DETAILED ACTION
Notice of Pre-AIA or AIA Status
In the present application, filed on or after March 16, 2013, claims 1-20 have been considered and examined under the first inventor to file provisions of the AIA .
Information Disclosure Statement
The information disclosure statements (IDS) submitted on 07/17/2024 is in compliance with the provision of 37 CFR 1.97. Accordingly, the information disclosure statements are being considered by Examiner.
Claim Rejections - 35 USC § 112
The following is a quotation of 35 U.S.C. 112(b):
(B) CONCLUSION – The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
The following is a quotation of 35 U.S.C. 112(pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
Claim 16 is rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre- AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor, or for pre-AIA the applicant regards as the invention.
Claim 16 lacks antecedent basis for various limitations in claim 16 (see the below bold limitations for detail) including the control unit using the following to detect an atrial fibrillation: if a length of the ECG is 0, then the result is inconclusive; if a median absolute deviation of the R to R peak intervals is less than or equal to 50 and first order standard deviation of the duration between two successive R to R peaks is less than or equal to 44, or if the square root of the mean of the sum of successive differences between adjacent R to R peak intervals is less than or equal to 50, then the signal indicates a normal sinus rhythm (NSR); if the median absolute deviation of the R to R peak intervals is greater than 50 and less than 500, and the first order standard deviation of the duration between two successive R to R peaks is greater than 44 and less than 440, and the outliers are between 4 and 40, or if the square root of the mean of the sum of successive differences between adjacent R to R peak intervals is greater than 50 and less than 500, then the signal indicates atrial fibrillation; and any other condition is ignored as inconclusive.
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 for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
Claims 1 and 11 are rejected under 35 U.S.C. 103 as being unpatentable over Tran et al. (Tran – US 10,998,101 B1) in view of Gibson et al. (Gibson – US 2016/0019283 A1).
As to claim 1, Tran discloses a wearable device for monitoring a user’s health, comprising:
a heart rate monitor (Tran: FIG. 1 the EKG sensor 102) that detects a heart rate of the user and generates heart rate data (Tran: column 5 lines 20-24, column 6 lines 20-33, column 12 lines 47-column 13 lines 3, column 40 lines 53-column 41 lines 24, column 55 lines 42-65, and FIG. 1 the EKG sensor 102, and FIG. 6: The sensor's heart-rate pulse sensor can identify cardiac issues such as atrial fibrillation. The device 102 periodically checks for irregularities in the heart rate. One embodiment uses the optical sensors, while other embodiments use EKG sensors on the device 102);
a body temperature monitor that detects a body temperature of the user and generates body temperature data (Tran: column 5 lines 54-column 6 lines 10, column 19 lines 39-44, and FIG. 1);
a blood pressure monitor that a blood pressure of the user and generates blood pressure data (Tran: column 5 lines 25-53, column 6 lines 20-33, column 9 lines 38-46, column 35 lines 24-47, column 55 lines 42-65, FIG. 2, and FIG. 6: FIG. 6 shows learning system architectures for determining glucose, heart rate, blood pressure, among others. The same architecture can also recommend treatment based on sensor data captured over time and based on treatment data for a population of users. For example, during examination, a doctor uses a smartphone to review sensor data from a biologic such as a human or an animal. Feature extraction is done on the data as detailed herein);
a control unit (Tran: FIG. 1 the local computer 104) comprising a processor (Tran: column 55 lines 7-17 and FIG. 1: In the above embodiments, the local computer 104 can perform the bioelectric signal processing to extract patient parameters from data captured by the contacts. In this case, the local computer may need a DSP or powerful CPU to perform the calculations), memory (Tran: column 8 lines 11-22 and FIG. 1: In some embodiments, the CPU/GPU can be an MPU with low processing power; thus, each time the sensor gets new data, the EKG data, the EMG data, the bio-impedance data, or the raw measurement data from the IMU is communicated from the sensor device to the local computer according to a pre-specified protocol. The local computer computes the orientation, state, and/or color information, and sends a set color message back to the sensor device to configure the LED color. The local computer further updates the configuration application to display a color that matches the color set on the sensor device. The orientation, state, and/or color information is stored on the local computer), and a communications system (Tran: column 4 lines 37-54, column 7 lines 52-column 8 lines 10, and FIG. 1: he sensor devices are connected (e.g., via a wireless communication interface such as Bluetooth interface) to a local computing device 104, which can be a personal computer, a smartphone, a tablet, or any other appropriate computing device that is configured to perform the data processing, evaluation, and/or feedback), the control unit generating user health information based at least upon one or more of the heart rate data, blood oxygen data, body temperature data, and blood pressure data (column 5 lines 54-column 6 lines 10, column 8 lines 11-37, and FIG. 1: the CPU/GPU can be an MPU with low processing power; thus, each time the sensor gets new data, the EKG data, the EMG data, the bio-impedance data, or the raw measurement data from the IMU is communicated from the sensor device to the local computer according to a pre-specified protocol. The local computer computes the orientation, state, and/or color information, and sends a set color message back to the sensor device to configure the LED color. The local computer further updates the configuration application to display a color that matches the color set on the sensor device. The orientation, state, and/or color information is stored on the local computer); and
an emergency notification module that operably transmits an emergency notification based at least upon the user health information (Tran: column 5 lines 54-column 6 lines 10, column 7 lines 52-column 8 lines 37, column 55 lines 7-17, and FIG. 1: The body temperature and sweating sensor module is adapted to sense an early stage exhaustion signal by collecting information regarding monitoring body surface temperature, humidity and capillary contraction to monitor muscle exercise to determine whether the early stage exhaustion appears. Upon detecting the early stage exhaustion, an alert will be announced).
Tran does not explicitly disclose a blood oxygen monitor that detects a blood oxygen level of the user and generates blood oxygen data.
However, it has been known in the art of monitoring conditions of a user to implement a blood oxygen monitor that detects a blood oxygen level of the user and generates blood oxygen data, as suggested by Gibson, which discloses a blood oxygen monitor (Gibson: Abstract, [0019] and FIG. 1 the wearable device 200) that detects a blood oxygen level of the user and generates blood oxygen data (Gibson: [0003], [0017], [0030], and FIG. 1-5: a wearable device may collect physiological and other data from a wearer of the device and transmit that data to the cloud or other remote server or device. For example, the wearable device may detect one or more physiological parameters, such as heart rate, blood pressure, respiration rate, blood oxygen saturation (SpO.sub.2), skin temperature, skin color, galvanic skin response (GSR), muscle movement, eye movement, blinking, and speech); and an emergency notification module that operably transmits an emergency notification based at least upon the user health information (Gibson: [0039], and FIG. 1-2: the wearable device 200 may also include an interface 280 via which the wearer of the device may receive one or more recommendations or alerts generated either from a remote server 140, remote computing device 130, or from the processor 250 provided on the device. The alerts could be any indication that can be noticed by the person wearing the wearable device. For example, the alert could include a visual component (e.g., textual or graphical information on a display), an auditory component (e.g., an alarm sound), and/or tactile component (e.g., a vibration). Further, the interface 280 may include a display 282 where a visual indication of the alert or recommendation may be displayed. The display 282 may further be configured to provide an indication of the detected or collected physiological, motion, contextual or personal parameters, for instance, the wearer's heart rate. )
Therefore, in view of teachings by Tran and Gibson, it would have been obvious to one of the ordinary skill in the art before ethe effective filing date of the claimed invention to implement in the monitoring system of Tran to include a blood oxygen monitor that detects a blood oxygen level of the user and generates blood oxygen data, as suggested by Gibson. The motivation for this is to implement a known alternative parameter for monitoring conditions of a user.
As to claim 11, Tran and Gibson disclose the limitations of claim 1 further comprising the device of claim 1, configured to detect atrial fibrillation, and the control unit generating user health information based at least on the detection of the atrial fibrillation (Tran: column 5 lines 20-24 and FIG. 1: the sensor's heart-rate pulse sensor can identify cardiac issues such as atrial fibrillation. The device 102 periodically checks for irregularities in the heart rate. One embodiment uses the optical sensors, while other embodiments use EKG sensors on the device 102.).
Claims 2-5, 7, and 18 are rejected under 35 U.S.C. 103 as being unpatentable over Tran et al. (Tran – US 10,998,101 B1) in view of Gibson et al. (Gibson – US 2016/0019283 A1) and further in view of Otto et al. (Otto – US 2009/0048540 A1).
As to claim 2, Tran and Gibson disclose the limitations of claim 1 except for the claimed limitations of the device of claim 1, comprising a fall detection monitor that detects a potential fall of the user and generates fall data, and the control unit using the generated fall data for generating the user health information.
However, it has been known in the art of user monitoring conditions to implement a fall detection monitor that detects a potential fall of the user and generates fall data, and the control unit using the generated fall data for generating the user health information, as suggested by Otto, which discloses a fall detection monitor (Otto: FIG. 4 the accelerometer 406) that detects a potential fall of the user and generates fall data, and the control unit using the generated fall data for generating the user health information (Otto: [0008]-[0009], [0028], [0049], [0051], [0061], [0066]-[0068], [0070]-[0075], and FIG. 4-5: The change in orientation is indicated by the change in location on the acceleration axis of the signals 501-503 following the fall. Note that this orientation is calculated as a function the static response due to gravity and how it acts on each axis. Hence, after the indicated fall, the signal 501 in the X-direction changes from approximately 0 g prior to the fall to approximately Acceleration=1 g after the fall. The signal 502 in the Y-direction remains very near its original value, and the signal 503 in the Z-direction changes from approximately 1 g prior to the fall to slightly less than 0 g after the fall. The change in the DC components of the acceleration values indicates a change in orientation. As an example, prior to the fall, the user 301 may have been in an upright position; however, after the fall, the user may now be in a supine position).
Therefore, in view of teachings by Tran, Gibson, and Otto, it would have been obvious to one of the ordinary skill in the art before the effective filing date of the claimed invention to implement in the monitoring system of Tran and Gibson to include a fall detection monitor that detects a potential fall of the user and generates fall data, and the control unit using the generated fall data for generating the user health information, as suggested by Otto. The motivation for this is to detect a fall condition of a user based on information from an accelerometer/motion sensor.
As to claim 3, Tran and Gibson disclose the limitations of claim 1 except for the claimed limitations of the device of claim 1, comprising a motion detection monitor that detects a position and acceleration of the device, and wherein the control unit generates position data indicative of the motion of the device.
However, it has been known in the art of user monitoring conditions to implement a motion detection monitor that detects a position and acceleration of the device, and wherein the control unit generates position data indicative of the motion of the device, as suggested by Otto, which discloses a motion detection monitor (Otto: FIG. 4 the accelerometer 406) that detects a position and acceleration of the device, and wherein the control unit generates position data indicative of the motion of the device (Otto: [0008]-[0009], [0028], [0049], [0051], [0061], [0066]-[0068], [0070]-[0075], and FIG. 4-5: The change in orientation is indicated by the change in location on the acceleration axis of the signals 501-503 following the fall. Note that this orientation is calculated as a function the static response due to gravity and how it acts on each axis. Hence, after the indicated fall, the signal 501 in the X-direction changes from approximately 0 g prior to the fall to approximately Acceleration=1 g after the fall. The signal 502 in the Y-direction remains very near its original value, and the signal 503 in the Z-direction changes from approximately 1 g prior to the fall to slightly less than 0 g after the fall. The change in the DC components of the acceleration values indicates a change in orientation. As an example, prior to the fall, the user 301 may have been in an upright position; however, after the fall, the user may now be in a supine position).
Therefore, in view of teachings by Tran, Gibson, and Otto, it would have been obvious to one of the ordinary skill in the art before the effective filing date of the claimed invention to implement in the monitoring system of Tran and Gibson to include a motion detection monitor that detects a position and acceleration of the device, and wherein the control unit generates position data indicative of the motion of the device, as suggested by Otto. The motivation for this is to detect a fall condition of a user based on information from an accelerometer/motion sensor.
As to claim 4, Tran, Gibson, and Otto disclose the limitations of claim 3 further comprising the device of claim 3, the generated position data used to determine whether the wearable device is in a standard operating procedure (SOP) position for collecting health information of the user (Otto: [0008]-[0009], [0028], [0049], [0051], [0061], [0066]-[0068], [0070]-[0075], and FIG. 4-5: The change in orientation is indicated by the change in location on the acceleration axis of the signals 501-503 following the fall. Note that this orientation is calculated as a function the static response due to gravity and how it acts on each axis. Hence, after the indicated fall, the signal 501 in the X-direction changes from approximately 0 g prior to the fall to approximately Acceleration=1 g after the fall. The signal 502 in the Y-direction remains very near its original value, and the signal 503 in the Z-direction changes from approximately 1 g prior to the fall to slightly less than 0 g after the fall. The change in the DC components of the acceleration values indicates a change in orientation. As an example, prior to the fall, the user 301 may have been in an upright position; however, after the fall, the user may now be in a supine position).
As to claim 5, Tran, Gibson, and Otto disclose the limitations of claim 3 further comprising the device of claim 3, the generated position data used to determine whether the wearable device is in a non-SOP position for collecting health information of the user, and the control unit generating an alert to the user that indicates the non-standard operating position status (Otto: [0008]-[0009], [0028], [0049], [0051], [0061], [0066]-[0068], [0070]-[0075], and FIG. 4-5: The change in orientation is indicated by the change in location on the acceleration axis of the signals 501-503 following the fall. Note that this orientation is calculated as a function the static response due to gravity and how it acts on each axis. Hence, after the indicated fall, the signal 501 in the X-direction changes from approximately 0 g prior to the fall to approximately Acceleration=1 g after the fall. The signal 502 in the Y-direction remains very near its original value, and the signal 503 in the Z-direction changes from approximately 1 g prior to the fall to slightly less than 0 g after the fall. The change in the DC components of the acceleration values indicates a change in orientation. As an example, prior to the fall, the user 301 may have been in an upright position; however, after the fall, the user may now be in a supine position).
As to claim 7, Tran, Gibson, and Otto disclose the limitations of claim 3 further comprising the device of claim 3, the motion detection monitor detecting: lateral movement of the device; shift in position of the device; angular twist or rotation of the device; and acceleration of the device (Otto: [0008]-[0009], [0028], [0049], [0051], [0061], [0066]-[0068], [0070]-[0075], and FIG. 4-5: The change in orientation is indicated by the change in location on the acceleration axis of the signals 501-503 following the fall. Note that this orientation is calculated as a function the static response due to gravity and how it acts on each axis. Hence, after the indicated fall, the signal 501 in the X-direction changes from approximately 0 g prior to the fall to approximately Acceleration=1 g after the fall. The signal 502 in the Y-direction remains very near its original value, and the signal 503 in the Z-direction changes from approximately 1 g prior to the fall to slightly less than 0 g after the fall. The change in the DC components of the acceleration values indicates a change in orientation. As an example, prior to the fall, the user 301 may have been in an upright position; however, after the fall, the user may now be in a supine position).
As to claim 18, Tran, Gibson, and Otto disclose the limitations of claim 2 further comprising the device of claim 2, the fall detection monitor utilizing a motion detection monitor that detects a position and acceleration of the device, and wherein the control unit generates position data indicative of the motion of the device to determine if a fall is detected (Otto: [0008]-[0009], [0028], [0049], [0051], [0061], [0066]-[0068], [0070]-[0075], and FIG. 4-5: The change in orientation is indicated by the change in location on the acceleration axis of the signals 501-503 following the fall. Note that this orientation is calculated as a function the static response due to gravity and how it acts on each axis. Hence, after the indicated fall, the signal 501 in the X-direction changes from approximately 0 g prior to the fall to approximately Acceleration=1 g after the fall. The signal 502 in the Y-direction remains very near its original value, and the signal 503 in the Z-direction changes from approximately 1 g prior to the fall to slightly less than 0 g after the fall. The change in the DC components of the acceleration values indicates a change in orientation. As an example, prior to the fall, the user 301 may have been in an upright position; however, after the fall, the user may now be in a supine position).
Claim 6 is rejected under 35 U.S.C. 103 as being unpatentable over Tran et al. (Tran – US 10,998,101 B1) in view of Gibson et al. (Gibson – US 2016/0019283 A1) and Otto et al. (Otto – US 2009/0048540 A1) and further in view of McCarthy et al. (McCarthy – US 2017/0296116 A1) and V5 (V5 - V5 Inertial Sensor).
As to claim 6, Tran, Gibson, and Otto disclose the limitations of claim 3 except for the claimed limitations of the device of claim 3, the motion detection monitor comprising a microelectromechanical system (MEMS) that is a six-dimensional sensor comprising an accelerometer that senses linear accelerations, and a gyroscopic that senses angular velocities in three dimensions.
However, it has been known in the art of user monitoring conditions to implement the motion detection monitor comprising a microelectromechanical system (MEMS) that is a six-dimensional sensor comprising an accelerometer that senses linear accelerations, and a motion that senses angular velocities in three dimensions, as suggested by McCarthy, which discloses the motion detection monitor comprising a microelectromechanical system (MEMS) that is a six-dimensional sensor comprising an accelerometer that senses linear accelerations, and a motion that senses angular velocities in three dimensions (McCarthy [0054]-[0055], [0057], and FIG. 1: the sensor 200 can include a 6-Dimensional motion capture device 204 that detects the changes in motion via a 6-degrees of freedom Micro-Electro-Mechanical Systems (MEMS) based sensor which determines linear acceleration in 3 dimensions, A.sub.x, A.sub.y, A.sub.z and rotational motion as pitch, yaw, and roll).
Therefore, in view of teachings by Tran, Gibson, Otto, and McCarthy, it would have been obvious to one of the ordinary skill in the art before the effective filing date of the claimed invention to implement in the monitoring system of Tran, Gibson, and Otto, to include the motion detection monitor comprising a microelectromechanical system (MEMS) that is a six-dimensional sensor comprising an accelerometer that senses linear accelerations, and a motion that senses angular velocities in three dimensions, as suggested by McCarthy. The motivation for this is to implement a known alternative sensor for sensing motion information of a user.
The combination of Tran, Gibson, Otto, and McCarthy does not explicitly disclose an inertial sensor comprising an accelerometer and a gyroscope.
However, it has been known in the art of user monitoring conditions to implement an inertial sensor comprising an accelerometer and a gyroscope, as suggested by V5, which discloses an inertial sensor comprising an accelerometer and a gyroscope (V5 - V5 Inertial Sensor: The Inertial Sensor is a combination of a 3-axis (X,Y, and Z) accelerometer and a 3-axis gyroscope. The accelerometer measures linear acceleration of the robot (including gravity), while the gyroscope electronically measures the rate of rotation about the V5 inertial sensor three-axis.).
Therefore, in view of teachings by Tran, Gibson, Otto, McCarthy, and V5, it would have been obvious to one of the ordinary skill in the art before the effective filing date of the claimed invention to implement in the monitoring system of Tran, Gibson, Otto, and McCarthy to include an inertial sensor comprising an accelerometer and a gyroscope, as suggested by V5. The motivation for this is to implement a known alternative sensor for sensing motion information.
Claims 8-9 are rejected under 35 U.S.C. 103 as being unpatentable over Tran et al. (Tran – US 10,998,101 B1) in view of Gibson et al. (Gibson – US 2016/0019283 A1) and Otto et al. (Otto – US 2009/0048540 A1) and further in view of Sobol et al. (Sobol – US 2021/0319894 A1).
As to claim 8, Tran, Gibson, and Otto disclose the limitations of claim 4 except for the claimed limitations of the device of claim 4, the SOP position comprising merely one position wherein the device is disposed in a substantially horizontal position with a top of the device facing substantially upward, and not substantially moving.
However, it has been known in the art of user monitoring conditions to implement the SOP position comprising merely one position wherein the device is disposed in a substantially horizontal position with a top of the device facing substantially upward, and not substantially moving, as suggested by Otto, which discloses the SOP position comprising merely one position wherein the device is disposed in a substantially horizontal position with a top of the device facing substantially upward, and not substantially moving (Sobol: [0277]-[0279], and FIG. 11: within the uppermost strata 5100, a distinction between movement (activity) and no movement (static) is shown, while (using the “activity” labeled classification as an example) analysis of the type of activity, such as whether the movement-based activity of the highest-level strata 5100 can be more particularly identified as a fall, walking, transitional movement or something else, and from there (using the “transitional” category as an example) whether it involves transition between upright positions, transition from upright to a supine position, transition from supine to upright, transition between supine positions or the like. From this, the attempt at a particular classification proceeds from an understanding of more certain (but less granular) activities at the higher strata 5100 to less certain (but more granular) activities at the intermediate and lowest strata 5200 through 5400).
Therefore, in view of teachings by Tran, Gibson, Otto, and Sobol, it would have been obvious to one of the ordinary skill in the art before the effective filing date of the claimed invention to implement in the monitoring system of Tran, Gibson, and Otto to include the SOP position comprising merely one position wherein the device is disposed in a substantially horizontal position with a top of the device facing substantially upward, and not substantially moving, as suggested by Sobol. The motivation for this is to detect various positions of a user based on information from an accelerometer/motion sensor.
As to claim 9, Tran, Gibson, Otto, and Sobol disclose the limitations of claim 8 further comprising the device of claim 8, a non-SOP position comprising any other position that is not the SOP position (Sobol: [0277]-[0279], and FIG. 11: within the uppermost strata 5100, a distinction between movement (activity) and no movement (static) is shown, while (using the “activity” labeled classification as an example) analysis of the type of activity, such as whether the movement-based activity of the highest-level strata 5100 can be more particularly identified as a fall, walking, transitional movement or something else, and from there (using the “transitional” category as an example) whether it involves transition between upright positions, transition from upright to a supine position, transition from supine to upright, transition between supine positions or the like. From this, the attempt at a particular classification proceeds from an understanding of more certain (but less granular) activities at the higher strata 5100 to less certain (but more granular) activities at the intermediate and lowest strata 5200 through 5400).
Claim 10 is rejected under 35 U.S.C. 103 as being unpatentable over Tran et al. (Tran – US 10,998,101 B1) in view of Gibson et al. (Gibson – US 2016/0019283 A1) and Otto et al. (Otto – US 2009/0048540 A1) further in view of Phillips et al. (Phillips – US 2022/0249906 A1).
As to claim 10, Tran, Gibson, and Otto disclose the limitations of claim 3 further comprising the device of claim 3, the motion detection monitor, in conjunction with the control unit, detecting: the user is stationary (Otto: [0006], [0072]-[0075], [0119], and FIG. 5); the user is walking (Otto: [0077], [0119], [0072]-[0075], and FIG. 5); the user is running or jogging (Otto: [0006], [0119], and FIG. 4-5: Category of Activity, for purposes within, refers to whether the user is resting, standing/sitting, walking, or fast walking/running. Sleep/Wake patterns refer to more general categories of activity (sleeping or not sleeping). Levels of Activity refer to any quantitative measure of activity such as caloric expenditure or some other relative units for measuring activity);except for the claimed limitations of the user is riding a human powered machine; and the user is in a powered vehicle.
However, it has been known in the art of user monitoring conditions to implement the user is riding a human powered machine; and the user is in a powered vehicle, as suggested by Phillips, which discloses the user is riding a human powered machine; and the user is in a powered vehicle (Phillips: Abstract, [0133]-[0139], and FIG. 1: Example input data 342 may be motion data generated by motion sensors of computing devices carried by or worn by users as the users perform various physical activities that machine-learned model 300 is trained to recognize. For example, example input data that corresponds to riding a bicycle may be motion data generated by motion sensors of wearable computing devices worn by users while the users were riding bicycles, example input data that corresponds to walking may be motion data generated by motion sensors of wearable computing devices worn by users while the users were walking, example input data that corresponds to running may be motion data generated by motion sensors of wearable computing devices worn by users while the users were running, and example input data that corresponds to remaining still may be motion data generated by motion sensors of wearable computing devices worn by users while the users were remaining still… the example input data that corresponds to remaining still may include motion data generated by users that were driving or sitting in vehicles, such as users driving or sitting in cars, buses, trains, and the like. Specifically, the example input data may include motion data generated by motion sensors of computing devices carried by or worn by users that were driving or sitting in vehicles that are labeled as remaining still. By using such example input data to train machine-learned model 300, machine-learned model 300 may be trained to not recognize such motion data generated by motion sensors of computing devices carried by or worn by users that were driving or sitting in vehicles as walking, running, or any form of physical exercise).
Therefore, in view of teachings by Tran, Gibson, Otto, and Phillips, it would have been obvious to one of the ordinary skill in the art before the effective filing date of the claimed invention to implement in the monitoring system of Tran, Gibson, and Otto to include the user is riding a human powered machine; and the user is in a powered vehicle, as suggested by Phillips. The motivation for this is to detect various activities of a user based on information from an accelerometer/motion sensor.
Claims 12 and 14 are rejected under 35 U.S.C. 103 as being unpatentable over Tran et al. (Tran – US 10,998,101 B1) in view of Gibson et al. (Gibson – US 2016/0019283 A1) and further in view of Namkoong et al. (Namkoong – US 2017/0296120 A1).
As to claim 12, Tran and Gibson disclose the limitations of claim 11 except for the claimed limitations of the device of claim 11, comprising a positive lead, a negative lead, and a neutral lead that in conjunction are used to detect an electrocardiogram (ECG) signal of the user.
However, it has been known in the art of user monitoring conditions to implement a positive lead, a negative lead, and a neutral lead that in conjunction are used to detect an electrocardiogram (ECG) signal of the user, as suggested by Namkoong, which discloses a positive lead, a negative lead, and a neutral lead that in conjunction are used to detect an electrocardiogram (ECG) signal of the user (Namkoong: Abstract, [0021]-0022], [0024], [0057]-[0059], [0066], [0092]-[0094], FIG. 2-5, and FIG. 16: the first outer electrode 141, the second outer electrode 142, the first inner electrode 131, and the second inner electrode 132: in the case where the ECG signal is measured through three electrodes, the first inner electrode 131 may be used as a reference electrode, and either of the first and second outer electrodes 141 and 142 may be used as a positive electrode and the second inner electrode 132 as a negative electrode. Alternatively, the second inner electrode 132 may be used as a reference electrode and either of the first and second outer electrodes 141 and 142 may be used as a positive electrode and the first inner electrode 131 as a negative electrode. Here, the positive electrode and the negative electrode may be switched with each other.).
Therefore, in view of teachings by Tran, Gibson, and Namkoong, it would have been obvious to one of the ordinary skill in the art before the effective filing date of the claimed invention to implement in the monitoring system of Tran and Gibson, to include a positive lead, a negative lead, and a neutral lead that in conjunction are used to detect an electrocardiogram (ECG) signal of the user, as suggested by Namkoong. The motivation for this is to implement a known alternative sensor for sensing ECG signals from a wearable device associated with a user.
As to claim 14, Tran, Gibson, and Namkoong disclose the limitations of claim 12 further comprising the device of claim 12, the positive lead disposed on a top or side of the device not in contact with the user’s skin when worn, and the negative and neutral leads disposed in contact with the user’s skin when worn (Namkoong: Abstract, [0021]-0022], [0024], [0057]-[0059], [0066], [0092]-[0094], FIG. 2-5, and FIG. 16: the first outer electrode 141, the second outer electrode 142, the first inner electrode 131, and the second inner electrode 132: in the case where the ECG signal is measured through three electrodes, the first inner electrode 131 may be used as a reference electrode, and either of the first and second outer electrodes 141 and 142 may be used as a positive electrode and the second inner electrode 132 as a negative electrode. Alternatively, the second inner electrode 132 may be used as a reference electrode and either of the first and second outer electrodes 141 and 142 may be used as a positive electrode and the first inner electrode 131 as a negative electrode. Here, the positive electrode and the negative electrode may be switched with each other.).
Claim 13 is rejected under 35 U.S.C. 103 as being unpatentable over Tran et al. (Tran – US 10,998,101 B1) in view of Gibson et al. (Gibson – US 2016/0019283 A1) and Namkoong et al. (Namkoong – US 2017/0296120 A1) and further in view of Gilham et al. (Gilham – US 2012/0232416 A1) .
As to claim 13, Tran, Gibson, and Namkoong disclose the limitations of claim 12 except for the claimed limitations of the device of claim 12, the control unit utilizing the ECG signal data in combination with the heart rate data to detect an atrial fibrillation.
However, it has been known in the art of user monitoring conditions to implement the control unit utilizing the ECG signal data in combination with the heart rate data to detect an atrial fibrillation, as suggested by Gilham, which discloses the control unit utilizing the ECG signal data in combination with the heart rate data to detect an atrial fibrillation (Gilham: [0025]-[0026], [0031]-[0033], [0036]-[0048], FIG. 1-5: In another example, if an ECG analysis suggests a rhythm change to atrial fibrillation, the NIBP cuff on the patient is inflated in order to monitor the strength and regularity of the pulse measured in the NIBP cuff. This additional NIBP data is then used to confirm or suppress the atrial fibrillation diagnosis. Similarly, out of bounds heart rate alarms are checked via the NIBP cuff to confirm or deny rate violations before the alarm is sounded).
Therefore, in view of teachings by Tran, Gibson, Namkoong, and Gilham, it would have been obvious to one of the ordinary skill in the art before the effective filing date of the claimed invention to implement in the monitoring system of Tran, Gibson, and Namkoong to include the control unit utilizing the ECG signal data in combination with the heart rate data to detect an atrial fibrillation, as suggested by Gilham. The motivation for this is to detect an occurrence of an atrial fibrillation based on ECG signals and heart rate data to reduce false alarms.
Claim 15 is rejected under 35 U.S.C. 103 as being unpatentable over Tran et al. (Tran – US 10,998,101 B1) in view of Gibson et al. (Gibson – US 2016/0019283 A1) and further in view of Gilham et al. (Gilham – US 2012/0232416 A1) .
As to claim 15, Tran and Gibson disclose the limitations of claim 11 except for the claimed limitations of the device of claim 11, the atrial fibrillation detection detected using the control unit, wherein the control unit collects a series of heart rate data over a period of time, and the control units collects ECG signal data over the same period of time.
However, it has been known in the art of user monitoring conditions to implement the atrial fibrillation detection detected using the control unit, wherein the control unit collects a series of heart rate data over a period of time, and the control units collects ECG signal data over the same period of time, as suggested by Gilham, which discloses the atrial fibrillation detection detected using the control unit, wherein the control unit collects a series of heart rate data over a period of time, and the control units collects ECG signal data over the same period of time (Gilham: [0025]-[0026], [0031]-[0033], [0036]-[0048], FIG. 1-5: in one embodiment, for example, false ECG arrhythmia alarms are detected and suppressed, using the aforementioned method of the present invention, by simultaneously observing pulse signals from invasive pressure sensor, cuff pressure sensor, and/or the pulse oximeter and when adequate confidence in the pulse signal(s) allows the suppression of the ECG based alarm).
Therefore, in view of teachings by Tran, Gibson, and Gilham, it would have been obvious to one of the ordinary skill in the art before the effective filing date of the claimed invention to implement in the monitoring system of Tran and Gibson, to include the atrial fibrillation detection detected using the control unit, wherein the control unit collects a series of heart rate data over a period of time, and the control units collects ECG signal data over the same period of time, as suggested by Gilham. The motivation for this is to detect an occurrence of an atrial fibrillation based on ECG signals and heart rate data to reduce false alarms.
Claim 17 is rejected under 35 U.S.C. 103 as being unpatentable over Tran et al. (Tran – US 10,998,101 B1) in view of Gibson et al. (Gibson – US 2016/0019283 A1) and further in view of Lafon et al. (Lafon – US 2020/0000441 A1).
As to claim 17, Tran and Gibson disclose the limitations of claim 1 except for the claimed limitations of the device of claim 1, the heart rate monitor using a photoplethysmography (PPG) signal that detects one or more of: volumetric changes in arterial blood; variations in venous blood volume; user tissue optical property; and energy changes in the user’s body.
However, it has been known in the art of user monitoring conditions to implement the heart rate monitor using a photoplethysmography (PPG) signal that detects one or more of: volumetric changes in arterial blood; variations in venous blood volume; user tissue optical property; and energy changes in the user’s body, as suggested by Lafon, which discloses the heart rate monitor using a photoplethysmography (PPG) signal that detects one or more of: volumetric changes in arterial blood; variations in venous blood volume; user tissue optical property; and energy changes in the user’s body (Lafon: [0019], [0023], [0025], [0036], [0068], [0071]-[0085], and FIG. 6: Although some embodiments are described with reference to HR or cardiac components of PPG signals, the techniques described herein may be extended to other types of physiological metrics described herein, such as may relate to SpO.sub.2, or other types of signals that can be extracted from the PPG signals to determine such physiological metrics. For example, in some embodiments, a method for determining an SpO.sub.2 value comprises receiving a first set of one or more PPG signals from one or more PPG sensors, which may include analog signals or digital data sampled from analog components and stored in computer memory. The first set of PPG signals may correspond to red and/or infrared light previously emitted by one or more emitters after the emitted light has interacted with the user's skin, when the monitoring device is worn by the user).
Therefore, in view of teachings by Tran, Gibson, and Lafon, it would have been obvious to one of the ordinary skill in the art before the effective filing date of the claimed invention to implement in the monitoring system of Tran and Gibson, to include the heart rate monitor using a photoplethysmography (PPG) signal that detects one or more of: volumetric changes in arterial blood; variations in venous blood volume; user tissue optical property; and energy changes in the user’s body, as suggested by Lafon. The motivation for this is to detect heart data based on PPG signals.
Claims 19-20 are rejected under 35 U.S.C. 103 as being unpatentable over Tran et al. (Tran – US 10,998,101 B1) in view of Otto et al. (Otto – US 2009/0048540 A1).
As to claim 19, Tran discloses a system for remotely monitoring a patient’s health, comprising:
a wearable device that is worn by the patient (Tran: column 8 lines 37-column 10 lines 22 and FIG. 2 the wearable device sensor 102), the device comprising:
a plurality of monitors (Tran: FIG. 1 the light senor 290, the inertial magnetic unit (IMU) 210, the EKG sensor 216, the EMG sensor 218, the bioimpedance senor 222, and the vital sign sensor 224) respectively generating health data indicative of a different characteristic of the patient’s health status in real-time (Tran: column 5 lines 20-24, column 5 lines 54-column 6 lines 10, column 6 lines 20-33, column 9 lines 38-46, column 12 lines 47-column 13 lines 3, column 40 lines 53-column 41 lines 24, column 55 lines 42-65, and FIG. 1, and FIG. 6: The system allows patients to conduct a low-cost, comprehensive, real-time monitoring of their vital parameters such as ambulation and falls. Information can be viewed using an Internet-based website, a personal computer, or simply by viewing a display on the monitor);
a communications component (Tran: FIG. 1 the PAN/WAN cellular communication interface 220) that provides the health data to one or more of:
a local device (Tran: FIG. 1 the local computer 104) that collects and sends health data (Tran: column 8 lines 11-22 and FIG. 1: In some embodiments, the CPU/GPU can be an MPU with low processing power; thus, each time the sensor gets new data, the EKG data, the EMG data, the bio-impedance data, or the raw measurement data from the IMU is communicated from the sensor device to the local computer according to a pre-specified protocol. The local computer computes the orientation, state, and/or color information, and sends a set color message back to the sensor device to configure the LED color. The local computer further updates the configuration application to display a color that matches the color set on the sensor device. The orientation, state, and/or color information is stored on the local computer) to a remote health processing service (Tran: column 4 lines 37-54, column 7 lines 52-column 8 lines 10, and FIG. 1 the server 120: the sensor devices are connected (e.g., via a wireless communication interface such as Bluetooth interface) to a local computing device 104, which can be a personal computer, a smartphone, a tablet, or any other appropriate computing device that is configured to perform the data processing, evaluation, and/or feedback); and
the remote health processing service (Tran: the server 120);
an emergency notification component that transmits an emergency notification when activated, based at least on the health data and/or the fall data (Tran: column 5 lines 54-column 6 lines 10, column 7 lines 52-column 8 lines 37, column 55 lines 7-17, and FIG. 1: The body temperature and sweating sensor module is adapted to sense an early stage exhaustion signal by collecting information regarding monitoring body surface temperature, humidity and capillary contraction to monitor muscle exercise to determine whether the early stage exhaustion appears. Upon detecting the early stage exhaustion, an alert will be announced);
the remote health processing service that receives the health data and generates a patient health record based at least on the health data (Tran: column 4 lines 38-64, column 6 lines 40-54, column 33 lines 50 – column 34 lines 17, column 49 lines 61 – column 50 lines 8, column 55 lines 7-17, and FIG. 1: The management device executes one or more configurations and other related management applications to manage the configuration and operations of the sensor devices. In some embodiments, the management functions are performed by the sensor device directly. In some embodiments, the local device 104 (or the sensor device 102 if the sensor device directly performs processing) is optionally connected to a server 120 via a network such as the Internet. Data such as configuration, measurements, performance, etc. can be stored on the server to be accessed later and/or further processed), the patient health record retrievable on a remote device by a third-party authorized by the patient (column 31 lines 26-34, column 37 lines 56-65, column 42 lines 16-38, and FIG. 1: The user interface is preferably an application accessed through a computing device, or alternatively, a website presented as a separate online social network site or online community. The user interface may alternatively be hosted by a third-party social network site. Providing feedback may include one or more of several steps as described below; however, the feedback may be provided in any suitable manner).
Tran does not explicitly disclose a fall detection component that detects a potential fall of the user and generates fall data.
However, it has been known in the art of user monitoring conditions to implement a fall detection component that detects a potential fall of the user and generates fall data, as suggested by Otto, which discloses a fall detection component (Otto: FIG. 4 the accelerometer 406) that detects a potential fall of the user and generates fall data (Otto: [0008]-[0009], [0028], [0049], [0051], [0061], [0066]-[0068], [0070]-[0075], and FIG. 4-5: The change in orientation is indicated by the change in location on the acceleration axis of the signals 501-503 following the fall. Note that this orientation is calculated as a function the static response due to gravity and how it acts on each axis. Hence, after the indicated fall, the signal 501 in the X-direction changes from approximately 0 g prior to the fall to approximately Acceleration=1 g after the fall. The signal 502 in the Y-direction remains very near its original value, and the signal 503 in the Z-direction changes from approximately 1 g prior to the fall to slightly less than 0 g after the fall. The change in the DC components of the acceleration values indicates a change in orientation. As an example, prior to the fall, the user 301 may have been in an upright position; however, after the fall, the user may now be in a supine position).
Therefore, in view of teachings by Tran, Gibson, and Otto, it would have been obvious to one of the ordinary skill in the art before the effective filing date of the claimed invention to implement in the monitoring system of Tran and Gibson to include a fall detection component that detects a potential fall of the user and generates fall data, as suggested by Otto. The motivation for this is to detect a fall condition of a user based on information from an accelerometer/motion sensor.
As to claim 20, Tran discloses a system for remotely monitoring a patient’s health, comprising:
a communications component that r