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 .
Information Disclosure Statement
The information disclosure statements (IDS) submitted on Dec. 20, 2023, Sep. 23, 2024, and Jan. 15, 2025 are in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statement is being considered by the examiner.
Response to Amendment
The Amendment filed January 21, 2026 has been entered. Claims 1-21 remain pending in the application. Claims 1, 4-5, 8, 11-12, 16, 18 & 20 have been amended. Claim 21 is new. Applicant’s amendments to the Drawings have overcome each and every objection previously set forth in the Non-Final Office Action mailed October 30, 2025, hereafter referred to as the Non-Final Office Action.
Response to Arguments
Applicant’s arguments, see pp. 8-10 of applicant’s remarks, filed January 21, 2026, that the prior art reference with respect to the rejection(s) of amended independent claim(s) 1, 8 & 16, under U.S.C. § 102(a)(1), Eom et al. (US 2021/0041912, hereinafter Eom), have been fully considered and are persuasive. Therefore, the rejections have been withdrawn. However, upon further consideration, a new ground(s) of rejection is made in view of Eom, in view of Wolf et al. (US 2008/0234935 A1), and further in view of Jin et al. (US 2021/0247812 A1). Therefore, the rejections of amended independent claims 1, 8 & 16, and dependent claims 2-7, 9-15 & 17-21, which depend from and incorporate the limitations of amended independent claims 1, 8 & 16, are respectively maintained. Updated rejections based on amended features follow.
Applicant’s arguments, see pp. 8-10 of applicant’s remarks, filed January 21, 2026, that the prior art references with respect to the rejection(s) of amended dependent claim(s) 4, 11 & 18, under U.S.C. § 103, Eom, in view of Liu (CN 109756630 A, hereinafter Liu), have been fully considered and are persuasive. Therefore, the rejections have been withdrawn. However, upon further consideration, a new ground(s) of rejection is made in view of Eom, in view of Liu, in view of Wolf, in view of Jin, and further in view of DiFonzo (US 2017/0083071 A1, hereinafter DiFonzo). Therefore, the rejections of amended dependent claims 4, 11 & 18, are respectively maintained. Updated rejections based on amended features follow.
Applicant’s arguments, see pp. 8-10 of applicant’s remarks, filed January 21, 2026, that the prior art references with respect to the rejection(s) of dependent claim(s) 6 & 13, under U.S.C. § 103, Eom, in view of Zhang (US 2022/0261093 A1, hereinafter, Zhang), have been fully considered and are persuasive. Therefore, the rejections have been withdrawn. However, upon further consideration, a new ground(s) of rejection is made in view of Eom, in view of Zhang, in view of Jin, and further in view of Wolf. Therefore, the rejections of dependent claims 6 & 13, which depend from amended independent claims 1 & 8, which have been updated with new grounds of rejection, are respectively maintained. Updated rejections based on amended features (independent claims 1 & 8) follow.
Applicant’s arguments, see pp. 8-10 of applicant’s remarks, filed January 21, 2026, that the prior art references with respect to the rejection(s) of dependent claim(s) 7 & 15, under U.S.C. § 103, Eom, in view of Kim(US 12288492 B2, hereinafter, Kim), have been fully considered and are persuasive. Therefore, the rejections have been withdrawn. However, upon further consideration, a new ground(s) of rejection is made in view of Eom, in view Kim, in view of Jin, and further in view of Wolf. Therefore, the rejections of dependent claims 7 & 15, which depend from amended independent claims 1 & 8, which have been updated with new grounds of rejection, are respectively maintained. Updated rejections based on amended features (independent claims 1 & 8) follow.
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 1-3, 5, 8-10, 12, 16-17 & 19-20 are rejected under 35 U.S.C. 103 as being unpatentable over Eom et al. (US 2021/0041912 A1, Pub. Date Feb. 11, 2021, hereinafter, Eom), in view of Jin et al. (US 2021/0247812 A1, Pub. Date Aug. 12, 2021, hereinafter, Jin), and further in view of Wolf et al. (US 2008/0234935 A1, Pub. Date Sep. 25, 2008, hereinafter, Wolf).
Regarding independent claim 1, Eom, teaches:
A device, comprising (Fig. 1; [Abstract]):
a first component including (Fig. 2A; [0056]-[0059] & [0063]-[0067]: first housing structure 210 interpreted as first component):
a second component coupled to the first component, the first and second components configured to rotate with respect to a hinge axis, the second component including (Fig. 2A & 2B; [Abstract], [0005], [0056]-[0060], [0067]-[0069] & [0102]: second housing structure 220 interpreted as second component coupled to the first housing 210):
determine an angle between the first component and the second component ([0008], [0085]-[0090], [0095], [0102], [0114] & [0121]);
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Eom, is silent in regard to:
a third processor coupled to the first sensor unit and the second sensor unit, the third processor configured to:
However, Eom, in combination with Jin, further teach:
a third processor coupled to the first sensor unit and the second sensor unit, the third processor configured to (Disclosed in combination: Eom: Figs. 1, 2A, & 4A; [0030]-[0031], [0085]-[0090]: overall main processor 120/410 (third processor) coupled to the first and second motion sensor modules; Jin: [0108]-[[0109]: supports distributed multi-processor bus architecture across a hinge):
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It would have been obvious to one of ordinary skill in the art at the time of the invention to modify the foldable electronic device of Eom to incorporate the distributed, multi-processor architecture taught by Jin. A POSITA would have been motivated to apply Jin’s distributed processor/sensor hub architecture to Eom’s angle-detecting device to reduce power consumption and decrease the continuous computational burden on the main application processor. By offloading the constant polling and baseline calculations of the IMU sensors to dedicated, localized processors (sensor hubs) as taught by Jin, Eom’s device could continuously monitor its folding state in a low-power background mode without draining the battery by keeping the main processor awake, according to known methods, and yielding predictable results (KSR).
Eom, in combination with Jin, are silent in regard to:
a first sensor unit including a first accelerometer, a first gyroscope, and a first processor, the first processor configured to determine a first orientation of the first component based on measurements by the first accelerometer and the first gyroscope;
a second sensor unit including a second accelerometer, a second gyroscope, and a second processor, the second processor configured to determine a second orientation of the second component based on measurements by the second accelerometer and the second gyroscope; and
rotate the second orientation of the second component such that the second orientation of the second component is realigned with the first orientation of the first component based on the first orientation of the first component and the angle between the first component and the second component; and
estimate the angle between the first component and the second component based on the first orientation and the rotated second orientation.
However, Eom, in combination with Wolf, further teach:
a first sensor unit including a first accelerometer, a first gyroscope, and a first processor (Disclosed in combination: Eom: Figs. 1, 2A, & 4A; [0030], [0070]-[0071], & [0083]-[0089]: first motion sensor module 240/340 (first sensor) disposed in the first housing structure 210, sensor module is a combination of at least two an acceleration sensor, an angular velocity sensor (gyro sensor) or a geomagnetic sensor, the overall main processor 120/410; Wolf: Fig. 3; [0039]: teaches a MSMPU (sensor unit) that integrates a local processor (320) with the accelerometer and gyroscope), the first processor configured to determine a first orientation of the first component based on measurements by the first accelerometer and the first gyroscope (Disclosed in combination: Eom: Figs. 1, 2A, & 4A; [0030], [0070]-[0071], & [0082]-[0089]; Wolf: Fig. 5; [0065]-[0067]: teaches the local processor determining local orientation/motion integration using its specific sensors);
a second sensor unit including a second accelerometer, a second gyroscope, and a second processor, the second processor configured to determine a second orientation of the second component based on measurements by the second accelerometer and the second gyroscope (Disclosed in combination: Eom: Figs. 1, 2A, & 4A; [0030], [0071], [0085]-[0089], [0103]: second motion sensor module 250/350 (second sensor unit) disposed in the second housing structure 220, sensor module is a combination of at least two acceleration sensor, an angular velocity sensor (gyro sensor) or a geomagnetic sensor, overall main processor 120/410; Wolf: Fig. 5; [0054]); and
estimate the angle between the first component and the second component based on the first orientation and the rotated second orientation (Disclosed in combination: Eom: [0134]: teaches combining the orientation states to estimate the final angle, leveraging Wolf’s rotate and realigned data; Wolf: Fig. 5; [0025], [0054]-[0055] & [0069]).
It would have been obvious to one of ordinary skill in the art at the time of the invention to upgrade Eom’s passive motion sensor modules into Wolf’s multi-sensor measurement processing units (smart sensors with local processors) to preprocess orientation data locally. Eom provides the foldable device structure, the hinge, the dual sensor modules in each component, and the central processor determining the hinge angle. Wolf teaches a smart sensor unit architecture (a local processor packaged directly with an accelerometer and gyroscope) to compute local orientations, as well as the specific mathematical steps of using rotation matrices to rotate and realign orientation frames back to a common reference frame. This modification reduces processing load on Eom’s central processor and improves power management, which Wolf identifies as an advantage. Furthermore, it would have been obvious to apply Wolf’s matrix rotation algorithms in Eom’s central processor to accurately combine the localized orientation vectors into an accurate relative hinge angle, according to known methods, and yield predictable results (KSR).
However, Wolf, further teaches:
rotate the second orientation of the second component such that the second orientation of the second component is realigned with the first orientation of the first component based on the first orientation of the first component and the angle between the first component and the second component (Fig. 9; [0007], [0011] & [0069]: teaches creating a rotation matrix to rotate sensor data back to a starting/reference measurement frame, which aligns the two orientation reference frames); and
It would have been obvious to one of ordinary skill in the art at the time of the invention to upgrade Eom’s passive motion sensor modules into Wolf’s multi-sensor measurement processing units (smart sensors with local processors) to preprocess orientation data locally. This modification reduces processing load on Eom’s central processor and improves power management, which Wolf identifies as an advantage. Furthermore, it would have been obvious to apply Wolf’s matrix rotation algorithms in Eom’s central processor to accurately combine the localized orientation vectors into an accurate relative hinge angle, according to known methods, and yield predictable results (KSR).
Regarding dependent claim 2, Eom, teaches:
The device of claim 1 ([Abstract]) wherein the third processor is configured to (Figs. 1 & 4A; [0030] & [0085]-[0090]):
determine an orientation change of the second component due to an angle rotation with respect to an axis in Earth's reference frame based on the angle between the first component and the second component ([0085]-[0091], [0114], & [0120]-[0121]); and
realign the second orientation with the first orientation based on the orientation change and the first orientation ([0085]-[0091], [0102], [0139]-[0140], [0144]-[0145], [0148],[0152], & [0155]).
Regarding dependent claim 3, Eom, teaches:
The device of claim 1 ([Abstract]) wherein the third processor is configured to determine the angle between the first component and the second component based on measurements generated by at least one (Figs. 1, 2A, & 4A; [0008], [0030]-[0031], [0070]-[0071], [0085]-[0090], [0095], [0102], & [0121]) accelerometer ([0070]-[0071], [0085]-[0087], [0103], & [0121]: first and second motion sensor modules 240/250 contain an acceleration sensor (accelerometer) and an angular velocity sensor (gyro sensor)), gyroscope ([0070]-[0071], [0085]-[0087], [0103], & [0121]), magnetometer, or hall sensor ([0008], [0070]-[0071], [0091]-[0093], & [0103]-[0104]: magnetic sensor module 252 detects a magnetic force, the motion sensor can include a geomagnetic sensor (magnetometer) and uses a magnetic force sensor and a magnetic body to determine the angle, the magnetic force sensor module detecting a magnet corresponds to a Hall sensor and detects a magnetic force to estimate the angle).
Regarding dependent claim 5, Eom, teaches:
The device of claim 1 ([Abstract]) wherein the third processor is configured to (Figs. 1, 2A, & 4A; [0008], [0030]-[0031] & [0085]-[0090]):
update the angle between the first component and the second component ([0087]: teaches tracking changed (updated) angular data from the sensors to continuously calculate/detect the folding angle between the first and second housing structures) based on measurements by the first accelerometer, the first gyroscope, the second accelerometer, and the second gyroscope ([0008], [0070]-[0071], [0085]-[ 0093], [0095], [0114], [0121] & [0153]-[0155]:teaches using sensing data (acceleration and angular velocity) from both the first and second motion sensor modules to determine the angle).
Regarding independent claim 8, Eom, teaches:
A method, comprising ([Abstract]):
Eom, is silent in regard to:
determining, by a third processor, an angle between the first component and the second component; and
However, Eom, in combination with Jin, further teach:
determining, by a third processor, an angle between the first component and the second component (Disclosed in combination: Eom: Figs. 1, 2A, & 4A; [0008], [0030]-[0031], [0085]-[0090], [0095], [0102], [0104] & [0121]: teaches the central processor step of determining the angle, processor calculates “first angle” (folding angle) from motion sensor data of both housings; Jin: [0108]-[0109]: teaches the multi-processor methodology, where a separate, third application processor calculates the final states based on data from the local sensor processors); and
It would have been obvious to one of ordinary skill in the art at the time of the invention to execute Eom’s angle-calculating method using Wolf’s local sensor orientation determinations and Wolf’s rotational realignment matrix steps, managed across Jin’s distributed processor architecture. The motivation to do so is to efficiently and accurately estimate the hinge angle while reducing the processing burden on the central processor, according to known methods, and yielding predictable results (KSR).
Eom, in combination with Jin, are silent in regard to:
determining, by a first sensor unit, a first orientation of a first component of a device, the first component including the first sensor unit, the first sensor unit including a first accelerometer and a first gyroscope, the first sensor unit determining the first orientation based on measurements by the first accelerometer and the first gyroscope;
determining, by a second sensor unit, a second orientation of a second component of the device, the first and second components configured to rotate with respect to a hinge axis, the second component including the second sensor unit, the second sensor unit including a second accelerometer and a second gyroscope, the second sensor unit determining the second orientation based on measurements by the second accelerometer and the second gyroscope;
and rotating, by the third processor, the second orientation of the second component such that the second orientation of the second component is realigned with the first orientation of the first component based on the first orientation of the first component and the angle between the first component and the second component; and
However, Wolf, further teaches:
and rotating, by the third processor, the second orientation of the second component such that the second orientation of the second component is realigned with the first orientation of the first component based on the first orientation of the first component and the angle between the first component and the second component (Fig. 9; [0007], [0011] & [0069]: teaches the mathematical methodology, creating a rotation matrix to rotate the second orientation back to the original/reference measurement frame, successfully realigning the two coordinate systems); and
It would have been obvious to one of ordinary skill in the art at the time of the invention to modify the angle-detecting device of Eom to incorporate the smart sensor units and rotation matrix mathematics taught by Wolf. The motivation to do so would be to optimize distributed processing and power efficiency, and to accurately resolve the shifting coordinate frames. A POSITA would recognize that Wolf’s kinematic rotation matrix techniques must be applied by the processors to precisely rotate and realign the second component’s coordinate frame with the first component’s coordinate frame, allowing the system to accurately estimate the final joint angle. This combination represents the application of a known technique (Wolf’s local smart-sensor architecture and kinematic rotation mathematics) to a known device (Eom’s foldable dual-sensor device) ready for improvement to yield predictable results (KSR). That would allow the combined elements to perform their standard, known functions to yield a more efficient and mathematically accurate angle-detecting device.
However, Eom, in combination with Wolf, further teach:
determining, by a first sensor unit, a first orientation of a first component of a device, the first component including the first sensor unit, the first sensor unit including a first accelerometer and a first gyroscope, the first sensor unit determining the first orientation based on measurements by the first accelerometer and the first gyroscope (Disclosed in combination: Eom: Figs. 1, 2A, & 4A; [0030], [0055]-[0060], [0070]-[0071] & [0082]-[0089]: first motion sensor module 240/340 (accelerometer & gyroscope) in first housing structure 210 detects pose/orientation; Wolf: [0039], [0054]-[0055] & [0065]-[0067]);
determining, by a second sensor unit, a second orientation of a second component of the device, the first and second components configured to rotate with respect to a hinge axis, the second component including the second sensor unit, the second sensor unit including a second accelerometer and a second gyroscope, the second sensor unit determining the second orientation based on measurements by the second accelerometer and the second gyroscope (Disclosed in combination: Eom: Figs: 1, 2A, & 4A; [Abstract, [0005], ][0030], [0055]-[0060], [0068], [0070]-[0071], [0082]-[0089] & [0102]-[0103]: second motion sensor module 250/350 (accelerometer & gyroscope) in second housing structure 220 detects pose/orientation, hinge structure connects housings; Wolf: [0054]-[0055]: smart sensor methodology makes it obvious that the second sensor unit determines the second orientation locally using its own accelerometer and gyroscope);
estimating by the third processor the angle between the first component and the second component based on the first orientation and the rotated second orientation (Disclosed in combination: Eom: [0134]: teaches estimating the final joint angle based on the two individual orientations; Wolf: Fig. 9; [0025], [0054]-[0055] & [0069]: provides the mechanism to combine this data once the second orientation has been successfully rotated/realigned).
It would have been obvious to one of ordinary skill in the art at the time of the invention to modify the foldable device of Eom/Jin to incorporate the smart sensor units and rotation matrix mathematics taught by Wolf. The motivation to do so would be to reduce central processing bandwidth/power, reducing the continuous computational burden and data-routing overhead on the central processor. To improve the accuracy of the joint angle calculation, a POSITA would be motivated to apply Wolf’s known mathematical rotation matrix techniques to Eom’s central processor to rotate and realign the second component’s coordinate frame with the first component’s coordinate frame, ensuring an accurate calculation of the final folding angle. This combination represents the application of a known technique (Wolf’s local smart-sensor architecture and rotation matrix mathematics) to a known device (Eom’s/Jin’s foldable dual-sensor device) ready for improvement to yield predictable results (KSR). That would allow the combined elements to perform their standard, known functions to yield a more efficient and accurate angle-detecting device.
Regarding dependent claim 9, Eom, teaches:
The method of claim 8, further comprising ([Abstract]):
determining, by the third processor (Figs. 1 & 4A; [0030] & [0085]-[0090]), an orientation change of the second component due to an angle rotation with respect to an axis in Earth's reference frame based on the angle between the first component and the second component ([0085]-[0091], [0114] & [0120]-[0121]); and
realigning, by the third processor, the second orientation with the first orientation based on the orientation change and the first orientation ([0085]-[0091], [0102], [0139]-[0140], [0144]-[0145], [0148], [0152] & [0155]).
Regarding dependent claim 10, Eom, teaches:
The method of claim 8, further comprising ([Abstract]):
determining, by the third processor, the angle between the first component and the second component based on measurements generated by at least one (Figs. 1, 2A, & 4A; [0008], [0030]-[0031], [0070]-[0071], [0085]-[0090], [0095], [0102] & [0121]) accelerometer ([0070]-[0071], [0085]-[0087], [0103] & [0121]: first and second motion sensor modules 240/250 contain an acceleration sensor (accelerometer) and an angular velocity sensor (gyro sensor)), gyroscope ([0070]-[0071], [0085]-[0087], [0103] & [0121]), magnetometer, or hall sensor ([0008], [0070]-[0071], [0091]-[0093] & [0103]-[0104]: magnetic sensor module 252 detects a magnetic force, the motion sensor can include a geomagnetic sensor (magnetometer) and uses a magnetic force sensor and a magnetic body to determine the angle, the magnetic force sensor module detecting a magnet corresponds to a Hall sensor and detects a magnetic force to estimate the angle).
Regarding dependent claim 12, Eom, teaches:
The method of claim 8, further comprising ([Abstract]):
updating, by the third processor (Figs. 1, 2A, & 4A; [0008], [0030]-[0031], & [0085]-[0090], [0095], [0114], [0121] & [0153]-[0155]), the angle between the first component and the second component ([0087]: teaches tracking changed (updated) angular data from the sensors to continuously calculate/detect the folding angle between the first and second housing structures) based on measurements by the first accelerometer, the first gyroscope, the second accelerometer, and the second gyroscope ([0008], [0070]-[0071], [0085]-[0093], [0095], [0114], [0121], & [0153]-[0155]: teaches using sensing data (acceleration and angular velocity) from both the first and second motion sensor modules to determine the angle).
Regarding independent claim 16, Eom, teaches:
A device, comprising ([Abstract] & [0008]):
a first sensor unit ([0008], [0057], [0070]-[0071] & [0082]-[0085]: first motion sensor module 240/340 interpreted as first sensor unit);
a first housing including the first sensor unit ([0057 & [0070]-[0071]: teaches the first housing and the first sensor unit (motion sensor module)),
a second sensor unit ([0008], [0056], [0070]-[0071] & [0082]-[0085]: second motion sensor module 250/350 interpreted as second sensor unit);
a second housing coupled to the first housing, the first and second housings configured to rotate with respect to a hinge axis (Fig. 2A; [0008], [0030], [0055]-[0060] & [0070]-[0071]: second housing structure 220 interpreted as second component coupled to the first housing 210, hinge structure connects housings),
a processor configured to determine an angle between the first housing and the second housing (Figs. 1, 2A, & 4A; [0008], [0030]-[0031], [0085]-[0091], [0095], [0102] & [0114]: overall main processor 120/410 coupled to the first and second motion sensor modules), and
Eom, in combination with Jin, are silent in regard to:
the first sensor unit configured to determine a first orientation of the first housing based on measurements generated by the first sensor unit;
the second housing including the second sensor unit, the second sensor unit configured to determine a second orientation of the second housing based on measurements generated by the second sensor unit; and
rotate the second orientation of the second component such that the second orientation of the second component is realigned with the first orientation of the first component based on the first orientation of the first component and the angle between the first housing and the second housing.
However, Eom, in combination with Wolf, further teach:
the first sensor unit configured to determine a first orientation of the first housing based on measurements generated by the first sensor unit (Disclosed in combination: Eom: Figs. 1, 2A, & 4A; [0008], [0030], [0055]-[0060], [0070]-[0071] & [0082]-[0089]: first housing structure 210 interpreted as first component, first motion sensor module 240/340 (first sensor) disposed in the first housing structure 210, sensor module is a combination of at least two an acceleration sensor, an angular velocity sensor (gyro sensor) or a geomagnetic sensor, the overall main processor 120/410; Wolf: [0065]-[0067]:uses a smart sensor unit MSMPU capable of determining its own local orientation (motion integration) based on its own generated measurements);
the second housing including the second sensor unit, the second sensor unit configured to determine a second orientation of the second housing based on measurements generated by the second sensor unit (Disclosed in combination: Eom: Figs: 1, 2A, & 4A; [0030], [0055]-[0060], [0070]-[0071], [0083]-[0089] & [0103]: second motion sensor module 250/350 (accelerometer & gyroscope) in second housing structure 220 detects pose/orientation; Wolf: [0054]-[0055]: combining Eom’s physical layout with Wolf’s smart sensor units); and
It would have been obvious to one of ordinary skill in the art at the time of the invention to modify the foldable device of Eom to incorporate the smart sensor units (MSMPUs) and coordinate rotation matrix mathematics taught by Wolf. The motivation to do so would be to reduce central processing bandwidth/power, reducing the continuous computational burden and data-routing overhead on the central processor and kinematic accuracy. To improve the accuracy of the joint angle calculation, a POSITA would be motivated to apply Wolf’s known mathematical rotation matrix techniques to Eom’s central processor to rotate and realign the second component’s coordinate frame with the first component’s coordinate frame, ensuring an accurate calculation of the final folding angle. This combination represents the substitution of a known element (a standard IMU) for another known element ( a smart IMU with local processing), and the application of a known mathematical technique (coordinate rotation) to a known device ready for improvement to yield predictable results (KSR). That would allow the combined elements to perform their standard, known functions to yield a more efficient and accurate angle-detecting device.
However, Wolf, further teaches:
rotate the second orientation of the second component such that the second orientation of the second component is realigned with the first orientation of the first component based on the first orientation of the first component and the angle between the first housing and the second housing (Fig. 9; [0007], [0011] & [0069]: teaches the mathematical processor step of utilizing a rotation matrix to rotate the second orientation back to the original/reference measurement frame, aligning the coordinate systems across the joint).
It would have been obvious to one of ordinary skill in the art at the time of the invention to modify the angle-detecting device of Eom to incorporate the smart sensor units and rotation matrix mathematics taught by Wolf. The motivation to do so would be to optimize distributed processing and power efficiency, and to accurately resolve the shifting coordinate frames. A POSITA would recognize that Wolf’s kinematic rotation matrix techniques must be applied by the processors to precisely rotate and realign the second component’s coordinate frame with the first component’s coordinate frame, allowing the system to accurately estimate the final joint angle. This combination represents the application of a known technique (Wolf’s local smart-sensor architecture and kinematic rotation mathematics) to a known device (Eom’s foldable dual-sensor device) ready for improvement to yield predictable results (KSR). That would allow the combined elements to perform their standard, known functions to yield a more efficient and mathematically accurate angle-detecting device.
Regarding dependent claim 17, Eom, teaches:
The device of claim 16 ([Abstract], [0071], [0083] & [0102]) wherein the processor is configured to (Figs. 1 & 4A; [0030], [0085]-[0090] & [0102]):
determine an orientation change of the second housing due to an angle rotation with respect to an axis in Earth's reference frame based on the angle between the first housing and the second housing ([0085]-[0091], [0114] & [0120]-[0121]); and
realign the second orientation with the first orientation based on the orientation change and the first orientation ([0085]-[0091], [0102], [0139]-[0140], [0144]-[0145], [0148], [0152] & [0155]).
Regarding dependent claim 19, Eom, teaches:
The device of claim 16 ([Abstract], [0056]-[0057], [0071], [0075], [0082]-[0083] & [0102]) wherein the processor is configured (Figs. 1 & 4A; [0030], [0085]-[0090] & [0102]) to determine the angle between the first housing and the second housing based on measurements generated by at least one (Figs. 1, 2A, & 4A; [0008], [0030]-[0031], [0070]-[0071], [0085]-[0090], [0095], [0102] & [0121]) accelerometer ([0070]-[0071], [0085]-[0087], [0103] & [0121]) gyroscope ([0070]-[0071], [0085]-[0087], [0103] & [0121]), magnetometer, or hall sensor [0008], [0070]-[0071], [0091]-[0093] & [0103]-[0104]).
Regarding dependent claim 20, Eom, teaches:
The device of claim 16 ([Abstract], [0029]-[0030], [0056]-[0057], [0071], [0075], [0082]-[0085] & [0102]) wherein the processor is configured to (Figs. 1 & 4A; [0008], [0030]-[0031], [0085]-[0090] & [0102]):
estimate the angle between the first housing and the second housing based on the first orientation and the second orientation ([0008], [0082]-[0090], [0092]-[0093], [0095], [0102], [0114], [0121] & [0134]); and
update the angle between the first housing and the second housing based on measurements by the first sensor unit and measurements by the second sensor unit ([0008], [0070]-[0071], [0085]-[0093], [0095]-[0100], [0112], [0114], [0116]-[0117], [0121], [0128]-[0135] & [0153]-[0155]).
Claims 4, 11, 14, & 18 are rejected under 35 U.S.C. 103 as being unpatentable over Eom et al., in view of Liu (CN 109756630 A, Pub. Date May 14, 2019, hereinafter, Liu), in view of Jin, in view of Wolf, and further in view of DiFonzo (US 2017/0083071 A1, Pub. Date Mar. 23, 2017, hereinafter, DiFonzo).
Regarding dependent claim 4, Eom, teaches:
The device of claim 1 ([Abstract], [0008], [0030]-[0031], [0081], [0085]-[0090])
Eom, in combination with Liu, are silent in regard to:
wherein the third processor is configured to:
However, Jin, further teaches:
wherein the third processor is configured to ([0108]-[0109]):
It would have been obvious to one of ordinary skill in the art at the time of the invention to modify the foldable electronic device of Eom to incorporate the distributed, multi-processor architecture taught by Jin. A POSITA would have been motivated to apply Jin’s distributed processor/sensor hub architecture to Eom’s angle-detecting device to reduce power consumption and decrease the continuous computational burden on the main application processor. By offloading the constant polling and baseline calculations of the IMU sensors to dedicated, localized processors (sensor hubs) as taught by Jin, Eom’s device could continuously monitor its folding state in a low-power background mode without draining the battery by keeping the main processor awake, according to known methods, and yielding predictable results (KSR).
Eom, in combination with Jin, and Wolf, are silent in regard to:
detect a screen off event in which the device is set to a low-powered or off state,
However, Liu, in combination with DiFonzo, further teach:
detect a screen off event in which the device is set to a low-powered or off state (Disclosed in combination: Liu: [Pg. 2, Claim 1], [0007], [0011], [0052]-[0053],[0084], & [0099]-[0106]: teaches detecting events (e.g., no face in image, user input to stop a call) that trigger the processor to control a screen to an off or low-power state (lowering brightness), which directly corresponds to detecting a “screen off event” (extinguished event) that sets the device to a “low-powered or off state” DiFonzo: [0050] & [Claim 19]: teaches setting the device to a low-powered “sleep mode” when the device is closed),
It would have been obvious to one of ordinary skill in the art at the time of the invention to combine the low-power and screen-off management teachings of Jin and Liu with the closed-state sleep mode calibration trigger of DiFonzo. Jin teaches a distributed processor architecture where a first processor (sensor hub) operates in a low-power state while monitoring device arrangement. DiFonzo teaches that when a device is physically closed, the system should enter a low-power “sleep mode,” and that the fully closed state should be used to take a baseline reading to calibrate the rotational sensors. A POSITA would recognize that when a foldable device is physically closed, the screens are obscured and no longer needed, making it the optimal time to trigger Liu’s screen-off/extinguished state to save power. Furthermore, a POSITA would be motivated to apply DiFonzo’s teaching to this sequence by using this specific transition into the screen-off/low-power state as the trigger to record a baseline sensor calibration. Combining these teachings allows the device to calibrate its sensors during known periods of inactivity, improving sensor accuracy without interrupting the user’s active operation of the device, according to known methods. This is the application of known techniques (power state management and baseline sensor polling) to yield predictable results (KSR), a power-efficient foldable device with self-calibrating sensors.
Eom, in combination with Liu, and Jin, are silent in regard to:
the second orientation being rotated in response to the screen off event being detected.
However, Wolf, in combination with DiFonzo, further teach:
the second orientation being rotated in response to the screen off event being detected (Disclosed in combination: Wolf: [0069]: provides the mathematical mechanism for how an IMU is calibrated: by computing a rotation matrix and rotating the orientation back to the measurement; DiFonzo: [0038]: provides a trigger logic: performing sensor calibration (zeroing or baseline recording) in response to the device entering the fully closed/sleep mode state).
It would have been obvious to one of ordinary skill in the art at the time of the invention to apply the specific mathematical coordinate rotation steps taught by Wolf to execute the closed-state baseline calibration triggered in DiFonzo. DiFonzo teaches that the 0-degree (fully closed) sleep state, is the mechanically locked environment needed to calibrate hinged sensors. A POSITA would inherently need a mathematical method to reset the accumulated drift of the IMU gyroscopes and accelerometers, therefore would be highly motivated to program the device’s processor to execute Wolf’s orientation rotation algorithms when DiFonzo’s screen-off/sleep event is detected. This combination represents the substitution of one known element for another, or the application of a known mathematical technique to a known method. Wolf’s orientation rotation matrix is a standard, effective mathematical tool for realigning inertial sensors. Applying Wolf’s mathematical steps to DiFonzo’s baseline calibration requirements yields the predictable results (KSR) of an accurate sensor system that realigns its second orientation reference frame with its first orientation reference frame every time the user closes the device and the screen turns off.
Regarding dependent claim 11, Eom, teaches:
The method of claim 8, further comprising ([Abstract], [0008], [0030]-[0031], [0081], & [0086]-[0090]):
Eom, in combination with Jin, and Wolf, are silent in regard to:
detect a screen off event in which the device is set to a low-powered or off state,
However, Liu, in combination with DiFonzo, further teach:
detect a screen off event in which the device is set to a low-powered or off state (Disclosed in combination: Liu: [Pg. 2, Claim 1], [0007], [0011], [0052]-[0053], [0084] & [0099]-[0106]: teaches detecting events (e.g., no face in image, user input to stop a call) that trigger the processor to control a screen to an off or low-power state (lowering brightness), which directly corresponds to detecting a “screen off event” (extinguished event) that sets the device to a “low-powered or off state” DiFonzo: [0050] & [Claim 19]: teaches setting the device to a low-powered “sleep mode” when the device is closed),
It would have been obvious to one of ordinary skill in the art at the time of the invention to combine the low-power and screen-off management teachings of Jin and Liu with the closed-state sleep mode calibration trigger of DiFonzo. Jin teaches a distributed processor architecture where a first processor (sensor hub) operates in a low-power state while monitoring device arrangement. DiFonzo teaches that when a device is physically closed, the system should enter a low-power “sleep mode,” and that the fully closed state should be used to take a baseline reading to calibrate the rotational sensors. A POSITA would recognize that when a foldable device is physically closed, the screens are obscured and no longer needed, making it the optimal time to trigger Liu’s screen-off/extinguished state to save power. Furthermore, a POSITA would be motivated to apply DiFonzo’s teaching to this sequence by using this specific transition into the screen-off/low-power state as the trigger to record a baseline sensor calibration. Combining these teachings allows the device to calibrate its sensors during known periods of inactivity, improving sensor accuracy without interrupting the user’s active operation of the device, according to known methods. This is the application of known techniques (power state management and baseline sensor polling) to yield predictable results (KSR), a power-efficient foldable device with self-calibrating sensors.
Eom, in combination with Liu, and Jin, are silent in regard to:
the second orientation being rotated in response to the screen off event being detected.
However, Wolf, in combination with DiFonzo, further teach:
the second orientation being rotated in response to the screen off event being detected (Disclosed in combination: Wolf: [0069]: provides the mathematical mechanism for how an IMU is calibrated: by computing a rotation matrix and rotating the orientation back to the measurement; DiFonzo: [0038]: provides a trigger logic: performing sensor calibration (zeroing or baseline recording) in response to the device entering the fully closed/sleep mode state).
It would have been obvious to one of ordinary skill in the art at the time of the invention to apply the specific mathematical coordinate rotation steps taught by Wolf to execute the closed-state baseline calibration triggered in DiFonzo. DiFonzo teaches that the 0-degree (fully closed) sleep state, is the mechanically locked environment needed to calibrate hinged sensors. A POSITA would inherently need a mathematical method to reset the accumulated drift of the IMU gyroscopes and accelerometers, therefore would be highly motivated to program the device’s processor to execute Wolf’s orientation rotation algorithms when DiFonzo’s screen-off/sleep event is detected. This combination represents the substitution of one known element for another, or the application of a known mathematical technique to a known method. Wolf’s orientation rotation matrix is a standard, effective mathematical tool for realigning inertial sensors. Applying Wolf’s mathematical steps to DiFonzo’s baseline calibration requirements yields the predictable results (KSR) of an accurate sensor system that realigns its second orientation reference frame with its first orientation reference frame every time the user closes the device and the screen turns off.
Regarding dependent claim 14, Eom, teaches:
The method of claim 8, further comprising ([Abstract]):
setting the device to a sleep state in which the third processor is set to a low-powered or off state ([0029]-[0031] & [0153]-[0155]), the first orientation and the second orientation being determined ([0008], [0082]-[0093] & [Claim 1])
Eom, is silent in regard to:
detecting a screen off event in which a screen of the device is set to a low-powered or off state; and
in response to the device being set to the sleep state.
However, Liu, further teaches:
detecting a screen off event in which a screen of the device is set to a low-powered or off state ([Pg. 2, Claim 1], [0007], [0011], [0052]-[0057],[0084] & [0099]-[0106]); and
in response to the device being set to the sleep state ([Pg. 2, Claim 1], [0007], [0011], [0052]-[0057], [0084] & [0099]-[0106]).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate detecting a screen off event in which a screen of the device is set to a low-powered or off state, in response to the device being set to the awake state, of Liu to Eom, in order to attain and improve, by implementing the orientation detection of Eom while managing power consumption, motivated by Liu’s clear teaching of power management (e.g., turning off screens and cameras), to adapt to Eom’s system to operate in a sleep or low-power state, where Eom discloses all limitations related to determining the orientation of the first and second housings, and Liu discloses the limitations of detecting a screen-off event and setting the device to a sleep. low-power state, the combination would arrive at the claimed method, yielding the expected predictable results of power savings by the combination of the prior art references (KSR).
Regarding dependent claim 18, Eom, teaches:
The device of claim 16 ([Abstract], [0049], [0071], [0073], [0083], & [0102]) wherein the processor is configured to (Figs. 1 & 4A; [0029]-[0030], [0085]-[0090] & [0102]):
Eom, in combination with Jin, and Wolf, are silent in regard to:
detect a screen off event in which the device is set to a low-powered or off state,
However, Liu, in combination with DiFonzo, further teach:
detect a screen off event in which the device is set to a low-powered or off state (Disclosed in combination: Liu: [Pg. 2, Claim 1], [0007], [0011], [0052]-[0053], [0084] & [0099]-[0106]: teaches detecting events (e.g., no face in image, user input to stop a call) that trigger the processor to control a screen to an off or low-power state (lowering brightness), which directly corresponds to detecting a “screen off event” (extinguished event) that sets the device to a “low-powered or off state” DiFonzo: [0050] & [Claim 19]: teaches setting the device to a low-powered “sleep mode” when the device is closed),
It would have been obvious to one of ordinary skill in the art at the time of the invention to combine the low-power and screen-off management teachings of Jin and Liu with the closed-state sleep mode calibration trigger of DiFonzo. Jin teaches a distributed processor architecture where a first processor (sensor hub) operates in a low-power state while monitoring device arrangement. DiFonzo teaches that when a device is physically closed, the system should enter a low-power “sleep mode,” and that the fully closed state should be used to take a baseline reading to calibrate the rotational sensors. A POSITA would recognize that when a foldable device is physically closed, the screens are obscured and no longer needed, making it the optimal time to trigger Liu’s screen-off/extinguished state to save power. Furthermore, a POSITA would be motivated to apply DiFonzo’s teaching to this sequence by using this specific transition into the screen-off/low-power state as the trigger to record a baseline sensor calibration. Combining these teachings allows the device to calibrate its sensors during known periods of inactivity, improving sensor accuracy without interrupting the user’s active operation of the device, according to known methods. This is the application of known techniques (power state management and baseline sensor polling) to yield predictable results (KSR), a power-efficient foldable device with self-calibrating sensors.
Eom, in combination with Liu, and Jin, are silent in regard to:
the second orientation being rotated in response to the screen off event being detected.
However, Wolf, in combination with DiFonzo, further teach:
the second orientation being rotated in response to the screen off event being detected (Disclosed in combination: Wolf: [0069]: provides the mathematical mechanism for how an IMU is calibrated: by computing a rotation matrix and rotating the orientation back to the measurement; DiFonzo: [0038]: provides a trigger logic: performing sensor calibration (zeroing or baseline recording) in response to the device entering the fully closed/sleep mode state).
It would have been obvious to one of ordinary skill in the art at the time of the invention to apply the specific mathematical coordinate rotation steps taught by Wolf to execute the closed-state baseline calibration triggered in DiFonzo. DiFonzo teaches that the 0-degree (fully closed) sleep state, is the mechanically locked environment needed to calibrate hinged sensors. A POSITA would inherently need a mathematical method to reset the accumulated drift of the IMU gyroscopes and accelerometers, therefore would be highly motivated to program the device’s processor to execute Wolf’s orientation rotation algorithms when DiFonzo’s screen-off/sleep event is detected. This combination represents the substitution of one known element for another, or the application of a known mathematical technique to a known method. Wolf’s orientation rotation matrix is a standard, effective mathematical tool for realigning inertial sensors. Applying Wolf’s mathematical steps to DiFonzo’s baseline calibration requirements yields the predictable results (KSR) of an accurate sensor system that realigns its second orientation reference frame with its first orientation reference frame every time the user closes the device and the screen turns off.
Claims 6 & 13 are rejected under 35 U.S.C. 103 as being unpatentable over Eom, in view of Zhang et al. (US 2022/0261093 A1, Fil. Date Jul. 17, 2020, hereinafter, Zhang), in view of Jin, and further in view of Wolf.
Regarding dependent claim 6, Eom, teaches:
The device of claim 5 ([Abstract]) wherein the third processor is configured to (Figs. 1, 2A, & 4A; [0008], [0030]-[0031], [0058] & [0085]-[0090]):
convert the first orientation and the second orientation from a first format to a second format different from the first format (Figs. 4A; [0081]-[0083],[0085]-[0098], [0102]-[0103], [0105]-[0114] & [0121]: requires processor to calculate a pose (orientation) for two housing structures using raw sensor data (acceleration & angular velocity));
remap the distance to the estimated angle (Fig. 9; [0058], [0081], [0085]-[0091]-[0093], [0095] & [0114]: Step 905).
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Eom, is silent in regard to:
determine a distance between the converted first orientation and the second orientation; and
However, Zhang, further teaches:
determine a distance between the converted first orientation and the second orientation ([0174]-[0176]); and
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate determine a distance between the converted first orientation and the second orientation, of Zhang to Eom, in order to attain and improve, by taking the calculated folding angle (the “distance” or Eom’s “first angle”) and use it as the final “estimated angle” to control a device feature or calibrate a sensor, as taught by both references, where both Eom and Zhang teach a process where raw motion sensor data (first format) is processed (converted) into a calculated angle (second format) representing the spatial separation (distance) between the two foldable components, Eom describes using the corrected angle of two housings structures to determine the folding angle, Zhang calculates the included angle between the sub-screens based on measured vectors, would be considered an obvious implementation to the broader functionality taught, in order to attain the claimed elements, yielding the expected results (KSR).
Regarding dependent claim 13, Eom, teaches:
The method of claim 12, further comprising ([Abstract]):
converting, by the third processor (Figs. 1, 2A, & 4A; [0008], [0030]-[0031], [0058] & [0085]-[0090]), the first orientation and the second orientation from a first format to a second format different from the first format (Figs. 4A; [0081]-[0083],[0085]-[0098], [0102]-[0103], [0105]-[0114] & [0121]: requires processor to calculate a pose (orientation) for two housing structures using raw sensor data (acceleration & angular velocity));
remapping, by the third processor, the distance to the estimated lid angle (Fig. 9; [0058], [0081], [0085]-[0091]-[0093], [0095] & [0114]: Step 905).
Eom, is silent in regard to:
determining, by the third processor, a distance between the converted first orientation and the second orientation; and
However, Zhang, further teaches:
determining, by the third processor, a distance between the converted first orientation and the second orientation ([0174]-[0176]); and
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate determining, by the third processor, a distance between the converted first orientation and the second orientation, of Zhang to Eom, in order to attain and improve, by taking the calculated folding angel (the “distance” or Eom’s “first angle”) and use it as the final “estimated lid angle” to control a device feature or calibrate a sensor, as taught by both references, where both Eom and Zhang teach a process where raw motion sensor data (first format) is processed (converted) into a calculated angle (second format) representing the spatial separation (distance) between the two foldable components, Eom describes using the corrected angle of two housings structures to determine the folding angle, Zhang calculates the included angle between the sub-screens based on measured vectors, would be considered an obvious implementation to the broader functionality taught, in order to attain the claimed elements, yielding the expected results (KSR).
Claims 7 & 15 are rejected under 35 U.S.C. 103 as being unpatentable over Eom, in view of Kim et al. (US 12288492 B2, Fil. Date Feb. 10, 2022, hereinafter, Kim), in view of Jin, and further in view of Wolf.
Regarding dependent claim 7, Eom, teaches:
The device of claim 1 ([Abstract]) wherein the first processor determines the first orientation (Figs. 1, 2A, & 4A; [0030]-[0031], [0070]-[0071] & [0085]-[0089]: first motion sensor module 240/340 and overall main processor 120/410) and the second processor determines the second orientation (Figs. 1, 2A, & 4A; [0030]-[0031], [0070]-[0071] & [0083]-[0089]: second motion sensor module 250/350 and overall main processor 120/410)
Eom, is silent in regard to:
in a case where the device is in a sleep state, and
the third processor determines the angle in a case where the device is in an awake state.
However, Kim, further teaches:
in a case where the device is in a sleep state (Fig. 1; [Col. 11, ll. 36-49]), and
the third processor determines the angle (Fig. 1; [Col. 19, ll. 27-33 & 58-67] & [Col. 20, ll. 1-10]) in a case where the device is in an awake state (Fig. 1; [Col. 19, ll. 4-19] & [Col. 29, ll. 57-65]).
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It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate in a case where the device is in a sleep state, and the third processor determines the angle in a case where the device is in an awake state, of Kim to Eom, in order to attain and improve, by modifying the system of Eom with the power-state dependent processing architecture of Kim, and the power-saving tasks (determining instantaneous orientation) to the lower-power processor during the sleep state (as implied by Eom and reinforced by the power management of Kim), and reserve the computationally intensive task (determining the final angle) for the main processor during the awake/active state, where the design choice would be driven by power conservation in portable electronic devices, and motivation would be to offload the initial orientation processing to lower-power, dedicated modules in a sleep state for efficiency, would achieve the claimed invention and yield the expected predictable results of power efficiency by the combination of the prior art references (KSR).
Regarding dependent claim 15, Eom, teaches:
The method of claim 8, further comprising ([Abstract]):
Eom, is silent in regard to:
detecting a screen on event in which a screen of the device is set to an on state; and
setting the device to an awake state in which the third processor is set to an on state, the angle being determined in response to the device being set to the awake state.
However, Kim, further teaches:
detecting a screen on event in which a screen of the device is set to an on state ([Col. 14, ll. 18-25 & 38-50] & [Col. 28, ll. 7-22]); and
setting the device to an awake state in which the third processor is set to an on state ([Col. 13, ll. 4-26] & [Col. 14, ll. 18-25 & 38-50]), the angle being determined in response to the device being set to the awake state ([Col. 2, ll. 14-36], [Col. 15, ll. 55-67], [Col. 16, ll. 1-36 & 56-67], [Col. 17, ll. 1-11] & [Col. 25, ll. 40-53], [Col. 26, ll.8-46]).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate detecting a screen on event in which a screen of the device is set to an on state, setting the device to an awake state in which the third processor is set to an on state, and the angle being determined in response to the device being set to the awake state, of Kim to Eom, in order to attain and improve, by modifying the system of Eom with a foldable electronic device that transitions between power states while maintaining folding awareness, where Kim teaches that when a user input or event cause the “Always On Display (AOD) mode” (low-power display mode) to be turned off (2230), the device switches to a general mode (2235) where the screen is turned on and applications run, and both prior references confirm that accurately detecting the folding angle is important to the operation of a foldable device, and would be a logical and obvious step for the processor to immediately resume or accelerate its angle detection routine to accurately establish the current angle for visual reorganization (taught by Kim) that occurs, the operation being performed in response to the device being set to the active wake/state, would achieve the claimed invention and yield the expected predictable results (KSR).
Claim 21 is rejected under 35 U.S.C. 103 as being unpatentable over Eom, in view of Jin, in view of Wolf, and further in view of Luinge et al. (US 2011/0028865 A1, Pub. Date Feb. 3, 2011, hereinafter, Luinge).
Regarding dependent claim 21, Eom, teaches:
The device of claim 1 ([Abstract]) wherein the rotation of the second orientation of the second component includes ([0086]-[0087]):
Eom, in combination with, Jin, and Wolf, are silent in regard to:
a first rotation of the second orientation of the second component with respect to an axis in Earth's reference frame by an amount determined based on the angle between the first component and the second component; and
a second rotation of the second orientation of the second component by an amount determined based on the first orientation of the first component.
However, Luinge, further teaches:
a first rotation of the second orientation of the second component with respect to an axis in Earth's reference frame by an amount determined based on the angle between the first component and the second component ([0025]-[0028] & [0085]-[0088]: teaches applying rotational transformations expressed in a global/Earth reference frame. The mathematical rotation matrix of the second segment relies on the relative orientation/angle established at the connecting joint); and
a second rotation of the second orientation of the second component by an amount determined based on the first orientation of the first component ([0085]-[0088]: teaches determining the orientation of the second segment based on the known orientation of the first segment and their shared kinematic data).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to apply the mathematical kinematic coupling transformations taught by Luinge to the foldable electronic device of Eom, according to known methods. The motivation to do so would be to resolve the 3D spatial orientation and folded state of the device’s secondary housing by utilizing standard rigid-body kinematic algorithms that reference a global coordinate system (Earth’s gravity/magnetic frame) and the known spatial orientation of the primary housing. Utilizing a sequence of coordinate frame rotations (e.g., rotation matrices or quaternions) to track bodies is a standard, predictable engineering practice for multi-sensor devices, that would yield predictable results (KSR).
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure. Cui et al. (US2022/0350373A1) discloses hinge angle detection.
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). 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.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to HUGO NAVARRO whose telephone number is (571)272-6122. The examiner can normally be reached Monday-Friday 07:30-5:00 pm MST.
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/HUGO NAVARRO/ Examiner, Art Unit 2858 March 31, 2026
/EMAN A ALKAFAWI/ Supervisory Patent Examiner, Art Unit 2858 4/2/2026
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