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 .
Status of Claims
This correspondence is in response to the amendments filed April 22, 2026.
Claims 7 has been cancelled, and claims 12-13 were previously canceled.
Claims 1, 4, 10, 11, 16, and 19 have been amended.
Claims 21-22 have been newly added.
Claims 1-6, 8-11 and 14-22 are currently pending and have been fully examined.
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claims 1-6, 8-11 and 14-22 are rejected under 35 U.S.C. 101 because the claimed invention is directed to a judicial exception without significantly more.
Step 1 – Statutory Categories of Invention:
Claims 1-22 are drawn to a method or apparatus, which are statutory categories of invention.
Step 2A – Judicial Exception Analysis, Prong 1:
Independent claims 1 and 16 recite acquiring physiological data associated with a user, the physiological data comprising at least skin temperature data comprising skin temperature measurements of the user; determining one or more skin temperature measurements of the skin temperature data that are outside a baseline temperature range of the user; acquiring temperature data associated with an environment surrounding the user based at least in part on the one or more skin temperature measurements being outside the baseline temperature range of the user; determining a difference in a rate of change between the skin temperature data and the surrounding temperature data based at least in part on a comparison of the skin temperature data and the surrounding temperature data; identifying one or more physiological characteristics associated with the user based at least in part on a comparison of the skin temperature data and the surrounding temperature data, wherein the identifying comprises determining whether the one or more skin temperature measurements are outside the baseline temperature range of the user due to the environment surrounding the user or to a physiological condition of the user based at least in part on the difference in the rate of change between the skin temperature data and the surrounding temperature data.
These steps of receiving physiological data including skin temperature, receiving surrounding temperature data, determining a difference in a rate of change between temperatures and identifying physiological characteristics based on a comparison of the temperatures, amount to functions performable in the mind or with pen and paper and are only concepts relating to organizing or analyzing information in a way that can be performed in the human mind (MPEP 2106.04(a)(2)(III)(B) citing the abstract idea grouping for mental processes with or without physical aid).
Dependent claims 2 and 17 recite determining that the user is engaged in a physical activity based at least in part on the comparison between the skin temperature data and the surrounding temperature data.
Dependent claims 3 and 18 recite that the physiological data comprises motion data and determining that the user is engaged in the physical activity based at least in part on the motion data and the comparison between the skin temperature data and the surrounding temperature data.
Dependent claims 4 and 19 recite classifying the physical activity into a physical activity type of a plurality of candidate physical activity types based at least in part on the comparison between the skin temperature data and the surrounding temperature data.
Dependent claims 5 and 20 recite determining one or more characteristics associated with the physical activity based at least in part on the comparison between the skin temperature data and the surrounding temperature data, wherein the one or more characteristics comprise an outdoor physical activity, an indoor physical activity, an exertion metric of the physical activity, or any combination thereof.
Dependent claim 6 recites determining a difference between the skin temperature data and the surrounding temperature data based at least in part on the comparison; and identifying a probability that the user is drowsy or will become drowsy exceeds a threshold probability based at least in part on the difference between the skin temperature data and the surrounding temperature data.
Dependent claim 8 recites the physiological data further comprises motion data and identifying the probability that the user is drowsy or will become drowsy based at least in part on the motion data being less than or equal to a motion threshold.
Dependent claim 15 recites collecting physiological data from the user based on arterial blood flow.
Each of the steps of the preceding dependent claims 2-6, 8, 15, and 17-20 only serve to further limit or specify the features of independent claims 1 and 16 accordingly, and hence are directed towards fundamentally the same abstract idea as the independent claim.
Step 2A – Judicial Exception Analysis, Prong 2:
The judicial exception is not integrated into a practical application because the additional elements within the claims only amount to instructions to implement the judicial exception in a particular environment (MPEP 2106.05(h)).
Claim 1 recites “acquiring, via a first set of sensors positioned on an inner surface of a wearable ring device, wherein the acquiring comprises continuously sampling the skin temperature data at one or more sampling rates throughout at least one of a day or night to capture temperature fluctuations over different time periods” and “causing, by the one or more processors of the wearable ring device, a second set of sensors positioned on an outer surface of the wearable ring device to acquire surrounding temperature data associated with an environment surrounding the user based at least in part on the skin temperature data being outside the baseline temperature range of the user”. These are both examples of selecting by type or source the data to be manipulated, which is insignificant extra-solution activity that is not sufficient to integrate the abstract idea into a practical application (MPEP 2106.05(g)).
Claim 1 recites a first set of sensors of a wearable ring device with a second set of sensors on the outside of the ring device different from the first set of sensors on the inside of the ring device, and a graphical user interface of a user device as well as displaying an indication of the one or more physiological characteristics, a message or alert associated with the one or more physiological characteristics, or both. In paragraph 38, the specification describes a list of exemplary sensors non-comprehensively including temperature sensors, PPG sensors, or motion sensors. The limitations are only recited as a tool to perform an existing process and only amounts to an instruction to implement the abstract idea using a computer (MPEP § 2106.05(f)(2) see case requiring the use of software to tailor information and provide it to the user on a generic computer within the “Other examples.. v.”). In paragraph 18, the specification mentions GUIs as providing outputs in a very general manner. The use of these sensors and GUIs only serves as a tool to perform an existing process and only amounts to an instruction to implement the abstract idea using a computer (MPEP § 2106.05(f)(2) see case requiring the use of software to tailor information and provide it to the user on a generic computer within the “Other examples.. v.”).
Dependent claim 9 recites displaying a message associated with the probability that the user is drowsy or will become drowsy. The limitations are only recited as a tool to perform an existing process and only amounts to an instruction to implement the abstract idea using a computer (MPEP § 2106.05(f)(2) see case requiring the use of software to tailor information and provide it to the user on a generic computer within the “Other examples.. v.”).
Claim 10 recites one or more additional devices. The specification defines the one or more additional devices in a non-exhaustive list of additional devices in paragraph 21. Some of the additional devices are described as being generic versions of smart devices (for example, smart televisions, smart speakers, and smart appliances). The use of a one or more additional devices, in this case to receive a message or an instruction based at least in part on the probability that the user is drowsy or will become drowsy, only recites the one or more additional devices as a tool which only serves to input data for use by the abstract idea (MPEP § 2106.05(g) - insignificant pre/post-solution activity) and is therefore not a practical application of the recited judicial exception.
Claim 11 recites transmitting an instruction to a television to pause a movie or television program, transmitting an instruction to a light source to deactivate or dim the light source, transmitting an instruction to an audio device to deactivate or reduce a volume of an audio source, transmitting an instruction to a thermostat to adjust a temperature, of the environment, or any combination thereof. The use of transmitting an instruction to a television to pause a movie or television program, transmitting an instruction to a light source to deactivate or dim the light source, transmitting an instruction to an audio device to deactivate or reduce a volume of an audio source, transmitting an instruction to a thermostat to adjust a temperature, of the environment, or any combination thereof, only serves to output data for use by the abstract idea (MPEP § 2106.05(g) - insignificant post-solution activity) and is therefore not a practical application of the recited judicial exception.
Claim 12 recites a wearable ring device. The specification defines the wearable ring device as being from the group of electronic devices known in the art in paragraph 18. The use of a wearable ring device, in this case to be the wearable device, only recites the wearable ring device as a tool to apply data to an algorithm and report the results (MPEP § 2106.05(f)(2) see case involving a commonplace business method or mathematical algorithm being applied on a general purpose computer within the “Other examples.. i.”) amounting to instruction to implement the abstract idea using a general purpose computer. Alice Corp. Pty. Ltd. V. CLS Bank Int’l, 134 S. Ct. 2347, 1357 (2014).
Claim 13 recites a first sensors on an inner circumferential surface of the wearable ring device and second sensors on an outer circumferential surface of the wearable ring device. The specification defines the first sensors on an inner circumferential surface of the wearable ring device and second sensors on an outer circumferential surface of the wearable ring device as possibly including resistors, transistors, diodes, or other electrical/electronic components or a negative temperature coefficient thermistor. These options are presented non-exhaustively in paragraph 55. The use of a first sensors on an inner circumferential surface of the wearable ring device and second sensors on an outer circumferential surface of the wearable ring device, in this case to sense temperatures, only recites the first sensors on an inner circumferential surface of the wearable ring device and second sensors on an outer circumferential surface of the wearable ring device as a tool which only serves to input data for use by the abstract idea (MPEP § 2106.05(g) - insignificant pre/post-solution activity) and is therefore not a practical application of the recited judicial exception.
Claim 14 recites a first set of sensors positioned on a first surface of a wearable surface proximate to a skin surface of a user and second set of sensors positioned on a second surface of the wearable device different from the first surface. The specification defines the first set of sensors positioned on a first surface of a wearable surface proximate to a skin surface of a user and second set of sensors positioned on a second surface of the wearable device different from the first surface as possibly including resistors, transistors, diodes, or other electrical/electronic components or a negative temperature coefficient thermistor. These options are presented non-exhaustively in paragraph 55. The use of a first set of sensors positioned on a first surface of a wearable surface proximate to a skin surface of a user and second set of sensors positioned on a second surface of the wearable device different from the first surface, in this case to sense temperatures, only recites the first set of sensors positioned on a first surface of a wearable surface proximate to a skin surface of a user and second set of sensors positioned on a second surface of the wearable device different from the first surface as a tool which only serves to input data for use by the abstract idea (MPEP § 2106.05(g) - insignificant pre/post-solution activity) and is therefore not a practical application of the recited judicial exception.
Claim 16 recites a processor, memory coupled with the processor, a first set of sensors of a wearable device, a second set of sensors different from the first set of sensors, and a graphical user interface of a user device. In paragraph 133, the processor is described as possibly being a general-purpose processor. Paragraph 47 of the specification describes the memory as non-exhaustively being from a large array of possible memory devices, like RAM, ROM, and EEPROM. In paragraph 38, the specification describes a list of exemplary sensors non-comprehensively including temperature sensors, PPG sensors, or motion sensors. In paragraph 18, the specification mentions GUIs as providing outputs in a very general manner. The limitations of processor, memory, first set of sensors of a wearable device, second set of sensors, and graphical user interface of a user device are only recited as tools to perform an existing process and only amount to an instruction to implement the abstract idea using a computer (MPEP § 2106.05(f)(2) see case requiring the use of software to tailor information and provide it to the user on a generic computer within the “Other examples.. v.”).
Claim 21 recites transmitting a signal to one or more additional device to adjust the environment surrounding the user based at least in part on the one or more physiological characteristics.
The use of transmitting a signal to a device to adjust the environment surrounding the user only serves to output data (MPEP § 2106.05(g) - insignificant post-solution activity) and is therefore not a practical application of the recited judicial exception. Though the intended result of transmitting the signal to the additional device is to adjust the environment, no adjustment of the environment using the additional device is recited. Thus, there is no improvement in technology or technical field, and the abstract idea is not integrated into a practical application.
Claim 22 recites that one or more portions of the wearable ring device that include the first set of sensors comprise one or more thermally insulative portions that insulate the first set of sensors from ambient temperature. These details do not transform the wearable ring device into a different state or thing, do not improve the functioning of the wearable ring device or improve technology or a technical field, and do not effect a particular treatment or prophylaxis. Instead, it serves to generally link the judicial exception to a particular technical environment.
Step 2B – Additional Elements that Amount to Significantly More:
The present claims do not include additional elements that are sufficient to amount to more than the abstract idea because the additional elements or combination of elements amount to no more than a recitation to implement the abstract idea in particular environments.
Claims 1 and 16 recite causing/cause a graphical user interface of a user device to display an indication of the one or more physiological characteristics, a message or alert associated with the one or more physiological characteristics, or both. Claim 16 recites a processor and memory coupled with the processor. Claim 9 recites displaying a message associated with the probability that the user is drowsy or will become drowsy.
Claim 16 recites a processor, memory coupled with the processor, a first set of sensors of a wearable device, a second set of sensors different from the first set of sensors, and a graphical user interface of a user device.
Claim 9 recites causing the graphical user interface of the user device to display a message associated with the probability that the user is drowsy or will become drowsy.
Claim 10 recites transmitting a message or an instruction to one or more additional devices based at least in part on the probability that the user is drowsy or will become drowsy.
Claim 12 recites the wearable device comprises a wearable ring device.
Each of these elements is only recited as a tool for performing steps of the abstract idea, such as the use of the storage medium to store data, the processor to apply the algorithm of the judicial exception, and the display device to display results of the algorithm. These additional elements therefore only amount to mere instructions to perform the abstract idea and are not sufficient to amount to significantly more than the abstract idea (MPEP 2016.05(f) see for additional guidance on the “mere instructions to apply an exception”).
Each additional element under Step 2A, Prong 2 is analyzed in light of the specification’s explanation of the additional element’s structure. The claimed invention’s additional elements do not have sufficient structure in the specification to be considered a not well-understood, routine, and conventional use of generic computer components. Note that the specification can support the conventionality of generic computer components if “the additional elements are sufficiently well-known that the specification does not need to describe the particulars of such additional elements to satisfy 35 U.S.C. 112(a)” (Berkheimer in Ill. Impact on Examination Procedure, A. Formulating Rejections, 1. on p. 3).
The additional element of claims 1 and 16 includes receive/ing physiological data collected via a first sensor and receiving surrounding temperature data associated with an environment surrounding the user, which is well-understood, routine, and conventional. MPEP 2106.05(d)(II) states that receiving or transmitting data or a network is recognized as a well-understood, routine, and conventional activity. Therefore, the receive/ing physiological data collected via a first sensor and receiving surrounding temperature data associated with an environment surrounding the user additional element is not sufficient to amount to significantly more than the recited judicial exception.
The additional element of claim 11 includes transmitting an instruction to a television to pause a movie or television program, transmitting an instruction to a light source to deactivate or dim the light source, transmitting an instruction to an audio device to deactivate or reduce a volume of an audio source, transmitting an instruction to a thermostat to adjust a temperature, of the environment, or any combination thereof, which is well-understood, routine, and conventional. The courts have decided that receiving or transmitting data over a network as well-understood, routine, conventional activity when claimed in a merely generic manner (e.g., at a high level of generality) or as insignificant extra-solution activity (MPEP § 2106.05(d)(II) other types of activities example i. receiving or transmitting data over a network, OIP Techs., Inc., v. Amazon.com, Inc., 788 F.3d 1359, 1363, 115 USPQ2d 1090, 1093 (Fed. Cir. 2015) (sending messages over a network). Therefore, the transmitting an instruction to a television to pause a movie or television program, transmitting an instruction to a light source to deactivate or dim the light source, transmitting an instruction to an audio device to deactivate or reduce a volume of an audio source, transmitting an instruction to a thermostat to adjust a temperature, of the environment, or any combination thereof additional element is not sufficient to amount to significantly more than the recited judicial exception.
The additional element of claim 13 includes the first set of sensors are positioned on an inner circumferential surface of the wearable ring device and the second set of sensors are positioned on an outer circumferential surface of the wearable ring device, which is well-understood, routine, and conventional. This position is supported by (1) von Badinsky et al. (US 2018/0120892 – see paragraph 216) and ; (2) Dusan (US 20160228025 A1 – electrodes are described on inner and outer circumferences of wearable device in figure 4 and paragraphs 27 and 28; the wearable device being embodied as a ring is disclosed in paragraph 4); and (3) Mendenhall et al. (WO 2016161152 A1 – figure 2 discloses sensors on the inner and outer circumference of a ring, elements 20 and 18 respectively). Therefore, that the first set of sensors are positioned on an inner circumferential surface of the wearable ring device and the second set of sensors are positioned on an outer circumferential surface of the wearable ring device additional element is not sufficient to amount to significantly more than the recited judicial exception.
The additional element of claim 14 includes that the first set of sensors are positioned on a first surface of the wearable device proximate to a skin surface of the user and the second set of sensors are positioned on a second surface of the wearable device different from the first surface, which is well-understood, routine, and conventional. This position is supported by (1) Mendenhall et al. (WO 2016161152 A1 – figure 2 discloses sensors on the inner and outer circumference of a ring, elements 20 and 18 respectively), (2) von Badinsky (US 2018/0120892 – see paragraph 216), and (3) Stivoric et al. (US 2007/0100666 – see paragraph 175 and figure 7B, particularly elements 120 and 125). Therefore, that the first set of sensors are positioned on a first surface of the wearable device proximate to a skin surface of the user and the second set of sensors are positioned on a second surface of the wearable device different from the first surface additional element is not sufficient to amount to significantly more than the recited judicial exception.
Thus, taken alone, the additional elements do not amount to significantly more than the above-identified judicial exception. Looking at the limitations as an ordered combination adds noting that is not already present when looking at the elements taken individually. Their collective functions merely provide conventional data gathering and processing.
The additional element of claim 21 includes transmitting a signal to one or more additional devices to adjust the environment surrounding the user, which is well-understood, routine, and conventional. The courts have decided that receiving or transmitting data over a network as well-understood, routine, conventional activity when claimed in a merely generic manner (e.g., at a high level of generality) or as insignificant extra-solution activity (MPEP § 2106.05(d)(II) other types of activities example i. receiving or transmitting data over a network, OIP Techs., Inc., v. Amazon.com, Inc., 788 F.3d 1359, 1363, 115 USPQ2d 1090, 1093 (Fed. Cir. 2015) (sending messages over a network). Therefore, the transmitting a signal to one or more additional devices to adjust the environment surrounding the user is not sufficient to amount to significantly more than the recited judicial exception.
The additional element of claim 22 includes that the first set of sensors are thermally insulated from ambient temperature, which is well-understood, routine, and conventional. This position is supported by (1) von Badinsky (US 2018/0120892 – see paragraph 144), (2) Stivoric et al. (US 2007/0100666 – see paragraphs 138, 154, 163-164, 167-168) and (3) Matsumura (US 5050612 – see col. 6, lines 33-45). Therefore, that the first set of sensors are thermally insulated from ambient temperature is not sufficient to amount to significantly more than the recited judicial exception.
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 1-6, 9-11, and 14-22 is rejected under 35 U.S.C. 103 as being unpatentable over Miller (US PG Pub. 2023/0335287) in view of von Badinski et al. (US 2018/0120892) in view of Vardi et al. (US 20190021701).
Claim 1
With respect to claim 1, Miller teaches
A method
Par. [0002], “The disclosed technology generally relates to systems for, devices for, and methods of obtaining measurements of emergent properties of a complex adaptive system, such as a biological system, an organism, or for example a human, or a non-biological system, such as for example a protocell.”
Acquiring, via a first set of sensors positioned on an inner surface of a wearable device, physiological data associated with a user, the physiological data comprising at least skin temperature data comprising skin temperature measurements of the user
Par. [0161], “In one embodiment of Sensor Example No. 1, the system described herein includes a sensor comprising a sensor module to measure skin temperature and ambient temperature. For example, as shown in FIGS. 6, 7, and 8, a sensor device may comprise a sensor module or modules to measure skin temperature and ambient temperature and generate data reflecting such measurements. Information about the temperature or core temperature of a biological system may be inferred from such measurements. In others embodiment, as shown in FIGS. 6, 7, 8 and 9, the system may comprise a sensor module to measure simultaneously, or substantially simultaneously, at least the following properties: (i) skin temperature, preferably to the precision of 0.1° C., (ii) ambient temperature, and (iii) motion in three dimensions.”
Figure 8 shows the sensor suite module with skin temperature on the bottom side, which corresponds to the inner side of the wearable device.
see figure 28 for a wearable health monitor
Causing a second set of sensors positioned on an outer surface of the wearable device to acquire surrounding temperature data associated with an environment surrounding the user
figure 8 shows the sensor suite module collecting the ambient temperature on the top side
Identifying one or more physiological characteristics associated with the user based at least in part on a comparison of the skin temperature data and the surrounding temperature data
paragraph 546 teaches subtracting the air temperature from the skin temperature and using the result as a proxy for heat elimination of a biological system, which is a physiological characteristic);
Transmitting a signal configured to cause a graphical user interface of a user device to display an indication of the one or more physiological characteristics, a message or alert associated with the one or more physiological characteristics, or both
figure 10 shows a device in communication with the wearable device that can be a phone or tablet and includes a user interface; in the first sentence of paragraph 162, Miller et al. says that data from the wearable device is to be displayed on a smartphone or tablet; the data from the wearable device is described in paragraph 161, and it is described as being related to skin temperature, ambient temperature and motion in three dimensions; figure 11 shows a graphical plot of an exemplary output of the wearable device where the ΔT is described as the temperature differential dT in paragraph 546 as the difference between the skin temperature and the surrounding temperature).
Wherein the acquiring comprises continuously sampling the skin temperature data at one or more sampling rates throughout at least one of a day or night to capture temperature fluctuations over different time periods;
Para. [0383], parameters are selected that can be detected by sensors with low power requirements controlled by firmware algorithms that automatically adjust sampling rate and frequency based on pre-set thresholds or changes in baseline. In a preferred embodiment, the device will measure heat flux in 20 second intervals
Para. [0544-0546], In one example of utilizing “thermal fit” as the core health metric, an experiment was performed by tracking heat generation and heat elimination on a circadian rhythm cycle or multiple circadian rhythm cycles. The heat generation was tracked via measuring activity… The measurement device includes accelerometers and temperature sensors. The measurement intervals were scheduled (for example, 30 second sampling rate) by device firmware and sensor measurements were recorded to device memory in a normalized form…
Para. [0165-0166], Sensor Example No. 1 contains at least two pre-calibrated solid-state digital temperature sensors that simultaneously measure skin temperature and ambient temperature of the air proximate to the point of skin temperature measurement. By continuously measuring the local difference between ambient and skin temperature, Sensor Example No. 1 quantifies heat flow (loss) through the skin—the predominant mode of energy loss in humans….Sensor Example No. 1, in one embodiment, is neither as accurate nor as precise as direct or indirect clinical calorimetry, but Sensor Example No. 1 has at least the following advantage over such methods: the continuous measurement of metabolic rate at scale. This enables Sensor Example No. 1, in certain embodiments, to detect even subtle changes in metabolic rate over long period of time—days—and to employ automated machine learning on both individuals and populations.
However, Miller does not teach
Acquiring, via a first set of sensors positioned on an inner surface of a wearable ring device
Determining, using one or more processors of the wearable ring device, one or more skin temperature measurements of the skin temperature data that are outside a baseline temperature range
Causing, by the one or more processors of the wearable ring device, a second set of sensors positioned on an outer surface of the wearable ring device to acquire surrounding temperature data associated with an environment surrounding the user based at least in part on the one or more skin temperature measurements being outside the baseline temperature range of the user
Von Badinski teaches
Acquiring, via a first set of sensors positioned on an inner surface of a wearable ring device
Par. [0211], “Since the WCD has the form factor of a ring, the WCD is designed to be worn over long periods of time by a user with little to no discomfort or interference. In this regard, the WCD can monitor the above-described, monitored characteristics over long periods of time (e.g. weeks, months, etc.), and determine trends in the data.”
Par. [0216], “The inward facing temperature sensor 2410a can be near the skin of a user when the user is wearing the ring, and can therefore measure the skin temperature of the user.”
It would have been obvious to one having ordinary skill in the art before the effective filing date of this application to substitute the wearable device in the system of Miller with a wearable ring device, as taught by von Badinski, because a smaller device, such as a ring device is smaller and more compact for users, and they are less likely to be intrusive or interfere with a user’s daily life than bulky wearable devices (von Badinski, par. [0003]).
Von Badinski further teaches
Determining, using one or more processors of the wearable device, one or more skin temperature measurements of the skin temperature data that are outside a baseline temperature range of the user
Par. [0210], “The WCD can also monitor heart rate and/or temperature, in addition to the other monitored characteristics described above. If any of the monitored characteristics is abnormal, e.g., measured parameters outside of a predetermined threshold range, an alert can be sent to a third party.”
Causing, by the one or more processors of the wearable ring device, a second set of sensors positioned on an outer surface of the wearable ring device to acquire surrounding temperature data associated with an environment surrounding the user based at least in part on the one or more skin temperature measurements being outside the baseline temperature range of the user
Par. [0216], “The outward facing temperature sensors 2410b can be disposed away from the finger of the user, and can therefore be arranged to measure an ambient temperature of the room in which the user currently resides with sufficient thermal isolation from the user's hand and his/her body heat…. In another example, the WCD can employ multiple outwardly facing temperature sensors 2410b and compare the temperature values of each to the inward facing sensor 2410a. The WCD can then select the most accurate temperature value from the outward facing sensors.”
Par. [0217], “Based on the measured skin temperature and measured ambient temperature, the WCD can automatically adjust the thermostat 2420 to alter the ambient temperature of the room. In this regard, if a user's skin temperature is too high, the WCD can instruct the thermostat 2420 to lower the ambient temperature. Similarly, if the user's skin temperature is too cold, the WCD can instruct the thermostat 2420 to raise the temperature. The WCD 2410 can instruct the thermostat (and/or an HVAC controller) directly, e.g., via a direct wireless link 2415, or indirectly, e.g., via one or more of the mobile device 2440 and the access point 2430. The WCD can also use historic temperature data to develop trend temperature data.”
It would have been obvious to one having ordinary skill in the art before the effective filing date of this application to add to the system of Miller and von Badinski the ability to determine that the user’s skin temperature is outside a baseline of a predetermined range of a user and to monitor the temperature of the surrounding environment based on the determination that the skin temperature is outside the range, as taught by von Badinski, because it allows the system to take actions and/or provide recommendations to the user to adjust the temperature of the environment in order to address the skin temperature being outside the range (see von Badinski, par. [00216]-[0217]).
Although not explicitly taught by Miller or von Badinski, Vardi et al. teaches:
determining, using the one or more processors of the wearable device, a difference in a rate of change between the skin temperature data and the surrounding temperature data based at least in part on a comparison of the skin temperature data and the surrounding temperature (embodiments include receiving from a first sensor skin temperature measurements during a first period of time… embodiments include receiving from a second sensor measurements of ambient temperature during the first period of time; analyzing the rate of changes in the measured skin and/or ambient temperatures may allow to study the ambient influence. The outcome of the analysis may be used in further manipulation of the measured skin temperature; [0028-0031]);
identifying one or more physiological characteristics associated with the user based at least in part on the difference in the rate of change between the skin temperature data and the surrounding temperature data (the method may include receiving from a user computing device user related data and manipulating the temperature measurements (e.g., skin temperature measurements, body temperature, manipulated skin temperature measurements, ambient, etc.) using the user related data. Processor 52 and/or processor 112 may receive from user device 60 and/or an external data base (e.g., storage unit 120 or other) user related data, for example, age, gender, weight, height and a medical condition (e.g., PCOS—Polycystic ovary syndrome). The user may log into an application on user device 60 and may enter the user related data. For example, processor 52 and/or processor 112 may receive information that the user is a 30 years old woman, accordingly, processor 52 and/or processor 112 may look for a bi-phasic temperature patterns over time in the manipulated temperatures (e.g. skin temperature, body temperature or temperature information) for determining the menstrual cycle circadian pattern or further manipulating the temperature data thereof. The user related data may further include subjective information recited from the user, for example, a subjective assessment of the user reading his/hers medical condition or feeling. For example, a woman using device 10 may fill an online questionnaire running on device 60 regarding her current menstrual condition: e.g., bleeding, spotting, mild bleeding, medium bleeding and heavy bleeding. [0035]).
Vardi also teaches continuously sampling the skin temperature at one or more sampling rates throughout at least one of a day or night to capture temperature fluctuations over different time periods (sensor skin temperature measurements during a first period of time, wherein the first sensor is detachably and thermally couple - able to a user's skin. First sensor 20 may send (e.g., every second, every minute, when a button 27 is pressed by a user, etc.) skin temperature measurements to processor 52 and/or to processor 112. In some embodiments, the first period of time may be several minutes, several hours, overnight, during sleeping time, one day, a week, a month, etc. In operation 320, embodiments include receiving from a second sensor measurements of ambient temperature during the first period of time. Second sensor 25 may send (e.g., every second, every minute, etc.) ambient temperature measurements to processor 52 and / or to processor 112 [0028-0029]); and
determining, using the one or more processors of the wearable ring device, whether the one or more skin temperature measurements are outside the baseline temperature range of the user due to the environment surrounding the user or to a physiological condition of the user based at least in part on the difference in the rate of change between the skin temperature data and the surrounding temperature data (Processor 52 and/or processor 112 may compare the measurements from first sensor 20 and second sensor 25 and define time intervals in the first period at which the skin temperature is less influenced by the ambient temperature, for example, when the difference between the two measurements (at the same time) is smaller than a threshold value or that the ratio between the two measurements is smaller than a threshold value. In some embodiments, manipulating the skin temperature measurements may include, filtering undesired measurements, extrapolating between skin temperature measurements, integrating, differentiating, or any mathematical manipulation that may be applied to time dependent temperature measurements known in the art. In some embodiments, in order to define periods at which the ambient conditions may have influence on the measurements received from the skin temperature sensor, a skin temperature measurement and an ambient temperature measurement taken at the same day/night time (in the past, for example between 02:00-04:00 AM) may be compared. In some embodiments, if the difference between the two is larger than a threshold value, the skin temperature measurement is identified as “influenced by the ambient temperature” [0030]).
Vardi monitors body temperature in order to determine physiological conditions, teaching the use of sensors to collect skin temperature measurements and ambient temperature measurements, which may indicate a physiological condition. Similarly, Miller uses wearable devices to measure, record, transmit and use physical and physiological measurements for the pre-symptomatic detection and interception of disease states in a biological system. Thus, Vardi and Miller are analogous references are they directed towards solving similar problems. Therefore, it would have been obvious to one having ordinary skill in the art before the effective filing date of this application to modify the system of Miller and von Badinski the ability to continuously sample skin temperature throughout the day or night, determine a difference in a rate of change between the skin temperature data and the surrounding temperature data to identify one or more physiological characteristics associated with the user, and determine whether the one or more skin temperature measurements are outside the baseline temperature range of the user due to the environment surrounding the user, as taught by Vardi et al., because accurate measurements of the body temperature can identify and help to diagnose and/or prevent several physiological conditions [see Vardi et al., 0002], and allows the system to take actions and/or provide recommendations to the user to adjust the temperature of the environment in order to address the skin temperature being outside the range (see von Badinski, par. [00216]-[0217]).
With respect to claim 2, the combination of Miller, von Badinski and Vardi et al. teaches determining that the user is engaged in a physical activity based at least in part on the comparison between the skin temperature and the surrounding temperature data (figure 18 shows the comparison as the heat sensor data – in paragraph 171, Miller et al. says that the heat sensor signal stream can be the differential temperature; paragraph 171 also talks about how the heat elimination signal, which is derived from the differential temperature, relates to physical exercise).
With respect to claim 3, the combination of Miller, von Badinski and Vardi et al. teaches the physiological data further comprises motion data and the system determines that the user is engaged in the physical activity based at least in part on the motion data and the comparison between the skin temperature data and the surrounding temperature data (figure 18 shows the heat sensor data and the work data, which can come from an accelerometer, as described in paragraph 171; these sources of data are combined to estimate physical activity, among other things).
With respect to claim 4, the combination of Miller, von Badinski and Vardi et al. teaches classifying, using a machine learning classifier, the physical activity into a physical activity type of a plurality of candidate physical activity types based at least in part on the comparison between the skin temperature data and the surrounding temperature data (figure 21 shows a difference between sleep and being awake by the shading; as disclosed in paragraph 180, heat elimination coincides with sleep-wake cycles; in paragraph 332 Miller et al. discloses deriving activity level from device-derived data; in paragraph 296, Miller et al. breaks data down into different levels; in paragraph 173, Miller et al. discloses a machine learning classifier to analyze signals. In some embodiments, the decision support system extracts a plurality of features from the signals by generating a feature vector for each time period. A feature vector is generated for each epoch of the plurality of epochs and the feature vector consists of the plurality of features. The feature vector is inputted into the machine learning classifier to automatically classify each epoch).
With respect to claim 5, the combination of Miller, von Badinski and Vardi et al. teaches determining one or more characteristics associated with the physical activity based at least in part on the comparison between the skin temperature data and the surrounding temperature data, wherein the one or more characteristics comprise an outdoor physical activity, an indoor physical activity, an exertion metric of the physical activity, or any combination thereof (in paragraph 332, Miller et al. discloses deriving activity level from device-derived data where activity level is taken to be synonymous with exertion metric of the physical activity; figure 20 shows the relationship between work – which is taken to be synonymous with an exertion metric of the physical activity – and heat elimination, which Miller et al. derives from the difference between skin and ambient temperatures).
With respect to claim 6, the combination of Miller, von Badinski and Vardi et al. teaches
identifying a probability that the user is drowsy or will become drowsy exceeds a threshold probability based at least in part on the difference between the skin temperature and the surrounding temperature data (in paragraph 191, Miller et al. describes one embodiment, Sensor Example No. 1, which is directed to using the temperature differential between skin and surroundings; this paragraph twice mentions drowsiness in roughly the eleventh line; the last sentence of this paragraph gives the option of “weighting a probability that a set of the sensor output signals illustrate a presence of [a] particular cumulative physiological condition” – this anticipates that a probability would have been calculated – while the paragraph has focused on fatigue, this condition is clearly being used as an illustration, and any of the other conditions listed in the paragraph, which includes drowsiness, is clearly shown by “particular cumulative physiological condition”; figure 28 shows thresholds, and paragraph 184 talks about triggering alerts when health decision thresholds are crossed by health metrics; paragraph 95 teaches that health metrics include sensors that are on the wearable device, which includes the temperature differential used in Sensor Example No. 1).
With respect to claim 9, the combination of Miller, von Badinski and Vardi et al. teaches causing the graphical user interfaces of the user device to display a message associated with the probability that the user is drowsy or will become drowsy (paragraph 191 includes a display that outputs an identification where the identification is of a particular cumulative physiological condition which can include drowsiness).
With respect to claim 10, the combination of Miller, von Badinski and Vardi et al. teaches transmitting a signal to one or more additional devices to control the one or more additional devices based at least in part on the probability that the user is drowsy or will become drowsy (as described in paragraph 26, the system will produce indicators that a person should go to sleep; in paragraph 294, Miller et al. discloses using near-field communication to detect proximity to another device and triggering actions on that second device).
With respect to claim 11, the combination of Miller, von Badinski and Vardi et al. teaches teaches the limitations of claim 10, including identifying a probability that the person wearing a monitoring device will become or is drowsy and transmitting a message or instruction to one or more additional devices based at least in part on the probability that the user is drowsy or will become drowsy.
Miller fails to disclose the following limitation of claim 11: transmitting an instruction to a television to pause a movie or television program, transmitting an instruction to a light source to deactivate or dim the light source, transmitting an instruction to an audio device to deactivate or reduce a volume of an audio source, transmitting an instruction to a thermostat to adjust a temperature, of the environment, or any combination thereof. However, von Badinsky does disclose transmitting an instruction based on the measured skin temperature and measured ambient temperature from a wearable device to adjust a thermostat in paragraph 217.
Therefore It would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to modify the instructions being transmitted from Miller et al.’s system to include adjusting a thermostat as taught by von Badinsky with the motivation of ensuring that a person’s body temperature is maintained in a normal range.
With respect to claim 14, the combination of Miller, von Badinski and Vardi et al. teaches the first set of sensors are positioned on a first surface of the wearable device proximate to a skin surface of the user, and wherein the second set of sensors are positioned on a second surface of the wearable device different from the first surface (figure 8 shows the skin temperature being measured on the skin side and the ambient temperature being measured on the opposite side of the sensor suite module).
With respect to claim 15, the combination of Miller, von Badinski and Vardi et al. teaches that the wearable device collects the physiological data from the user based on arterial blood flow (in paragraph 298, Miller et al. teaches using wearable devices to measure pulse transit time – pulse is based on arterial blood flow; in paragraph 295, there is a heart rate sensor that uses photoplethysmography, which measures arterial blood flow, among other things).
Claim 16 is an apparatus claim that recites an apparatus comprising components configured to perform functions that are the same or substantially similar to the steps of the method described in claim 1. Miller teaches the following limitations not directly addressed in the rejection of claim 1:
a processor (paragraph 191);
a memory coupled with the processor (paragraph 191);
instructions stored in the memory and executable by the processor to cause the apparatus to (paragraph 191):
Please refer to the rejection of claim 1 for additional limitations.
Claims 17-20 are apparatus claims dependent from claim 16 that recite limitations that are the same or substantially similar to the limitations of claims 2-5, respectively. Please refer to the rejections of claims 16 and 2-5.
With respect to claim 21, Miller et al. teaches transmitting a signal to one or more additional devices to adjust the environment surrounding the user based at least in part on the one or more physiological characteristics.
Par. [0217], “Based on the measured skin temperature and measured ambient temperature, the WCD can automatically adjust the thermostat 2420 to alter the ambient temperature of the room. In this regard, if a user's skin temperature is too high, the WCD can instruct the thermostat 2420 to lower the ambient temperature. Similarly, if the user's skin temperature is too cold, the WCD can instruct the thermostat 2420 to raise the temperature. The WCD 2410 can instruct the thermostat (and/or an HVAC controller) directly, e.g., via a direct wireless link 2415, or indirectly, e.g., via one or more of the mobile device 2440 and the access point 2430. The WCD can also use historic temperature data to develop trend temperature data.”
With respect to claim 22, Miller et al. does not explicitly teach wherein one or more portions of the wearable ring device that include the first set of sensors comprise one or more thermally insulative portions that insulate the first set of sensors from ambient temperature.
However, von Badinski teaches a wearable ring device including a set of sensors with insulators,
Par. [0144], “Also shown in FIGS. 7 and 8 is an alternative design of the housing for the WCD where the ring includes an outer ring 812 a, an inner ring 812 b, and insulators 814 a and 814 b”.
It would have been obvious to one having ordinary skill in the art before the effective filing date of this application to add to the system of Miller and von Badinski the ability to include thermally insulative portions to insulate sensors from ambient temperature, as taught by von Badinski, because it increases the ability to create an accurate history tracking activities and creating accurate results and further because the arrangement of the temperature sensors within the ring can facilitate accurate ambident temperate measurements (see von Badinski, par. [0121]-[0122], [0216]).
Claim(s) 8 is rejected under 35 U.S.C. 103 as being unpatentable over the combination of Miller and von Badinski in view of Vardi et al. in further view of Heaton (US PG Pub. 2015/0354941).
With respect to claim 8, the combination of Miller, von Badinski and Vardi et al. teaches motion data (Miller paragraph 161 says that the sensor module for Sensor Example No. 1 measures motion in three dimensions) and identifying the probability that the user is drowsy or will become drowsy (paragraph 191 talks about probability of drowsiness in the last sentence; this in in the context of Sensor Example No. 1 – which includes motion data) based at least in part on a threshold (paragraph 184 teaches health metric thresholds that generate automated health decision outputs using the health metrics and the thresholds, and the data collected by Sensor Example No. 1 includes motion data).
Miller does not disclose that the identifying is based at least in part on the motion data being less than or equal to a motion threshold. However, Heaton et al. identifying that a user is drowsy or will become drowsy based at least in part on motion data being less than or equal to a motion threshold (Heaton, par. [0099] shows predicting drowsiness when movements begin to slow beyond a motion threshold – the beginning is the equal to the motion threshold).
Therefore It would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to modify Miller et al. identification of drowsiness to include identifying that a user is drowsy or will become drowsy based at least in part on motion data being less than or equal to a motion threshold as taught by Heaton et al. with the motivation of “warn such operators [of moving vehicles] when their alertness is compromised” which can “cause a serious accident” (Heaton, par. [0099]).
Response to Arguments
101 Rejections
Applicant's arguments filed April 22, 2026, have been fully considered but they are not persuasive.
Applicant argues that the features of amended independent claim 1 are not mental processes. Specifically, “acquiring, via a first set of sensors positioned on an inner surface of a wearable ring device, physiological data associated with a user, … wherein the acquiring comprises continuously sampling the skin temperature data at one or more sampling rates throughout at least one of a day or night to capture temperature fluctuations over different time periods”, “determining, using one or more processors of the wearable ring device, one or more skin temperature measurements of the skin temperature data that are outside a baseline temperature range of the user”, “determining, using the one or more processors of the wearable ring device, whether the one or more skin temperature measurements are outside the baseline temperature rang of the user due to the environment surrounding the user or to a physiological condition of the user based at least in part on the difference in the rate of change between the skin temperature data and the surrounding temperature data”, and “classifying, using a machine learning classifier, the physical activity into a physical activity type of a plurality of candidate physical activity types based at least in part on the comparison between the skin temperature data and the surrounding temperature data”. Applicant asserts that these limitations are not mental processor nor can be practically performed in the human mind.
These arguments are not persuasive. Per MPEP 2106.04(a)(2)(III), The courts do not distinguish between mental processes that are performed entirely in the human mind and mental processes that require a human to use a physical aid (e.g., pen and paper or a slide rule) to perform the claim limitation. See, e.g., Benson, 409 U.S. at 67, 65, 175 USPQ at 674-75, 674 (noting that the claimed "conversion of [binary-coded decimal] numerals to pure binary numerals can be done mentally," i.e., "as a person would do it by head and hand."); Synopsys, Inc. v. Mentor Graphics Corp., 839 F.3d 1138, 1139, 120 USPQ2d 1473, 1474 (Fed. Cir. 2016) (holding that claims to a mental process of "translating a functional description of a logic circuit into a hardware component description of the logic circuit" are directed to an abstract idea, because the claims "read on an individual performing the claimed steps mentally or with pencil and paper"). Nor do the courts distinguish between claims that recite mental processes performed by humans and claims that recite mental processes performed on a computer. As the Federal Circuit has explained, "[c]ourts have examined claims that required the use of a computer and still found that the underlying, patent-ineligible invention could be performed via pen and paper or in a person’s mind." Versata Dev. Group v. SAP Am., Inc., 793 F.3d 1306, 1335, 115 USPQ2d 1681, 1702 (Fed. Cir. 2015). See also Intellectual Ventures I LLC v. Symantec Corp., 838 F.3d 1307, 1318, 120 USPQ2d 1353, 1360 (Fed. Cir. 2016) (‘‘[W]ith the exception of generic computer-implemented steps, there is nothing in the claims themselves that foreclose them from being performed by a human, mentally or with pen and paper.’’); Mortgage Grader, Inc. v. First Choice Loan Servs. Inc., 811 F.3d 1314, 1324, 117 USPQ2d 1693, 1699 (Fed. Cir. 2016) (holding that computer-implemented method for "anonymous loan shopping" was an abstract idea because it could be "performed by humans without a computer").
The examiner does not dispute that the human mind is not capable of measuring temperature data or cause sensors of the wearable ring device to acquire surrounding temperature data. However, it is noted that the independent claims recite the use of sensors in acquiring physiological data and surrounding temperature data, which are continuously sampled at one or more sampling rates throughout at least one of a day or night, which was not stated as being part of the identified abstract idea, nor was the step of causing sensors of the wearable ring device to acquire surrounding temperature data. As articulated in the rejection, acquiring physiological data associated with a user, determining that the acquired data is outside a baseline (e.g., determining whether one or more skin temperature measurements are outside the baseline temperature range), causing the acquisition of surrounding temperature data, determining a difference in a rate of change between skin temperature and surrounding temperature, identifying one or more physiological characteristics based at least in part on the different in rate of change are a series of observations and determinations capable of being made by a person, either, mentally, or with the use of pencil and paper, or a computer.
Further, the sensors are recited with no specificity or techniques in how the sensors acquire said temperature data and the claims do not make clear or evident that there is any particularity in any improvement in how temperature data is acquired. The claims only recite the frequency (continuously sampled at one or more sampling rates throughout at least one of a day or night) at which skin temperature measurements are acquired or recorded using the sensor.
Therefore, the sensors are not considered to constitute or provide any improvement in technology or the technical field, and are seen as merely a tool used in an “apply it” manner to acquire temperature data. Similarly, the claims are not considered to be an improvement to the sensors themselves. Paragraphs 38-39 of the specification disclose that the sensors may be temperature sensors, and paragraph 55 disclose that example temperature sensors may include a thermistor, such as a negative temperature coefficient thermistor. Thus, not only does the claimed invention not require any particular or specific temperature sensor, the specification identifies a category of sensor types (temperature sensors, thermistors) that could be used in implementation. Thus, temperature sensors acquire temperature data, performing in the intended manner.
Applicant argues that the same limitations (argued above) recite a practical application of a judicial exception, by including an additional element that reflects an improvement in the functioning of a computer, or an improvement to other technology or technical field. Applicant argues that the continuous sampling of skin temperature data at one or more sampling rates throughout at least one of a day or night is a technological improvement and has a practical application of providing improved wearable device technology with increased accuracy of skin and/or body temperature measurements which in turn, improves determining conditions associated with a user. Applicant argues that the recited features reflect technical improvements to wearable device technology that “improve an ability of a wearable device to accurately determine conditions associated with a user based on skin temperature of a user”.
These arguments are not persuasive. The claims do not recite any change or improvement in the sensors themselves with respect to how they acquire or measure skin temperature. At most the claims specify that skin temperature measurements are not acquired or measured a single time, but a plurality of times by continuous sampling throughout the day or night. This does not constitute an improvement to the sensors used in measuring skin temperature. Collecting a greater volume of measurements is not an improvement in the functioning of a computer, the sensors, or any technology or technical field.
Applicant argues that recited elements of independent claim 1 recite specific improvements similar to the independent claims in Ex parte Desjardins. Applicant argues that, similar to Ex parte Desjardins, the recited elements of independent claim 1 reflect specific improvements as described in the specification, in particular, enabling a “more robust condition determination of the user”.
These arguments are not persuasive. Ex parte Desjardins is eligible because of the manner in which the claimed machine learning model is trained, such that it effectively learns new tasks in succession whilst protecting knowledge about previous tasks (overcoming the problem of “catastrophic forgetting”). The instant independent claims do not recite machine learning or machine learning models. Dependent claims 4 and 19 introduces machine learning in the form of a classifier used to classify physical activity into physical activity types. There is no training recited of the machine learning classifier, nor does it constitute any improvement to the machine learning classifier, or address any technical problems with the machine learning classifier, computer, sensor, or any other technology or technical field. Claims 4 and 19 utilizes machine learning in an “apply it” manner at a high level of generality.
Prior art Rejections
Applicant argues that Miller, von Badinski, Heaton and Vardi, alone or in any combination do not teach or suggest all of the features of independent claims 1 and 16: “determining, using one or more processors of the wearable ring device, one or more skin temperature measurements of the skin temperature data that are outside a baseline temperature range of the user” and “determining, using the one or more processors of the wearable ring device, whether the one or more skin temperature measurements are outside the baseline temperature range of the user due to the environment surrounding the user or to a physiological condition of the user based at least in part on the difference in the rate of change between the skin temperature data and the surrounding temperature data”.
This argument is not persuasive. With respect to “determining, using one or more processors of the wearable ring device, one or more skin temperature measurements of the skin temperature data that are outside a baseline temperature range of the user”, the wearable device of von Badinski is disclosed as having at least one internal facing temperature sensor to measure the skin temperature of the user and at least one outward facing temperature sensor to measure an ambient temperature of the room. Von Badinski also teaches determining that skin temperature measurements are outside a baseline temperature range of the user (para [0210] “The WCD can also monitor heart rate and/or temperature, in addition to the other monitored characteristics described above. If any of the monitored characteristics is abnormal, e.g., measured parameters outside of a predetermined threshold range), which could lead to an alert being sent to a third party. One action taken as a result of the measured skin temperature and measured ambient temperature is the WCD automatically adjusting the thermostat based on whether the user’s skin temperature is too high or too low (para [0217]). Upon determining that the skin temperature is abnormal, the ambient temperature is measured to adjust the thermostat accordingly. The ambient temperature is acquired based on the skin temperature data being outside temperature range in order to know how to adjust the thermostat. Thus, the skin temperature data being outside the baseline temperature range of the user “causes a second set of sensors to acquire surrounding temperature data”.
With respect to “determining, using the one or more processors of the wearable ring device, whether the one or more skin temperature measurements are outside the baseline temperature range of the user due to the environment surrounding the user or to a physiological condition of the user based at least in part on the difference in the rate of change between the skin temperature data and the surrounding temperature data”, this amended limitation is addressed in the updated rejection above.
Vardi teaches processor 52 and/or processor 112 may compare the measurements from first sensor 20 and second sensor 25 and define time intervals in the first period at which the skin temperature is less influenced by the ambient temperature, for example, when the difference between the two measurements (at the same time) is smaller than a threshold value or that the ratio between the two measurements is smaller than a threshold value. In some embodiments, manipulating the skin temperature measurements may include, filtering undesired measurements, extrapolating between skin temperature measurements, integrating, differentiating, or any mathematical manipulation that may be applied to time dependent temperature measurements known in the art. In some embodiments, in order to define periods at which the ambient conditions may have influence on the measurements received from the skin temperature sensor, a skin temperature measurement and an ambient temperature measurement taken at the same day/night time (in the past, for example between 02:00-04:00 AM) may be compared. In some embodiments, if the difference between the two is larger than a threshold value, the skin temperature measurement is identified as “influenced by the ambient temperature” [0030]). In other words, by comparing the skin and ambient temperature measurement to a similar measurement taken in the past (e.g., a baseline) and determining that the rate of change exceeds a threshold value, it is determined that the skin temperature measurement is “influenced by the ambient temperature” (e.g., due to the environment surrounding the user).
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Matsumura (US Patent 5,050,612)
Pho (US PG Pub 20210407684)
Zakharov (US Patent 9,823,138)
Blank (US Patent 9,220,416)
Ghoreyshi (US PG Pub 20210278290, 20210275030)
Marriott (US PG Pub 20210059586)
Maher (US PG Pub 20200060545)
Stivoric (US PG Pub 20170156594)
Cheatham (US PG Pub 20160258641)
Rausch (US PG Pub 20070161921)
Prachar (US Patent 10,750,951)
THIS ACTION IS MADE FINAL. Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
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/PETER H CHOI/Supervisory Patent Examiner, Art Unit 3681
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