 18, as explained above.
Litvak additionally teaches wherein a processor (¶ [0036], lines 1-3) is configured with instructions to process (The processor is enabled to perform the functions of the device…..¶ [0038], lines 3-5) and physiologic sensor signals (A sensor for detecting wearer heart rate…..¶ [0016], lines 6-9) and one or more non-physiologic sensor signals (An accelerometer for detecting wearer movement…..¶ [0025], lines 16-21) and contextual factor data (The stress level of a wearer…..¶ [0015], lines 6-10), via a machine learning algorithm (analogous to neural networks.....¶[0024], lines 3-6), to adjust (Sensor data, the detection of tinnitus severity, and user input are jointly evaluated by a machine learning algorithm to predictively apply changes to the tinnitus treatment…..¶ [0025], lines 1-17, ¶ [0024], lines 1-6) a tinnitus treatment signal produced by a generator (Stimulation produced by a stimulator.....¶[0014], lines 1-3) using one or more of the physiologic sensor signals (A sensor for detecting wearer heart rate…..¶[0016], lines 6-9), and the parameter values associated with the specified acoustic environment (Sound pressure levels.....¶[0019], lines 1-3), and non-physiologic sensor signals (¶[0025], lines 16-21), and contextual factor data (¶ [0015], lines 6-10).
Therefore, it would have been obvious to someone of ordinary skill in the art before the effective filing date of the claimed invention to have modified the combination of Melman, Dragicevic, Eder, and Litvak to further incorporate the teachings of Litvak and provide wherein deep neural network of Dragicevic, combined to implement and enhance the control circuitry of Melman, is further configured to process the physiologic sensor signals and one or more of the non-physiologic sensor signals and the contextual factor data, via a machine learning algorithm, to adjust the tinnitus masking sound produced by the sound generator using one or more of the physiologic sensor signals, and the parameter values associated with the specified acoustic environment, and the non-physiologic sensor signals, and the contextual factor data. This would provide the benefit of a system wherein the masking sound may be adjusted by the controller without the recipient indicating that the tinnitus has changed (Litvak, ¶[0024], lines 18-20).
Regarding claim 22, the combination of Melman, Dragicevic, Eder, and Litvak teach the device of claim 18, as explained above.
Litvak additionally teaches wherein a processor (¶ [0036], lines 1-3) is further configured with instructions to: process (The processor is enabled to perform the functions of the device…..¶ [0038], lines 3-5) first data comprising physiologic sensor signals (A sensor for detecting wearer heart rate…..¶ [0016], lines 6-9), non-physiologic sensor signals (An accelerometer for detecting wearer movement…..¶ [0025], lines 16-21), and contextual factor data (The stress level of a wearer…..¶ [0015], lines 6-10) via a machine learning algorithm (analogous to neural networks.....¶[0024], lines 3-6) to adjust (Sensor data, the detection of tinnitus severity, and user input are jointly evaluated by a machine learning algorithm to predictively apply changes to the tinnitus treatment…..¶ [0025], lines 1-17, ¶ [0024], lines 1-6) a tinnitus treatment signal produced by a generator (Stimulation produced by a stimulator.....¶[0014], lines 1-3); and detect mitigation or non-mitigation of the wearer's tinnitus, via the machine learning algorithm, in response to second data comprising one or more of the physiologic sensor signals, the non-physiologic sensor signals, and the contextual factor data acquired subsequent to the tinnitus masking sound adjustment (Over time (implying multiple datasets) the machine learning aspect builds associations between physiological, non-physiological, and context factor data, and is able to independently determine improvement or worsening (mitigation or non-mitigation) of a user’s tinnitus symptoms…..¶ [0024], lines 1-6, ¶ [0025], lines 10-16).
Therefore, it would have been obvious to someone of ordinary skill in the art before the effective filing date of the claimed invention to have modified the combination of Melman, Dragicevic, Eder, and Litvak to further incorporate the teachings of Litvak and provide wherein deep neural network of Dragicevic, combined to implement and enhance the control circuitry of Melman, is further configured with instructions to process first data comprising one or more of the physiologic sensor signals, the non-physiologic sensor signals, and the contextual factor data via a machine learning algorithm to adjust the tinnitus masking sound produced by the sound generator; and detect mitigation or non-mitigation of the wearer's tinnitus, via a neural network, in response to second data comprising one or more of the physiologic sensor signals, the non- physiologic sensor signals, and the contextual factor data acquired subsequent to the tinnitus masking sound adjustment. This would provide the benefit of a system wherein the masking sound may be adjusted by the controller (Litvak, ¶[0024], lines 18-20).
Claims 23-25 are rejected under 35 U.S.C. 103 as being unpatentable over in view of Litvak in view of Dragicevic.
Regarding claim 23, Litvak discloses a method implemented by an ear-wearable electronic device (A controller of a cochlear implant system, implemented in a sound processor (an electronic device) external to the wearer (about the ear).....¶[0044], lines 4-5) configured for deployment about an ear of a wearer (The sound processor may be worn behind (about) the ear of a wearer.....¶[0045], lines 3-4), comprising: measuring (External sensors measure and provide data to the controller.....¶[0016], lines 4-5), using a physiologic sensor arrangement (External sensors may detect heart rate and body temperature (physiologic properties) of a wearer.....¶[0016], line 9) communicatively coupled to the device (The controller receives data from the sensor.....¶[0018], lines 1-3), a plurality of physiologic parameters of the wearer (Heart rate and body temperature…..¶[0016], lines 4-5); producing, by the physiologic sensor arrangement, physiologic sensor signals (The sensors output sensor data (signals).....¶[0016], lines 5-6) in response to the physiologic sensor measurements (The data is representative of wearer physiologic properties measured by the sensors.....¶[0016], lines 5-6); and detecting, using a controller of the device (Treatment of tinnitus is performed by the controller in response to signals received at the controller, therefore such a response may be considered a detection of tinnitus by the controller.....¶[0018], lines 3-5), severity of tinnitus (The controller uses a machine learning algorithm trained on the sensor signals to detect improvement or worsening (relative severity) of a wearer’s tinnitus.....¶[0024], lines 9-12) of the wearer using the physiologic sensor signals (The controller addresses and evaluates the detected tinnitus based on the received sensor data.....¶[0018], lines 3-5).
Litvak fails to disclose wherein the physiologic sensor arrangement is of the device, instead only disclosing wherein it is coupled to the device.
Dragicevic teaches a hearing device (A wireless earpiece embodied as a hearing device.....¶[0073], lines 4-6) for sensing presence of tinnitus (¶[0074], lines 1-2), wherein a physiologic sensor arrangement is provided to the device (Shown in Fig. 2, device (60) may contain a pulse oximeter (78) and temperature sensor (80), among other physiologic sensors.....¶[0036], lines 2-11).
Therefore, it would have been obvious to someone of ordinary skill in the art before the effective filing date of the claimed invention to have modified the disclosure of Litvak to incorporate the teachings of Dragicevic, and provide wherein the physiologic sensors are provided to the ear-wearable device. This would provide the benefit of where a device may be manufactured in a fewer number of parts, providing a cost savings per unit (¶[0038], lines 16-18).
Regarding claim 24, the combination of Litvak and Dragicevic, as explained above, teaches the method of claim 23.
Litvak additionally discloses measuring (External sensors measure and provide data to the controller.....¶[0016], lines 4-5), using a non-physiologic sensor arrangement communicatively coupled to the device (External sensors may include an accelerometer.....¶[0025], lines 16-23), at least one non-physiologic parameter impacting a current context of the wearer (The accelerometer may measure the wearer acceleration and correlate (impact) the use of a vehicle (context).....¶[0025], lines 16-23); producing (The sensors output sensor data (signals).....¶[0016], lines 5-6), by the non-physiologic sensor arrangement, non-physiologic sensor signals in response to the non-physiologic sensor measurement (Sensors output data representing user conditions.....¶[0011], lines 6-11); and detecting, using the controller (Treatment of tinnitus is performed by the controller in response to signals received at the controller, therefore such a response may be considered a detection of tinnitus.....¶[0018], lines 3-5), severity of tinnitus (The controller uses a machine learning algorithm trained on the sensor signals to detect improvement or worsening (relative severity) of a wearer’s tinnitus.....¶[0024], lines 9-12) of the wearer using the physiologic sensor signals and the non-physiologic sensor signals (The controller addresses and evaluates the detected tinnitus based on the received physiologic and non-physiologic sensor data.....¶[0018], lines 3-5).
This further combination fails to disclose wherein the physiologic sensor arrangement is of the device, instead only disclosing wherein it is coupled to the device.
Dragicevic additionally wherein a non-physiologic sensor arrangement is provided to the device (Shown in Fig. 2, device (60) may contain inertial sensors (accelerometers) (74 and 76) among other non-physiologic sensors.....¶[0036], lines 2-5).
Therefore, it would have been obvious to someone of ordinary skill in the art before the effective filing date of the claimed invention to have modified the combination of Litvak and Dragicevic to further incorporate the teachings of Dragicevic, and provide wherein the non-physiologic sensors are provided to the ear-wearable device. This would provide the benefit of where a device may be manufactured in a fewer number of parts, providing a cost savings per unit (¶[0038], lines 16-18).
Regarding claim 25, the combination of Litvak and Dragicevic, as explained above, teaches the method of claim 24.
Litvak additionally teaches receiving, from an external electronic device (External sensors measure and provide data to the controller.....¶[0016], lines 4-5), contextual factor data (A wearer’s stress level.....¶[0016], lines 6-8) indicative of factors impacting a current wellbeing of the wearer (Stress is a measure of wellbeing); and detecting, using the controller, a severity of tinnitus of the wearer (Measured properties of implanted and external sensors are used with user input and machine learning algorithms to correlate sensor readings with the change in severity of user tinnitus…..¶ [0025], lines 10-16, ¶ [0024], lines 1-6) using the physiologic sensor signals (A sensor for detecting wearer heart rate…..¶ [0016], lines 6-9), the non-physiologic sensor signals (An accelerometer for detecting wearer movement…..¶ [0025], lines 16-21), and the contextual factor data (The stress level of a wearer…..¶ [0015], lines 6-10).
Conclusion
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.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to SEAN M RINEHART whose telephone number is (571)272-2778. The examiner can normally be reached M-F 10:00 AM - 6:00 PM ET.
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/SEAN M RINEHART/Examiner, Art Unit 2694
/FAN S TSANG/Supervisory Patent Examiner, Art Unit 2694