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 .
Summary
Claims 1-20 are pending. Claims 1-20 are rejected herein. This is a First Action on the Merits.
Claim Objections
Claim(s) 2, 8, 15, 17, and 19 is/are objected to because of the following informalities. Appropriate correction is required.
Regarding claims 2 and 8: Claim 2 recites “a fall alert mitigation manager.” Claim 8 recites “the alert mitigation manager.” It is assumed that these are the same limitation. The same terminology should be used throughout the claims.
Regarding claim 8: There is no antecedent basis for “the validation rule.”
Regarding claim 15: Change “over during the filter time constant” to --during the filter time constant--.
Regarding claim 17: Change “radar based” to --radar-based--.
Regarding claim 19: Change “increasing the confidence level (CL) is increased to 2” to --increase the confidence level to 2--.
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(s) 2-11 and 16-20 is/are 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 applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention.
Regarding claim 2: The scope of this claim is impossible to determine because it presents arbitrary nomenclature for the purpose of the invention. Claim 2 recites “analyzing additional mitigation features.” What are the original mitigation features to which are now added “additional” ones. What is a mitigation feature? It is not defined nor is it given any special definition in the spec. The claim states that these “additional mitigation features” are “selected to distinguish real falls from other fall-like detections? How is this done? What is the data? How is it analyzed? Since the present application and all of the references cited in this office action are radar systems used to process radar data and detect falls, then inherently any system that does this will process data which has many different “features” to distinguish real falls from fall-like detections.
Regarding claims 3 and 9: As in claim 2, the terms in claim 3 are undefined and can mean many things in the context of a radar fall detector. A “telemetric system” is any system that performs measurement at a distance. Therefore all radar is a “telemetric system.” “Sensitivity map” is undefined in the claims and given no special definition in the specification. All radar data can be considered a “sensitivity map” because the system constantly measures reflected signals and those signals all have a strength. Therefore a 2-D or 3-D map of the radar’s field of view with all signals plotted according to strength would be a “sensitivity map.” If this is what is meant by sensitivity map in the present claim then the claim should be canceled because it amounts to saying “…is configured to receive radar data and use radar data” which is inherent in the fact that it is a radar unit as defined in claim 1.
Regarding claim 4: It is impossible to determine the scope of claim 4 because all it does is assign an arbitrary confidence level to an indefinite process (see 112 rejection of claim 3 above).
Regarding claims 6, 18, and 20: It is impossible to determine the scope of these claims because they are based on arbitrarily defined variables used in calculation. It is not enough to list variables such as low energy index, high energy index, dynamic consistence index, etc. How these variables are calculated must be defined in the claims so that the scope of the claims is clear. Using dynamic consistency index as an example: what is it a measure of? Consistency can mean many different things. Measurements are being taken in a dynamic environment. There is no way to determine from the language of the claims what these terms mean. Claim 20 contains the terms low energy index, low energy threshold
Regarding claims 8, 19, and 20: The terms in this “rule” are not sufficiently defined. There is no definition as to what “frame” means. It is a time frame? Is it the two-dimensional extent which the radar can “see.” Is it one capture of data in a time sequence? All of these can be a “frame.” There is no antecedent basis for “confidence rating.” It is not defined and therefore it is completely indefinite as to what it means for this undefined quantity to be increased to 2. This reasoning applies to claim 19 as well.
Regarding claim 17: It is impossible to determine the scope of “verifying the fall event.” Processing radar data to make a determination as whether a human being in the radar’s field of view has fallen is a complicated calculational process with many different steps. The present application and the prior art presented below use machine learning techniques for this complex calculation. Such calculations work by probabilities and the algorithms get better over time as more data is collected and the model is further trained. Any latter step in such a complicated calculation could be considered “verifying” therefore there is no way to determine the scope of this language as used in claim 17.
Regarding claims 3-11 and 16-19: These claims are rejected as indefinite for depending from an indefinite claim.
Claim Rejections - 35 USC § 102
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of 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.
(a)(2) the claimed invention was described in a patent issued under section 151, or in an application for patent published or deemed published under section 122(b), in which the patent or application, as the case may be, names another inventor and was effectively filed before the effective filing date of the claimed invention.
Claim(s) 17 is/are rejected under 35 U.S.C. 102(a1 and a2) as being anticipated by ZACK et al. (US 2016/0377705).
Regarding claim 17: ZACK discloses: A method for generating fall alerts by a radar based target monitoring and alert system comprising at least one transmitter antenna (Tx antennas in FIG. 1B) configured to transmit electromagnetic waves into a monitored region, at least one receiver antenna (Rx antennas in FIG. 1B) configured to generate raw data from electromagnetic waves reflected by objects within the monitored region (para. 59), and a processor unit (250, 260), the method comprising: collecting frame data from the radar (para. 59; All radar can be considered “frame data”); analyzing the frame data (para. 59); detecting a fall event in at least one frame of the frame data (para. 55, 59, 66); verifying the fall event (“most probable fit” in para. 59); and generating fall alert only if the fall event is verified (“most probable fit” and alerting caregiver in para. 59).
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
Claim(s) 1-14 is/are rejected under 35 U.S.C. 103 as being unpatentable over ZACK et al. (US 2016/0377705) in view of LAGACE et al. (US 2021/0321222).
Regarding claim 1: ZACK discloses: A target monitoring and alert system (FIG. 1B) comprising a radar unit (115), a processor unit (250, 260) and a communication module (150), the radar unit including at least one transmitter antenna (Tx antennas) connected to an oscillator (221) and configured to transmit electromagnetic waves into a monitored region (para. 7-8), and at least one receiver antenna (Rx antennas) configured to receive electromagnetic waves reflected by objects within the monitored region and operable to generate raw data (para. 59); the processor unit including a moving body isolation processor (“extract from the filtered echo signals, a quantified representation of position postures, movements, motions and breathing” in para. 59), and the communication module configured and operable to communicate alerts to third parties (para. 66); wherein: the processor unit further comprises: a tracker module configured to receive data from the radar unit and further configured to process the data received from the radar unit to identify moving targets and to track the location of the moving targets over time thereby generating target data (para. 59); and an alert-threshold generator operable to generate an alert-threshold (inherent in the setting of alarm conditions in order to contact third parties as discussed in para. 59, 66); machine learning configured to receive from the tracker module target data inputs selected from height profiles, signal-to-noise ratio and radial distance to object and operable to generate a fall likelihood score (Machine learning is discussed in para. 56. Uniquely determining posture, location, motion and emergency situations such as a fall will include probability calculations.); and a fall identification module configured to receive the fall likelihood score from the machine learning and to detect a fall event if the likelihood score is above an alert-threshold value (para. 56, 59, 66).
While ZACK mentions both machine learning (para. 9, 56) and cognitive situation analysis (para. 55, 66). He does not specify that the calculations are occurring on a neural network.
LAGACE however does teach a neural network as one of the machine learning algorithms (para. 158) that can be used on his radar-based environmental monitor (abstract) that can be used to track bodies and detect falls (para. 75-76).
One skilled in the art at the time the application was effectively filed would be motivated to use the neural network of LAGACE as the machine learning algorithm of ZACH because it allows adaptive learning based variable input and can be a powerful tool for pattern recognition (para. 75 of LAGACE), yielding more accurate results for the motion and posture analysis of ZACK (para. 56 of ZACK). Furthermore, neural networks are known in the art of pattern recognition and signal processing as are all the computational methods listed in para. 158 of LAGACE. Therefore using one known computational method over another is a matter of “Simple Substitution of One Known Element for Another to Obtain Predictable Results” (see MPEP 2143 B). In the present case the known elements are machine learning algorithms listed in para. 158 of LAGACE and the predictable results are that the data is processed to recognize movement patterns (such as falls) in the radar data as taught in para. 75-76 of LAGACE and para. 56 and 66 of ZACK.
Regarding claim 2: As best understood, ZACK discloses: a fall alert mitigation manager configured to prevent false positives by analyzing additional mitigation features selected to distinguish real falls from other fall-like detections (Para. 58 states that the system is set up to combat a high rate of false alarms and misdetections.).
Regarding claim 3: As best understood, ZACK discloses: the fall alert mitigation manager is configured to receive input from a telemetric system and to use a sensitivity map (“data that is spatio-temporally characterized” in abstract).
Regarding claim 4: As best understood, ZACK discloses: the fall alert mitigation manager is configured to register a confidence rating for a fall event selected from a confidence rating of 1 indicating a positive, but not validated, detection of a fall event, a confidence rating of 2 indicating a validated fall event and a confidence rating of 0 indicating that the fall event is a false positive (As discussed in the 112 rejection above, this is an arbitrary designation. ZACK discloses determining the probability of determining a certain state, such as a fall, in para. 59. Therefore determining the probability that the data indicates a fall is a “confidence rating.”)
Regarding claim 5: As best understood, ZACK discloses: the fall alert mitigation manager is configured to assign prediction values to frames of the data from the radar unit (“identify most probable fit” in para. 59; also determining relative probability in para. 65, 120).
Regarding claim 6: As best understood, ZACK discloses: the alert mitigation manager is configured to extract mitigation features from height profile maps of a sequence of frames selected from: a low energy (LE) index, a high energy (HE) index, a height of low energy (HoLE) index, a dynamic consistency (DynC) index, a signal to noise ratio (SNR) index (para. 107-108), a maximum height (Z) jump index and combinations thereof.
Regarding claim 7: As best understood, ZACK discloses: the alert mitigation manager is configured to apply at least one validation rule (para. 82).
Regarding claim 8: As best understood, ZACK discloses: the alert mitigation manager is configured to apply at least the validation rule: IF a fall event is detected in a frame, THEN IF number of frames collected since first detection exceeds a frame-count threshold AND event-count exceeds a count-threshold, THEN increase confidence rating to 2 and generate fall-alert (Para. 59, 65, and 120 discuss determining the probability that a specific state, such as a fall, exists. Giving such a probability an arbitrary confidence rating on a scale of 0 to 2 is just another way to express the probability.).
Regarding claim 9: As best understood, ZACK discloses: the fall alert mitigation manager is configured and operable to receive input from a telemetric system and to use a sensitivity map to generate the alert threshold value (“data that is spatio-temporally characterized” in abstract. As discussed in the 112 rejection above, all radar data is a telemetric sensitivity map. Generating any alert based on measurement data, such as the threshold recited in para. 10, inherently involves passing a threshold value.)
Regarding claim 10: As best understood, ZACK discloses: the sensitivity map comprises a binary file having a stack of two-dimensional arrays (The radar data in a 2-D matrix is discussed in para. 103-104. There will be “stack” of them as they are constantly changing in time.).
Regarding claim 11: As best understood, ZACK discloses: the sensitivity map consists of a stack of ten two-dimensional arrays each having 20 rows and 20 columns (Para. 103 states that the total number of bins will be determined by the scan window. It will also be determined by the resolution of the radar. Therefore designating any particular size of data is just a matter arbitrary choice based on the desired precision and the physical limitations of the radar system. Using larger chunks of radar data has the advantage of being less computationally intensive. Using smaller chunks gives more accuracy. Therefore, the goal of any system would be to make the least computationally intense use of data while detecting all falls. Such design tradeoffs are obvious to the skilled artisan.)
Regarding claim 12: ZACK discloses: a frame buffer memory unit for storing frame data (para. 66); and a data filter configured to receive said raw data, and operable to process the raw data to remove data relating to reflections from static objects thereby generating filtered data (“environmental clutter cancelation” 230 in FIG. 1C; para. 59).
Regarding claim 13: ZACK discloses: the data filter comprises a temporal filter unit through which received data may be passed to produce filtered output (range-time energy signature used to determine motion characteristics of a human in para. 138).
Regarding claim 14: ZACK discloses: the temporal filter is operable to select a frame capture rate, to collect raw data from a first frame; to wait for a time delay, to collect raw data from a second frame; and to subtract first frame data from the second frame data (para. 63).
Claim(s) 15 is/are rejected under 35 U.S.C. 103 as being unpatentable over ZACK and LAGACE in view of AL-ALUSI (US 2015/0223733).
Regarding claim 15: ZACK discloses applying a filter to remove the background data in para. 59, but does not specify the particular type of filter.
AL-ALUSI however does specify the using a low-pass filter and an infinite impulse response filter to acquire the target data from the raw data (para. 52, 54) in his radar device (abstract) that can be used to sense human activity such as falls (para. 78).
One skilled in the art at the time the application was effectively filed would be motivated to use the filtering of AL-ALUSI on the raw radar data because it allows different signals to be extracted from the raw data (para. 50 of AL-ALUSI) such as posture (para. 56), which can allow the system to more accurately determine if the target has suffered a fall (para. 56 of AL-ALUSI).
Claim(s) 16 is/are rejected under 35 U.S.C. 103 as being unpatentable over ZACK and LAGACE in view of COUNTRYMAN (US 5,150,317).
Regarding claim 16: ZACK discloses applying a filter to remove the background data in para. 59, but does not specify an infinite impulse filter with a time constant that is updated on an ongoing basis.
COUNTRYMAN however does teach that it is known in the signal processing arts to have an infinite impulse response filter (col. 3 lines 25-29) with a variable time constant (col. 3 lines 30-40), which adapts to the rate of change of the input signal (col. 3 lines 30-40), as a part of general signal processing (col. 1 lines 12-35). This kind of filtering will eliminate noise such that there is no jerky or erratic output (i.e. artifacts) as discussed in col. 1 lines 12-36.
One skilled in the art at the time the application was effectively filed would be motivated to use the adaptive time constant filters of COUNTRYMAN to process the radar signals of ZACK in order to have a quicker response to rapidly changing input values. This optimizes the filtering giving more accurate lower noise outputs (col. 1 line 49-col. 2 line 11).
Double Patenting
The nonstatutory double patenting rejection is based on a judicially created doctrine grounded in public policy (a policy reflected in the statute) so as to prevent the unjustified or improper timewise extension of the “right to exclude” granted by a patent and to prevent possible harassment by multiple assignees. A nonstatutory double patenting rejection is appropriate where the conflicting claims are not identical, but at least one examined application claim is not patentably distinct from the reference claim(s) because the examined application claim is either anticipated by, or would have been obvious over, the reference claim(s). See, e.g., In re Berg, 140 F.3d 1428, 46 USPQ2d 1226 (Fed. Cir. 1998); In re Goodman, 11 F.3d 1046, 29 USPQ2d 2010 (Fed. Cir. 1993); In re Longi, 759 F.2d 887, 225 USPQ 645 (Fed. Cir. 1985); In re Van Ornum, 686 F.2d 937, 214 USPQ 761 (CCPA 1982); In re Vogel, 422 F.2d 438, 164 USPQ 619 (CCPA 1970); In re Thorington, 418 F.2d 528, 163 USPQ 644 (CCPA 1969).
A timely filed terminal disclaimer in compliance with 37 CFR 1.321(c) or 1.321(d) may be used to overcome an actual or provisional rejection based on nonstatutory double patenting provided the reference application or patent either is shown to be commonly owned with the examined application, or claims an invention made as a result of activities undertaken within the scope of a joint research agreement. See MPEP § 717.02 for applications subject to examination under the first inventor to file provisions of the AIA as explained in MPEP § 2159. See MPEP § 2146 et seq. for applications not subject to examination under the first inventor to file provisions of the AIA . A terminal disclaimer must be signed in compliance with 37 CFR 1.321(b).
The filing of a terminal disclaimer by itself is not a complete reply to a nonstatutory double patenting (NSDP) rejection. A complete reply requires that the terminal disclaimer be accompanied by a reply requesting reconsideration of the prior Office action. Even where the NSDP rejection is provisional the reply must be complete. See MPEP § 804, subsection I.B.1. For a reply to a non-final Office action, see 37 CFR 1.111(a). For a reply to final Office action, see 37 CFR 1.113(c). A request for reconsideration while not provided for in 37 CFR 1.113(c) may be filed after final for consideration. See MPEP §§ 706.07(e) and 714.13.
The USPTO Internet website contains terminal disclaimer forms which may be used. Please visit www.uspto.gov/patent/patents-forms. The actual filing date of the application in which the form is filed determines what form (e.g., PTO/SB/25, PTO/SB/26, PTO/AIA /25, or PTO/AIA /26) should be used. A web-based eTerminal Disclaimer may be filled out completely online using web-screens. An eTerminal Disclaimer that meets all requirements is auto-processed and approved immediately upon submission. For more information about eTerminal Disclaimers, refer to www.uspto.gov/patents/apply/applying-online/eterminal-disclaimer.
Claim(s) 1 and 12 is/are rejected on the ground of nonstatutory double patenting as being unpatentable over claim(s) 1 and 5 of U.S. Patent No. 11660023 (hereinafter ‘023) in view of ZACK and LAGACE.
Regarding claim 1: The limitations of claim 1 are taught in claim 1 of ‘023 with the limitations of an alert threshold generator taught in ZACK and a neural network taught in LAGACE as discussed above.
Regarding claim 1: The limitations of claim 1 are taught in claim 5 of ‘023 with the limitations of an alert threshold generator taught in ZACK and a neural network taught in LAGACE as discussed above.
Regarding claim 12: The limitations of claim 1 are taught in claim 1 of ‘023 with the limitations of an alert threshold generator taught in ZACK and a neural network taught in LAGACE as discussed above.
Regarding claim 12: The limitations of claim 1 are taught in claim 5 of ‘023 with the limitations of an alert threshold generator taught in ZACK and a neural network taught in LAGACE as discussed above.
Claim(s) 1, 12, 13, and 15 is/are rejected on the ground of nonstatutory double patenting as being unpatentable over claim(s) 1 of U.S. Patent No. 12347298 (hereinafter ‘298).
Regarding claim 1: The limitations of claim 1 are taught in claim 1 of ‘298.
Regarding claim 12: The limitations of claim 1 are taught in claim 1 of ‘298.
Regarding claim 13: The limitations of claim 1 are taught in claim 1 of ‘298.
Regarding claim 15: The limitations of claim 1 are taught in claim 1 of ‘298.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure. Additional references have been added to the Notice of References Cited for teaching radar systems for detecting falls.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to NATHANIEL J KOLB whose telephone number is (571)270-7601. The examiner can normally be reached M-F 9-5 EST.
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/NATHANIEL J KOLB/Examiner, Art Unit 2896