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
In response to amendments, filed November 19, 2025, claims 1 and 19-20 have been amended. No claims have been cancelled or added. Claims 1-17 and 19-20 are pending.
Response to Arguments
Applicant’s arguments, see Remarks, filed November 19, 2025, with respect to the prior art claim(s) have been considered but they are not persuasive.
In response to applicant’s argument that the combination of Rakshit/Bennett/Cline does not disclose all the features of amended independents claims 1, 19, and 20, particularly “providing… a first set of targets associated with one or more physiological metrics acquired via the one or more sensors of the wearable ring device when the user is in a non-pregnant state,” Examiner respectfully disagrees.
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). Rakshit provides a smart ring device that, per [00072], includes one or more sensors (e.g., movement sensors, object sensors, biometric sensors, accelerometers, etc.), cameras, audio input devices, Internet of Things (IoT) devices, etc. With the combination of Rakshit/Bennett, the sensors included in the smart ring device of Rakshit may be used in a mode of operation for predicting and displaying an optimal time for impregnation described in Bennett [0193]. Further, the ring of Rakshit may evaluate targets associated with one or more physiological metrics via imaging and temperature sensing to track clinically relevant changes related to an ovulation event and or the lack thereof and obtain a fertility profile, as described in Bennett [0173]. The remaining features of the independent claims not particularly argued are disclosed by the combination of Rakshit/Bennett/Cline as described in the 35 USC 103 section below.
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.
Claim(s) 1-14 and 17-20 are rejected under 35 U.S.C. 103 as being unpatentable over Rakshit (US 20200155058 A1) in view of Bennett (US 20110190595 A1) and Cline (US 20160331299 A1).
Regarding claim 1, Rakshit teaches a method ([0003] “computer-implemented method includes: monitoring, by a computing device, stimuli exposed to an unborn child based on sensor data”) comprising:
acquiring, via one or more sensors of a wearable ring device configured to be worn by a user, physiological data associated with the user ([0065] “gathering sensor data of participants [e.g., pregnant women] wearing various types of wearable sensor devices (e.g., smart watches/ring/eyewear, electronic tattoos, smart clothing, etc.]… smart ring devices”);
receiving, via a transceiver of a user device and from the wearable ring device, the physiological data associated with the user ([0064] “As shown in FIG. 4, movement/kick patterns of an unborn child are determined from sensor data (e.g., from sensor devices, such as those implemented in wearable computing devices worn by a mother of the unborn child). The sensor data, combined with data from a knowledge corpus, is used to make a health-related prediction regarding the unborn child (e.g., a prediction of possible hearing loss in the unborn child)”).
However, Rakshit fails to disclose physiological targets when a user is in a non-pregnant state. Bennett teaches intravaginal monitoring devices, supporting networks, web services, modes of operation of the devices and networks, and processing of data harvested by an intravaginal device and communication to the network.
The combination of Rakshit/Bennett discloses:
providing, to the user device associated with the user and in accordance with a first operational mode of an application associated with the wearable ring device (Rakshit: [0065] “smart ring device;” Bennett: [0047] “server 173 or other network node includes a select service mode of operation, which provides various functionalities on device 115 … For example, the menu includes an STD detection mode of operation and or service, an ovulation detection mode of operation or service, a rhythm method (infertility) mode of operation or service, a precancerous tissue monitoring or service, a general cervix monitoring mode of operation, an infection mode of operation and or service),
a first set of targets associated with one or more physiological metrics acquired via the one or more sensors of the wearable ring device when the user is in a non-pregnant state and a first set of messages associated with the one or more physiological metrics acquired via the one or more sensors of the wearable ring device based at least in part on the physiological data acquired via the one or more sensors of the wearable ring device, the first set of targets and the first set of messages associated with the first operational mode of the application associated with the wearable ring device that is associated with the user (Rakshit: [0065] “smart ring device;” [00072] “The sensor devices 210 include one or more sensors (e.g., movement sensors, object sensors, biometric sensors, accelerometers, etc.), cameras, audio input devices, Internet of Things (IoT) devices, etc.” Bennett: Fig. 4; [0193] “a mode of operation for predicting and displaying an optimal time for impregnation;” [0173] “The Internet based system, geographically remote intravaginal monitoring devices [rather the smart ring device per Rakshit] further consists of an imager for imaging and tracking clinically relevant changes related to an ovulation event and or the lack thereof to obtain imaged and tracked data, and temperature sensing and tracking capability to obtain sensed and tracked data, the image and tracked data being optionally correlated to the sensed and tracked data to obtain a fertility profile.”).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the method of Rakshit to include physiological targets when a user is in a non-pregnant state as disclosed in Bennett to provide for a way for a woman to readily know about the status of her reproductive health and fertility from the comfort of her own home (Bennett [0019, 0173]).
While, the combination of Rakshit/Bennett includes a pregnancy mode that may be selected, it fails to disclose specific user input information regarding the user being pregnant. Cline teaches devices, systems and methods that enable and make assessments related to pregnancy.
Cline discloses receiving, via the user device, a user input comprising an indication of the user being pregnant ([0079] “The pregnancy monitoring system may integrate clinical data, such as gestational age, number of fetuses, body mass index of the mother, parity of the mother, whether the mother has had previous preterm deliveries, cervical remodeling [including measures of cervical length, softness, ripening, and/or effacement], maternal respiration rate, maternal heart rate, and/or fetal heart rate into the assessment of the likelihood of labor and/or delivery within a specified length of time or before a specified gestational age. For example, a patient, patient's physician, or other person may enter said clinical data into an electronic interface, such as a smartphone application.”).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the combination of Rakshit/Bennett to include user input indicating the user being pregnant as disclosed in Cline to adjust pregnancy assessment parameters for more accurate tracking and notification of pregnancy and labor-related status (Cline [0079, [0083]).
The combination of Rakshit/Bennett/Cline discloses:
identifying a trigger to transition from the first operational mode to a second operational mode of the application associated with the wearable ring device that is associated with the user based at least in part on receiving the indication (Rakshit: [0065] “smart ring device;” Bennett: [0193] “a mode of operation for predicting and displaying an optimal time for impregnation;” [0047] “The menu is provided to a medical professional, purchaser of the intravaginal device or user of the intravaginal device for the individual to select device functionality. For example, the menu includes an STD detection mode of operation and or service, an ovulation detection mode of operation or service, a rhythm method (infertility) mode of operation or service, a precancerous tissue monitoring or service, a general cervix monitoring mode of operation, an infection mode of operation and or service, a pregnancy mode of operation and or service.” Cline: [0083] “In some embodiments, the pregnancy monitoring system makes at least one transition between states as part of operation … the pregnancy monitoring system may initially gather data regarding uterine activity as part of a baseline assessment state. After gathering a sufficient amount of baseline data, the system may transition to an active monitoring state.” [0079] “The pregnancy monitoring system may integrate clinical data, … [via] a smartphone application.”
and providing, to the user device based at least in part on identifying the trigger, a second set of targets associated with the one or more physiological metrics and a second set of messages associated with the one or more physiological metrics that are adjusted for pregnancy and different from the first set of targets and the first set of messages based at least in part on the second operational mode (Cline: [0083] “Transitioning to the active monitoring state may involve enabling notifications that were not enabled in the baseline assessment state. In some embodiments, when the pregnancy monitoring system is operating in the active monitoring state and detects a contraction, the pregnancy monitoring system may determine the likelihood of a labor-related status based on comparison of the contraction to one or more contraction detected in the baseline assessment state; if the likelihood is determined to be above a threshold, a notification may be delivered. The term baseline assessment mode may be used to describe the baseline assessment state; the term active monitoring mode may be used to describe the active monitoring state.” [0084] “the pregnancy monitoring system comprises at least two electrodes coupled to a pregnant female, a processor configured to analyze uterine activity, a notification delivery system in a first notification mode, and a notification manager configured to compare received uterine activity data to a threshold, and if the uterine activity data exceeds the threshold, transition the notification delivery system to a second notification mode, wherein at least one additional type of notification is enabled.”).
Regarding claim 2, the combination of Rakshit/Bennett/Cline discloses the method of claim 1 (Rakshit: [0003] “computer-implemented method includes: monitoring, by a computing device, stimuli exposed to an unborn child based on sensor data”), further comprising:
determining, during a first time interval corresponding to the first operational mode, one or more scores associated with the user using a first algorithm and based at least in part on the physiological data; and determining, during a second time interval corresponding to the second operational mode, the one or more scores associated with the user being pregnant and using a second algorithm different from the first algorithm and based at least in part on the physiological data ([0082] At least one algorithm used by the patient monitoring system may adapt based on input data for a specific patient. For example, after placement on the patient's belly, the pregnancy monitoring phase may first undergo a training phase. The pregnancy monitoring system may adjust pregnancy assessment parameters based on this training phase for a subsequent active monitoring phase. In some cases, training and active monitoring phases may partly or fully overlap; [0084] compare received uterine activity data to a threshold).
Regarding claim 3, the combination of Rakshit/Bennett/Cline discloses the method of claim 2 (Rakshit: [0003] “computer-implemented method includes: monitoring, by a computing device, stimuli exposed to an unborn child based on sensor data”), wherein the one or more scores comprise a Sleep Score, a Readiness Score, an Activity Score, or any combination thereof (Cline: [0081] the pregnancy monitoring system may collect and use one or more of the following: fetal sleep or wakefulness status; maternal sleep or wakefulness status; fetal orientation; maternal respiration rate; correlation of fetal heart rate and/or fetal movement, including fetal heart rate and/or movement triggered by acoustic and/or vibroacoustic stimulation; correlation of contractions and fetal heart rate; maternal skin temperature; data collected using a strain gage, for example a strain gage incorporated into the pregnancy monitoring system. The system may deliver said data to the patient and/or the patient's physician, as well as derived metrics including frequency and trends in occurrence [metrics or scores incorporating sleep/readiness/activity]).
Regarding claim 4, the combination of Rakshit/Bennett/Cline discloses the method of claim 1 (Rakshit: [0003] “computer-implemented method includes: monitoring, by a computing device, stimuli exposed to an unborn child based on sensor data”), further comprising:
identifying a second trigger to transition away from the second operational mode (Bennett: [0156] “The program and operational logic 1993 [of the memory 1981] consist of operating instructions that direct the processing circuitry 1941 in carrying out the various independent and dependent modes of operation. Moreover, the program and operation logic 1993 defines processes for the selection from the plurality of modes and switching there between… responding to the user input devices 1965 and to incoming control signals from external supporting computing devices.”);
transitioning from the second operational mode to a third operational mode of the application associated with the wearable ring device that is associated with the user based at least in part on the second trigger (Rakshit: [0065] “smart ring device;” Bennett: [0193] “a pregnancy mode of operation and or service,” Cline: [0083] “active monitoring mode” being the second operational mode; Bennett: [0192] “a mode of operation effected once a threshold of a value has been met;” [0193] “a mode of operation for monitoring and/or logging impregnation, a birthing process, and/or a post birthing process” being the third operational mode), wherein the third operational mode comprises an intermediary mode for transitioning from the second operational mode to the first operational mode (Cline: [0069] “temperature, removal of an adhesive backer, removal from a sealed pouch, impedance between electrodes, insertion of a battery, and/or presence of a cardiac signal, or another predetermined input and/or trigger is used to determine whether said device has been placed on the patient's belly and/or will soon be put into use. In some cases, said device wakes from said sleep mode to check for said predetermined input and/or trigger; in some cases, said predetermined input and/or trigger triggers waking from sleep mode. After said predetermined sensor input is obtained, said device in some cases automatically enters the mode for monitoring the patient's pregnancy, and/or in some cases enters a mode of preparation and/or readiness for calibration and/or syncing with other components of the pregnancy monitoring system, and/or in some cases enters a different state in a state machine.”);
and providing, to the user device based at least in part on transitioning to the third operational mode, a third set of targets associated with the one or more physiological metrics and a third set of messages associated with the one or more physiological metrics that are adjusted for postpartum and different from the second set of targets and the second set of messages associated with the one or more physiological metrics based at least in part on the third operational mode (Bennett: [0193] “a mode of operation for monitoring and/or logging impregnation, a birthing process, and/or a post birthing process” [0192] “intravaginal monitoring devices, each of the devices consisting of a data capture system; the data capture system consists of one or more the following, alone or in combination; … (8) a mode of operation effected once a threshold of a value has been met; (9) a warning alert mode, wherein the warning is selected from the group consisting of a warning to the expectant mother and/or father that an abnormal event associated with a pregnancy is occurring or has occurred”).
Regarding claim 5, the combination of Rakshit/Bennett/Cline discloses the method of claim 4 (Rakshit: [0003] “computer-implemented method includes: monitoring, by a computing device, stimuli exposed to an unborn child based on sensor data”), wherein identifying the second trigger comprises: receiving, via the user device, a user input comprising an indication that the user is in a postpartum state (Bennett: [0156] “selection from the plurality of modes and switching there between… responding to the user input devices 1965 and to incoming control signals from external supporting computing devices”; [0071] “Post labor the network and modes of operation provide for a management system for post partum depression through the social network site established during the pregnancy”).
Regarding claim 6, the combination of Rakshit/Bennett/Cline discloses the method of claim 4 (Rakshit: [0003] “computer-implemented method includes: monitoring, by a computing device, stimuli exposed to an unborn child based on sensor data”), further comprising:
identifying a third trigger (Bennett: [0053] “As miscarriage involves a process and stages all of these are monitored using the device and network of the present invention in one mode of operation. For example, in threatened miscarriage, the device harvests data and the network processes data … An alert is sent that miscarriage may be inevitable when there is harvesting of dilation data and or effacement of the cervix data, and/or data indicative of a rupture of the membranes [trigger]”) to transition from the third operational mode ([0193] “a mode of operation for monitoring and/or logging impregnation, a birthing process, and/or a post birthing process) to the first operational mode (Bennett: “ovulation detection mode of operation or service,” Cline: [0083] “baseline assessment state”); transitioning from the third operational mode to the first operational mode based at least in part on the third trigger (Cline: [0069] “After said predetermined sensor input is obtained, said device in some cases automatically enters the mode for monitoring the patient's pregnancy, and/or in some cases enters a mode of preparation and/or readiness for calibration and/or syncing with other components of the pregnancy monitoring system, and/or in some cases enters a different state in a state machine.”);
and providing, to the user device based at least in part on transitioning to the first operational mode, the first set of targets and the first set of messages based at least in part on the first operational mode (Bennett: [0193] “a mode of operation for predicting and displaying an optimal time for impregnation;” [0173] “The Internet based system, geographically remote intravaginal monitoring devices further consists of an imager for imaging and tracking clinically relevant changes related to an ovulation event and or the lack thereof to obtain imaged and tracked data, and temperature sensing and tracking capability to obtain sensed and tracked data, the image and tracked data being optionally correlated to the sensed and tracked data to obtain a fertility profile.” Cline: [0083] “the pregnancy monitoring system may initially gather data regarding uterine activity as part of a baseline assessment state;” [0084] “a notification delivery system in a first notification mode [baseline assessment state], and a notification manager configured to compare received uterine activity data to a threshold”).
Regarding claim 7, the combination of Rakshit/Bennett/Cline discloses the method of claim 6 (Rakshit: [0003] “computer-implemented method includes: monitoring, by a computing device, stimuli exposed to an unborn child based on sensor data”), wherein identifying the third trigger is based at least in part on measured physiological parameters included within the physiological data that indicate the user is no longer pregnant (Bennett: [0053] “As miscarriage involves a process and stages all of these are monitored using the device and network of the present invention in one mode of operation. For example, in threatened miscarriage, the device harvests data and the network processes data … An alert is sent that miscarriage may be inevitable when there is harvesting of dilation data and or effacement of the cervix data, and/or data indicative of a rupture of the membranes”).
Regarding claim 8, the combination of Rakshit/Bennett/Cline discloses the method of claim 4 (Rakshit: [0003] “computer-implemented method includes: monitoring, by a computing device, stimuli exposed to an unborn child based on sensor data”), wherein the first operational mode comprises a non-pregnant mode (Bennett: [0193] “a mode of operation for predicting and displaying an optimal time for impregnation;” Cline: [0083] “baseline assessment mode”), the second operational mode comprises a pregnancy mode (Bennett: [0193] “a pregnancy mode of operation and or service”; Cline: [0083] “active monitoring mode”), and the third operational mode comprises a postpartum mode (Bennett: [0193] “a mode of operation for monitoring and/or logging impregnation, a birthing process, and/or a post birthing process”).
Regarding claim 9, the combination of Rakshit/Bennett/Cline discloses the method of claim 1 (Rakshit: [0003] “computer-implemented method includes: monitoring, by a computing device, stimuli exposed to an unborn child based on sensor data”), further comprising:
identifying a second trigger to transition away from the second operational mode; transitioning from the second operational mode to the first operational mode based at least in part on the second trigger (Cline: [0129] “one of said components may identify whether the other component is available for communication by periodically transmitting a preset signal and wait a predetermined time for a predetermined response sequence. If a said response is received, communications may begin; otherwise, said initiating component may enter a sleep mode”; [0069] temperature, removal of an adhesive backer, removal from a sealed pouch, impedance between electrodes, insertion of a battery, and/or presence of a cardiac signal, or another predetermined input and/or trigger … [results in] waking from sleep mode. After said predetermined sensor input is obtained, said device in some cases automatically enters the mode for monitoring the patient's pregnancy, and/or in some cases enters a mode of preparation and/or readiness for calibration and/or syncing with other components of the pregnancy monitoring system, and/or in some cases enters a different state in a state machine.”);
and providing, to the user device based at least in part on transitioning to the first operational mode, the first set of targets and the first set of messages based at least in part on the first operational mode (Bennet: [0193] “a mode of operation for predicting and displaying an optimal time for impregnation;” [0173] “The Internet based system, geographically remote intravaginal monitoring devices further consists of an imager for imaging and tracking clinically relevant changes related to an ovulation event and or the lack thereof to obtain imaged and tracked data, and temperature sensing and tracking capability to obtain sensed and tracked data, the image and tracked data being optionally correlated to the sensed and tracked data to obtain a fertility profile.”). Cline: [0083] “the pregnancy monitoring system may initially gather data regarding uterine activity as part of a baseline assessment state”; [0084] a notification delivery system in a first notification mode [baseline assessment state], and a notification manager configured to compare received uterine activity data to a threshold).
Regarding claim 10, the combination of Rakshit/Bennett/Cline discloses the method of claim 1 (Rakshit: [0003] “computer-implemented method includes: monitoring, by a computing device, stimuli exposed to an unborn child based on sensor data”), wherein the physiological data comprises temperature data (Cline: [0081] “the pregnancy monitoring system may collect and use one or more of the following: … maternal skin temperature … The system may deliver said data to the patient and/or the patient's physician, as well as derived metrics including frequency and trends in occurrence.”), the method further comprising:
identifying that the temperature data satisfies a temperature threshold for the user, wherein identifying the trigger is based at least in part on the temperature data satisfying the temperature threshold for the user (Cline: [0069] “temperature, … or another predetermined input and/or trigger is used to determine whether said device has been placed on the patient's belly and/or will soon be put into use. In some cases, said device wakes from said sleep mode to check for said predetermined input and/or trigger; in some cases, said predetermined input and/or trigger triggers waking from sleep mode. After said predetermined sensor input is obtained, said device in some cases automatically enters the mode for monitoring the patient's pregnancy, and/or in some cases enters a mode of preparation and/or readiness for calibration and/or syncing with other components of the pregnancy monitoring system, and/or in some cases enters a different state in a state machine.”).
Regarding claim 11, the combination of Rakshit/Bennett/Cline discloses the method of claim 1 (Rakshit: [0003] “computer-implemented method includes: monitoring, by a computing device, stimuli exposed to an unborn child based on sensor data”), wherein the first operational mode comprises a non-pregnant mode and the second operational mode comprises a pregnancy mode (Bennet: [0193] “a mode of operation for predicting and displaying an optimal time for impregnation;” [0047] “the menu includes an STD detection mode of operation and or service, an ovulation detection mode of operation or service, a rhythm method (infertility) mode of operation or service, a precancerous tissue monitoring or service, a general cervix monitoring mode of operation, an infection mode of operation and or service, a pregnancy mode of operation and or service.” Cline: “[0083] The term baseline assessment mode may be used to describe the baseline assessment state; the term active monitoring mode may be used to describe the active monitoring state.), the first set of targets comprise targets associated with the user when the user is in the non-pregnant state (Bennett: [0173] “The Internet based system, geographically remote intravaginal monitoring devices further consists of an imager for imaging and tracking clinically relevant changes related to an ovulation event and or the lack thereof to obtain imaged and tracked data, and temperature sensing and tracking capability to obtain sensed and tracked data, the image and tracked data being optionally correlated to the sensed and tracked data to obtain a fertility profile.”), the second set of targets comprise a set of adjusted targets associated with the user when the user is pregnant, and the second set of messages are configured to promote the set of adjusted targets ([0083] Transitioning to the active monitoring state may involve enabling notifications that were not enabled in the baseline assessment state. In some embodiments, when the pregnancy monitoring system is operating in the active monitoring state and detects a contraction, the pregnancy monitoring system may determine the likelihood of a labor-related status based on comparison of the contraction to one or more contraction detected in the baseline assessment state; if the likelihood is determined to be above a threshold, a notification may be delivered.).
Regarding claim 12, the combination of Rakshit/Bennett/Cline discloses the method of claim 1 (Rakshit: [0003] “computer-implemented method includes: monitoring, by a computing device, stimuli exposed to an unborn child based on sensor data”), further comprising:
receiving, via the user device, a user input comprising a date of a user's last menstrual cycle, an estimated date of conception, a date of a first positive pregnancy test, an estimated due date, an actual birth date, or a combination thereof, wherein identifying the trigger is based at least in part on receiving the user input (Cline: [0079] “The pregnancy monitoring system may integrate clinical data, such as gestational age [inherently based on the date of the last menstrual cycle and is directly related to estimated date of conception, a date of a first positive pregnancy test, an estimated due date/projected birth date] … into the assessment of the likelihood of labor and/or delivery within a specified length of time or before a specified gestational age. For example, a patient, patient's physician, or other person may enter said clinical data into an electronic interface, such as a smartphone application.”).
Regarding claim 13, the combination of Rakshit/Bennett/Cline discloses the method of claim 1 (Rakshit: [0003] “computer-implemented method includes: monitoring, by a computing device, stimuli exposed to an unborn child based on sensor data”), further comprising:
causing a graphical user interface of the user device to display pregnancy symptom tags based at least in part on the second operational mode (Cline: [0079] “the pregnancy monitoring system may contain means for assessing parameters such as maternal respiration rate … maternal heart rate … fetal heart rate … maternal stress …, maternal temperature …, maternal posture …, maternal activity …, maternal steps taken … and/or maternal fluid status. Parameters such as these may displayed to the pregnant woman and/or to another user, and/or status regarding parameters such as these may be reported via a notification. For example, a daily step count of the pregnant woman may be derived from data collected with an accelerometer that is part of the data acquisition device, and the daily step count may be displayed to the pregnant woman on the patient interface device.”).
Regarding claim 14, the combination of Rakshit/Bennett/Cline discloses the method of claim 1 (Rakshit: [0003] “computer-implemented method includes: monitoring, by a computing device, stimuli exposed to an unborn child based on sensor data”), further comprising:
causing a graphical user interface of the user device to display the second set of targets and the second set of messages that are adjusted for pregnancy based at least in part on the second operational mode (Cline: [0007] “the labor-related status may comprise one or more of the following: absence of true labor, presence of true labor, onset of true labor, predicted amount of time until onset of true labor, predicted amount of time until the delivery of an infant, and delivery of an infant. In some embodiments, delivery of the notification may be automated. … the notification may comprise one or more of the following: a text message, an electronic mail, a message within a smartphone application, a social media notification, and a phone call. [0047] Said patient interface device may comprise the pregnant woman's cellular telephone [0049] Assessment of data (for example to determine the likelihood of delivery) and determination of whether notification (for example of the pregnant woman and/or her physician) is necessary may be performed by the data acquisition device, and/or the patient interface device. Said assessment and determination to generate a notification may be conducted in an automated of semi-automated process).
Regarding claim 17, the combination of Rakshit/Bennett/Cline discloses the method of claim 1 (Rakshit: [0003] “computer-implemented method includes: monitoring, by a computing device, stimuli exposed to an unborn child based on sensor data”), wherein the one or more physiological metrics comprise one or more sleep metrics (Cline: [0081] “the pregnancy monitoring system may collect and use one or more of the following: fetal sleep or wakefulness status; maternal sleep or wakefulness status… The system may deliver said data to the patient and/or the patient's physician, as well as derived metrics including frequency and trends in occurrence.”).
Regarding claim 19, Rakshit teaches an apparatus (Fig. 1; Fig. 5, sensor devices 210; [0065] “smart ring device”), comprising: a processor; memory coupled with the processor; and instructions stored in the memory and executable by the processor ([0005] “a system includes: a processor, a computer readable memory and a computer readable storage medium associated with a computing device; program instructions to determine, based on sensor data gathered by one or more sensor devices”) to cause the apparatus to:
acquire, via one or more sensors of a wearable ring device configured to be worn by a user, physiological data associated with the user ([0065] “gathering sensor data of participants [e.g., pregnant women] wearing various types of wearable sensor devices (e.g., smart watches/ring/eyewear, electronic tattoos, smart clothing, etc.]… smart ring devices”);
receive, via a transceiver of a user device and from the wearable ring device, physiological data associated with the user ([0064] “As shown in FIG. 4, movement/kick patterns of an unborn child are determined from sensor data (e.g., from sensor devices, such as those implemented in wearable computing devices worn by a mother of the unborn child). The sensor data, combined with data from a knowledge corpus, is used to make a health-related prediction regarding the unborn child (e.g., a prediction of possible hearing loss in the unborn child)”).
However, Rakshit fails to disclose physiological targets when a user is in a non-pregnant state. Bennett teaches intravaginal monitoring devices, supporting networks, web services, modes of operation of the devices and networks, and processing of data harvested by an intravaginal device and communication to the network.
The combination of Rakshit/Bennett discloses:
provide, to the user device associated with the user and in accordance with a first operational mode of an application associated with the wearable ring device (Rakshit: [0065] “smart ring device;” Bennett: [0047] “server 173 or other network node includes a select service mode of operation, which provides various functionalities on device 115 … For example, the menu includes an STD detection mode of operation and or service, an ovulation detection mode of operation or service, a rhythm method (infertility) mode of operation or service, a precancerous tissue monitoring or service, a general cervix monitoring mode of operation, an infection mode of operation and or service),
a first set of targets associated with one or more physiological metrics acquired via the one or more sensors of the wearable ring device when the user is in a non-pregnant state and a first set of messages associated with the one or more physiological metrics acquired via the one or more sensors of the wearable ring device based at least in part on the physiological data acquired via the one or more sensors of the wearable ring device, the first set of targets and the first set of messages associated with the first operational mode of the application associated with the wearable ring device that is associated with the user (Rakshit: [0065] “smart ring device;” [00072] “The sensor devices 210 include one or more sensors (e.g., movement sensors, object sensors, biometric sensors, accelerometers, etc.), cameras, audio input devices, Internet of Things (IoT) devices, etc.” Bennett: Fig. 4; [0193] “a mode of operation for predicting and displaying an optimal time for impregnation;” [0173] “The Internet based system, geographically remote intravaginal monitoring devices [rather the smart ring device per Rakshit] further consists of an imager for imaging and tracking clinically relevant changes related to an ovulation event and or the lack thereof to obtain imaged and tracked data, and temperature sensing and tracking capability to obtain sensed and tracked data, the image and tracked data being optionally correlated to the sensed and tracked data to obtain a fertility profile.”).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the method of Rakshit to include physiological targets when a user is in a non-pregnant state as disclosed in Bennett to provide for a way for a woman to readily know about the status of her reproductive health and fertility from the comfort of her own home (Bennett [0019, 0173]).
While, the combination of Rakshit/Bennett includes a pregnancy mode that may be selected, it fails to disclose specific user input information regarding the user being pregnant. Cline teaches devices, systems and methods that enable and make assessments related to pregnancy.
Cline discloses receive, via the user device, a user input comprising an indication of the user being pregnant ([0079] “The pregnancy monitoring system may integrate clinical data, such as gestational age, number of fetuses, body mass index of the mother, parity of the mother, whether the mother has had previous preterm deliveries, cervical remodeling [including measures of cervical length, softness, ripening, and/or effacement], maternal respiration rate, maternal heart rate, and/or fetal heart rate into the assessment of the likelihood of labor and/or delivery within a specified length of time or before a specified gestational age. For example, a patient, patient's physician, or other person may enter said clinical data into an electronic interface, such as a smartphone application.”).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the combination of Rakshit/Bennett to include user input indicating the user being pregnant as disclosed in Cline to adjust pregnancy assessment parameters for more accurate tracking and notification of pregnancy and labor-related status (Cline [0079, [0083]).
The combination of Rakshit/Bennett/Cline discloses:
identify a trigger to transition from the first operational mode to a second operational mode of the application associated with the wearable ring device that is associated with the user based at least in part on receiving the indication (Rakshit: [0065] “smart ring device;” Bennett: [0193] “a mode of operation for predicting and displaying an optimal time for impregnation;” [0047] “The menu is provided to a medical professional, purchaser of the intravaginal device or user of the intravaginal device for the individual to select device functionality. For example, the menu includes an STD detection mode of operation and or service, an ovulation detection mode of operation or service, a rhythm method (infertility) mode of operation or service, a precancerous tissue monitoring or service, a general cervix monitoring mode of operation, an infection mode of operation and or service, a pregnancy mode of operation and or service.” Cline: [0083] “In some embodiments, the pregnancy monitoring system makes at least one transition between states as part of operation … the pregnancy monitoring system may initially gather data regarding uterine activity as part of a baseline assessment state. After gathering a sufficient amount of baseline data, the system may transition to an active monitoring state.” [0079] “The pregnancy monitoring system may integrate clinical data, … [via] a smartphone application.”
and provide, to the user device based at least in part on identifying the trigger, a second set of targets associated with the one or more physiological metrics and a second set of messages associated with the one or more physiological metrics that are adjusted for pregnancy and different from the first set of targets and the first set of messages based at least in part on the second operational mode (Cline: [0083] “Transitioning to the active monitoring state may involve enabling notifications that were not enabled in the baseline assessment state. In some embodiments, when the pregnancy monitoring system is operating in the active monitoring state and detects a contraction, the pregnancy monitoring system may determine the likelihood of a labor-related status based on comparison of the contraction to one or more contraction detected in the baseline assessment state; if the likelihood is determined to be above a threshold, a notification may be delivered. The term baseline assessment mode may be used to describe the baseline assessment state; the term active monitoring mode may be used to describe the active monitoring state.” [0084] “the pregnancy monitoring system comprises at least two electrodes coupled to a pregnant female, a processor configured to analyze uterine activity, a notification delivery system in a first notification mode, and a notification manager configured to compare received uterine activity data to a threshold, and if the uterine activity data exceeds the threshold, transition the notification delivery system to a second notification mode, wherein at least one additional type of notification is enabled.”).
Regarding claim 20, Cline teaches a non-transitory computer-readable medium storing code, the code comprising instructions executable by a processor ([0005] “a system includes: a processor, a computer readable memory and a computer readable storage medium associated with a computing device; program instructions to determine, based on sensor data gathered by one or more sensor devices;” Fig. 1; Fig. 5) to:
acquire, via one or more sensors of a wearable ring device configured to be worn by a user, physiological data associated with the user ([0065] “gathering sensor data of participants [e.g., pregnant women] wearing various types of wearable sensor devices (e.g., smart watches/ring/eyewear, electronic tattoos, smart clothing, etc.]… smart ring devices”);
receive, via a transceiver of a user device and from the wearable ring device, physiological data associated with the user ([0064] “As shown in FIG. 4, movement/kick patterns of an unborn child are determined from sensor data (e.g., from sensor devices, such as those implemented in wearable computing devices worn by a mother of the unborn child). The sensor data, combined with data from a knowledge corpus, is used to make a health-related prediction regarding the unborn child (e.g., a prediction of possible hearing loss in the unborn child)”).
However, Rakshit fails to disclose physiological targets when a user is in a non-pregnant state. Bennett teaches intravaginal monitoring devices, supporting networks, web services, modes of operation of the devices and networks, and processing of data harvested by an intravaginal device and communication to the network.
The combination of Rakshit/Bennett discloses:
provide, to the user device associated with the user and in accordance with a first operational mode of an application associated with the wearable ring device (Rakshit: [0065] “smart ring device;” Bennett: [0047] “server 173 or other network node includes a select service mode of operation, which provides various functionalities on device 115 … For example, the menu includes an STD detection mode of operation and or service, an ovulation detection mode of operation or service, a rhythm method (infertility) mode of operation or service, a precancerous tissue monitoring or service, a general cervix monitoring mode of operation, an infection mode of operation and or service),
a first set of targets associated with one or more physiological metrics acquired via the one or more sensors of the wearable ring device when the user is in a non-pregnant state and a first set of messages associated with the one or more physiological metrics acquired via the one or more sensors of the wearable ring device based at least in part on the physiological data acquired via the one or more sensors of the wearable ring device, the first set of targets and the first set of messages associated with the first operational mode of the application associated with the wearable ring device that is associated with the user (Rakshit: [0065] “smart ring device;” [00072] “The sensor devices 210 include one or more sensors (e.g., movement sensors, object sensors, biometric sensors, accelerometers, etc.), cameras, audio input devices, Internet of Things (IoT) devices, etc.” Bennett: Fig. 4; [0193] “a mode of operation for predicting and displaying an optimal time for impregnation;” [0173] “The Internet based system, geographically remote intravaginal monitoring devices [rather the smart ring device per Rakshit] further consists of an imager for imaging and tracking clinically relevant changes related to an ovulation event and or the lack thereof to obtain imaged and tracked data, and temperature sensing and tracking capability to obtain sensed and tracked data, the image and tracked data being optionally correlated to the sensed and tracked data to obtain a fertility profile.”).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the method of Rakshit to include physiological targets when a user is in a non-pregnant state as disclosed in Bennett to provide for a way for a woman to readily know about the status of her reproductive health and fertility from the comfort of her own home (Bennett [0019, 0173]).
While, the combination of Rakshit/Bennett includes a pregnancy mode that may be selected, it fails to disclose specific user input information regarding the user being pregnant. Cline teaches devices, systems and methods that enable and make assessments related to pregnancy.
Cline discloses receive, via the user device, a user input comprising an indication of the user being pregnant ([0079] “The pregnancy monitoring system may integrate clinical data, such as gestational age, number of fetuses, body mass index of the mother, parity of the mother, whether the mother has had previous preterm deliveries, cervical remodeling [including measures of cervical length, softness, ripening, and/or effacement], maternal respiration rate, maternal heart rate, and/or fetal heart rate into the assessment of the likelihood of labor and/or delivery within a specified length of time or before a specified gestational age. For example, a patient, patient's physician, or other person may enter said clinical data into an electronic interface, such as a smartphone application.”).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the combination of Rakshit/Bennett to include user input indicating the user being pregnant as disclosed in Cline to adjust pregnancy assessment parameters for more accurate tracking and notification of pregnancy and labor-related status (Cline [0079, [0083]).
The combination of Rakshit/Bennett/Cline discloses:
identify a trigger to transition from the first operational mode to a second operational mode of the application associated with the wearable ring device that is associated with the user based at least in part on receiving the indication (Rakshit: [0065] “smart ring device;” Bennett: [0193] “a mode of operation for predicting and displaying an optimal time for impregnation;” [0047] “The menu is provided to a medical professional, purchaser of the intravaginal device or user of the intravaginal device for the individual to select device functionality. For example, the menu includes an STD detection mode of operation and or service, an ovulation detection mode of operation or service, a rhythm method (infertility) mode of operation or service, a precancerous tissue monitoring or service, a general cervix monitoring mode of operation, an infection mode of operation and or service, a pregnancy mode of operation and or service.” Cline: [0083] “In some embodiments, the pregnancy monitoring system makes at least one transition between states as part of operation … the pregnancy monitoring system may initially gather data regarding uterine activity as part of a baseline assessment state. After gathering a sufficient amount of baseline data, the system may transition to an active monitoring state.” [0079] “The pregnancy monitoring system may integrate clinical data, … [via] a smartphone application.”
and provide, to the user device based at least in part on identifying the trigger, a second set of targets associated with the one or more physiological metrics and a second set of messages associated with the one or more physiological metrics that are adjusted for pregnancy and different from the first set of targets and the first set of messages based at least in part on the second operational mode (Cline: [0083] “Transitioning to the active monitoring state may involve enabling notifications that were not enabled in the baseline assessment state. In some embodiments, when the pregnancy monitoring system is operating in the active monitoring state and detects a contraction, the pregnancy monitoring system may determine the likelihood of a labor-related status based on comparison of the contraction to one or more contraction detected in the baseline assessment state; if the likelihood is determined to be above a threshold, a notification may be delivered. The term baseline assessment mode may be used to describe the baseline assessment state; the term active monitoring mode may be used to describe the active monitoring state.” [0084] “the pregnancy monitoring system comprises at least two electrodes coupled to a pregnant female, a processor configured to analyze uterine activity, a notification delivery system in a first notification mode, and a notification manager configured to compare received uterine activity data to a threshold, and if the uterine activity data exceeds the threshold, transition the notification delivery system to a second notification mode, wherein at least one additional type of notification is enabled.”).
Claim(s) 15 is rejected under 35 U.S.C. 103 as being unpatentable over Rakshit (US 20200155058 A1) in view of Cline (US 20160331299 A1) and Bennett (US 20110190595 A1), and in further view of Neumann (US 20210241133 A1).
Regarding claim 15, the combination of Rakshit/Bennett/Cline discloses the method of claim 14 (Rakshit: [0003] “computer-implemented method includes: monitoring, by a computing device, stimuli exposed to an unborn child based on sensor data”), wherein the second set of messages (Cline: [0003] notifying one or more persons on the register may involve delivering to one or more persons on the register, one or more of the following: a text message, an electronic mail, a message within a smartphone application, a social media notification, a phone call).
However the combination of Rakshit/Bennett/Cline fails to disclose recommendations and educational content associated with pregnancy.
Neumann teaches a system for physiologically informed gestational inquiries. Neumann discloses further comprise trimester-specific physiological insights associated with pregnancy, a recommended wake time during which the user wakes up, a recommended bedtime during which the user goes to sleep, a recommended sleep duration, a recommended time of day during with the user rests, a request to input symptoms associated with pregnancy, educational content associated with pregnancy, or a combination thereof ([0021] “A ‘gestational inquiry,’ as used in this disclosure, is data containing any advice sought and/or question relating to any gestational phase. A gestational inquiry 128 may contain an inquiry related to any gestational phase including advice sought [educational content associated with pregnancy] regarding medications including both prescription and non-prescription medications, vitamins, and supplements; pets; household products; fitness; chemicals; food consumption and food recommendations; alcohol consumption and alcohol recommendations; use of cosmetics; building materials such as paint; activities such as sports, leisure time activities [sleep/wake/rest recommendations]; medical treatments; exposure to environmental toxins; travel including travel by cars, planes, trains, boats, and the like. … In yet another non-limiting example a gestational inquiry 128 may seek advice about what types of medical treatments are safe to be performed during a user's third trimester [trimester-specific physiological insights associated with pregnancy”]; [0088] “For instance and without limitation, computing device 104 may determine that hair dye is not suitable for a user in the first trimester or the second trimester but is suitable in the third trimester and in the postpartum phase”; [0047] “With continuing reference to FIG. 1, physiological state data may include one or more user-entered descriptions of a person's physiological state. One or more user-entered descriptions may include, without limitation, user descriptions of symptoms [request to input symptoms associated with pregnancy”]).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the method of Cline to include insights and symptoms associated with pregnancy as disclosed in Neumann to provide users with the ability to determine if products and services are safe/compatible with the user based on the gestational phase of the user (Neumann [0002]).
Claim(s) 16 is rejected under 35 U.S.C. 103 as being unpatentable over Rakshit (US 20200155058 A1) in view of Cline (US 20160331299 A1) and Bennett (US 20110190595 A1), and in further view of Altini (US 20170224268 A1).
Regarding claim 16, the combination of Rakshit/Bennett/Cline discloses the method of claim 1 (Rakshit: [0003] “computer-implemented method includes: monitoring, by a computing device, stimuli exposed to an unborn child based on sensor data”). However, the combination of Rakshit/Bennett/Cline fails to disclose a machine learning classifier.
Altini teaches systems and methods for monitoring the onset or occurrence of labor contractions and detecting or estimating labor in a pregnant female. Altini discloses further comprising: inputting the physiological data into a machine learning classifier ([0070] “analyzing the parameter of interest includes feeding the parameter into a machine learning model or algorithm trained to detect labor. The machine learning model or algorithm may be trained to detect labor based on past physiological data and recorded experiences provided by past users of the system”).
The combination of Rakshit/Bennett/Cline/Altini then discloses wherein providing, to the user device, the second set of targets and the second set of messages (Cline: [0083] “when the pregnancy monitoring system is operating in the active monitoring state and detects a contraction, the pregnancy monitoring system may determine the likelihood of a labor-related status based on comparison of the contraction to one or more contraction detected in the baseline assessment state; if the likelihood is determined to be above a threshold, a notification may be delivered”) is based at least in part on inputting the physiological data into the machine learning classifier (Altini: [0070] “analyzing the parameter of interest includes feeding the parameter into a machine learning model or algorithm trained to detect labor”).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the combination of Rakshit/Bennett/Cline to include a machine learning classifier as disclosed in Altini to mine through vast quantities of data to identify common trends, rules, or correlations and compare recorded data to observed outcomes to identify patterns that can be used to predict or identify labor (Altini [0070]).
Conclusion
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/M.H./Examiner, Art Unit 3791
/DEVIN B HENSON/Primary Examiner, Art Unit 3791