DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Claim Rejections - 35 USC § 102
The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention.
Claim(s) 1-15 is/are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Zhang et al. (US 2019/0158340 A1), hereinafter referred to as D1.
Regarding claims 1, 13, and 15, D1 discloses an apparatus, system, and method for fall-down detection based on a wireless signal, which comprises:
acquire multipath channel state property information based on a wireless signal received from an access point (AP) communicating with the electronic device (Referring to Figure 2, a system, apparatus and/or method for determining at least one characteristics and/or spatial-temporal information of an object associated with a movement of the object (e.g. current movement, and/or prior movement) comprises obtaining one or more time series of channel information (CI) of a wireless multipath channel (e.g. wireless multipath channel) using a processor (acquire multipath channel state property information), a memory communicatively coupled with the processor and a set of instructions stored in the memory. The at least one time series of channel information is obtained from a wireless signal sent through the wireless multipath channel. The wireless multipath channel is impacted by the movement of the object. The system, apparats and/or method further comprises determining the one or more characteristics and/or spatial-temporal information of the object associated with the movement of the object based on the one or more time series of channel information. See paragraph 0399. Comprising communication devices such as access points and wireless devices. See paragraph 0143.);
calculate signal similarity for each predetermined section of the multipath channel state property information based on the multipath channel state property information (Referring to Figure 2, the transient motion monitor is further configured for: determining a sliding time window having a duration comparable to the transient motion of the object; and computing an intermediate quantity (IQ) based on CI of the time series in the sliding time window, wherein the transient motion of the object is monitored based on the IQ. The IQ can also be intermediate values used to compute speed. For example, CSI may be a vector of CFR (channel frequency response). The IQ may be: magnitude or magnitude square of each CFR component of CSI, autocorrelation function (ACF) of magnitude square of a CFR component of CSI, first local maximum of the ACF, time offset corresponding to first local maximum of the ACF (calculate signal similarity for each predetermined section of multipath channel state property information based on the multipath channel state property information). See paragraphs 0376 and 0377.); and
determine, based on a pattern of the signal similarity for each predetermined section, whether motion detection based on the multipath channel state property information is available (Referring to Figure 2, the object is a person. The transient motion represents a fall-down action of the person (determine, based on a pattern of the signal similarity for each predetermined section, per the auto-correlation functions and factors as described in paragraphs 0376-0378, motion detection based on the multipath channel state property information is available based on a determination of whether a pattern of signal similarity for each predetermined section of the multipath channel state property information determined based on the multipath channel state property information is caused by motion of a user, per the auto-correlation function to analyze to data to determine a fall-down action). The transient motion monitor is coupled to at least one of: the transmitter, the receiver, an additional transmitter, an additional receiver, a cloud server, a fog server, a local server, and an edge server. See paragraph 0374.)
Regarding claims 2 and 14, D1 discloses wherein the processor is configured to execute the at least one executable instruction to, in response to it being determined that the pattern of the signal similarity for each predetermined section is not caused by motion of a user, determine that the motion detection based on the multipath channel state property information is unavailable (Referring to Figures 2-4, the system detects a fall-down by analyzing the speed, e.g. by computing two quantities: (1) maximum change of acceleration in 0.5 s window, and (2) maximum speed in the 0.5 s window. A threshold can be put on each of the two quantities. If both are larger than their corresponding thresholds, the system determines that the fall-down is detected. Otherwise a fall is not detected based on patterns of the signal similarity for each predetermined section; thereby, determining that the motion detection on the multipath channel state property information is unavailable (fall was not detected). See paragraphs 0384-0386.)
Regarding claim 3, D1 discloses wherein the processor is configured to execute the at least one executable instruction to determine whether the motion detection is available based on a difference between a length of one of sections that remain greater than or equal to a threshold predetermined in the signal similarity for each predetermined section and an average length of the sections (Referring to Figures 2-4, the system detects a fall-down by analyzing the speed, e.g. by computing two quantities: (1) maximum change of acceleration in 0.5 s window, and (2) maximum speed in the 0.5 s window. A threshold can be put on each of the two quantities (interpreted as the a difference between a length of one of sections that remain greater than or equal to a threshold in each section and an average length of the sections). If both are larger than their corresponding thresholds, the system determines that the fall-down is detected. See paragraphs 0384-0386.)
Regarding claim 4, D1 discloses wherein the processor is configured to execute the at least one executable instruction to, in response to a value based on the difference between the length of one of the sections that remain greater than or equal to the threshold predetermined in the signal similarity for each predetermined section being less than a second threshold, determine that the motion detection based on the multipath channel state property information is unavailable (Referring to Figures 2-4, the system detects a fall-down by analyzing the speed, e.g. by computing two quantities: (1) maximum change of acceleration in 0.5 s window, and (2) maximum speed in the 0.5 s window (interpreted as the a difference between a length of one of sections that remain greater than or equal to a threshold in each section being less than a second threshold, determine that the motion detection based on the multipath channel state property information is unavailable as the acceleration below a threshold value is indicative of not a fall-down). A threshold can be put on each of the two quantities. If both are larger than their corresponding thresholds, the system determines that the fall-down is detected. See paragraphs 0384-0386.)
Regarding claim 5, D1 discloses wherein the processor is configured to execute the at least one executable instruction to determine whether the motion detection is available based on similarity between patterns of sections that remain greater than or equal to a threshold predetermined in the signal similarity for each predetermined section (Referring to Figures 2-4, the system detects a fall-down by analyzing the speed, e.g. by computing two quantities: (1) maximum change of acceleration in 0.5 s window, and (2) maximum speed in the 0.5 s window (interpreted as similarity between patterns of sections that remain greater than or equal to a threshold predetermined in the signal similarly for each predetermined section). A threshold can be put on each of the two quantities. If both are larger than their corresponding thresholds, the system determines that the fall-down is detected. See paragraphs 0384-0386.)
Regarding claim 6, D1 discloses wherein the processor is configured to execute the at least one executable instruction to determine whether the motion detection is available based on whether a length of one of sections that remain greater than or equal to a threshold predetermined in the signal similarity for each predetermined section is less than a third threshold (Referring to Figures 2-4, the system detects a fall-down by analyzing the speed, e.g. by computing two quantities: (1) maximum change of acceleration in 0.5 s window, and (2) maximum speed in the 0.5 s window. A threshold can be put on each of the two quantities. If both are larger than their corresponding thresholds, the system determines that the fall-down is detected. See paragraphs 0384-0386. Computing, based on the nonlinear mapping, a matching score between the first IQ in the first analysis time window and the second IQ in the second analysis time window; monitoring the transient motion of the object based on the matching score; and detecting the transient motion of the object when the matching score is less than or equal to a threshold. See paragraphs 0391-0392.)
Regarding claim 7, D1 discloses wherein the third threshold is determined based on a minimum length of a section in which the signal similarity for each predetermined section remains greater than or equal to the threshold due to motion of a user (Referring to Figures 2-4, the system detects a fall-down by analyzing the speed, e.g. by computing two quantities: (1) maximum change of acceleration in 0.5 s window, and (2) maximum speed in the 0.5 s window. A threshold can be put on each of the two quantities. If both are larger than their corresponding thresholds, the system determines that the fall-down is detected. See paragraphs 0384-0386. Computing, based on the nonlinear mapping, a matching score between the first IQ in the first analysis time window and the second IQ in the second analysis time window; monitoring the transient motion of the object based on the matching score; and detecting the transient motion of the object (motion of a user) when the matching score is less than or equal to a threshold. See paragraphs 0391-0392.)
Regarding claim 8, D1 discloses wherein the third threshold is determined based on a window length for calculating the signal similarity for each predetermined section, a minimum duration of motion of a user that influences the signal similarity for each predetermined section, and a minimum detection time required to detect motion of a user through the signal similarity for each predetermined section (Referring to Figures 2-4, the system detects a fall-down by analyzing the speed, e.g. by computing two quantities: (1) maximum change of acceleration in 0.5 s window, and (2) maximum speed in the 0.5 s window. A threshold can be put on each of the two quantities. If both are larger than their corresponding thresholds, the system determines that the fall-down is detected. See paragraphs 0384-0386. Computing, based on the nonlinear mapping, a matching score between the first IQ in the first analysis time window and the second IQ in the second analysis time window; monitoring the transient motion of the object based on the matching score; and detecting the transient motion of the object (motion of a user) when the matching score is less than or equal to a threshold. See paragraphs 0391-0392.)
Regarding claim 9, D1 discloses wherein the processor is configured to execute the at least one executable instruction to determine whether the motion detection is available based on whether a length of a section that remains greater than or equal to a fourth threshold predetermined in the signal similarity for each predetermined section is greater than or equal to a fifth threshold (Referring to Figures 2-4, the system detects a fall-down by analyzing the speed, e.g. by computing two quantities: (1) maximum change of acceleration in 0.5 s window, and (2) maximum speed in the 0.5 s window. A threshold can be put on each of the two quantities. If both are larger than their corresponding thresholds, the system determines that the fall-down is detected (interpreted as fourth and fifth thresholds). See paragraphs 0384-0386.)
Regarding claim 10, D1 discloses wherein the processor is configured to execute the at least one executable instruction to determine whether the motion detection is available based on whether an interval at which the multipath channel state property information is received from the AP is greater than or equal to a threshold interval (Referring to Figures 2-4, the system detects a fall-down by analyzing the speed, e.g. by computing two quantities: (1) maximum change of acceleration in 0.5 s window, and (2) maximum speed in the 0.5 s window. A threshold can be put on each of the two quantities. If both are larger than their corresponding thresholds, the system determines that the fall-down is detected. See paragraphs 0384-0386. According to access points as cited above in the parent claim.)
Regarding claim 11, D1 discloses wherein the processor is configured to execute the at least one executable instruction to, in response to it being determined that motion detection based on the multipath channel state property information is unavailable, suspend motion detection based on the multipath channel state property information received from the AP (Referring to Figures 2-4, the system detects a fall-down by analyzing the speed, e.g. by computing two quantities: (1) maximum change of acceleration in 0.5 s window, and (2) maximum speed in the 0.5 s window. A threshold can be put on each of the two quantities. If both are larger than their corresponding thresholds, the system determines that the fall-down is detected. Otherwise a fall-down is not detected (unavailable/suspend motion detection). See paragraphs 0384-0386. According to access points as cited above in the parent claim.)
Regarding claim 12, D1 discloses wherein the electronic device is one of a mobile phone, a smartphone, a personal digital assistant (PDA), a netbook, a tablet computer, a laptop computer, a mobile device, a smartwatch, a smart band, smart glasses, a wearable device, a desktop, a computing device, a television, a set-top box, a refrigerator, an appliance, a door lock, or a security device (Referring to Figure 2, Hardware modules may be constructed to contain either the Type 1 transceiver and the Type 2 transceiver. The hardware modules may be sold to/used by variable brands to design, build and sell final commercial products. Products using the disclosed system and/or method may be home/office security products, motion monitoring products, WiFi products, mesh products, TV, STB, entertainment system, HiFi, speaker, home appliance, lamps, stoves, oven, microwave oven, table, chair, bed, shelves, tools, utensils, torches, vacuum cleaner, smoke detector, sofa, piano, fan, door, window, door/window handle, locks, smoke detectors, car accessories, computing devices, office devices, air conditioner, heater, pipes, connectors, surveillance camera, access point, computing devices, mobile devices, LTE devices, 3G/4G/5G/6G devices, gaming devices, eyeglasses, glass panels, VR goggles, necklace, watch, waist band, belt, wallet, pen, hat, wearables, implantable device, tags, parking tickets, smart phones, etc. See paragraphs 0142-144.)
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Tang et al. (US 2024/0171941 A1) - the second track is used to represent a moving track of a Bluetooth positioning device; calculating a similarity between the first track and the second track in a preset time period; and determining that the first electronic device is tracked by the Bluetooth positioning device if the track similarity is greater than a preset similarity threshold.
Lee et al. (US 2018/0227714 A1) - adjusting the adaptive noise immunity threshold from a first level to a second level prior to the comparing of the received wireless signal to the noise immunity threshold, where the second level is higher than the first level.
Ozturk et al. (US 2023/0273291 A1) - performing a classification of a sliding time window by analyzing channel information (CI) of the TSCI in the sliding time window; computing a motion information (MI) for the sliding time window based on the TSCI and the classification of the sliding time window; and monitoring the motion of the object based on the MI.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to DONALD L MILLS whose telephone number is (571)272-3094. The examiner can normally be reached Monday through Friday from 9-5 PM EST.
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DONALD L. MILLS
Primary Examiner
Art Unit 2462
/Donald L Mills/Primary Examiner, Art Unit 2462
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