DETAILED ACTION
This action is pursuant to claims filed on 04/23/2026. Claims 1, 7, 11-15, and 18-23 are pending. An action on the merits of claims 1, 7, 11-15, and 18-23 is as follows.
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and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114.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 04/23/2026 has been entered.
Drawings
The drawings are objected to under 37 CFR 1.83(a). The drawings must show every feature of the invention specified in the claims. The following limitations are not shown in the drawings:
“a plurality of supporting surfaces” in claim 1, line 4 and claim 15, line 4
“a corresponding loading surface angularly offset from the support surface” in claim 1, lines 5-6 and claim 15, lines 5-6
“each supporting surface comprises a fixed portion coplanar with a cap of a load sensor assembly” in claim 1, lines 11-12 and claim 15, lines 11-12
“each supporting surface and corresponding loading surface are shaped to create a ramp from the floor to the cap that one of the wheels can be rolled from the floor to the cap” in claim 21, lines 1-3 and claim 23, lines 1-3
“a number of the multiple wheels of the substrate is the same number as the number of supporting surfaces and as the number of loading surfaces” in claim 22, lines 1-3
Therefore, the claimed limitations must be shown or the feature(s) canceled from the claim(s). No new matter should be entered.
Corrected drawing sheets in compliance with 37 CFR 1.121(d) are required in reply to the Office action to avoid abandonment of the application. Any amended replacement drawing sheet should include all of the figures appearing on the immediate prior version of the sheet, even if only one figure is being amended. The figure or figure number of an amended drawing should not be labeled as “amended.” If a drawing figure is to be canceled, the appropriate figure must be removed from the replacement sheet, and where necessary, the remaining figures must be renumbered and appropriate changes made to the brief description of the several views of the drawings for consistency. Additional replacement sheets may be necessary to show the renumbering of the remaining figures. Each drawing sheet submitted after the filing date of an application must be labeled in the top margin as either “Replacement Sheet” or “New Sheet” pursuant to 37 CFR 1.121(d). If the changes are not accepted by the examiner, the applicant will be notified and informed of any required corrective action in the next Office action. The objection to the drawings will not be held in abeyance.
Claim Rejections - 35 USC § 112
The following is a quotation of the first paragraph of 35 U.S.C. 112(a):
(a) IN GENERAL.—The specification shall contain a written description of the invention, and of the manner and process of making and using it, in such full, clear, concise, and exact terms as to enable any person skilled in the art to which it pertains, or with which it is most nearly connected, to make and use the same, and shall set forth the best mode contemplated by the inventor or joint inventor of carrying out the invention.
The following is a quotation of the first paragraph of pre-AIA 35 U.S.C. 112:
The specification shall contain a written description of the invention, and of the manner and process of making and using it, in such full, clear, concise, and exact terms as to enable any person skilled in the art to which it pertains, or with which it is most nearly connected, to make and use the same, and shall set forth the best mode contemplated by the inventor of carrying out his invention.
Claims 1, 7, 11-15, and 18-23 are rejected under 35 U.S.C. 112(a) or 35 U.S.C. 112 (pre-AIA ), first paragraph, as failing to comply with the written description requirement. The claim(s) contains subject matter which was not described in the specification in such a way as to reasonably convey to one skilled in the relevant art that the inventor or a joint inventor, or for applications subject to pre-AIA 35 U.S.C. 112, the inventor(s), at the time the application was filed, had possession of the claimed invention.
Regarding claim 1, Applicant has added the limitation “a plurality of supporting surfaces” in line 4, which is not described in the originally filed claims, specification, or drawings to support this newly added limitation. Thus, the newly added limitation is deemed to be new matter. In particular, the limitation of having a plurality of supporting surfaces are not described in the claim or the specification. Therefore, the claim fails the new matter requirement and is rejected under 35 U.S.C. 112(a) or pre-AIA 35 U.S.C. 112, first paragraph. Claims 7, 11-14, and 21-22 are also rejected due to their dependence on claim 1.
Further regarding claim 1, Applicant has added the limitation “for each supporting surface, a corresponding loading surface angularly offset from the support surface” in lines 5-6, which is not described in the originally filed claims, specification, or drawings to support this newly added limitation. Thus, the newly added limitation is deemed to be new matter. In particular, the limitation of the correspond loading surface is not described in the claim or specification. Additionally, any surface being angularly offset from the supporting surface is not described either. Therefore, the claim fails the new matter requirement and is rejected under 35 U.S.C. 112(a) or pre-AIA 35 U.S.C. 112, first paragraph. Claims 7, 11-14, and 21-22 are also rejected due to their dependence on claim 1.
Further regarding claim 1, Applicant has added the limitation “each supporting surface comprises a fixed portion coplanar with a cap of a load sensor assembly” in lines 11-12, which is not described in the originally filed claims, specification, or drawings to support this newly added limitation. Thus, the newly added limitation is deemed new matter. In particular, the limitation of the supporting surface having a fixed portion that is coplanar with a cap is not described in the claim or specification. Therefore, the claim fails the new matter requirement and is rejected under 35 U.S.C. 112(a) or pre-AIA 35 U.S.C. 112, first paragraph. Claims 7, 11-14, and 21-22 are also rejected due to their dependence on claim 1.
Regarding claim 15, Applicant has added the limitation “a plurality of supporting surfaces” in line 4, which is not described in the originally filed claims, specification, or drawings to support this newly added limitation. Thus, the newly added limitation is deemed to be new matter. In particular, the limitation of having a plurality of supporting surfaces are not described in the claim or the specification. Therefore, the claim fails the new matter requirement and is rejected under 35 U.S.C. 112(a) or pre-AIA 35 U.S.C. 112, first paragraph. Claims 18-20 and 23 are also rejected due to their dependence on claim 15.
Further regarding claim 15, Applicant has added the limitation “for each supporting surface, a corresponding loading surface angularly offset from the support surface” in lines 5-6, which is not described in the originally filed claims, specification, or drawings to support this newly added limitation. Thus, the newly added limitation is deemed to be new matter. In particular, the limitation of the correspond loading surface is not described in the claim or specification. Additionally, any surface being angularly offset from the supporting surface is not described either. Therefore, the claim fails the new matter requirement and is rejected under 35 U.S.C. 112(a) or pre-AIA 35 U.S.C. 112, first paragraph. Claims 18-20 and 23 are also rejected due to their dependence on claim 15.
Further regarding claim 15, Applicant has added the limitation “each supporting surface comprises a fixed portion coplanar with a cap of a load sensor assembly” in lines 11-12, which is not described in the originally filed claims, specification, or drawings to support this newly added limitation. Thus, the newly added limitation is deemed new matter. In particular, the limitation of the supporting surface having a fixed portion that is coplanar with a cap is not described in the claim or specification. Therefore, the claim fails the new matter requirement and is rejected under 35 U.S.C. 112(a) or pre-AIA 35 U.S.C. 112, first paragraph. Claims 18-20 and 23 are also rejected due to their dependence on claim 15.
Regarding claim 21, Applicant has added the limitation “wherein each supporting surface and corresponding loading surface are shaped to create a ramp from the floor to the cap that one of the wheels can be rolled from the floor to the cap” in lines 1-3, which is not described in the originally filed claims, specification, or drawings to support this newly added limitation. Thus, the newly added limitation is deemed new matter. In particular, the limitation of the structure of the supporting surface and loading surface forming a ramp is not described in the claim or specification. Therefore, the claim fails the new matter requirement and is rejected under 35 U.S.C. 112(a) or pre-AIA 35 U.S.C. 112, first paragraph.
Regarding claim 22, Applicant has added the limitation “wherein a number of the multiple wheels of the substrate is the same number as the number of supporting surfaces and as the number of loading surfaces” in lines 1-3, which is not described in the originally filed claims, specification, or drawings to support this newly added limitation. Thus, the newly added limitation is deemed new matter. In particular, the limitation of the multiple supporting surfaces and the multiple loading surfaces are not supported in the specification, therefore the limitation of the number of wheels matching these numbers are not described in the claim or specification. Therefore, the claim fails the new matter requirement and is rejected under 35 U.S.C. 112(a) or pre-AIA 35 U.S.C. 112, first paragraph.
Regarding claim 23, Applicant has added the limitation “wherein each supporting surface and corresponding loading surface are shaped to create a ramp from the floor to the cap that one of the wheels can be rolled from the floor to the cap” in lines 1-3, which is not described in the originally filed claims, specification, or drawings to support this newly added limitation. Thus, the newly added limitation is deemed new matter. In particular, the limitation of the structure of the supporting surface and loading surface forming a ramp is not described in the claim or specification. Therefore, the claim fails the new matter requirement and is rejected under 35 U.S.C. 112(a) or pre-AIA 35 U.S.C. 112, first paragraph.
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.
Claims 1, 7, 11-15, and 18-23 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 1, the claim recites the limitation “a corresponding loading surface angularly offset from the support surface” in lines 5-6. It is unclear what the corresponding loading surface is, or how it is angularly offset from the support surface. The broad and indefinite scope of the limitation fails to inform a person of ordinary skill in the art with reasonable certainty of the metes and bounds of the claimed invention, therefore the claim is rendered indefinite. For purposes of examination, it is being interpreted as referring to any surface that is angularly offset from the supporting surface. Claims 7, 11-14, and 21-22 are also rejected due to their dependence on claim 1.
Further regarding claim 1, the claim recites the limitation “the support surface” in line 6. It is unclear if this limitation is meant to refer to the supporting surfaces from line 4, or a different support surface. If it is meant to refer to the plurality of supporting surfaces, it should read “the supporting surface”. If it is meant to refer to a different support surface, it needs to be distinguished from the supporting surfaces from line 4. For purposes of examination, it is being interpreted as referring to the plurality of support surfaces from line 4. Claims 7, 11-14, and 21-22 are also rejected due to their dependence on claim 1.
Regarding claim 15, the claim recites the limitation “a corresponding loading surface angularly offset from the support surface” in lines 5-6. It is unclear what the corresponding loading surface is, or how it is angularly offset from the support surface. The broad and indefinite scope of the limitation fails to inform a person of ordinary skill in the art with reasonable certainty of the metes and bounds of the claimed invention, therefore the claim is rendered indefinite. For purposes of examination, it is being interpreted as referring to any surface that is angularly offset from the supporting surface. Claims 18-20 and 23 are also rejected due to their dependence on claim 15.
Further regarding claim 15, the claim recites the limitation “the support surface” in line 6. It is unclear if this limitation is meant to refer to the supporting surfaces from line 4, or a different support surface. If it is meant to refer to the plurality of supporting surfaces, it should read “the supporting surface”. If it is meant to refer to a different support surface, it needs to be distinguished from the supporting surfaces from line 4. For purposes of examination, it is being interpreted as referring to the plurality of support surfaces from line 4. Claims 18-20 and 23 are also rejected due to their dependence on claim 15.
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.
The factual inquiries 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 1, 7, 11-15, and 18-23 are rejected under 35 U.S.C. 103 as being unpatentable over Pearlman (US 20180008168) in view of Siegel (US 3961675).
Regarding independent claim 1, Pearlman teaches a system for measuring data specific to a subject using gravity ([0002]: “The present invention pertains to systems for physical and health related parameters, and in particular, to a monitoring system, such as a weight management system, that may be integrated within a piece of furniture such as a bed.”), the system comprising:
a bay (Fig. 1 shows the bed, and the location that the bed is in is the bay).
However, Pearlman does not teach a plurality of supporting surfaces, and for each supporting surface, a corresponding loading surface angularly offset from the support surface; wherein each supporting surface is configured to receive one of multiple wheels of a substrate on which the subject lies, the substrate having i) multiple legs extending from the substrate to a floor to support the substrate, and ii) the multiple wheels each shaped to allow the substrate to be wheeled, wherein each of the legs is attached to one of the wheels.
Siegel discloses a portable housing for weighing systems. Specifically, Siegel teaches a plurality of supporting surfaces (receptacles 20 and 22, which are located on both ends of the bed), and for each supporting surface, a corresponding loading surface angularly offset from the support surface (front walls 36 and 38, which form the entrance portions 32 and 34, which are angularly offset from the supporting surfaces); wherein each supporting surface is configured to receive one of multiple wheels of a substrate on which the subject lies (Fig. 1 shows the receptacles 30 and 22 receiving the wheels), the substrate having i) multiple legs extending from the substrate to a floor to support the substrate (Fig. 6 shows the bed (the substrate) having four legs), and ii) the multiple wheels each shaped to allow the substrate to be wheeled, wherein each of the legs is attached to one of the wheels (Fig. 6 shows each leg having a wheel). Pearlman and Siegel are analogous art as they are both related to bed weighing systems.
Therefore, it would have been obvious to a person having ordinary skill in the art before the effective filing date of the invention to include the plurality of supporting surfaces form Siegel into the system from Pearlman as it allows a specific loading location for the device, which provides a specific location to be used for measurement. Additionally, the loading surface angularly offset from the support surface allows for a ramp to be created, so that the bed can easily be placed on the support surface. Incorporating the wheels also allows the substrate to be mobile, which can allow for the user to be moved around without having to remove them from the bed.
The Pearlman/Siegel combination teaches a cap of a load sensor assembly (Pearlman, [0010]: “the present invention provides a load cell apparatus for use with a bed”; [0010]: “a housing having a top portion and a bottom portion and a load cell device held by the bottom portion of the housing”. The top portion is the cap).
However, the Pearlman. However, the Pearlman/Siegel combination does not teach wherein each supporting surface comprises a fixed portion coplanar with a cap of a load sensor assembly, the load sensor assembly positioned in the supporting surface to support one of the wheels.
Siegel teaches wherein each supporting surface comprises a fixed portion coplanar with a top of a load sensor assembly, the load sensor assembly positioned in the supporting surface to support one of the wheels (Column 2, lines 37-43: “The housing 10 comprises an elongated box-like apparatus 11 having a central section 12 and two end sections 16 and 18 each of which contains at least one operably positioned weight responsive element 14. In the particular embodiment shown elements 14 each extend at least partially from the bottom surface of the end sections 16 and 18”. The weight responsive element is the load sensor assembly, which is coplanar to the sections 16 and 18, which include the receptacles 20 and 22, as shown in Fig. 1).
Therefore, it would have been obvious to a person having ordinary skill in the art before the effective filing date of the invention to include the location of the load sensor assembly from Siegel into the Pearlman/Siegel combination as it is a simple rearrangement of parts to place the load sensor assembly in the supporting surfaces, as it will provide the same results for measurement.
The Pearlman/Seigel combination teaches the cap, wherein the cap is configured to receive a load from the substrate (the cap is underneath the receptacle that receives the load from the substrate, therefore the cap would receive the load as well);
a base configured to provide contact with the floor (Pearlman, [0050]: “bottom housing portion 32 includes a base member 34 having an outer wall 36 extending upwardly therefrom”. The base member is the base), the base and cap configured to fit together to maintain alignment of the cap to the base while allowing vertical movement of the cap (Pearlman, [0067]: “bottom housing portion 104 includes a plurality of channel members 109 that are each structured to receive and hold a respective pin member 106 in a manner which holds the pin member 106 in place horizontally but allows for vertical movement.”);
a load cell between the base and the cap, one of the base and cap configured to translate the load to the load cell (Pearlman, [0067]: “Load cell assembly 108 may be substituted for load cell assembly 8 in the various embodiments described herein. Load cell assembly 108 includes a disk-shaped housing that includes a top housing portion 102 that is similar in structure to top housing portion 32 that is coupled to a bottom housing portion 104. Top housing portion 102 and bottom housing portion 104 of the present alternative embodiment are structured to house and support the various components of load cell assembly 108, which include a load cell 44”); and
a printed circuit board that processes and outputs data from the load cell (Pearlman, [0051]: “load cell 44 includes a load cell cantilever piece 48 as shown in FIG. 8, which may be made of steel or any other suitable material. Load cell cantilever piece 48 includes an outer support frame portion 50 having a cantilever portion 52 extending therefrom and into an interior thereof. Cantilever portion 52 includes a proximal end 54 and a distal end 56. As seen in FIG. 3, load cell 44 further includes a number of strain gauges 58 that are provided on the surface of proximal end 54 of cantilever portion 52. In one particular exemplary embodiment, strain gauges 58 are provided on both the top and the bottom surfaces of proximal end 54. Strain gauges 58 are electrically connected to the electronic components provided on printed circuit board 46 such that measurements made by strain gauges 58 are communicated to printed circuit board 46 for further processing and/or transmission thereof as described herein.”), wherein a combination of all of the load sensor assemblies receive the load to which the substrate is subjected (Pearlman, [0011]: “The load cell apparatus may include a support mechanism, such as a flexible member provided between the top portion of the housing and the bottom portion of the housing or a series of flexible diaphragm or bushings held by the housing, that is meant to eliminate off-axis forces being transferred through the body of the housing. That is, this design is tailored to ensure all of the force transferred from the bed leg passes directly into the tab load-cell”).
Regarding claim 7, the Pearlman/Siegel combination teaches the system of claim 1, wherein the cap has a single sidewall and the base has a double sidewall configured to receive the single sidewall of the cap, the double sidewall configured to restrain the cap from lateral movement while allowing movement in a vertical direction (Pearlman, [0050]: “bottom housing portion 32 includes a base member 34 having an outer wall 36 extending upwardly therefrom. Base member 34 includes a recessed pocket 38, and outer wall 36 includes a ledge portion 40 adjacent recessed pocket 38. In the exemplary embodiment, recessed pocket 38 is structured to receive and securely hold a mounting tray 42 as shown in FIG. 1. Mounting tray 42 is, in turn, structured to receive and hold a load cell 44 as seen in FIGS. 3 and 4. Furthermore, ledge portion 40 is structured to receive and hold a printed circuit board 46 (that includes thereon appropriate measurement, control and communications electronics) as shown in FIGS. 3 and 4. Load cell 44 and printed circuit board 46 are structured to, in cooperation with other parts of load cell assembly 8 described herein, generate the force indicative signals that are described elsewhere herein.”; [0068]: “Top housing portion 112 and bottom housing portion 114 are structured such that outer wall 120 of bottom housing portion 114 engages the flange member 116 but allows relative vertical movement between the 2 components”; Fig. 21).
Regarding claim 11, the Pearlman/Siegel combination teaches the system of claim 1, further comprising a controller in communication with each of the load sensor assemblies (Pearlman, [0048]: “processor apparatus 14 comprises a processor 26 and a memory 28. Processor 26 may be, for example and without limitation, a microprocessor (μP), a microcontroller, an application specific integrated circuit (ASIC), or some other suitable processing device, that interfaces with memory 28”), the controller configured to collect signals from each of the load sensor assemblies and determine a center of mass of the subject on the substrate (Pearlman, [0059]: “center of pressure could be determined by identifying the average location of the weight and monitoring whether that average location moves by a certain percentage or distance (assuming the bed size is known)”; [0060]: “changes in such weight distribution are monitored for conditions that indicate that a fall out of bed 4 is imminent, such as the center of pressure of an occupant of bed 12 approaching the edge of bed 12”).
Regarding claim 12, the Pearlman/Siegel combination teaches the system of claim 1, further comprising a controller in communication with each of the load sensor assemblies (Pearlman, [0048]: “processor apparatus 14 comprises a processor 26 and a memory 28. Processor 26 may be, for example and without limitation, a microprocessor (μP), a microcontroller, an application specific integrated circuit (ASIC), or some other suitable processing device, that interfaces with memory 28”) and at least one external device in communication with the controller (Pearlman, [0066]: “Patient monitoring system 100 further includes a remote computing device in the form of central control and monitoring unit 104, which may be located at, for example without limitation, a nurse's station”), the controller configured to:
collect signals from each of the load sensor assemblies (Pearlman, [0066]: “the control unit 10 of each bed monitor 102 is structured to receive the signal generated by each of the load cell assemblies 8 associated therewith”);
determine if the subject is asleep or awake (Pearlman, [0016]: “The data could be used by the person who uses the bed or be passed to other family members (for example, to monitor whether grandma is sleeping, etc.) or clinicians to monitor behavior”); and
control the at least one external device based on whether the subject is asleep or awake (Pearlman, [0063]: “FIG. 25 is a top-level schematic illustrating an exemplary machine learning algorithm as just described implemented in monitoring system 2 according to another particular exemplary embodiment wherein weight, sleep quality, fall risk and pressure sore risk information, among others, may be monitored for two users. FIG. 25 illustrates the data variables, classifier, events, and alarm/outcome that may be implemented in such an embodiment. In addition, FIG. 26 is a flowchart 300 illustrating operation of such a machine learning algorithm according to one particular implementation. As seen in FIG. 26, operation of the machine learning algorithm includes a first branch 302 that is executed when one of the users enters or exits bed 4, and a second branch 304 that is executed when, instead, it is determined that a user of bed 4 has moved.”).
Regarding claim 13, the Pearlman/Siegel combination teaches the system of claim 1, further comprising a controller in communication with each of the load sensor assemblies (Pearlman, [0048]: “processor apparatus 14 comprises a processor 26 and a memory 28. Processor 26 may be, for example and without limitation, a microprocessor (μP), a microcontroller, an application specific integrated circuit (ASIC), or some other suitable processing device, that interfaces with memory 28”) and at least one external device in communication with the controller (Pearlman, [0066]: “Patient monitoring system 100 further includes a remote computing device in the form of central control and monitoring unit 104, which may be located at, for example without limitation, a nurse's station”), the controller configured to:
collect signals from each of the load sensor assemblies (Pearlman, [0066]: “the control unit 10 of each bed monitor 102 is structured to receive the signal generated by each of the load cell assemblies 8 associated therewith”);
determine that the subject previously on the substrate has exited the substrate (Pearlman, [0063]: “operation of the machine learning algorithm includes a first branch 302 that is executed when one of the users enters or exits bed 4, and a second branch 304 that is executed when, instead, it is determined that a user of bed 4 has moved.”); and
change a status of the at least one external device in response to the determination (Pearlman, [0063]: “FIG. 25 is a top-level schematic illustrating an exemplary machine learning algorithm as just described implemented in monitoring system 2 according to another particular exemplary embodiment wherein weight, sleep quality, fall risk and pressure sore risk information, among others, may be monitored for two users. FIG. 25 illustrates the data variables, classifier, events, and alarm/outcome that may be implemented in such an embodiment. In addition, FIG. 26 is a flowchart 300 illustrating operation of such a machine learning algorithm according to one particular implementation. As seen in FIG. 26, operation of the machine learning algorithm includes a first branch 302 that is executed when one of the users enters or exits bed 4, and a second branch 304 that is executed when, instead, it is determined that a user of bed 4 has moved.”).
Regarding claim 14, the Pearlman/Siegel combination teaches the system of claim 1, further comprising a controller in communication with each of the load sensor assemblies (Pearlman, [0048]: “processor apparatus 14 comprises a processor 26 and a memory 28. Processor 26 may be, for example and without limitation, a microprocessor (μP), a microcontroller, an application specific integrated circuit (ASIC), or some other suitable processing device, that interfaces with memory 28”) and at least one external device in communication with the controller (Pearlman, [0066]: “Patient monitoring system 100 further includes a remote computing device in the form of central control and monitoring unit 104, which may be located at, for example without limitation, a nurse's station”), the controller configured to:
collect signals from each of the load sensor assemblies (Pearlman, [0066]: “the control unit 10 of each bed monitor 102 is structured to receive the signal generated by each of the load cell assemblies 8 associated therewith”);
determine that the subject has laid down on the substrate (Pearlman, [0062]: “during a setup stage, each user (user 1 and user 2 in the present example) will set up a profile in processor apparatus 14 and then sit/rest on their side of the bed one at a time so that readings can be taken from each of the load cell assemblies 8. Next, during an operational stage, processing apparatus 14 will periodically receive and record weight data from each of the load cell assemblies 8 and determine the times at which the readings from the load cell assemblies 8 change. Processing apparatus 14 will then use the trained Naïve Bayes classifier to analyze the recorded data so that it will be able to segregate the data for any particular time into one of the four categories identified above. In addition, based on the categorization, processing apparatus 14 is able to determine and record individual weights for each of the users. In addition to recording weight information for each of the users individually, this classification mechanism may also be used to determine and store other parameters for each of the users individually), such as, without limitation, sleep quality and motion related data such as periods oi quiescence as described herein. In the example embodiment sleep quality is determined through activity, which is essentially the ratio of the amount of motion (in time) in bed normalized by the total time in bed.”); and
change a status of the at least one external device in response to the determination (Pearlman, [0063]: “FIG. 25 is a top-level schematic illustrating an exemplary machine learning algorithm as just described implemented in monitoring system 2 according to another particular exemplary embodiment wherein weight, sleep quality, fall risk and pressure sore risk information, among others, may be monitored for two users. FIG. 25 illustrates the data variables, classifier, events, and alarm/outcome that may be implemented in such an embodiment. In addition, FIG. 26 is a flowchart 300 illustrating operation of such a machine learning algorithm according to one particular implementation. As seen in FIG. 26, operation of the machine learning algorithm includes a first branch 302 that is executed when one of the users enters or exits bed 4, and a second branch 304 that is executed when, instead, it is determined that a user of bed 4 has moved.”).
Regarding independent claim 15, Pearlman teaches a system for measuring data specific to a subject using gravity ([0002]: “The present invention pertains to systems for physical and health related parameters, and in particular, to a monitoring system, such as a weight management system, that may be integrated within a piece of furniture such as a bed.”), the system comprising:
a bay (Fig. 1 shows the bed, and the location that the bed is in is the bay).
However, Pearlman does not teach a plurality of supporting surfaces, and for each supporting surface, a corresponding loading surface angularly offset from the support surface; wherein each supporting surface is configured to receive one of multiple wheels of a substrate on which the subject lies, the substrate having i) multiple legs extending from the substrate to a floor to support the substrate, and ii) the multiple wheels each shaped to allow the substrate to be wheeled, wherein each of the legs is attached to one of the wheels.
Siegel discloses a portable housing for weighing systems. Specifically, Siegel teaches a plurality of supporting surfaces (receptacles 20 and 22, which are located on both ends of the bed), and for each supporting surface, a corresponding loading surface angularly offset from the support surface (front walls 36 and 38, which form the entrance portions 32 and 34, which are angularly offset from the supporting surfaces); wherein each supporting surface is configured to receive one of multiple wheels of a substrate on which the subject rests (Fig. 1 shows the receptacles 30 and 22 receiving the wheels), the substrate having multiple legs extending from the substrate to a floor to support the substrate (Fig. 6 shows the bed (the substrate) having four legs), and ii) the multiple wheels each shaped to allow the substrate to be wheeled, wherein each of the legs is attached to one of the wheels (Fig. 6 shows each leg having a wheel). Pearlman and Siegel are analogous art as they are both related to bed weighing systems.
Therefore, it would have been obvious to a person having ordinary skill in the art before the effective filing date of the invention to include the plurality of supporting surfaces form Siegel into the system from Pearlman as it allows a specific loading location for the device, which provides a specific location to be used for measurement. Additionally, the loading surface angularly offset from the support surface allows for a ramp to be created, so that the bed can easily be placed on the support surface. Incorporating the wheels also allows the substrate to be mobile, which can allow for the user to be moved around without having to remove them from the bed.
The Pearlman/Siegel combination teaches a cap of a load sensor assembly (Pearlman, [0010]: “the present invention provides a load cell apparatus for use with a bed”; [0010]: “a housing having a top portion and a bottom portion and a load cell device held by the bottom portion of the housing”. The top portion is the cap).
However, the Pearlman. However, the Pearlman/Siegel combination does not teach wherein each supporting surface comprises a fixed portion coplanar with a cap of a load sensor assembly, the load sensor assembly positioned in the supporting surface to simultaneously support one of the wheels.
Siegel teaches wherein each supporting surface comprises a fixed portion coplanar with a top of at least two load sensor assemblies, each of the load sensor assemblies positioned in the supporting surface to support one of the wheels (Column 2, lines 37-43: “The housing 10 comprises an elongated box-like apparatus 11 having a central section 12 and two end sections 16 and 18 each of which contains at least one operably positioned weight responsive element 14. In the particular embodiment shown elements 14 each extend at least partially from the bottom surface of the end sections 16 and 18”. The weight responsive element is the load sensor assembly, which is coplanar to the sections 16 and 18, which include the receptacles 20 and 22, as shown in Fig. 1).
Therefore, it would have been obvious to a person having ordinary skill in the art before the effective filing date of the invention to include the location of the load sensor assembly from Siegel into the Pearlman/Siegel combination as it is a simple rearrangement of parts to place the load sensor assembly in the supporting surfaces, as it will provide the same results for measurement.
The Pearlman/Seigel combination teaches a controller (Pearlman, [0048]: “processor apparatus 14 comprises a processor 26 and a memory 28. Processor 26 may be, for example and without limitation, a microprocessor (μP), a microcontroller, an application specific integrated circuit (ASIC), or some other suitable processing device, that interfaces with memory 28”); and
communication means from each of the at least two load sensor assemblies to the controller (Pearlman, [0066]: “the control unit 10 of each bed monitor 102 is structured to receive the signal generated by each of the load cell assemblies 8 associated therewith”), wherein the controller processes output from each of the at least two load sensor assemblies (Pearlman, [0012]: “The system further includes a processing apparatus coupled to each of the load cell apparatuses that is structured to: (i) receive the signal generated by each of the load cell apparatuses, (ii) determine periods of quiescence based on the received signals, and (iii) determine a risk factor for pressure sores based on the periods of quiescence.”).
Regarding claim 18, the Pearlman/Siegel combination teaches the system of claim 15. further comprising at least one external device in communication with the controller (Pearlman, [0066]: “Patient monitoring system 100 further includes a remote computing device in the form of central control and monitoring unit 104, which may be located at, for example without limitation, a nurse's station”), the controller configured to:
collect signals from each of the load sensor assemblies (Pearlman, [0066]: “the control unit 10 of each bed monitor 102 is structured to receive the signal generated by each of the load cell assemblies 8 associated therewith”);
determine if the subject is asleep or awake (Pearlman, [0016]: “The data could be used by the person who uses the bed or be passed to other family members (for example, to monitor whether grandma is sleeping, etc.) or clinicians to monitor behavior”); and
control the at least one external device based on whether the subject is asleep or awake (Pearlman, [0063]: “FIG. 25 is a top-level schematic illustrating an exemplary machine learning algorithm as just described implemented in monitoring system 2 according to another particular exemplary embodiment wherein weight, sleep quality, fall risk and pressure sore risk information, among others, may be monitored for two users. FIG. 25 illustrates the data variables, classifier, events, and alarm/outcome that may be implemented in such an embodiment. In addition, FIG. 26 is a flowchart 300 illustrating operation of such a machine learning algorithm according to one particular implementation. As seen in FIG. 26, operation of the machine learning algorithm includes a first branch 302 that is executed when one of the users enters or exits bed 4, and a second branch 304 that is executed when, instead, it is determined that a user of bed 4 has moved.”).
Regarding claim 19, the Pearlman/Siegel combination teaches the system of claim 15, further comprising at least one external device in communication with the controller (Pearlman, [0066]: “Patient monitoring system 100 further includes a remote computing device in the form of central control and monitoring unit 104, which may be located at, for example without limitation, a nurse's station”), the controller configured to:
collect signals from each of the load sensor assemblies (Pearlman, [0066]: “the control unit 10 of each bed monitor 102 is structured to receive the signal generated by each of the load cell assemblies 8 associated therewith”);
determine that the subject previously on the substrate has exited the substrate (Pearlman, [0063]: “operation of the machine learning algorithm includes a first branch 302 that is executed when one of the users enters or exits bed 4, and a second branch 304 that is executed when, instead, it is determined that a user of bed 4 has moved.”); and
change a status of the at least one external device in response to the determination (Pearlman, [0063]: “FIG. 25 is a top-level schematic illustrating an exemplary machine learning algorithm as just described implemented in monitoring system 2 according to another particular exemplary embodiment wherein weight, sleep quality, fall risk and pressure sore risk information, among others, may be monitored for two users. FIG. 25 illustrates the data variables, classifier, events, and alarm/outcome that may be implemented in such an embodiment. In addition, FIG. 26 is a flowchart 300 illustrating operation of such a machine learning algorithm according to one particular implementation. As seen in FIG. 26, operation of the machine learning algorithm includes a first branch 302 that is executed when one of the users enters or exits bed 4, and a second branch 304 that is executed when, instead, it is determined that a user of bed 4 has moved.”).
Regarding claim 20, the Pearlman/Siegel combination teaches the system of claim 15, further comprising at least one external device in communication with the controller (Pearlman, [0066]: “Patient monitoring system 100 further includes a remote computing device in the form of central control and monitoring unit 104, which may be located at, for example without limitation, a nurse's station”), the controller configured to:
collect signals from each of the load sensor assemblies (Pearlman, [0066]: “the control unit 10 of each bed monitor 102 is structured to receive the signal generated by each of the load cell assemblies 8 associated therewith”);
determine that the subject has laid down on the substrate (Pearlman, [0062]: “during a setup stage, each user (user 1 and user 2 in the present example) will set up a profile in processor apparatus 14 and then sit/rest on their side of the bed one at a time so that readings can be taken from each of the load cell assemblies 8. Next, during an operational stage, processing apparatus 14 will periodically receive and record weight data from each of the load cell assemblies 8 and determine the times at which the readings from the load cell assemblies 8 change. Processing apparatus 14 will then use the trained Naïve Bayes classifier to analyze the recorded data so that it will be able to segregate the data for any particular time into one of the four categories identified above. In addition, based on the categorization, processing apparatus 14 is able to determine and record individual weights for each of the users. In addition to recording weight information for each of the users individually, this classification mechanism may also be used to determine and store other parameters for each of the users individually), such as, without limitation, sleep quality and motion related data such as periods oi quiescence as described herein. In the example embodiment sleep quality is determined through activity, which is essentially the ratio of the amount of motion (in time) in bed normalized by the total time in bed.”); and
change a status of the at least one external device in response to the determination (Pearlman, [0063]: “FIG. 25 is a top-level schematic illustrating an exemplary machine learning algorithm as just described implemented in monitoring system 2 according to another particular exemplary embodiment wherein weight, sleep quality, fall risk and pressure sore risk information, among others, may be monitored for two users. FIG. 25 illustrates the data variables, classifier, events, and alarm/outcome that may be implemented in such an embodiment. In addition, FIG. 26 is a flowchart 300 illustrating operation of such a machine learning algorithm according to one particular implementation. As seen in FIG. 26, operation of the machine learning algorithm includes a first branch 302 that is executed when one of the users enters or exits bed 4, and a second branch 304 that is executed when, instead, it is determined that a user of bed 4 has moved.”).
Regarding claim 21, the Pearlman/Siegel combination teaches the system of claim 1, wherein each supporting surface and corresponding loading surface are shaped to create a ramp from the floor to the cap that one of the wheels can be rolled from the floor to the cap (Siegel, Fig. 1, entrance portions 32 and 34).
Regarding claim 22, the Pearlman/Siegel combination teaches the system of claim 1, wherein a number of the multiple wheels of the substrate is the same number as the number of supporting surfaces and the number of loading surfaces (Fig. 6 shows 4 wheels, 4 supporting surfaces, and 4 loading surfaces).
Regarding claim 23, the Pearlman/Siegel combination teaches the system of claim 15, wherein each supporting surface and corresponding loading surface are shaped to create a ramp from the floor to the cap that one of the wheels can be rolled from the floor to the cap (Siegel, Fig. 1, entrance portions 32 and 34).
Response to Arguments
All of applicant’s argument regarding the rejections and objections previously set forth have been fully considered and are persuasive unless directly addressed subsequently.
Applicant’s amendments have overcome the 112 rejections, however the amendments have introduces new 112 rejections.
Applicant’s arguments with respect to the prior art rejections have been considered but are moot because the new ground of rejection does not rely on any reference applied in the prior rejection of record for any teaching or matter specifically challenged in the argument.
Conclusion
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/E.K.M./Examiner, Art Unit 3791
/MATTHEW KREMER/Primary Examiner, Art Unit 3791
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