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 .
Continued Examination Under 37 CFR 1.114
A request for continued examination under 37 CFR 1.114, including the fee set forth in 37 CFR 1.17(e), was filed in this application after final rejection. Since this application is eligible for continued examination under 37 CFR 1.114, and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114. Applicant's submission filed on 9/11/2025 has been entered.
Response to Arguments
Rejections under 35 USC 103
Applicant’s arguments, see pages 10-13 of Applicant Remarks filed 01/23/2026, with respect to the rejection(s) of claim(s) 1, 2, 6, 9, 10, 13-18, and 27-31 under 35 USC 103 have been fully considered and are persuasive. Therefore, the rejection has been withdrawn. However, upon further consideration, a new ground(s) of rejection is made in view of Shuler et al (US 20150039239 A1), Trapero Martin et al (US 11116448 B1), Goldfain (US 20160165852 A1), and Menkes et al (US 20140123912 A1) elaborated upon below.
Applicant argues that none of the prior art presented in the Non-Final Office Action dated 01/23/2025 teaches the limitation of “an array of non-contact transducers, lasers, and sensor.” The sensing array as taught by Shuler comprises contact only sensors and Shusterman does not cure this deficiency as the sensing array taught by Shusterman comprises a contact-based transducer and lasers/non-contact sensors that are configured for human use.
While Examiner agrees that the previously cited combination does not teach the claimed structures, it should be noted that this conclusion is based on the presence of the structural elements of an array of non-contact transducers, laser, and sensors. The argument presented that a sensing array is only configured for human use does not in any way preclude the array from being used with an animal, as long as it meets the structural limitations, and may be configured to be integrated into a wearable device.
Information Disclosure Statement
The Information Disclosure Statement (IDS) filed on 05/12/2023 has been considered by the examiner.
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
Claim(s) 1, 2, 6, 9, 10, 13, 14, 16, 18, and 27-31 is/are rejected under 35 U.S.C. 103 as being unpatentable over Shuler et al (US 20150039239 A1) in view of Trapero Martin et al (US 11116448 B1), hereinafter referred to as Trapero.
Regarding claim 1, Shuler teaches a system comprising a plurality of animal health devices (306, see [0083]; animal health monitoring system may be used with a population of animals) communicatively coupled to a network and configured to receive animal health data (see [0058]; data collection sensor device 306 has data transmission means such as transmitter or transceiver),
each animal health device (306) of the plurality of animal health devices associated with an associated animal (see [0054]; animal health monitoring system may be used with a population of animals, it can be appreciated that based on the nature of the data collection via data collection sensor device 306 that may be worn by an animal, that for a population of animals to be monitored by the system each animal has its own data collection sensor device),
each animal health device of the plurality of animal health devices including an array of sensors to detect the animal health data (see [0056]; data collection sensor device 306 includes a plurality of sensors of different types for measuring behaviors and physiological conditions of the animal),
the array of sensors being integrated in or attachable to a collar (see [0057]; data collection sensor device 306 is coupled to a collar worn by the animal) and
configured to detect the animal health data, the animal health data being vital signs of the animal (see [0056]; data collection sensor device has means to collect various physiological conditions including vital signs);
each animal health device of the plurality of animal health devices further comprising a memory (see [0058-0059]; data is stored in a non-volatile memory unit on sensor device 306), a processor (see [0055-0058]; sensor device 306 having sensor circuitry and transmission means that communicate with the monitoring system, it can therefore be appreciated that the device must have processing capabilities that allow for the collection and transmission of data in accordance with the system) and transmission means for sending data to a network (see [0058]; data collection sensor device 306 has data transmission means such as transmitter or transceiver),
the network being communicatively coupled to at least some of the plurality of animal health devices (see Fig. 5, [0061]; data analysis system 302 is coupled to receive data from system 300 including data collection sensor device 306),
the network (see Fig. 5, [0053]; data analysis system 302) including an artificial intelligence application (see Fig. 6; algorithms 312,316) executable by at least one processor (see [0109]; the system includes at least one computing device including at least one processor),
the at least one processor executing a series of instructions (see Fig. 6) that cause the artificial intelligence application to:
receive the animal health data and one or more parameters associated with the associated animal (see [0109]; system generates a baseline data signature based on a first set of collected data);
predict a health status for the associated animal based on the received animal health data and the one or more parameters (see [0112]; the processor may predictively diagnose a health condition, [0052]; the system monitors, manages, and diagnoses the health status of at least one animal in order to predict an oncoming illness before visible signs of the illness occur); and
aggregate the animal health data collected from the plurality of animal health devices and diagnostic results for improvement of a predictability of an animal health condition (see [0116]; the processor may generate an assessment for a plurality of animals and compare the health states of an animal to corresponding animals in another geographic location, [0064]; health state profiles may be based on data collected from an animal that is not the subject animal being monitored, but is of the same species).
Shuler is silent regarding wherein each animal health device of the plurality of animal health devices including an array of non-contact transducers, lasers and sensors to detect the animal health data,
the array of non-contact transducers, lasers and sensors being integrated in or attachable to a collar, harness or bridle and
configured for not contacting the associated animal to detect the animal health data, the animal health data being vital signs of the animal.
However, Trapero teaches a sensing electronic module (102) which may be integrated into a wearable device such as a smartwatch (Trapero [Col 9, lines 57-66]), wherein the sensing module includes an array of non-contact transducers, lasers, and sensors (240) to detect health data (see Trapero Fig. 2, [Col 12, line 14-Col 13, line 29]; bottom surface of PCB 224, which may be located in electronics module 102, may comprise various non-contact sensors 240 such as optical sensors, imaging sensors, thermal imaging sensors, laser sensors, ultrasonic Doppler flow meters, electromagnetic flow meters, etc.).
It can be appreciated that the module 102 as taught by Trapero can be integrated into an animal device such as a harness or collar, due to its ability to integrate into a wearable device such as a smart watch (Trapero [Col 9, lines 57-66]). The sensor array 240 is comprised of non-contact sensors, which may be lasers, such as in the case of a light emitter for use in a PPG system, in the form of a laser (Trapero [Col 12, lines 20-25]). It can be appreciated that the previously listed sensors may all act as a transducer as they convert a measured signal (for example, light intensity measured by a photodetector) into an electrical signal. The non-contact sensor array 240 is positioned within the electronics module 102 above the sensor window 112 located on the bottom surface of the module, allowing the non-contact sensor array to collect sensor data through the sensor window without the sensor itself directly contacting the user (Trapero [Col 11, line 63-Col 12, line 3]).
It would have been obvious for one of ordinary skill in the art prior to the effective filing date of the claimed invention to modify the animal health device as taught by Shuler with the array of non-contact transducers, lasers, and sensors as taught by Trapero. One of ordinary skill in the art would have been motivated to make this modification in order to facilitate the measurement of physiological data through a sensor window which allows for data gathering while protecting the electronics within the sensing module from outside contaminants (Trapero [Col 9, lines 12-16]).
Regarding claim 2, Shuler and Trapero teach the system of claim 1. Shuler further teaches the animal health data including heart rate, heart rhythm, respiration rate, calories burned, an activity level, a sleep score, body temperature, or pulse oximetry (see [0056]; data collection sensor device can include a plurality of sensors to measure heart rate, breathing rate, body temperature, number of steps taken).
Note that the non-contact sensing array as taught by Trapero also teaches wherein the animal health data includes heart rate, respiration rate, oxygen saturation, and other physiological metrics (Trapero [Col 12, lines 13-21]).
Regarding claim 6, Shuler and Trapero teach the system of claim 1. Shuler further teaches the system comprising an accelerometer ([0056]; data collection sensor device 306 can include an accelerometer).
Regarding claim 9, Shuler and Trapero teach the system of claim 1. Shuler further teaches the animal health device configured to connect to a cloud resource (see [0058]; Data collection sensor device 306 further includes a data transmission means such as transmitter or transceiver for transmitting data to data analysis system 302, Fig. 7, cloud 302).
Regarding claim 10, Shuler and Trapero teach the system of claim 9. Shuler further teaches the cloud resource configured to connect to a veterinary computing system or an animal owner's computing system (see Fig. 7, [0053]; user interface dashboard system 304 for animal care professionals and stakeholders).
Regarding claim 13, Shuler and Trapero teach the system of claim 1. Shuler further teaches the system comprising the animal health data is a predictor of a medical issue in an animal (see [0112]; the system predictively diagnoses a health condition in the animal based on a comparison to baseline physiological data).
Regarding claim 14, Shuler and Trapero teach the system of claim 13. Shuler further teaches wherein the predictor is an increase in heart rate and a decrease in activity level to indicate the medical issue is pain (see [0062-0063]; the baseline signature for an animal is determined based on data collected from a variety of sensors including heart rate or movement data from an accelerometer, deviation from the baseline signature may be used to indicate whether the animal is in pain).
Regarding claim 16, Shuler and Trapero teach the system of claim 13. Shuler further teaches herein the predictor is accelerometer data indicating how much scratching activity is occurring when the animal owner is not around (see [0061]; sensed activities including scratching activity may be used to deduce a health event in the animal including anxiety, it can be appreciated that based on the data collection method of the sensor device, that scratching/other activity data is collected at regular intervals over a pre-determined period of time that may span a time when the owner is not around [0055]).
Regarding claim 18, Shuler and Trapero teach the system of claim 13. Shuler further teaches wherein the predictor is accelerometer data indicating the animal has separation anxiety (see [0062-0063]; the baseline signature for an animal is determined based on data collected from a variety of sensors including movement data from an accelerometer, deviation from the baseline signature may be used to indicate whether the animal is anxious).
Regarding claim 27, Shuler teaches a method comprising:
communicatively coupling a plurality of animal health devices (306) to a network (see [0083]; animal health monitoring system may be used with a population of animals, [0058]; data collection sensor device 306 has data transmission means such as transmitter or transceiver);
configuring the plurality of animal health devices to receive animal health data (see [0056]; data collection sensor device 306 includes a plurality of sensors for measuring various behaviors and physiological conditions of an animal);
associating each animal health device of the plurality of animal health devices with an associated animal (see [0054]; animal health monitoring system may be used with a population of animals, it can be appreciated that based on the nature of the data collection via data collection sensor device 306 that may be worn by an animal, that for a population of animals to be monitored by the system each animal has its own data collection sensor device),
each animal health device of the plurality of animal health devices including an array of sensors to detect the animal health data, (see [0056]; data collection sensor device 306 includes a plurality of sensors of different types for measuring behaviors and physiological conditions of the animal),
the array of sensors being integrated in or attachable to a collar (see [0057]; data collection sensor device 306 is coupled to a collar worn by the animal), and
configured to detect the animal health data, the animal health data being vital signs of the animal (see [0056]; data collection sensor device has means to collect various physiological conditions including vital signs);
communicatively coupling at least some of the plurality of animal health devices to a network (see Fig. 7, [0058]; data collection sensor device is coupled to data analysis system 302),
each animal health device of the plurality of animal health devices further comprising a memory (see [0058-0059]; data is stored in a non-volatile memory unit on sensor device 306), a processor (see [0055-0058]; sensor device 306 having sensor circuitry and transmission means that communicate with the monitoring system, it can therefore be appreciated that the device must have processing capabilities that allow for the collection and transmission of data in accordance with the system), and transmission means for sending data to a network (see [0058]; data collection sensor device 306 has data transmission means such as transmitter or transceiver),
the network including an artificial intelligence application (see Fig. 5, [0053]; data analysis system 302) executable by at least one processor (see [0109]; the system includes at least one computing device including at least one processor), the at least one processor executing a series of instructions (Fig. 6) for:
receiving, by the artificial intelligence application, the animal health data and one or more parameters associated with the associated animal (see [0109]; system generates a baseline data signature based on a first set of collected data);
predicting, by the artificial intelligence application, a health status for the associated animal based on the received animal health data and the one or more parameters (see [0112]; the processor may predictively diagnose a health condition, [0052]; the system monitors, manages, and diagnoses the health status of at least one animal in order to predict an oncoming illness before visible signs of the illness occur); and
aggregating, by the artificial intelligence application, the animal health data collected from the plurality of animal health devices and diagnostic results for improvement of a predictability of an animal health condition (see [0116]; the processor may generate an assessment for a plurality of animals and compare the health states of an animal to corresponding animals in another geographic location, [0064]; health state profiles may be based on data collected from an animal that is not the subject animal being monitored, but is of the same species).
Shuler is silent regarding an animal health device including an array of non-contact transducers, lasers and sensors to detect the animal health data.
However, Trapero teaches a sensing electronic module (102) which may be integrated into a wearable device such as a smartwatch (Trapero [Col 9, lines 57-66]), wherein the sensing module includes an array of non-contact transducers, lasers, and sensors (240) to detect health data (see Trapero Fig. 2, [Col 12, line 14-Col 13, line 29]; bottom surface of PCB 224, which may be located in electronics module 102, may comprise various non-contact sensors 240 such as optical sensors, imaging sensors, thermal imaging sensors, laser sensors, ultrasonic Doppler flow meters, electromagnetic flow meters, etc.).
It can be appreciated that the module 102 as taught by Trapero can be integrated into an animal device such as a harness or collar, due to its ability to integrate into a wearable device such as a smart watch (Trapero [Col 9, lines 57-66]). The sensor array 240 is comprised of non-contact sensors, which may be lasers, such as in the case of a light emitter for use in a PPG system, in the form of a laser (Trapero [Col 12, lines 20-25]). It can be appreciated that the previously listed sensors may all act as a transducer as they convert a measured signal (for example, light intensity measured by a photodetector) into an electrical signal. The non-contact sensor array 240 is positioned within the electronics module 102 above the sensor window 112 located on the bottom surface of the module, allowing the non-contact sensor array to collect sensor data through the sensor window without the sensor itself directly contacting the user (Trapero [Col 11, line 63-Col 12, line 3]).
It would have been obvious for one of ordinary skill in the art prior to the effective filing date of the claimed invention to modify the animal health device as taught by Shuler with the array of non-contact transducers, lasers, and sensors as taught by Trapero. One of ordinary skill in the art would have been motivated to make this modification in order to facilitate the measurement of physiological data through a sensor window which allows for data gathering while protecting the electronics within the sensing module from outside contaminants (Trapero [Col 9, lines 12-16]).
Regarding claim 28, Shuler and Trapero teach the method of claim 27. Shuler further teaches the animal health data including heart rate, heart rhythm, respiration rate, calories burned, an activity level, a sleep score, body temperature, or pulse oximetry (see [0056]; data collection sensor device can include a plurality of sensors to measure heart rate, breathing rate, body temperature, number of steps taken).
Note that the non-contact sensing array as taught by Trapero also teaches wherein the animal health data includes heart rate, respiration rate, oxygen saturation, and other physiological metrics (Trapero [Col 12, lines 13-21]).
Regarding claim 29, Shuler and Trapero teach the method of claim 27. Shuler further teaches collecting a subset of the animal health data by an accelerometer (see [0056]; an accelerometer is used to measure the animal’s movement).
Regarding claim 30, Shuler and Trapero teach the method of claim 27. Shuler further teaches the method comprising configuring the animal health device to connect to a cloud resource (see [0058]; Data collection sensor device 306 further includes a data transmission means such as transmitter or transceiver for transmitting data to data analysis system 302, Fig. 7, cloud 302).
Regarding claim 31, Shuler and Trapero teach the method of claim 30. Shuler further teaches the method comprising configuring the cloud resource to connect to a veterinary computing system or an animal owner's computing system (see Fig. 7, [0053]; user interface dashboard system 304 for animal care professionals and stakeholders).
Claim(s) 15 is/are rejected under 35 U.S.C. 103 as being unpatentable over Shuler et al (US 20150039239 A1) in view of Trapero Martin et al (US 11116448 B1), hereinafter referred to as Trapero, and Goldfain (US 20160165852 A1).
Regarding claim 15, Shuler and Trapero teach the system of claim 13. They are silent regarding wherein the predictor is an increase in respiration rate when at rest to indicate the medical issue is heart or lung disease.
However, Goldfain teaches a system for monitoring one or more conditions of an animal (Goldfain [0042]) and using the collected data to predict actionable information related to the animal’s health (Goldfain [0092]), wherein the predictor is an increase in respiration rate when at rest to indicate the medical issue is heart or lung disease (see Goldfain [0097]; pulmonary information, including respiratory rate, and cardiac information may be of interest to DMS to derive inferences such as kennel cough & other developing respiratory conditions and/or developing heart conditions).
It would have been obvious for one of ordinary skill in the art prior to the effective filing date of the claimed invention to modify the system as taught by Shuler and Trapero with the use of respiration rate to predict heart and/or lung disease as taught by Goldfain. One of ordinary skill in the art would have been motivated to make this modification in order to provide an indicator to an owner concerning a probable complication to the animal’s health which may allow them to provide the animal with further medical care (Goldfain [0094]).
Claim(s) 17 is/are rejected under 35 U.S.C. 103 as being unpatentable over Shuler et al (US 20150039239 A1) in view of Trapero Martin et al (US 11116448 B1), hereinafter referred to as Trapero, and Menkes et al (US 20140123912 A1).
Regarding claim 17, Shuler and Trapero teach the system of claim 13 wherein accelerometer data is used as a predictor of a health event (see Shuler [0061]; sensed activities including scratching activity may be used to deduce a health event in the animal).
They are silent regarding wherein the accelerometer data is a predictor that the animal has suffered a seizure.
However, Menkes teaches a system for monitoring animal health using vital sign measurements to arrive at a tentative diagnosis (Menkes [0039], [0088]) wherein the predictor is an accelerometer indicating the animal has suffered a seizure (see Menkes [0047]; the specific medical condition is a seizure and the abnormal pattern of movement is sensed by the accelerometer).
It would have been obvious to one of ordinary skill in the art prior to the effective filing date of the claimed invention to modify the system as taught by Shuler and Trapero to use an accelerometer as the predictor to indicate the animal has suffered a seizure as taught by Menkes. One of ordinary skill in the art would have been motivated to make this modification in order to predict a state of duress of the animal caused by a seizure by identifying abnormal movement patterns such as paddling, head-shaking, or twitching occurring when the animal is laying down on either side (Menkes [0047]).
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to ALISHA J SIRCAR whose telephone number is (571)272-0450. The examiner can normally be reached Monday - Thursday 9-6:30, Friday 9-5:30 CT.
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/A.J.S./Examiner, Art Unit 3792
/Benjamin J Klein/Supervisory Patent Examiner, Art Unit 3792