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 .
DETAILED ACTION
Claims 1-20 are presented for examination.
Claim Rejections - 35 USC § 101
The 35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claims 1, 9, and 17 are rejected under 35 USC 101. Claims 2-8, 10-16, and 18-20 are rejected for being dependent on claims 1, 9, and 14.
The claimed invention is directed to Abstract ideas without significantly more. The claims recite organizing human activity (receiving patient images and from these images, determine if the patient has changed position, to include falling). This judicial exception is not integrated into a practical application because the steps to analyzing the patient’s position changes are not provided beyond human observation and human response. The claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception because they lack discrete mechanisms and specific steps to determine the movement of the patient that would differentiate between human analysis/response and a computerized version. See MPEP 2106.04.
Claim Rejections – Obviousness 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 claims at issue 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); and 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 a nonstatutory double patenting ground provided the reference application or patent either is shown to be commonly owned with this 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 §§ 706.02(l)(1) - 706.02(l)(3) 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 USPTO Internet website contains terminal disclaimer forms which may be used. Please visit www.uspto.gov/forms/. The 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 http://www.uspto.gov/patents/process/file/efs/guidance/eTD-info-I.jsp.
Claims (see below) are rejected on the ground of nonstatutory double patenting as being unpatentable over claims (see below) of application 17/319,508 in view of see list of copending applications listed below. Although the claims at issue are not identical, they are not patentably distinct from each other because of reasons listed below. This is a provisional nonstatutory double patenting rejection because the patentably indistinct claims have not in fact been patented.
Below are listings of the claimed invention and the relevant copending applications corresponding to the double patent rejections. All recitations to the claims of this application are emboldened.
18/958,755
1. A method performed by a monitoring device, the method comprising:
receiving an image stream of at least a portion of a patient room;
identifying a first position of a patient from the image stream using an image analysis model;
determining, using the image analysis model, that the patient has remained in the first position for at least a first threshold time; and
transmitting, based on determining that the patient has remained in the first position for the at least the first threshold time, a first alert based on the patient remaining in the first position.
9. A system for monitoring patient conditions, the system comprising:
a monitoring device configured to:
receive an image stream of at least a portion of a patient room;
identify a first position of a patient from the image stream using an image analysis model;
determine, using the image analysis model, that the patient has remained in the first position for at least a first threshold time; and
transmit, based on the determination that the patient has remained in the first position for at least the first threshold time, a first alert based on the patient remaining in the first position.
17. Non-transitory computer-readable media having stored thereon instructions that, when executed by one or more processors, cause the one or more processors to perform operations comprising:
receiving an image stream of at least a portion of a patient room; identifying a first position of a patient from the image stream using an image analysis model;
determining, using the image analysis model, that the patient has remained in the first position for at least a first threshold time; and
transmitting, based on determining that the patient has remained in the first position for at least the first threshold time, a first alert based on the patient remaining in the first position.
18/299,876/U.S. 11,943,567
14. An apparatus for monitoring a monitored environment, comprising: memory; and a processor configured to execute instructions stored in the memory to: identify, from an image stream, a first image and a second image of the monitored environment; obtain, from the first image, first states of the monitored environment; responsive to determining that the first states include a monitored condition, record a time associated with the monitored condition; obtain, from the second image, second states of the monitored environment; and responsive to determining that the second states include the monitored condition and that the monitored condition persisted for a threshold duration of time, transmit a notification that includes an indication of the monitored condition and the threshold duration of time of the monitored condition.
Claim 1 is directed to an embodiment wherein an image stream, including a portion of a patient’s room and the patient himself, is received. An image analysis model or algorithm, analyzes the amount of time the patient remains in a certain position, and after a predetermined amount of time has passed, if the patient’s position remains unchanged, an alert is transmitted to a caregiver.
Claim 14 is directed to an embodiment wherein an apparatus includes obtaining an image stream and identify, from the image stream, a first and second image from a monitored environment. In this obtaining of the first image stream, determine a first state of the monitored environment while concurrently time stamping the determined first state. The apparatus also obtains a second image of the monitored environment, a second state of the monitored environment. In response to determining that the second states include the monitored condition and that the monitored condition persisted for a threshold duration of time, transmit a notification that includes an indication of the monitored condition and the threshold duration of time of the monitored condition.
Claim 1 is obvious over claim 14. While claim 1 is directed to monitoring of a patient’s position and using an image analysis model, determining if the patient hadn’t moved after a predetermined time as indicated by an unchanged position recorded in the recorded images, an alert is provided to a caregiver.
Claim 14’s embodiment, while not directed to monitoring a patient, includes a similar feature where an image stream is analyzed for a monitored condition, and if that the monitored condition persisted for a threshold duration of time, transmit a notification that includes an indication of the monitored condition and the threshold duration of time of the monitored condition.
It would have been obvious to one of ordinary skill before the effective filing date of the claimed invention to modify claim 14 to include anything subjected to video monitoring, such that claim 1 is obvious over claim 14. Claim 14 could be said to be a generalized version of claim 1 and one of ordinary skill would have a likelihood of success including any subject being monitored, to include patients, such that claim 1 would have been obvious over claim 14.
Claim 9 is obvious over claim 14 for the same reasons articulate for the reasons why claim 1 is obvious over claim 14.
Claim 17 is obvious over claim 14 for the same reasons articulate for the reasons why claim 1 is obvious over claim 14.
Claim Rejections - 35 USC § 102(a)(1)
Claims 1-3, 6, 7, 9, 10, 12, 13, 17, and 18 are rejected under 35 USC 102(a)(1) as being unpatenable over Derenne et al., U.S. 2012/0075464 (see IDS).
On claim 1, Derenne cites:
A method performed by a monitoring device, the method comprising:
receiving an image stream of at least a portion of a patient room;
[0093] A patient pain detection algorithm may also be included within system 20. Such an algorithm may first include a step of identifying a patient within a room. After the patient is identified, comparisons of real time images of the patient with a baseline image may be performed at intervals. The baseline image may be stored in database 50, and may be derived from previous images taken while the patient is in the room, or an admissions photograph, or other sources.
identifying a first position of a patient from the image stream using an image analysis model;
[0062] and figure 13. For each point 58, skeleton 54, system 20 computes the three dimensional position of that point multiple times a second
determining, using the image analysis model, that the patient has remained in the first position for at least a first threshold time; and
transmitting, based on determining that the patient has remained in the first position for the at least the first threshold time, a first alert based on the patient remaining in the first position.
[0006] In other embodiments, the computer device may determine from the output signals how long a patient has been lying on a particular side, front, or back of the patient's body. An alert may be issued to a caregiver if the patient has been lying on a particular side, front, or back of the patient for longer than a predetermined amount of time.
[0087] System 20 may record a series of sequential movements made by the patient. Object recognition data may further be added to the sequential movement data such that any objects that the patient interacts with are identified. The recorded data is analyzed and compared to a predetermined database of sequential behaviors and/or objects. When the recorded data closely resembles one in the database, the movements are tagged as a certain behavior. A time/date stamp may added to this data. The recorded patient behaviors may include any one or more of the following: eating (FIG. 4), exiting the bed, walking, walking to the bathroom, having a seizure, falling, getting entrapped in side rails (FIG. 5), sleeping (FIG. 6), experiencing pain (FIG. 7), sitting in a recliner, etc. System 20 may then send this information to a remote computer, to a display, or as an alert to a caregiver.
On claim 2, Derenne cites:
The method of claim 1, wherein the image analysis model comprises a multi-label classification machine learning model that is trained to receive an image and output values corresponding to patient position states identified in the image.
[0093] A patient pain detection algorithm may also be included within system 20. Such an algorithm may first include a step of identifying a patient within a room. After the patient is identified, comparisons of real time images of the patient with a baseline image may be performed at intervals. The baseline image may be stored in database 50, and may be derived from previous images taken while the patient is in the room, or an admissions photograph, or other sources.
On claim 3, Derenne cites except as underlined:
The method of claim 1, further comprising: identifying, using the image analysis model, that the patient has transitioned from the first position to a second position; and
transmitting, based on identifying that the patient has transitioned from the first position to the second position, a second alert indicating the second position.
[0087] System 20 may record a series of sequential movements made by the patient. Object recognition data may further be added to the sequential movement data such that any objects that the patient interacts with are identified. The recorded data is analyzed and compared to a predetermined database of sequential behaviors and/or objects. When the recorded data closely resembles one in the database, the movements are tagged as a certain behavior. A time/date stamp may added to this data. The recorded patient behaviors may include any one or more of the following: eating (FIG. 4), exiting the bed, walking, walking to the bathroom, having a seizure, falling, getting entrapped in side rails (FIG. 5), sleeping (FIG. 6), experiencing pain (FIG. 7), sitting in a recliner, etc. System 20 may then send this information to a remote computer, to a display, or as an alert to a caregiver.
On claim 6, Derenne cites:
The method of claim 1, wherein the first alert comprises an image of the first position of the patient from the image stream.
See the rejection of claim 1 which discloses the same subject matter as claim 6 and is rejected for the same reasons.
On claim 7, Derenne cites:
The method of claim 1, wherein the first alert comprises instructions to reposition the patient.
See the rejection of claim 1 which discloses the same subject matter as claim 7 and is rejected for the same reasons. The cited alert is considered a shortcut way to tell the caregiver to move the patient to prevent bedsores.
On claim 9, Derenne cites:
A system for monitoring patient conditions, the system comprising:
a monitoring device configured to:
receive an image stream of at least a portion of a patient room;
identify a first position of a patient from the image stream using an image analysis model;
determine, using the image analysis model, that the patient has remained in the first position for at least a first threshold time; and
transmit, based on the determination that the patient has remained in the first position for at least the first threshold time, a first alert based on the patient remaining in the first position.
See the rejection of claim 1 which discloses the same subject matter as claim 9 and is rejected for the same reasons.
On claim 10, Derenne cites:
The system of claim 9, further comprising:
a user device configured to:
receive the first alert from the monitoring device;
[0006] In other embodiments, the computer device may determine from the output signals how long a patient has been lying on a particular side, front, or back of the patient's body. An alert may be issued to a caregiver if the patient has been lying on a particular side, front, or back of the patient for longer than a predetermined amount of time.
and
output the first alert.
[0071] In addition to identifying who individuals are within a given room or other area, system 20 also records the data generated from cameras 22 that show the movement of the caregiver and/or patient. Any objects that are involved in this series of movements are also recorded and analyzed by computer device 24. The recorded and analyzed data is compared to a predetermined database of sequential behaviors which may include objects. When the recorded data closely resembles a stored object in the database, the movements are tagged as constituting a specific behavior or task. A time and/or date stamp may be added to this recorded data so that the time and/or date of the specific behavior or task is stored. When the behavior or task is a clinical protocol, information is sent to remote computer (such as EMR computer device 34) or it may be stored locally or displayed. Such local storage or display may occur within the room in which the task or behavior occurred, or it may occur at a nurse's workstation, at both locations, or at other locations. Computer device 24 may therefore include a display coupled thereto for displaying information, or computer device 24 may be in communication with one or more other computers that are capable of displaying information generated by computer device 24.
On claim 12, Derenne cites:
The system of claim 9, further comprising: a user device configured to:
display a history of positions of the patient; and
display a duration of the first threshold time.
[0018] One or more of the video cameras used in the system may include, in addition to the ability to record digital images, the ability to sense distances from the camera to the objects or individuals that are positioned in the camera's field of view. Such depth sensing ability may be based upon the projection of infrared light and the detection of reflections of that infrared light by sensors that are part of the system. The depth information may be used in combination with the image information to determine the three dimensional position and/or movement of individuals and/or objects within the viewing field of the camera.
[0063] Further, for any of the algorithms discussed below, a patient's head and face may be identified based on the skeleton so that a software algorithm can automatically blur the face to protect the patient's identity. In this manner, any images that are recorded and later played back will appear having a blurred-face patient, thereby protecting the patient's identify. Such blurring can even be used, if desired, in situations (described below) where system 20 identifies a patient by facial recognition. In such cases, system 20 may use the unblurred image data to determine the patient's identity through facial recognition, but only store blurred facial images so that any later playback will show a patient with an anonymous, blurred face. The identification of the patient through facial recognition may then be used for determining which medical records certain information should be forwarded to, or for other internal purposes. In this manner, the patient's identify can still be determined, but all visual records of the patient will not carry any visual images that identify the patient to viewers of the visual images.
[0076] When system 20 is used to monitor the turning of patients, system 20 may identify when a clinician is in the room. System 20 thereafter identifies--through the processing of data from one or more cameras 22--that the patient is turned and adds a date/time stamp to the data. System 20 then sends the data to remote computer. The remote computer may be an EMR computer, such as EMR computer device 34. Alternatively, or additionally, system 20 may store and/or displays the data locally. System 20 may further identify what side a patient is on (left, right, back, front) and track how long the patient has been on a particular side. System 20 may further send an alert to a clinician if patient has been on a particular side longer than a predetermined time. Such an alert may be forwarded to the clinician by sending a signal to caregiver alert computer device 38, which is programmed to carry out the alerting process.
Derenne discloses an embodiment for recording digital images, to include movement of individual. Derenne discloses an embodiment for playing back video. Derenne discloses date/time stamping videos with respect to how long a patient has been lying on his side. Taken together, Derenne discloses the claimed invention.
On claim 13, Derenne cites:
The system of claim 9, wherein the image analysis model comprises a multi-label classification machine learning model that analyzes at least one image of the image stream to output values corresponding to patient position states.
[0087] System 20 may record a series of sequential movements made by the patient. Object recognition data may further be added to the sequential movement data such that any objects that the patient interacts with are identified. The recorded data is analyzed and compared to a predetermined database of sequential behaviors and/or objects. When the recorded data closely resembles one in the database, the movements are tagged as a certain behavior. A time/date stamp may added to this data. The recorded patient behaviors may include any one or more of the following: eating (FIG. 4), exiting the bed, walking, walking to the bathroom, having a seizure, falling, getting entrapped in side rails (FIG. 5), sleeping (FIG. 6), experiencing pain (FIG. 7), sitting in a recliner, etc. System 20 may then send this information to a remote computer, to a display, or as an alert to a caregiver.
On claim 17, Derenne cites:
Non-transitory computer-readable media having stored thereon instructions that, when executed by one or more processors, cause the one or more processors
[0050] Computer device 24 may be a conventional server that communicates with both cameras 22 and projectors 30 over network 26, or it may be one or more personal computers (PCs), or it may be a dedicated electronic structure configured to carry out the logic and algorithms described herein, or any combination of these or other known devices capable of carrying out the logic and algorithms described herein. Such dedicated electronic structures may include any combination of one or more processors, systems on chip (SoC), field programmable gate arrays (FPGA), microcontrollers, discrete logic circuitry, software and/or firmware. Regardless of whether computer device 24 is a single physical device, or is multiple physical devices working together (which may be located in different physical locations), computer device 24 represents the hardware, software and/or firmware necessary to carry out the algorithms described herein.
to perform operations comprising: receiving an image stream of at least a portion of a patient room;
identifying a first position of a patient from the image stream using an image analysis model; determining, using the image analysis model, that the patient has remained in the first position for at least a first threshold time; and transmitting, based on determining that the patient has remained in the first position for at least the first threshold time, a first alert based on the patient remaining in the first position.
See the rejection of claim 1 which discloses the same subject matter as claim 17 and is rejected for the same reasons.
On claim 18, Derenne cites:
The non-transitory computer-readable media of claim 17, the operations further comprising: identifying, using the image analysis model, that the patient has transitioned from the first position to a second position; and transmitting, based on identifying that the patient has transitioned from the first position to the second position, a second alert indicating the second position.
See the rejection of claim 3 which discloses the same subject matter as claim 18 and is rejected for the same reasons.
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 may not be obtained though the invention is not identically disclosed or described as set forth in section 102 of this title, if the differences between the subject matter sought to be patented and the prior art are such that the subject matter as a whole would have been obvious at the time the invention was made to a person having ordinary skill in the art to which said subject matter pertains. Patentability shall not be negatived by the manner in which the invention was made.
The factual inquiries set forth in Graham v. John Deere Co., 383 U.S. 1, 148 USPQ 459 (1966), that are applied for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
Claims 8 and 16 are rejected under 35 USC 103 as being unpatenable over Derenne et al., U.S. 2012/0075464 in view of Kusens, U.S. 2016/0324460.
On claim 8, Derenne cites except as underlined:
The method of claim 1, further comprising:
determining, subsequent to transmitting the first alert, that the patient has remained in first the position for a second threshold time;
See the rejection of claim 1 which discloses the same subject matter as claim 8 and is rejected for the same reasons.
and
transmitting additional alerts at regular intervals until the patient is repositioned.
Regarding the excepted claim limitations, Derenne, as previously disclosed, includes an embodiment for turning and maneuvering patients. Derenne doesn’t disclose the excepted claim limitations.
In the same art of patient monitoring Kusens cites:
[0058]A predetermined time may be used as a minimum for assessing whether the caregiver might reasonably have completed a bedsore prevention action. The time may be a default for all patients, such as 1-3 minutes, or may be customized for the type of patient or for a particular patient.
It would have been obvious to one of ordinary skill before the effective filing date of the claimed invention for the embodiment in Kusens to repeat the bedsore alert until the patient has been repositioned. One of ordinary skill would have included this feature to have the alert repeat until the immediate issue of the bedsore warning is resolved.
On claim 16, Derenne and Kusens cites:
The system of claim 9, wherein the monitoring device is further configured to: determine, subsequent to transmitting the first alert, the patient has remained in the first position for a second threshold time; and transmit additional alerts at regular intervals until the patient is repositioned.
See the rejection of claim 8 which discloses the same subject matter as claim 16 and is rejected for the same reasons.
Claim 11 is rejected under 35 USC 103 as being unpatenable over Derenne et al., U.S. 2012/0075464 in view of Kaps et al., U.S. 2016/0292509.
On claim 11, Derenne cites except as underlined:
The system of claim 9, further comprising:
a user device configured to:
display a plurality of images each corresponding to a respective patient room;
figure 1 discloses a plurality of cameras 22 assigned to each room 28
And
[0055] Work flow computer device 36 may be a conventional computer device or software application adapted to manage the assignment of caregivers to particular patients and to oversee the performance of specific caregiver functions. Information gathered from one or more video cameras 22 and processed by computer device 24 and/or master computer device 32 may therefore be transferred to work flow computer device 26, thereby avoiding the need for manual entry of such information. Such information may include data identifying the completion, or partial completion, of one or more caregiver tasks. Such information may also include data that indicates tasks, or partial tasks, that have yet to be competed.
display an image of the first position of the patient from the image stream as one image of the plurality of images;
[0093] A patient pain detection algorithm may also be included within system 20. Such an algorithm may first include a step of identifying a patient within a room. After the patient is identified, comparisons of real time images of the patient with a baseline image may be performed at intervals. The baseline image may be stored in database 50, and may be derived from previous images taken while the patient is in the room, or an admissions photograph, or other sources.
receive the first alert from the monitoring device; and
[0006] In other embodiments, the computer device may determine from the output signals how long a patient has been lying on a particular side, front, or back of the patient's body. An alert may be issued to a caregiver if the patient has been lying on a particular side, front, or back of the patient for longer than a predetermined amount of time.
highlight the image from the image stream based on the first alert from the monitoring device.
As to the excepted claim limitations, as previously disclosed, Derenne disclosed an embodiment in which video cameras detect movement of a patient. Derenne doesn’t disclose “highlighting the image.”
In the related art of video analysis, Kap cites:
[0093] In one or more embodiments, the computer may generate a highlight reel that combines the video for events that satisfy selection criteria. Such a highlight reel might include the entire video for the selected events, or a portion of the video that corresponds to the important moments in the event as determined by the motion analysis. In some embodiments the highlight reel might include overlays of data or graphics on the video or on selected frames showing the value of metrics from the motion analysis. Such a highlight reel may be generated automatically for a user once the user indicates which events to include by specifying selection criteria. In some embodiments the computer may allow the user to edit the highlight reel to add or remove events, to lengthen or shorten the video shown for each event, to add or remove graphic overlays for motion data, or to add special effects or soundtracks
It would have been obvious to one of ordinary skill before the effective filing date of the claimed invention to include into Derenne’s patient video monitoring system an embodiment, as disclosed in Kaps, wherein a portion of a video is highlighted. One of ordinary skill would have included the highlighting aspect of Kaps to point out details of a patient’s detected movement.
Claims 4, 14, and 19 are rejected under 35 USC 103 as being unpatenable over Derenne et al., U.S. 2012/007546
On claim 4, Derenne cites except as underlined:
The method of claim 1, further comprising:
identifying, using the image analysis model, that the patient has transitioned from the first position to a second position;
[0087] System 20 may record a series of sequential movements made by the patient. Object recognition data may further be added to the sequential movement data such that any objects that the patient interacts with are identified. The recorded data is analyzed and compared to a predetermined database of sequential behaviors and/or objects. When the recorded data closely resembles one in the database, the movements are tagged as a certain behavior. A time/date stamp may added to this data. The recorded patient behaviors may include any one or more of the following: eating (FIG. 4), exiting the bed, walking, walking to the bathroom, having a seizure, falling, getting entrapped in side rails (FIG. 5), sleeping (FIG. 6), experiencing pain (FIG. 7), sitting in a recliner, etc. System 20 may then send this information to a remote computer, to a display, or as an alert to a caregiver.
determining, using the image analysis model, that the patient has remained in the second position for less than a second threshold time;
In the case of [0087] and walking, a transition from a first position to a second position would be the act of the patient putting one foot in front of another. Continuous walking would indicate a walking pace where the claimed “second position for less than a second threshold time” would be the patient’s second step moving back being replaced by the first step. This act is repeated when a patient is walking.
and
identifying, using the image analysis model, that the patient has returned to the first position, wherein determining that the patient has remained in the first position for the at least the first threshold time comprises:
determining that a sum of a first time spent in the first position and a second time spent in the first position is at least the first threshold time, wherein the first time spent in the first position is before identifying that the patient has transitioned from the first position to the second position and the second time spent in the first position is after identifying that the patient has returned to the first position.
As previously disclosed above in [0087], the pace of a patient walking would include at least one foot traveling back and one foot traveling forward, wherein one leg assumes a first position for at least a first threshold time and upon repeating the step of walking, a second threshold time is determined. Because of the alternating positions of the patient’s feet as the patient walks, this behavior is sufficient to meet the claimed “wherein the first time spent in the first position is before identifying that the patient has transitioned from the first position to the second position and the second time spent in the first position is after identifying that the patient has returned to the first position.”
Derenne doesn’t disclose the excepted claim limitations. However, it would have been obvious to one of ordinary skill before the effective filing date of the claimed invention, using the features disclosed in Derenne, to arrive at an embodiment meeting the claimed invention. During the course of a patient walking, one could expect that as long as the pace of the patient remains constant, the time of at least one foot spent in a position is constant wherein if the sum of the time the foot spent in a first position and second position is relatively the same, where the end result of taking the sum of the foot’s position in a first time and a second time is the same as the claimed invention. One of ordinary skill, apprised of the mechanics of walking, would have arrived at this observation with a likelihood of success.
On claim 14, Derenne cites:
The system of claim 9, wherein the monitoring device is further configured to: identify, using the image analysis model, that the patient has transitioned from the first position to a second position;
determine, using the image analysis model, that the patient has remained in the second position for less than a second threshold time; and
identify, using the image analysis model, that the patient has returned to the first position, wherein to determine that the patient has remained in the first position for the at least the first threshold time comprises to:
determine that a sum of a first time spent in the first position and a second time spent in the first position is at least the first threshold time, wherein the first time spent in the first position is before identifying that the patient has transitioned from the first position to the second position and the second time spent in the first position is after identifying that the patient has returned to the first position.
See the rejection of claim 4 which includes the same subject matter as claim 14, and is rejected for the same reasons.
On claim 19, Derenne cites:
The non-transitory computer-readable media of claim 17, the operations further comprising: identifying, using the image analysis model, that the patient has transitioned from the first position to a second position; determining, using the image analysis model, that the patient has remained in the second position for less than a second threshold time; and identifying, using the image analysis model, that the patient has returned to the first position, wherein determining that the patient has remained in the first position for the at least the first threshold time comprises: determining that a sum of a first time spent in the first position and a second time spent in the first position is at least the first threshold time, wherein the first time spent in the first position is before identifying that the patient has transitioned from the first position to the second position and the second time spent in the first position is after identifying that the patient has returned to the first position.
See the rejection of claim 4 which includes the same subject matter as claim 19, and is rejected for the same reasons.
Allowable Subject Matter
Claims 5, 15, and 20 are objected to for depending on a rejected claim but are otherwise allowable subject matter if amending into their respective independent claims.
Claim 5 claims, in part:
“identifying, using the image analysis model, that the patient has transitioned from the first position to a second position;
determining, using the image analysis model, that the patient has remained in the second position for at least a second threshold time; and
identifying, using the image analysis model, that the patient has returned to the first position, wherein determining that the patient has remained in the first position for the at least the first threshold time comprises:
determining that a time spent in the first position after identifying that the patient has returned to the first position is at least the first threshold time.”
In short, this embodiment requires an image analysis model to determine if a patient has moved from a first position to a second position, dwelled in the second position for a predetermined time, then thereafter, the patient returns to the first position for at least the amount of time when the patient was first detected at the first position by the imaging system.
This embodiment is narrow in its construction because this relies on conditioned statements in which the imaging system not only measures the patient’s second position for a second predetermined time, but the patient’s return to the first position for a second time dwelling measured at the first predetermined time. For this reason, claim 1 has been deemed allowable subject matter. Claims 15 and 20 are also allowable subject matter for the same reasons articulated for the allowability of claim 1.
Conclusion
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/CAL J EUSTAQUIO/Examiner, Art Unit 2686
/BRIAN A ZIMMERMAN/Supervisory Patent Examiner, Art Unit 2686