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
This Office Action is in response to the amendment filed on 03/26/2026. Claims 1, 108, 110, 120, and 122 have been amended. Claims 2-98 are canceled. Claims 99-107, 109, 111-119, and 121 are as previously presented. As such, claims 1 and 99-122 are pending in the instant application.
All rejections pursuant of 35 U.S.C. 112(b) are withdrawn in light of the amendments.
Claim Rejections - 35 USC § 102
The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(2) the claimed invention was described in a patent issued under section 151, or in an application for patent published or deemed published under section 122(b), in which the patent or application, as the case may be, names another inventor and was effectively filed before the effective filing date of the claimed invention.
Claims 1, 99-103, 105-106, 108-115, 117-118, and 120-122 are rejected under 35 U.S.C. 102(a)(2) as being anticipated by Lee et al. (US 20050061315 A1; hereinafter “Lee”).
Regarding claim 1, Lee discloses a system (600; Fig. 6) comprising:
a respiratory therapy system (640, where 640 is a sleep disorder breathing therapy device, see [0120]; Fig. 6);
a sensor (612; Fig. 6) configured to generate physiological data associated with a user of the respiratory therapy system during a sleep session and to detect noise associated with the respiratory therapy system, noise associated with the user, or both (600 has external sensor 612, see Fig. 6, and monitoring device 601 can include a microphone to monitor various physiological conditions, see Table 1, hence it would be inherent to one of ordinary skill in the art that the external sensor 612 can be a microphone to detect noise associated with the user to generate physiological data associated with the user of the sleep disorder breathing therapy device 640, as displayed in Table 1; [0113] and [0120]);
a memory storing machine-readable instructions (636; Fig. 6); and
an electronic device (601; Fig. 6) including one or more processors configured to execute the machine- readable instructions ([0011] and [0217]) to:
process the generated physiological data to distinguish between on-therapy data and off- therapy data (physiological data generated by microphone, such as respiration pattern/rate, can detect if the patient is asleep or awake, see Tables 1 and 2, where it would be readily understood by one of ordinary skill in the art that a patient with a sleep disorder would be “on-therapy” when asleep and “off-therapy” when awake), wherein
(i) the on-therapy data is the generated physiological data while the respiratory therapy system is coupled to the user and supplies pressurized air to an airway of the user, the on-therapy data being generated while the user is awake or asleep (physiological data generated by microphone when the patient is asleep is physiological data of the patient while the sleep disorder therapy device 640 is supplying pressurized air to the airway of the patient; see [0039] and [0147]); and
(ii) the off-therapy data is the generated physiological data while the respiratory therapy system is not supplying pressurized air to the airway of the user (the (physiological data generated by microphone when the patient is awake is physiological data of the patient when the sleep disorder therapy device 640 is not supplying pressurized air to the airway of the patient, as it would be well understood by one of ordinary skill in the art that feedback information developed would lower, if not stop, the supply of pressurized air to the patient when requirements are met by the collected physiological data indicating the patient does not the assistive breathing therapy pressure; see [0039], [0059], [0110], and [0116]; treatment of sleep disordered breathing only occurs when the patient is asleep, see [0120]);
determine a sleep measure based at least in part on the off-therapy data (determine quality of sleep based at least in part on how many times and for how long a user is awake, see [0150]; [0111] and [0120]); and
distinguish the off-therapy data and the on-therapy data based on the noise associated with the respiratory therapy system, the noise associated with the user, or both (distinguish when user is awake or asleep based on noise of the user recorded by the microphone; Table 1; [0113] and [0120]).
Regarding claim 99, Lee discloses the invention as set forth in claim 1, wherein the electronic device (601; Fig. 6) is further configured to execute the machine-readable instructions to:
determine that the user is asleep based at least in part on the generated physiological data by detecting a change in breathing of the user based at least in part on the off-therapy data, by detecting changes in movement of the user based at least in part on the off-therapy data, by detecting changes in heart rate of the user (decreased in heart rate is an indication the patient is asleep, see Table 2; Table 1; [0113], [0121], and [0123]-[0124]), by detecting changes in heart rate variability of the user, by detecting changes in core temperature of the user, by detecting changes in electroencephalogram (EEG) signals associated with the user, or by any combination thereof.
Regarding claim 100, Lee discloses the invention as set forth in claim 99, wherein determining that the user is asleep (see claim 99 above) includes determining that the respiratory therapy system (640, where 640 is a sleep disorder breathing therapy device, see [0120]; Fig. 6) is supplying the pressured air to the airway of the user (treatment of sleep disordered breathing only occurs when the patient is asleep, see [0120]), determining that flow signals from the respiratory therapy system are indicative of breathing of the user, or a combination thereof.
Regarding claim 101, Lee discloses the invention as set forth in claim 1, wherein the electronic device (601; Fig. 6) is further configured to execute the machine readable instructions to:
determine an on-therapy sleep measure (duration of sleep; [0120]) and an off-therapy sleep measure (duration of arousal from sleep, see [0114]-[0115] and [0120], where the duration of arousal from sleep is the duration the patient is awake), the on-therapy sleep measure being determined from the on-therapy data (duration of sleep determined via the duration of time the user is identified as asleep according to the generated physiological data, see claim 1 above and [0120]) and the off-therapy sleep measure being determined from the off-therapy data (duration patient is awake determined via the duration of time the user is identified as awake according to the generated physiological data, see claim 1 above and [0114]-[0115] and [0120]), wherein determining the sleep measure is further based at least in part on the off-therapy sleep measure and the on- therapy sleep measure (quality of sleep is based at least in part on the duration the patient is awake and the duration the patient is asleep, see [0150] and [0120]).
Regarding claim 102, Lee discloses the invention as set forth in claim 1, wherein the electronic device (601; Fig. 6) is further configured to execute the machine readable instructions to:
determine an estimated off-therapy sleep measure for a portion of the sleep session that the respiratory therapy system is supplying pressurized air to the airway of the user (627 of 601 estimates arousals per unit time, where 640 is still supplying pressurized air to the patient; [0057], 0114]-0115], and [0120]).
Regarding claim 103, Lee discloses the invention as set forth in claim 1, wherein the on-therapy data (physiological data generated when the patient is asleep; [0039] and [0147]) includes physiological data received from the respiratory therapy system (patient’s therapy usage from 640; [0114] and [0119]), and wherein the electronic device (601; Fig. 6) is further configured to execute the machine readable instructions to:
determine a respiratory sleep measure based on the physiological data received from the respiratory therapy system (therapy impact is based on the patient’s therapy usage; [0114]); and
adjust the determined sleep measure based at least in part on the respiratory sleep measure (adjust sleep quality based at least in part on the therapy impact via feedback information from the therapy impact data by changing the therapy being supplied to the patient; [0121] and [0047]).
Regarding claim 105, Lee discloses the invention as set forth in claim 1, wherein noise associated with the user's breathing while the respiratory therapy system is coupled to the user and supplying pressurized air to the airway of the user, noise associated with the user's breathing while the respiratory therapy system is not supplying pressurized air to the airway of the user, or both are used to distinguish the off-therapy data and the on-therapy data (noise associated with the user’s breathing recorded by the microphone is recorded when the user is not receiving pressurized air from 640 – e.g. the patient is awake – and when the user is receiving pressurized air from 640 – e.g., the patient is asleep – see claim 1 above, and both are used to distinguish between when the patient is awake and when the patient is asleep, see claim 1 above where the physiological data can be data associated with the patient’s breathing – i.e., the patient’s respiration pattern/rate).
Regarding claim 106, Lee discloses the invention as set forth in claim 1, wherein the electronic device (601; Fig. 6) is further configured to execute the machine readable instructions to:
analyze audio data, generated by the sensor (analyze audio data recorded by sensor 612, where sensor 612 is a microphone, see claim 1 above), to distinguish between (i) the respiratory therapy system (640; Fig. 6) operating and (ii) the respiratory therapy system (640; Fig. 6) operating and supplying pressurized air to the airway of the user via a user interface (640 is a sleep disordered breathing therapy device, see [0119], where the sleep disordered sleeping device is a positive pressure therapy device, see [0039], and it would be well understood by one of ordinary skill in the art that a positive pressure therapy device supplying pressurized air to the airway of a patient supplies the said pressurized air using a user interface, such as a mask or cannula, that is worn by the patient) worn by the user (the analysis of the audio data distinguishes between when the patient is asleep and when the patient is awake during a therapy session, see claim 1 above, Tables 1 and 2, and [0120]; and the treatment of the patient’s sleep disordered breathing only occurs during periods of sleep, see [0120], where it would be well understood by one of ordinary skill in the art that treatment of the patient’s sleep disordered breathing is the supply of pressurized air to the patient; hence, the analysis of the audio data can distinguish between the respiratory therapy system 640 operating during a therapy session, but not actively supplying pressurized air to the patient because the patient is awake, and the respiratory therapy system 640 operating and supplying pressurized air to the patient because the patient is in a period of sleep).
Regarding claim 108, Lee discloses the invention as set forth in claim 1, wherein the electronic device (601; Fig. 6) is further configured to execute the machine readable instructions to:
analyze audio data, generated by the sensor (analyze audio data recorded by sensor 612, where sensor 612 is a microphone, see claim 1 above), to identify features indicative of exhalation by the user (audio data recorded by sensor 612 is used to generate the patient’s respiratory pattern, see Table 1, where a patient’s respiratory pattern can indicated exhalation by the patient), features indicative of leaking of a user interface of the respiratory therapy system, or both;
wherein the features indicative of the exhalation by the user (respiratory pattern of the patient, see Table 1), the leaking of the user interface of the respiratory therapy system, or both are used to distinguish the off-therapy data and the on-therapy data (respiratory pattern of the patient is used to detect when the patient is awake and when the patient is asleep, see Table 2).
Regarding claim 109, Lee discloses the invention as set forth in claim 1, wherein the electronic device (601; Fig. 6) is further configured to execute the machine readable instructions to:
generate second physiological data (blood pressure; Table 1; [0123], where the sleep detector 628 analyzes patient data from various patient sensors to detect sleep-related events, see [0115]) related to one or more comorbidities experienced by the user (blood pressure is related to cardiovascular disorders, such as hypertension, and respiratory disorders, such as disordered breathing; [0004] and [0152]).
Regarding claim 110, Lee discloses a method (method of monitoring patient conditions and developing feedback information for a device delivering sleep disordered breathing therapy, see [0110]) comprising:
generating, by a sensor, physiological data associated with a user during a sleep session (sensor 612 generates physiological data associated with a patient during a sleep session; [0110] and [0111]; Table 1);
detecting, by the sensor, noise associated with a respiratory therapy system, noise associated with the user (sensor 612 is a microphone and detects sounds associated with the user, see Table 1; [0113] and [0120]), or both;
processing, by an electronic device (601; Fig. 6) including one or more processors ([0011] and [00217]), the generated physiological data to distinguish between on-therapy data and off-therapy data (physiological data generated by microphone, such as respiration pattern/rate, can detect if the patient is asleep or awake, see Tables 1 and 2, where it would be readily understood by one of ordinary skill in the art that a patient with a sleep disorder would be “on-therapy” when asleep and “off-therapy” when awake) wherein
(i) the on-therapy data is the generated physiological data while a respiratory therapy system (640, where 640 is a sleep disorder breathing therapy device, see [0120]; Fig. 6) is coupled to the user and supplies pressurized air to an airway of the user, the on-therapy data being generated while the user is awake or asleep (physiological data generated by microphone when the patient is asleep is physiological data of the patient while the sleep disorder therapy device 640 is supplying pressurized air to the airway of the patient; see [0039] and [0147]); and
(ii) the off-therapy data is the generated physiological data while the respiratory therapy system is not supplying pressurized air to the airway of the user (the physiological data generated by microphone when the patient is awake is physiological data of the patient when the sleep disorder therapy device 640 is not supplying pressurized air to the airway of the patient, as it would be well understood by one of ordinary skill in the art that feedback information developed would lower, if not stop, the supply of pressurized air to the patient when requirements are met by the collected physiological data indicating the patient does not the assistive breathing therapy pressure; see [0039], [0059], [0110], and [0116]; treatment of sleep disordered breathing only occurs when the patient is asleep, see [0120]);
determining, by the electronic device (601; Fig. 6), a sleep measure based at least in part on the off- therapy data (determine quality of sleep based at least in part on how many times and for how long a user is awake, see [0150]; [0111] and [0120]); and
distinguishing the off-therapy data and the on-therapy data based on the noise associated with the respiratory therapy system, the noise associated with the user, or both (distinguish when user is awake or asleep based on noise of the user recorded by the microphone; Table 1; [0113] and [0120]).
Regarding claim 111, Lee discloses the invention as set forth in claim 110, further comprising:
determining, by the electronic device (601; Fig. 6), that the user is asleep based at least in part on the generated physiological data by detecting a change in breathing of the user based at least in part on the off-therapy data, by detecting changes in movement of the user based at least in part on the off-therapy data, by detecting changes in heart rate of the user (decreased in heart rate is an indication the patient is asleep, see Table 2; Table 1; [0113], [0121], and [0123]-[0124]), by detecting changes in heart rate variability of the user, by detecting changes in core temperature of the user, by detecting changes in electroencephalogram (EEG) signals associated with the user, or by any combination thereof.
Regarding claim 112, Lee discloses the invention as set forth in claim 111, wherein the determining that the user is asleep (see claim 111 above) includes determining that the respiratory therapy system (640, where 640 is a sleep disorder breathing therapy device, see [0120]; Fig. 6) is supplying the pressured air to the airway of the user (treatment of sleep disordered breathing only occurs when the patient is asleep, see [0120]), determining that flow signals from the respiratory therapy system are indicative of breathing of the user, or a combination thereof.
Regarding claim 113, Lee discloses the invention as set forth in claim 110, further comprising:
determining an on-therapy sleep measure (duration of sleep; [0120]) and an off-therapy sleep measure (duration of arousal from sleep, see [0114]-[0115] and [0120], where the duration of arousal from sleep is the duration the patient is awake), the on-therapy sleep measure being determined from the on-therapy data (duration of sleep determined via the duration of time the user is identified as asleep according to the generated physiological data, see claim 110 above and [0120]) and the off-therapy sleep measure being determined from the off-therapy data (duration patient is awake determined via the duration of time the user is identified as awake according to the generated physiological data, see claim 110 above and [0114]-[0115] and [0120]), wherein the determining the sleep measure is further based at least in part on the off-therapy sleep measure and the on- therapy sleep measure (quality of sleep is based at least in part on the duration the patient is awake and the duration the patient is asleep, see [0150] and [0120]).
Regarding claim 114, Lee discloses the invention as set forth in claim 110, further comprising:
determining an estimated off-therapy sleep measure for a portion of the sleep session that the respiratory therapy system is supplying pressurized air to the airway of the user (627 of 601 estimates arousals per unit time, where 640 is still supplying pressurized air to the patient; [0057], 0114]-0115], and [0120]).
Regarding claim 115, Lee discloses the invention as set forth in claim 110, wherein the on-therapy data (physiological data generated when the patient is asleep; [0039] and [0147]) includes physiological data received from the respiratory therapy system (patient’s therapy usage from 640; [0114] and [0119]), and the method further comprises:
determining a respiratory sleep measure based on the physiological data received from the respiratory therapy system (therapy impact is based on the patient’s therapy usage; [0114]); and
adjusting the determined sleep measure based at least in part on the respiratory sleep measure (adjust sleep quality based at least in part on the therapy impact via feedback information from the therapy impact data by changing the therapy being supplied to the patient; [0121] and [0047]).
Regarding claim 117, Lee discloses the invention as set forth in claim 110, wherein noise associated with the user's breathing while the respiratory therapy system is coupled to the user and supplying pressurized air to the airway of the user, noise associated with the user's breathing while the respiratory therapy system is not supplying pressurized air to the airway of the user, or both are used to distinguish the off-therapy data and the on-therapy data (noise associated with the user’s breathing recorded by the microphone is recorded when the user is not receiving pressurized air from 640 – e.g. the patient is awake – and when the user is receiving pressurized air from 640 – e.g., the patient is asleep – see claim 110 above, and both are used to distinguish between when the patient is awake and when the patient is asleep, see claim 110 above where the physiological data can be data associated with the patient’s breathing – i.e., the patient’s respiration pattern/rate).
Regarding claim 118, Lee discloses the invention as set forth in claim 110, further comprising:
analyzing audio data, generated by the sensor (analyzing audio data recorded by sensor 612, where sensor 612 is a microphone, see claim 110 above), to distinguish between (i) the respiratory therapy system (640; Fig. 6) operating and (ii) the respiratory therapy system (640; Fig. 6) operating and supplying pressurized air to the airway of the user via a user interface (640 is a sleep disordered breathing therapy device, see [0119], where the sleep disordered sleeping device is a positive pressure therapy device, see [0039], and it would be well understood by one of ordinary skill in the art that a positive pressure therapy device supplying pressurized air to the airway of a patient supplies the said pressurized air using a user interface, such as a mask or cannula, that is worn by the patient) worn by the user (the analysis of the audio data distinguishes between when the patient is asleep and when the patient is awake during a therapy session, see claim 1 above, Tables 1 and 2, and [0120]; and the treatment of the patient’s sleep disordered breathing only occurs during periods of sleep, see [0120], where it would be well understood by one of ordinary skill in the art that treatment of the patient’s sleep disordered breathing is the supply of pressurized air to the patient; hence, the analysis of the audio data can distinguish between the respiratory therapy system 640 operating during a therapy session, but not actively supplying pressurized air to the patient because the patient is awake, and the respiratory therapy system 640 operating and supplying pressurized air to the patient because the patient is in a period of sleep).
Regarding claim 120, Lee discloses the invention as set forth in claim 110, further comprising:
analyzing audio data, generated by the sensor (analyze audio data recorded by sensor 612, where sensor 612 is a microphone, see claim 110 above), to identify features indicative of exhalation by the user (audio data recorded by sensor 612 is used to generate the patient’s respiratory pattern, see Table 1, where a patient’s respiratory pattern can indicated exhalation by the patient), features indicative of leaking of a user interface of the respiratory therapy system, or both;
wherein the features indicative of the exhalation by the user (respiratory pattern of the patient, see Table 1), the leaking of the user interface of the respiratory therapy system, or both are used to distinguish the off-therapy data and the on-therapy data (respiratory pattern of the patient is used to detect when the patient is awake and when the patient is asleep, see Table 2).
Regarding claim 121, Lee discloses the invention as set forth in claim 110, further comprising generating second physiological data (blood pressure; Table 1; [0123], where the sleep detector 628 analyzes patient data from various patient sensors to detect sleep-related events, see [0115]) related to one or more comorbidities experienced by the user (blood pressure is related to cardiovascular disorders, such as hypertension, and respiratory disorders, such as disordered breathing; [0004] and [0152]).
Regarding claim 122, Lee discloses an electronic device (601; Fig. 6) comprising:
a memory storing machine-readable instructions (636; Fig. 6); and
a control system (637; Fig. 6) including one or more processors configured to execute the machine- readable instructions ([0011] and [0217]) to:
cause a sensor (612; Fig. 6) to generate physiological data associated with a user during a sleep session and to detect noise associated with a respiratory therapy system, noise associated with the user, or both (sensor 612 can be a microphone to generate data associated with various physiological conditions of the user; Table 1; [0113] and [0120]);
process the generated physiological data to distinguish between on-therapy data and off- therapy data (physiological data generated by microphone, such as respiration pattern/rate, can detect if the patient is asleep or awake, see Tables 1 and 2, where it would be readily understood by one of ordinary skill in the art that a patient with a sleep disorder would be “on-therapy” when asleep and “off-therapy” when awake), wherein
(i) the on-therapy data is the generated physiological data while a respiratory therapy system (640, where 640 is a sleep disorder breathing therapy device, see [0120]; Fig. 6), coupled to the user, supplies pressurized air to an airway of the user, the on-therapy data being generated while the user is awake or asleep (physiological data generated by microphone when the patient is asleep is physiological data of the patient while the sleep disorder therapy device 640 is supplying pressurized air to the airway of the patient; see [0039] and [0147]); and
(ii) the off-therapy data is the generated physiological data while the respiratory therapy system is not providing pressurized air to the airway of the user (the physiological data generated by microphone when the patient is awake is physiological data of the patient when the sleep disorder therapy device 640 is not supplying pressurized air to the airway of the patient, as it would be well understood by one of ordinary skill in the art that feedback information developed would lower, if not stop, the supply of pressurized air to the patient when requirements are met by the collected physiological data indicating the patient does not the assistive breathing therapy pressure; see [0039], [0059], [0110], and [0116]; treatment of sleep disordered breathing only occurs when the patient is asleep, see [0120]);
determine a sleep measure based at least in part on the off-therapy data (determine quality of sleep based at least in part on how many times and for how long a user is awake, see [0150]; [0111] and [0120]); and
distinguish the off-therapy data and the on-therapy data based on the noise associated with the respiratory therapy system, the noise associated with the user, or both (distinguish when user is awake or asleep based on noise of the user recorded by the microphone; Table 1; [0113] and [0120]).
Claim Rejections - 35 USC § 103
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
Claims 104 and 116 are rejected under 35 U.S.C. 103 as being unpatentable over Lee (US 20050061315 A1).
Regarding claim 104, Lee discloses the invention as set forth in claim 1, but the medical system (600; Fig. 6) disclosed by Lee fails to explicitly disclose the noise associated with the respiratory therapy system is noise associated with a motor of the respiratory therapy system, or the noise associated with the user is noise associated with movement of the user, or a combination thereof.
However, Lee teaches an analogous system (400; Fig. 4a) to monitor one or more patient conditions and generate feedback information for a sleep disordered breathing therapy device, where the monitoring device (435; Fig. 4a) is a component of a pulse generator (405; Fig. 4a), where the pulse generator (405; Fig. 4a) includes a motion sensor (420; Fig. 4a) that provides acoustic information, such as heart sounds and/or cardiac murmurs, to sense patient activity ([0083] and [0086]). Lee also teaches the sensors of the monitoring unit (601; Fig. 6) in the first embodiment presented (see claim 1 above) discloses monitoring various physiological conditions of the patient, including physiological conditions of both the cardiovascular system and respiratory system ([0113]; Table 1).
Therefore, Therefore, it would have been obvious to a person of ordinary skill in the art, before the effective filing date of the claimed invention, to modify the medical system (600; Fig. 6) taught by Lee with the motion sensor (420; Fig. 4a) taught by Lee, such that the noise detected by the microphone of the motion sensor (420; Fig. 4a) is associated with patient activity and movement ([0083] and [0086]) to detect if the patient is awake or asleep ([0086], lines 1-5).
Regarding claim 116, Lee discloses the invention as set forth in claim 110, but the method disclosed by Lee (see claim 110 above) fails to explicitly disclose, the noise associated with the respiratory therapy system is noise associated with a motor of the respiratory therapy system, or the noise associated with the user is noise associated with movement of the user, or a combination thereof.
However, an alternative method (method to monitor one or patient conditions and generate feedback information for a sleep disorder breathing therapy device; [0083]) taught by Lee teaches a method of detecting patient activity via a motion sensor (420; Fig. 4a; [0086]) which senses patient activity based on acoustic information, such as heart sounds and cardiac murmurs, to generate and monitor the pulse of the patient ([0083] and [0086]). The method taught by Lee presented in claim 110 further teaches monitoring various physiological conditions of the patient, including physiological conditions of both the cardiovascular system and respiratory system ([0113]; Table 1).
Therefore, it would have been obvious to a person of ordinary skill in the art, before the effective filing date of the claimed invention, to modify the method presented in claim 110 above with the method of monitoring the pulse of the patient via the motion sensor (420; Fig. 4a) such that the noise detected by the microphone of the motion sensor (420; Fig. 4a) is associated with patient activity and movement ([0083] and [0086]) to detect if the patient is awake or asleep ([0086], lines 1-5).
Claims 107 and 119 are rejected under 35 U.S.C. 103 as being unpatentable over Lee (US 20050061315 A1) in view of Holley et al. (US 20110313689 A1; hereinafter “Holley”).
Regarding claim 107, Lee discloses the invention as set forth in claim 1, but fails to explicitly disclose wherein the electronic device (601; Fig. 6) is further configured to execute the machine readable instructions to: analyze audio data, generated by the sensor, to detect that the respiratory therapy system is operating, a user interface is being worn by the user, and the respiratory therapy system is supplying pressurized air to the airway of the user via the user interface.
However, Holley teaches an analogous system with acoustic detection for a respiratory treatment apparatus, where data generated by a sound sensor, where the sound sensor is a microphone ([0030]), is analyzed to determine if a user is present and wearing a mask ([0158]-[0159], [0195], and [0146]). Additionally, Holley teaches if there are any technical problems with the mask, such as leaks and/or kinks in the system ([0146]), hence the acoustic detection system and method taught by Holley is capable of detecting whether the respiratory therapy system is operating and supplying pressurized air to the airway of the user via the mask.
Therefore, it would have been obvious to a person of ordinary skill in the art, before the effective filing date of the claimed invention, to modify the machine readable instructions taught by Lee (see claim 1 above) to further include the acoustic detection process taught by Holley (see above), such that the electronic device (601; Fig. 6) is further configured to execute the machine readable instructions to: analyze audio data, generated by the sensor (audio data recorded by sensor 612, where sensor 612 is a microphone, see claim 1 above), to detect that the respiratory therapy system is operating, a user interface is being worn by the user, and the respiratory therapy system is supplying pressurized air to the airway of the user via the user interface (analyze the audio data generated by sensor 612 with the acoustic detection method taught by Holley, where the acoustic detection method of Holley detects if a user is present and wearing a mask, and whether the respiratory therapy system is operating and supplying pressurized air to the airway of the user via the mask, see Holley [0158]-[0159], [0195], and [0146]) to authenticate a particular user of a respiratory therapy device and permit operation of the respiratory therapy device in accordance with the detected and authenticated user (Holley [0026]-[0028]).
Regarding claim 119, Lee discloses the invention as set forth in claim 110, but fails to explicitly disclose the method further comprising: analyzing audio data, generated by the sensor, to detect that the respiratory therapy system is operating, a user interface is being worn by the user, and the respiratory therapy system is supplying pressurized air to the airway of the user via the user interface.
However, Holley teaches a method of acoustic detection for a respiratory treatment apparatus, where data generated by a sound sensor, where the sound sensor is a microphone ([0030]), is analyzed to determine if a user is present and wearing a mask ([0158]-[0159], [0195], and [0146]). Additionally, Holley teaches if there are any technical problems with the mask, such as leaks and/or kinks in the system ([0146]), hence the acoustic detection system and method taught by Holley is capable of detecting whether the respiratory therapy system is operating and supplying pressurized air to the airway of the user via the mask.
Therefore, it would have been obvious to a person of ordinary skill in the art, before the effective filing date of the claimed invention, to modify the method taught by Lee (see claim 110 above) to further include the acoustic detection process taught by Holley (see above), such that the method taught by Lee (see claim 110 above) further comprises: analyzing audio data, generated by the sensor (audio data recorded by sensor 612, where sensor 612 is a microphone, see claim 1 above), to detect that the respiratory therapy system is operating, a user interface is being worn by the user, and the respiratory therapy system is supplying pressurized air to the airway of the user via the user interface (analyze the audio data generated by sensor 612 with the acoustic detection method taught by Holley, where the acoustic detection method of Holley detects if a user is present and wearing a mask, and whether the respiratory therapy system is operating and supplying pressurized air to the airway of the user via the mask, see Holley [0158]-[0159], [0195], and [0146]) to authenticate a particular user of a respiratory therapy device and permit operation of the respiratory therapy device in accordance with the detected and authenticated user (Holley [0026]-[0028]).
Response to Arguments
Applicant's arguments filed on 03/26/2026 have been fully considered but they are not persuasive.
On page 10 of the Remarks, Applicant argues Lee, either alone or in combination with Holley, fails to teach or suggest “the on-therapy data being generated while the user is awake or asleep”, as recited in amended independent claim 1 (line 13), independent claim 110 (line 9), and independent claim 122 (line 12). However, Lee does disclose the generation of physiological data by a microphone when the patient is asleep ([0039] and [0147]). The Examiner notes the recitation of “while the user is awake or asleep” (emphasis added) in the amended limitation above is an or-statement, where the limitation can be interpreted as – while the user is awake, while the user is asleep, and/or while the user is awake and asleep. As such, the above teachings of Lee disclose the generation of physiological data when the user is asleep (see Lee [0039] and [0147]). Therefore, independent claims 1, 120, and 122 do not overcome Lee.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure:
Kayyali & Kolkowski (US 8424527 B1): Regarding a device to acoustically monitor a patient’s airway during respiratory therapy and the ability to perform sleep analysis simultaneously.
Westbrook et al. (US 20020165462 A1): Regarding a system to collect and analyze physiological signals to detect a sleep apnea.
THIS ACTION IS MADE FINAL. Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
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/ABIGAYLE DALE/Examiner, Art Unit 3785
/BRANDY S LEE/Supervisory Patent Examiner, Art Unit 3785
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