Prosecution Insights
Last updated: April 19, 2026
Application No. 18/725,216

FALLING-DOWN DETECTION APPARATUS, SYSTEM AND METHOD, AND COMPUTER READABLE MEDIUM

Non-Final OA §103§112
Filed
Jun 28, 2024
Examiner
AYNALEM, NATHNAEL B
Art Unit
2488
Tech Center
2400 — Computer Networks
Assignee
NEC Corporation
OA Round
3 (Non-Final)
76%
Grant Probability
Favorable
3-4
OA Rounds
2y 7m
To Grant
90%
With Interview

Examiner Intelligence

Grants 76% — above average
76%
Career Allow Rate
505 granted / 662 resolved
+18.3% vs TC avg
Moderate +14% lift
Without
With
+13.9%
Interview Lift
resolved cases with interview
Typical timeline
2y 7m
Avg Prosecution
32 currently pending
Career history
694
Total Applications
across all art units

Statute-Specific Performance

§101
5.6%
-34.4% vs TC avg
§103
39.5%
-0.5% vs TC avg
§102
22.3%
-17.7% vs TC avg
§112
21.6%
-18.4% vs TC avg
Black line = Tech Center average estimate • Based on career data from 662 resolved cases

Office Action

§103 §112
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 . Continued Examination Under 37 CFR 1.114 A request for continued examination under 37 CFR 1.114, including the fee set forth in 37 CFR 1.17(e), was filed in this application after final rejection. Since this application is eligible for continued examination under 37 CFR 1.114, and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114. Applicant's submission filed on 01/30/2026 has been entered. Response to Amendment and Argument Applicant’s amendment and argument with respect to pending claims 1-7 and 10-11 filed on 01/30/2026 have been fully considered. The argument regarding the rejection under 35 USC § 103 has been rendered moot in view of a new ground of rejection. Drawings The drawings filed on 06/28/2024 are accepted. Claim Rejections - 35 USC § 112 In view of the amendment of the pending claims, the rejection under 35 USC § 112(b) of the pending claims is withdrawn. 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, 10 and 11 is/are rejected under 35 U.S.C. 103 as being unpatentable over Mani (US 20200391708 A1) in view of Russell (US 10915762 B1). Regarding claim 1, Mani teaches a falling-down detection apparatus comprising: at least one storage device configured to store instructions; and at least one processor configured to execute the instructions to: detect a skeletal point of a person present near a first vehicle from a first image taken by a first on-board camera (Figs. 1-9, ¶0050: The processor 31 analyzes the image information obtained through the rear camera 10 to detect children in various postures such as standing, sitting or creeping postures. ¶0069-0073: The processor 31 detects vertical edges among the edges for the child candidate object 110, aligns and compares the shapes formed by the detected edges and the reference shapes in the vertical direction of various postures of a child stored in a predetermined table…). Note that this interpretation is consistent with the disclosure of the current application ¶0029; detect a roadway area indicating an area of a roadway (¶0061-0062: The processor 31 may detect an edge (or boundary) in the rear image of the vehicle received from the rear camera 10 to detect the ground area 100 divided by the edge…The processor 31 uses an edge detection algorithm such as a Canny edge detection algorithm, a line edge detection algorithm, and a Laplacian edge detection algorithm to detect boundary lines in an image and extract the ground area 100); determine whether or not the person present in the roadway area is lying down on the roadway area based on a positional relationship between the skeletal point of the person and the roadway area (¶0050-0051: The processor 31 analyzes the image information obtained through the rear camera 10 to detect children in various postures such as standing, sitting or creeping postures…¶0070: The processor 31 may determine whether the child candidate object 110 is the child 111…whether it is connected to the ground, etc. in consideration of the sitting or creeping posture of the child). Note that this interpretation is consistent with the disclosure of the current application. See current application ¶0043. Mani does not explicitly disclose detecting a sidewalk area from the image. However, Russel teaches detecting a sidewalk area from the image (abstract, col. 12, lines 53-62: identifying sidewalk areas from images). It would have been obvious to a person having ordinary skill in the art before the effective filing date of the claimed invention to modify Mani by incorporating the teaching of Russel as noted above, in order to predict trajectories of detected pedestrians based on locations of sidewalks (Russel: col. 2, lines 32-36). Regarding claim 10, the claim is drawn to a falling-down detection method claim and recites the limitation analogous to claim 1, and is rejected due to the same reason set forth above with respect to claim 1. Regarding claim 11, the claim is drawn to a falling-down detection method claim and recites the limitation analogous to claim 1, and is rejected due to the same reason set forth above with respect to claim 1. Claim(s) 2, 6 and 7 is/are rejected under 35 U.S.C. 103 as being unpatentable over Mani (US 20200391708 A1) in view of Russell (US 10915762 B1) as applied to claim 1, and further in view of Katz et al. (US 20230196897 A1). Regarding claim 2, Mani in view of Russell does not explicitly disclose wherein the at least one processor is further configured to execute the instructions to: calculate, when a skeletal point of a head of the person is detected, a first distance of the skeletal point of the head from a ground based on the roadway area, wherein when the first distance is equal to or shorter than a first threshold, determine that the person is lying down. However, Katz teaches wherein the at least one processor is further configured to execute the instructions to: calculate, when a skeletal point of a head of the person is detected, a first distance of the skeletal point of the head from a ground based on the roadway area, wherein when the first distance is equal to or shorter than a first threshold, determine that the person is lying down (See Figs. 1-4, ¶0068, 0074, 0087: it may be assumed the person is lying on the floor and therefore in a fall position if the 3D positions are all below some height with respect to the floor, or in yet another example if the 3D position of the torso or head is below some height threshold). It would have been obvious to a person having ordinary skill in the art before the effective filing date of the claimed invention to modify Mani in view of Russell by incorporating the teaching of Katz as noted above, in order to accurately identify a status (i.e., a fall status) of a person the (¶0074, 0093). Claim 6, Mani teaches wherein the at least one processor is further configured to execute the instructions to: determine whether or not the person is lying down on the roadway based also on a positional relationship between the skeletal point detected from a (¶0050-0051: The processor 31 analyzes the image information obtained through the rear camera 10 to detect children in various postures such as standing, sitting or creeping postures…¶0070: The processor 31 may determine whether the child candidate object 110 is the child 111…whether it is connected to the ground, etc. in consideration of the sitting or creeping posture of the child). It is noted that Mani does not explicitly disclose a second image taken by a second on-board camera mounted on a second vehicle other than the first vehicle including the first on-board camera mounted thereon and the road area. However, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Mani in view of Russell to arrive at the claimed invention of a second image taken by a second on-board camera mounted on a second vehicle other than the first vehicle including the first on-board camera mounted thereon and the roadway area by duplicating the working parts of the prior arts, since it has been held that mere duplication of essential working parts of a device involves only routine skill in the art. St. Regis Paper Co. v. Bemis Co., 193 USPQ 8. Regarding claim 7, Mani in view of Russell does not explicitly disclose wherein the at least one processor is further configured to execute the instructions to: use a distance of the skeletal point from a ground calculated from the position of the skeletal point and the position of the roadway area as the positional relationship. However, Katz teaches wherein the at least one processor is further configured to execute the instructions to: use a distance of the skeletal point from a ground calculated from the position of the skeletal point and the position of the roadway area as the positional relationship (See Figs. 1-4, ¶0068, 0074, 0087: it may be assumed the person is lying on the floor and therefore in a fall position if the 3D positions are all below some height with respect to the floor, or in yet another example if the 3D position of the torso or head is below some height threshold). It would have been obvious to a person having ordinary skill in the art before the effective filing date of the claimed invention to modify Mani in view of Russell by incorporating the teaching of Katz as noted above, in order to accurately identify a status (i.e., a fall status) of a person the (¶0074, 0093). Claim(s) 3 and 4 is/are rejected under 35 U.S.C. 103 as being unpatentable over Mani (US 20200391708 A1) in view of Russell (US 10915762 B1) as applied to claim 1, and further in view of Groß et al. (US 20220108561 A1). Regarding claim 3, Mani in view of Russell does not explicitly disclose wherein the at least one processor is further configured to execute the instructions to: calculate, when a skeletal point of a knee of the person is detected, a second distance of the skeletal point of the knee from a ground based on the roadway area, and when the second distance is equal to or shorter than a second threshold, determine that the person is lying down. However, Groß teaches wherein the at least one processor is further configured to execute the instructions to: calculate, when a skeletal point of a knee of the person is detected, a second distance of the skeletal point of the knee from a ground based on the roadway area, and when the second distance is equal to or shorter than a second threshold, determine that the person is lying down (¶0200: the distance of skeleton points identified in the skeleton model to the ground can be used, i.e. a fall is detected as soon as these fall below a threshold value (e.g. at a distance of 25 cm in the case of the knee)). It would have been obvious to a person having ordinary skill in the art before the effective filing date of the claimed invention to modify Mani in view of Russell by incorporating the teaching of Groß as noted above, in order to obtain an alternative and/or additional way of fall detection based on the distance of skeleton points from the ground (Groß ¶0200). Regarding claim 4, Mani in view of Russell and Groß discloses the falling-down detection apparatus according to claim 3. Groß further teaches wherein the at least one processor is further configured to execute the instructions to: when the skeletal point of a head of the person has not been detected determine whether or not the second distance is equal to or shorter than the second threshold (¶0200: In this case, the system primarily uses the angle of the trunk, the position or angle of the head, the shoulders, and also the position of the legs relative to the perpendicular to recognize that the patient is in a falling posture, is lying on the floor or has dropped to his or her knees. As an alternative and/or additional evaluation, the distance of skeleton points identified in the skeleton model to the ground can be used, i.e. a fall is detected as soon as these fall below a threshold value (e.g. at a distance of 25 cm in the case of the knee)). The motivation statement set forth above with respect to claim 3 applies here. Claim(s) 5 is/are rejected under 35 U.S.C. 103 as being unpatentable over Mani (US 20200391708 A1) in view of Russell (US 10915762 B1) as applied to claim 1, and further in view of Ikeda et al. (US 20200103286 A1). Regarding claim 5, Mani teaches the falling-down detection apparatus according to claim 1 wherein the at least one processor is further configured to execute the instructions to: determined that the person is lying down based on a positional relationship between the skeletal point detected from the first image and the roadway area (¶0050-0051: The processor 31 analyzes the image information obtained through the rear camera 10 to detect children in various postures such as standing, sitting or creeping postures…¶0070: The processor 31 may determine whether the child candidate object 110 is the child 111…whether it is connected to the ground, etc. in consideration of the sitting or creeping posture of the child). Mani does not explicitly teach calculate, when it is determined that the person is lying down…a falling-down continuation time period of the person based on a first subsequent image taken after the first image is taken; and send, when the falling-down continuation time period is equal to or longer than a predetermined time period, a notification to that effect to a predetermined notification destination. However, Ikeda teaches calculate, when it is determined that the person is lying down … a falling-down continuation time period of the person based on a first subsequent image taken after the first image is taken; and send, when the falling-down continuation time period is equal to or longer than a predetermined time period, a notification to that effect to a predetermined notification destination (Figs. 4A-4B, ¶0063: it is assumed that the head 402 of the user 401, which is detected in any of the attention areas A to C defined in FIG. 3A and FIG. 3B, moves to the falling detection area 420 and remains in the falling detection area 420 for a predetermined time. In this case, the notification control device 101 determines that the user 401 has fell from the bed 103. In this case, the notification control device 101 sends the notification information including the falling detection information indicating that the user 401 has fell from the bed). It would have been obvious to a person having ordinary skill in the art before the effective filing date of the claimed invention to modify Mani in view of Russell by incorporating the teaching of Ikeda as noted above, in order to obtain a notification system based when fall detected (¶0062-0063). The following are the prior art made of record and not relied upon are considered pertinent to applicant's disclosure. Oniga et al. describes "Curb Detection Based on a Multi-Frame Persistence Map for Urban Driving Scenarios" Paven et al. describes "Road Curb Detection and Localization with Monocular Forward-view Vehicle Camera". Conclusion Any inquiry concerning this communication or earlier communications from the examiner should be directed to NATHNAEL AYNALEM whose telephone number is (571)270-1482. The examiner can normally be reached M-F 9AM-5:30 PM ET. Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice. If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, SATH PERUNGAVOOR can be reached at 571-272-7455. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300. Information regarding the status of published or unpublished applications may be obtained from Patent Center. Unpublished application information in Patent Center is available to registered users. To file and manage patent submissions in Patent Center, visit: https://patentcenter.uspto.gov. Visit https://www.uspto.gov/patents/apply/patent-center for more information about Patent Center and https://www.uspto.gov/patents/docx for information about filing in DOCX format. For additional questions, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000. /NATHNAEL AYNALEM/ Primary Examiner, Art Unit 2488
Read full office action

Prosecution Timeline

Jun 28, 2024
Application Filed
Jul 10, 2025
Non-Final Rejection — §103, §112
Oct 14, 2025
Response Filed
Oct 29, 2025
Final Rejection — §103, §112
Jan 30, 2026
Request for Continued Examination
Feb 08, 2026
Response after Non-Final Action
Feb 17, 2026
Non-Final Rejection — §103, §112 (current)

Precedent Cases

Applications granted by this same examiner with similar technology

Patent 12600319
VEHICLE DOOR INTERFACE SYSTEM
2y 5m to grant Granted Apr 14, 2026
Patent 12587634
Disallowing Unnecessary Layers in Multi-Layer Video Bitstreams
2y 5m to grant Granted Mar 24, 2026
Patent 12581103
VIDEO ENCODING/DECODING METHOD AND DEVICE, AND BITSTREAM STORAGE MEDIUM
2y 5m to grant Granted Mar 17, 2026
Patent 12581126
LOW COMPLEXITY NN-BASED IN LOOP FILTER ARCHITECTURES WITH SEPARABLE CONVOLUTION
2y 5m to grant Granted Mar 17, 2026
Patent 12572023
OPTICAL NAVIGATION DEVICE WITH INCREASED DEPTH OF FIELD
2y 5m to grant Granted Mar 10, 2026
Study what changed to get past this examiner. Based on 5 most recent grants.

AI Strategy Recommendation

Get an AI-powered prosecution strategy using examiner precedents, rejection analysis, and claim mapping.
Powered by AI — typically takes 5-10 seconds

Prosecution Projections

3-4
Expected OA Rounds
76%
Grant Probability
90%
With Interview (+13.9%)
2y 7m
Median Time to Grant
High
PTA Risk
Based on 662 resolved cases by this examiner. Grant probability derived from career allow rate.

Sign in with your work email

Enter your email to receive a magic link. No password needed.

Personal email addresses (Gmail, Yahoo, etc.) are not accepted.

Free tier: 3 strategy analyses per month