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 .
Notice of Amendment
In response to the amendment filed on 12/26/2025, amended claims 1, 4-6, 8, 10-11, 13-16, 19-20, 22-25, and 27-28 and cancelled claims 2 and 17 are acknowledged. Claims 1, 3-16, and 18-28 remain pending. The following new and reiterated grounds of rejection are set forth:
Claim Rejections - 35 USC § 101
The text of those sections of Title 35, U.S. Code not included in this action can be found in a prior Office action.
Claims 25-28 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Specifically, representative claim 25 recites the abstract idea of analyzing information from a sensor array to identify one or more pathogens and determine a presences of infection in the wound, wherein the one or more pathogens are identified based on time-dependent patterns of changes of the one or more properties indicating corresponding pathogens. This judicial exception is not integrated into a practical application because, under the broadest reasonable interpretation, it amounts to a mental process - concepts performed in the human mind (including an observation, evaluation, judgment, opinion), or by a human using pen and paper.
The claim(s) does/do not include additional elements that are sufficient to amount to significantly more than the judicial exception because the step of “receive, from sensor array, information pertaining to detection of one or more gases emanating from one or more pathogens in a wound that produce an infection, wherein the sensor array includes sensing materials that change one or more properties in response to a presence of the one or more gases” is merely insignificant extra-solution activity, such as mere data gathering, recited at a high level of generality and/or in a well-understood, routine, and conventional way, of the information needed to carry out the claimed algorithm.
The claimed “sensor array” is well-understood, routine, and conventional in the art. They represent components and/or activities which would routinely be used in applying the abstract idea. As such, they do not meaningfully limit the claim, taken as a whole, to a particular application of the abstract idea; rather, the claim would tend to monopolize the abstract idea itself in practice. Evidence that such a sensor is well-understood, routine, and conventional is provided by Tumey (US Publication 2002/0143286 A1), specifically [0006] as well as the various other U.S. patents described therein.
The claimed “processor” and “memory device” are merely a generic computer components performing generic computer functions which are well-understood, routine, and conventional in the art; as such, they do not meaningfully limit the claim to be more than just the abstract idea. See also Intellectual Ventures I LLC v. Symantec Corp., 838 F.3d 1307, 1318, 120 USPQ2d 1353, 1360 (Fed. Cir. 2016) (‘‘[W]ith the exception of generic computer-implemented steps, there is nothing in the claims themselves that foreclose them from being performed by a human, mentally or with pen and paper.’’).
Regarding dependent claims 26 and 28, the limitations of these dependent claim(s) merely add details to the algorithm which forms the abstract idea, but does not contain any further “additional elements”. Thus, the dependent claim(s) are not significantly more than the extended abstract idea.
Regarding dependent claim 27 the limitations of these dependent claim(s) contain a further additional element, namely “a negative pressure source applies negative pressure to the wound to promote healing, the software further causes the at least one processor to: adjust a rate of the negative pressure source based on the information from the sensor array”. However, this additional element is not sufficient to make the claim as a whole amount to significantly more than the abstract idea because these elements and/or steps well-understood, routine, and conventional in the art. They represent components and/or activities which would routinely be used in applying the abstract idea (see Tumey: [0003] as well as the various other U.S. patents described therein).
In contrast, the amendments to independent claims 1 and 16 are now sufficient to overcome the previous rejection under 35 U.S.C. 101 because they recite additional elements that, at least in combination, amount to significantly more than the abstract idea. In particular, the amendments now recite a sensor array including sensors i) responsive to one or more gases emanating from one or more pathogens in a wound that produce an infection and ii) a physiological status of the subject, wherein the physiological status of the subject comprises one or more parameters selected from heart rate, pulse rate, respiratory rate, blood oxygen saturation, blood pressure, hydration level, brain activity, cranial pressure, and skin and body temperature. This combination of sensors in a sensor array can no longer be considered well-understood, routine, and conventional in the art.
Claim Rejections - 35 USC § 102
The text of those sections of Title 35, U.S. Code not included in this action can be found in a prior Office action.
Claim(s) 1-3, 5-18, 20-25, and 27-28 is/are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Locke et al. (US Patent No. 12,178,598 B2) (previously cited).
Regarding claim 1, Locke et al. discloses a method of detecting a wound infection in a subject comprising:
generating, by a sensor array (310, 315, 320, 325), electrical signals in response to conditions comprising one or more gases emanating from one or more pathogens in a wound that produce an infection and a physiological status of the subject (see col. 9, lines 17-28 – “In some embodiments, the sensor for detecting a particular type of VOCs present at a tissue site may be a chemical gas sensor which may detect different gases in an area, especially those gases which might be harmful to humans or animals. The chemical gas sensors may comprise many kinds of materials such as, for example, polymers, semiconductors, carbon graphites, and organic/inorganic composites which have been used as sensing materials to detect the targeted gases based on various sensing techniques and principles. Such chemical gas sensors may include, for example, acoustic wave gas sensors, resistive gas sensors, photoelectric gas sensors, and optical gas sensors” and col. 12, line 58-col. 13, line 21 – “For example, the sensor device 305 may comprise a first VOC sensor 310 and a second VOC sensor 315 configured to detect and/or measure one or more particular VOCs found in gases emitted from the tissue site. In one example embodiment, either one of the VOC sensors may be a FAIMS sensor available from Owlstone Medical Ltd. In another example embodiment, either one of the VOC sensors may be a sensor available from Alphasense similar to the FAIMS sensor. The FAIMS sensor in some embodiments may provide outputs or fingerprints associated with various VOCs indicative of protease levels which can be used to identify normal wound healing or non-healing wound conditions as described above. The FAIMS sensor in some other embodiments may provide other outputs or fingerprints associated with other VOCs indicative of other biomarkers which can be used to identify normal wound healing or non-healing wound conditions. Additionally or alternatively, the sensor device 305 may be configured to detect and/or measure other parameters or variables, such as, for example, pH of wound exudates, temperature, oxygen concentration, humidity, glucose levels within wound exudates, among others. For example, the sensor device 305 may further comprise a pH sensor 320 and a humidity/temperature sensor 325. Thus, in some embodiments, the sensor device 305 may include one or more individual sensors, such as a VOC sensor, pH sensor, blood sensor, glucose sensor, growth factor sensor, or another type of sensor. Additionally, the sensor device 305 may include one or more sensors for detecting and/or measuring various electrolyte levels at a tissue site through electrical resistance sensing”);
transmitting, from the sensor array, the electrical signals pertaining to the detection of one or more gases to a computing device comprising at least one processor, wherein the at least one sensor includes sensing materials that change one or more properties in response to a presence of the one or more gases (see col. 9, lines 17-28 – “In some embodiments, the sensor for detecting a particular type of VOCs present at a tissue site may be a chemical gas sensor which may detect different gases in an area, especially those gases which might be harmful to humans or animals. The chemical gas sensors may comprise many kinds of materials such as, for example, polymers, semiconductors, carbon graphites, and organic/inorganic composites which have been used as sensing materials to detect the targeted gases based on various sensing techniques and principles. Such chemical gas sensors may include, for example, acoustic wave gas sensors, resistive gas sensors, photoelectric gas sensors, and optical gas sensors”); and
analyzing, via at least one processor (130), the electrical signals to identify the one or more pathogens and determine a presence of the infection in the wound, wherein the one or more pathogens are identified based on time-dependent patterns of changes of the one or more properties indicating corresponding pathogens (see Figure 6 and col. 9, line 51-col. 10, line 9 – “Wound protease activity often times is a very useful measurement of how the healing of a wound is progressing. During the initial inflammation stage of the wound healing process, there may be a higher level of protease activity. Referring to FIG. 6, protease levels initially increase rapidly in the normal course of wound healing. For example, the protease levels may peak at about the third day, but begin to reduce by about the fifth day. Thus, a directionally-changing level of protease activity may be a good indicator of normal wound healing. Thus, a directionally-changing activity from a rapidly increasing level to a decreasing level may be an indicator of normal wound healing that a device such as the diagnostic module 160 is capable of detecting by sensing one or more VOCs. However, if the level of activity increases rapidly to an abnormally high level or if the duration of the raised activity continues beyond the initial stage, it may be a good indicator that the wound is not healing as efficiently as desired. More specifically, increased levels of MMPs, often times MMP-2 and MMP-9 proteases, are commonly found in non-healing wounds. Thus, elevated protease activity may be an indicator of poor wound progress, and a device, such as the diagnostic module 160 capable of detecting the levels of the wound proteases via one or more VOCs, may be a useful tool for providing real-time feedback of wound healing to a clinician” and col. 20, lines 44-53 – “The systems, apparatuses, and methods described herein may provide significant advantages. For example, the ability to detect the status of a wound would be of great benefit, as healing progress may be tracked, and accordingly, treatment may be optimized to expedite closure of the tissue site. By analyzing fluid drawn off from the wound for wound factors associated with the different stages of healing, wound healing progress can be assessed. Additionally, indications of infection may be identified, thus allowing the opportunity for prompt intervention”),
wherein the physiological status of the subject comprises one or more parameters selected from heart rate, pulse rate, respiratory rate, blood oxygen saturation, blood pressure, hydration level, brain activity, cranial pressure, and skin and body temperature (see col. 13, lines 8-21 – “Additionally or alternatively, the sensor device 305 may be configured to detect and/or measure other parameters or variables, such as, for example, pH of wound exudates, temperature, oxygen concentration, humidity, glucose levels within wound exudates, among others. For example, the sensor device 305 may further comprise a pH sensor 320 and a humidity/temperature sensor 325. Thus, in some embodiments, the sensor device 305 may include one or more individual sensors, such as a VOC sensor, pH sensor, blood sensor, glucose sensor, growth factor sensor, or another type of sensor. Additionally, the sensor device 305 may include one or more sensors for detecting and/or measuring various electrolyte levels at a tissue site through electrical resistance sensing and col. 19, lines 5-10 – “As previously discussed, parameters detected and/or measured by the one or more sensors may include pH of wound exudates, O2 concentration of tissue at the tissue site 415, temperature, humidity within the dressing 102, glucose level in wound exudates, as well as others”).
Regarding claim 3, Locke et al. discloses the one or more pathogens include two or more pathogens from a group of bacteria and fungi, and the method further comprises: detecting and differentiating the two or more pathogens in polymicrobial infections (see col. 9, lines 17-28 – “In some embodiments, the sensor for detecting a particular type of VOCs present at a tissue site may be a chemical gas sensor which may detect different gases in an area, especially those gases which might be harmful to humans or animals. The chemical gas sensors may comprise many kinds of materials such as, for example, polymers, semiconductors, carbon graphites, and organic/inorganic composites which have been used as sensing materials to detect the targeted gases based on various sensing techniques and principles. Such chemical gas sensors may include, for example, acoustic wave gas sensors, resistive gas sensors, photoelectric gas sensors, and optical gas sensors”, col. 12, line 58-col. 13, line 21 – “For example, the sensor device 305 may comprise a first VOC sensor 310 and a second VOC sensor 315 configured to detect and/or measure one or more particular VOCs found in gases emitted from the tissue site. In one example embodiment, either one of the VOC sensors may be a FAIMS sensor available from Owlstone Medical Ltd. In another example embodiment, either one of the VOC sensors may be a sensor available from Alphasense similar to the FAIMS sensor. The FAIMS sensor in some embodiments may provide outputs or fingerprints associated with various VOCs indicative of protease levels which can be used to identify normal wound healing or non-healing wound conditions as described above. The FAIMS sensor in some other embodiments may provide other outputs or fingerprints associated with other VOCs indicative of other biomarkers which can be used to identify normal wound healing or non-healing wound conditions. Additionally or alternatively, the sensor device 305 may be configured to detect and/or measure other parameters or variables, such as, for example, pH of wound exudates, temperature, oxygen concentration, humidity, glucose levels within wound exudates, among others. For example, the sensor device 305 may further comprise a pH sensor 320 and a humidity/temperature sensor 325. Thus, in some embodiments, the sensor device 305 may include one or more individual sensors, such as a VOC sensor, pH sensor, blood sensor, glucose sensor, growth factor sensor, or another type of sensor. Additionally, the sensor device 305 may include one or more sensors for detecting and/or measuring various electrolyte levels at a tissue site through electrical resistance sensing” and claim 3).
Regarding claim 5, Locke et al. discloses the sensor array is disposed within one of a wearable device, a portable device, a disposable device, and a wound dressing, and the method further comprises: monitoring pathogen growth in real-time from incubation, colonization, until infection (see col. 2, lines 1-18 – “For example, in some embodiments, a system for treating a tissue site may include a dressing, a negative-pressure source, a container, and a sensor module. The dressing may be adapted to be placed on the tissue site, and the negative-pressure source may be adapted to be fluidly coupled to the dressing. The container may be adapted to be fluidly coupled to the dressing and to the negative-pressure source and to receive fluid from the tissue site. The sensor module may be adapted to be exposed to gas associated with the fluid from the tissue site. The sensor module may comprise a first sensor configured to detect a condition of the tissue site and to generate a first output based on the detected condition. The first sensor may be configured to detect a first volatile organic compound. Additionally, the sensor module may further comprise a second sensor configured to detect a second volatile organic compound. In some embodiments, the sensor module may be positioned on the container” and col. 9, lines 34-38 – “The diagnostic module 160 may also be positioned at other points in the therapy system 100 such as, for example, as a component attached to the fluid conductor 116 or a component of the dressing interface 123”).
Regarding claim 6, Locke et al. discloses the sensor array is further configured to differentiate two or more pathogens in polymicrobial infections (see col. 9, lines 17-28 – “In some embodiments, the sensor for detecting a particular type of VOCs present at a tissue site may be a chemical gas sensor which may detect different gases in an area, especially those gases which might be harmful to humans or animals. The chemical gas sensors may comprise many kinds of materials such as, for example, polymers, semiconductors, carbon graphites, and organic/inorganic composites which have been used as sensing materials to detect the targeted gases based on various sensing techniques and principles. Such chemical gas sensors may include, for example, acoustic wave gas sensors, resistive gas sensors, photoelectric gas sensors, and optical gas sensors”, col. 12, line 58-col. 13, line 21 – “For example, the sensor device 305 may comprise a first VOC sensor 310 and a second VOC sensor 315 configured to detect and/or measure one or more particular VOCs found in gases emitted from the tissue site. In one example embodiment, either one of the VOC sensors may be a FAIMS sensor available from Owlstone Medical Ltd. In another example embodiment, either one of the VOC sensors may be a sensor available from Alphasense similar to the FAIMS sensor. The FAIMS sensor in some embodiments may provide outputs or fingerprints associated with various VOCs indicative of protease levels which can be used to identify normal wound healing or non-healing wound conditions as described above. The FAIMS sensor in some other embodiments may provide other outputs or fingerprints associated with other VOCs indicative of other biomarkers which can be used to identify normal wound healing or non-healing wound conditions. Additionally or alternatively, the sensor device 305 may be configured to detect and/or measure other parameters or variables, such as, for example, pH of wound exudates, temperature, oxygen concentration, humidity, glucose levels within wound exudates, among others. For example, the sensor device 305 may further comprise a pH sensor 320 and a humidity/temperature sensor 325. Thus, in some embodiments, the sensor device 305 may include one or more individual sensors, such as a VOC sensor, pH sensor, blood sensor, glucose sensor, growth factor sensor, or another type of sensor. Additionally, the sensor device 305 may include one or more sensors for detecting and/or measuring various electrolyte levels at a tissue site through electrical resistance sensing”, and claim 3).
Regarding claim 7, Locke et al. discloses the information from the at least one sensor is monitored in real-time (col. 10, lines 3-8 – “Thus, elevated protease activity may be an indicator of poor wound progress, and a device, such as the diagnostic module 160 capable of detecting the levels of the wound proteases via one or more VOCs, may be a useful tool for providing real-time feedback of wound healing to a clinician” and col. 18, lines 6-13 – “Therefore, it is desirable to utilize the first VOC sensor 310 and the second VOC sensor 315 to monitor the VOCs that may be present in the gas chamber 225 and use the outputs or fingerprints from the VOCs sensors to determine the level of MMPs at the tissue site 415 in real time during therapy treatments to help guide appropriate management of the instillation and negative pressure fluids during therapy”).
Regarding claim 8, Locke et al. discloses the at least one sensor is disposed within a wound dressing, and the wound dressing and the sensor array is configured for disposable use (see col. 9, lines 34-38 – “The diagnostic module 160 may also be positioned at other points in the therapy system 100 such as, for example, as a component attached to the fluid conductor 116 or a component of the dressing interface 123”).
Regarding claim 9, Locke et al. discloses the one or more properties of the sensing materials that change include electrical conductivity, capacitance, resistance, or impedance (see col. 9, lines 26-28 – “Such chemical gas sensors may include, for example, acoustic wave gas sensors, resistive gas sensors, photoelectric gas sensors, and optical gas sensors” and col. 13, lines 18-21 – “Additionally, the sensor device 305 may include one or more sensors for detecting and/or measuring various electrolyte levels at a tissue site through electrical resistance sensing”).
Regarding claim 10, Locke et al. discloses providing alerts or notifications to healthcare providers or the subject based on output from the microprocessor using the electrical signals from the sensor array (see col. 10, lines 3-8 – “Thus, elevated protease activity may be an indicator of poor wound progress, and a device, such as the diagnostic module 160 capable of detecting the levels of the wound proteases via one or more VOCs, may be a useful tool for providing real-time feedback of wound healing to a clinician” and col. 15, lines 53-61 – “In situations where the tissue site 415 may be determined to be in a chronic or inflammatory state, the controller 130 may be programmed to alert a user of the therapy system 100 as to the status of the tissue site 415 so that the user may take one or more actions to address or remedy the status of the tissue site 415. In some embodiments, the controller 130 may be programmed to generate an output or alert to a user in order to direct the user to administer one or more forms of therapy”).
Regarding claim 11, Locke et al. discloses the one or more pathogens include at least one from a group of bacteria and fungi, and wherein analyzing further comprises identifying the one or more pathogens based on time-dependent patterns of changes of the one or more properties corresponding to the bacteria and fungi (see Figure 6 and col. 9, lines 17-28 – “In some embodiments, the sensor for detecting a particular type of VOCs present at a tissue site may be a chemical gas sensor which may detect different gases in an area, especially those gases which might be harmful to humans or animals. The chemical gas sensors may comprise many kinds of materials such as, for example, polymers, semiconductors, carbon graphites, and organic/inorganic composites which have been used as sensing materials to detect the targeted gases based on various sensing techniques and principles. Such chemical gas sensors may include, for example, acoustic wave gas sensors, resistive gas sensors, photoelectric gas sensors, and optical gas sensors”, col. 12, line 58-col. 13, line 21 – “For example, the sensor device 305 may comprise a first VOC sensor 310 and a second VOC sensor 315 configured to detect and/or measure one or more particular VOCs found in gases emitted from the tissue site. In one example embodiment, either one of the VOC sensors may be a FAIMS sensor available from Owlstone Medical Ltd. In another example embodiment, either one of the VOC sensors may be a sensor available from Alphasense similar to the FAIMS sensor. The FAIMS sensor in some embodiments may provide outputs or fingerprints associated with various VOCs indicative of protease levels which can be used to identify normal wound healing or non-healing wound conditions as described above. The FAIMS sensor in some other embodiments may provide other outputs or fingerprints associated with other VOCs indicative of other biomarkers which can be used to identify normal wound healing or non-healing wound conditions. Additionally or alternatively, the sensor device 305 may be configured to detect and/or measure other parameters or variables, such as, for example, pH of wound exudates, temperature, oxygen concentration, humidity, glucose levels within wound exudates, among others. For example, the sensor device 305 may further comprise a pH sensor 320 and a humidity/temperature sensor 325. Thus, in some embodiments, the sensor device 305 may include one or more individual sensors, such as a VOC sensor, pH sensor, blood sensor, glucose sensor, growth factor sensor, or another type of sensor. Additionally, the sensor device 305 may include one or more sensors for detecting and/or measuring various electrolyte levels at a tissue site through electrical resistance sensing”, and claim 3).
Regarding claim 12, Locke et al. discloses the one or more pathogens include at least one from a group of bacteria and fungi, wherein the bacteria include Escherichia coli, Salmonella enterica, Staphylococcus aureus, Streptococcus pneumoniae, Streptococcus pyogenes, Neisseria gonorrhoeae, Neisseria meningitidis, Haemophilus influenzae, Pseudomonas aeruginosa, Klebsiella pneumoniae, Enterococcus faecalis, Enterococcus faecium, Clostridioides difficile, Campylobacter jejuni, Listeria monocytogenes, Vibrio cholerae, Vibrio parahaemolyticus, Mycobacterium tuberculosis, Mycobacterium leprae, Helicobacter pylori, Bordetella pertussis, Legionella pneumophila, Shigella spp., Yersinia pestis, Francisella tularensis, Brucella spp., Borrelia burgdorferi, Chlamydia trachomatis, Chlamydia pneumoniae, Coxiella burnetiid, Rickettsia rickettsia, Rickettsia prowazekii, Bartonella henselae, Burkholderia pseudomallei, Burkholderia mallei, Acinetobacter baumannii, Moraxella catarrhalis, Nocardia spp., Propionibacterium acnes, Actinomyces spp., Treponema pallidum, Treponema denticola, Fusobacterium spp., Porphyromonas spp., Prevotella spp., Bacteroides fragilis, Bacteroides thetaiotaomicron, Capnocytophaga spp., Pasteurella multocida, Actinobacillus spp., Streptobacillus moniliformis, Erysipelothrix rhusiopathiae, Lactobacillus spp., Corynebacterium diphtheriae, Corynebacterium jeikeium, Nocardia asteroids, Mycoplasma pneumoniae, Ureaplasma urealyticum, Legionella longbeachae, Legionella bozemanii, Legionella dumoffli, Legionella micdadei, Legionella anisa, Legionella feeleii, Legionella gormanii, Legionella jordanis, Legionella londiniensis, Legionella maceachernii, Legionella oakridgensis, Legionella quateirensis, Legionella rubrilucens, Legionella sainthelensi, Legionella steigerwaltii, Legionella taurinensis, and Legionella wadsworthii, and the fungi include Candida albicans, Aspergillus fumigatus, Cryptococcus neoformans, Histoplasma capsulatum, Blastomyces dermatitidis, Coccidioides immitis, Candida glabrata, Candida tropicalis, Candida parapsilosis, Candida krusei, Trichophyton rubrum, Trichophyton mentagrophytes, Microsporum canis, Epidermophyton floccosum, Pneumocystisjirovecii, Fusarium solani, Fusarium oxysporum, Rhizopus oryzae, Mucor spp., Scedosporium prolificans, Sporothrix schenckii, Paracoccidioides brasiliensis, Candida dubliniensis, Candida lusitaniae, Candida guilliermondii, Candida kefyr, Candida famata, Candida lipolytica, Candida utilis, Candida zeylanoides, Candida rugosa, Candida norvegensis, Candida pelliculosa, Candida sake Candida stellatoidea, Candida zonata, Aspergillus flavus, Aspergillus niger, Aspergillus terreus, Candida haemulonii, Candida orthopsilosis, Candida metapsilosis, Candida auris, Trichosporon asahii, Trichosporon cutaneum, Trichosporon mucoides, Trichosporon ovoides, Trichosporon asteroid, Geotrichum candidum, Geotrichum capitatum, Paecilomyces spp., Acremonium spp., Alternaria spp., Cladosporium spp., Penicillium spp., Aspergillus nidulans, Aspergillus versicolor, Exophiala dermatitidis, Exophiala jeanselmei, Exophiala spinifera, Exophiala xenobiotica, Candida utilis var. utilis, Candida glabrata var. bracarensis, Trichosporon dohaense, Trichosporon domesticum, Trichosporon j aponicum, Trichosporon monihiforme, Trichosporon mucoidum, Trichosporon pullulans, Rhizomucor pusillus, Rhizomucor variabilis, Cunninghamella bertholletiae, Cunninghamella echinulate, Cunninghamella blakesleeana, Absidia corymbifera, Mucor circinelloides, Mucor racemosus, Saksenaea vasiformis, Rhizopus microspores, and Rhizopus spp (see col. 9, lines 17-28 – “In some embodiments, the sensor for detecting a particular type of VOCs present at a tissue site may be a chemical gas sensor which may detect different gases in an area, especially those gases which might be harmful to humans or animals. The chemical gas sensors may comprise many kinds of materials such as, for example, polymers, semiconductors, carbon graphites, and organic/inorganic composites which have been used as sensing materials to detect the targeted gases based on various sensing techniques and principles. Such chemical gas sensors may include, for example, acoustic wave gas sensors, resistive gas sensors, photoelectric gas sensors, and optical gas sensors”, col. 12, line 58-col. 13, line 21 – “For example, the sensor device 305 may comprise a first VOC sensor 310 and a second VOC sensor 315 configured to detect and/or measure one or more particular VOCs found in gases emitted from the tissue site. In one example embodiment, either one of the VOC sensors may be a FAIMS sensor available from Owlstone Medical Ltd. In another example embodiment, either one of the VOC sensors may be a sensor available from Alphasense similar to the FAIMS sensor. The FAIMS sensor in some embodiments may provide outputs or fingerprints associated with various VOCs indicative of protease levels which can be used to identify normal wound healing or non-healing wound conditions as described above. The FAIMS sensor in some other embodiments may provide other outputs or fingerprints associated with other VOCs indicative of other biomarkers which can be used to identify normal wound healing or non-healing wound conditions. Additionally or alternatively, the sensor device 305 may be configured to detect and/or measure other parameters or variables, such as, for example, pH of wound exudates, temperature, oxygen concentration, humidity, glucose levels within wound exudates, among others. For example, the sensor device 305 may further comprise a pH sensor 320 and a humidity/temperature sensor 325. Thus, in some embodiments, the sensor device 305 may include one or more individual sensors, such as a VOC sensor, pH sensor, blood sensor, glucose sensor, growth factor sensor, or another type of sensor. Additionally, the sensor device 305 may include one or more sensors for detecting and/or measuring various electrolyte levels at a tissue site through electrical resistance sensing”, and claim 3).
Regarding claim 13, Locke et al. discloses the sensor array is disposed within a wound dressing (see col. 9, lines 34-38 – “The diagnostic module 160 may also be positioned at other points in the therapy system 100 such as, for example, as a component attached to the fluid conductor 116 or a component of the dressing interface 123”), and the method further comprises: applying negative pressure to the wound, via a negative pressure source (105), to promote healing (see col. 17, lines 42-45 – “The controller 130 may also use feedback from the diagnostic module 160 to vary the level of negative pressure supplied by the negative-pressure source 105 to the tissue site 415”).
Regarding claim 14, Locke et al. discloses adjusting a rate of the negative pressure source based on the information from the sensor array (see col. 17, lines 42-45 – “The controller 130 may also use feedback from the diagnostic module 160 to vary the level of negative pressure supplied by the negative-pressure source 105 to the tissue site 415”).
Regarding claim 15, Locke et al. discloses determining, via the at least one processor, a treatment for the wound based on the information from the sensor array (see col. 16, lines 17-24 – “Furthermore, in some embodiments, the controller 130 may be programmed to automatically direct that one or more types of therapy to the tissue site 415 could be initiated, adjusted, or stopped. In some embodiments, the controller 130 may automatically make changes to one or more forms of therapy, and thus the adjustments to the therapy may be triggered independently of an operator of the therapy system 100”).
Regarding claim 16, Locke et al. discloses a system for detecting a wound infection in a subject comprising:
a sensor array (310, 315, 320, 325) comprising a plurality of volatile organic compound (VOC) sensors (310, 315) and one or more physiological sensors (320, 325) wherein each VOC sensor comprises a sensor material that changes one or more properties in response to a presence of the one or more VOC gases and each physiological sensor is configured to detect a physiological status (see col. 9, lines 17-28 – “In some embodiments, the sensor for detecting a particular type of VOCs present at a tissue site may be a chemical gas sensor which may detect different gases in an area, especially those gases which might be harmful to humans or animals. The chemical gas sensors may comprise many kinds of materials such as, for example, polymers, semiconductors, carbon graphites, and organic/inorganic composites which have been used as sensing materials to detect the targeted gases based on various sensing techniques and principles. Such chemical gas sensors may include, for example, acoustic wave gas sensors, resistive gas sensors, photoelectric gas sensors, and optical gas sensors” and col. 12, line 58-col. 13, line 21 – “For example, the sensor device 305 may comprise a first VOC sensor 310 and a second VOC sensor 315 configured to detect and/or measure one or more particular VOCs found in gases emitted from the tissue site. In one example embodiment, either one of the VOC sensors may be a FAIMS sensor available from Owlstone Medical Ltd. In another example embodiment, either one of the VOC sensors may be a sensor available from Alphasense similar to the FAIMS sensor. The FAIMS sensor in some embodiments may provide outputs or fingerprints associated with various VOCs indicative of protease levels which can be used to identify normal wound healing or non-healing wound conditions as described above. The FAIMS sensor in some other embodiments may provide other outputs or fingerprints associated with other VOCs indicative of other biomarkers which can be used to identify normal wound healing or non-healing wound conditions. Additionally or alternatively, the sensor device 305 may be configured to detect and/or measure other parameters or variables, such as, for example, pH of wound exudates, temperature, oxygen concentration, humidity, glucose levels within wound exudates, among others. For example, the sensor device 305 may further comprise a pH sensor 320 and a humidity/temperature sensor 325. Thus, in some embodiments, the sensor device 305 may include one or more individual sensors, such as a VOC sensor, pH sensor, blood sensor, glucose sensor, growth factor sensor, or another type of sensor. Additionally, the sensor device 305 may include one or more sensors for detecting and/or measuring various electrolyte levels at a tissue site through electrical resistance sensing”);
at least one processor (130) configured to: analyze electrical signals from the sensor array to identify the one or more pathogens and determine a presence of the infection in the wound, and the physiological status (see col. 9, lines 17-28 – “In some embodiments, the sensor for detecting a particular type of VOCs present at a tissue site may be a chemical gas sensor which may detect different gases in an area, especially those gases which might be harmful to humans or animals. The chemical gas sensors may comprise many kinds of materials such as, for example, polymers, semiconductors, carbon graphites, and organic/inorganic composites which have been used as sensing materials to detect the targeted gases based on various sensing techniques and principles. Such chemical gas sensors may include, for example, acoustic wave gas sensors, resistive gas sensors, photoelectric gas sensors, and optical gas sensors” and col. 12, line 58-col. 13, line 21 – “For example, the sensor device 305 may comprise a first VOC sensor 310 and a second VOC sensor 315 configured to detect and/or measure one or more particular VOCs found in gases emitted from the tissue site. In one example embodiment, either one of the VOC sensors may be a FAIMS sensor available from Owlstone Medical Ltd. In another example embodiment, either one of the VOC sensors may be a sensor available from Alphasense similar to the FAIMS sensor. The FAIMS sensor in some embodiments may provide outputs or fingerprints associated with various VOCs indicative of protease levels which can be used to identify normal wound healing or non-healing wound conditions as described above. The FAIMS sensor in some other embodiments may provide other outputs or fingerprints associated with other VOCs indicative of other biomarkers which can be used to identify normal wound healing or non-healing wound conditions. Additionally or alternatively, the sensor device 305 may be configured to detect and/or measure other parameters or variables, such as, for example, pH of wound exudates, temperature, oxygen concentration, humidity, glucose levels within wound exudates, among others. For example, the sensor device 305 may further comprise a pH sensor 320 and a humidity/temperature sensor 325. Thus, in some embodiments, the sensor device 305 may include one or more individual sensors, such as a VOC sensor, pH sensor, blood sensor, glucose sensor, growth factor sensor, or another type of sensor. Additionally, the sensor device 305 may include one or more sensors for detecting and/or measuring various electrolyte levels at a tissue site through electrical resistance sensing”),
wherein the one or more pathogens are identified based on time-dependent patterns of changes of the one or more properties indicating corresponding pathogens (see Figure 6 and col. 9, line 51-col. 10, line 9 – “Wound protease activity often times is a very useful measurement of how the healing of a wound is progressing. During the initial inflammation stage of the wound healing process, there may be a higher level of protease activity. Referring to FIG. 6, protease levels initially increase rapidly in the normal course of wound healing. For example, the protease levels may peak at about the third day, but begin to reduce by about the fifth day. Thus, a directionally-changing level of protease activity may be a good indicator of normal wound healing. Thus, a directionally-changing activity from a rapidly increasing level to a decreasing level may be an indicator of normal wound healing that a device such as the diagnostic module 160 is capable of detecting by sensing one or more VOCs. However, if the level of activity increases rapidly to an abnormally high level or if the duration of the raised activity continues beyond the initial stage, it may be a good indicator that the wound is not healing as efficiently as desired. More specifically, increased levels of MMPs, often times MMP-2 and MMP-9 proteases, are commonly found in non-healing wounds. Thus, elevated protease activity may be an indicator of poor wound progress, and a device, such as the diagnostic module 160 capable of detecting the levels of the wound proteases via one or more VOCs, may be a useful tool for providing real-time feedback of wound healing to a clinician” and col. 20, lines 44-53 – “The systems, apparatuses, and methods described herein may provide significant advantages. For example, the ability to detect the status of a wound would be of great benefit, as healing progress may be tracked, and accordingly, treatment may be optimized to expedite closure of the tissue site. By analyzing fluid drawn off from the wound for wound factors associated with the different stages of healing, wound healing progress can be assessed. Additionally, indications of infection may be identified, thus allowing the opportunity for prompt intervention”),
wherein the physiological status of the subject comprises one or more parameters selected from heart rate, pulse rate, respiratory rate, blood oxygen saturation, blood pressure, hydration level, brain activity, cranial pressure, and skin and body temperature (see col. 13, lines 8-21 – “Additionally or alternatively, the sensor device 305 may be configured to detect and/or measure other parameters or variables, such as, for example, pH of wound exudates, temperature, oxygen concentration, humidity, glucose levels within wound exudates, among others. For example, the sensor device 305 may further comprise a pH sensor 320 and a humidity/temperature sensor 325. Thus, in some embodiments, the sensor device 305 may include one or more individual sensors, such as a VOC sensor, pH sensor, blood sensor, glucose sensor, growth factor sensor, or another type of sensor. Additionally, the sensor device 305 may include one or more sensors for detecting and/or measuring various electrolyte levels at a tissue site through electrical resistance sensing and col. 19, lines 5-10 – “As previously discussed, parameters detected and/or measured by the one or more sensors may include pH of wound exudates, O2 concentration of tissue at the tissue site 415, temperature, humidity within the dressing 102, glucose level in wound exudates, as well as others”).
Regarding claim 18, Locke et al. discloses the one or more pathogens include at least one from a group of bacteria and fungi, wherein the bacteria include Escherichia coli, Salmonella enterica, Staphylococcus aureus, Streptococcus pneumoniae, Streptococcus pyogenes, Neisseria gonorrhoeae, Neisseria meningitidis, Haemophilus influenzae, Pseudomonas aeruginosa, Klebsiella pneumoniae, Enterococcus faecalis, Enterococcus faecium, Clostridioides difficile, Campylobacter jejuni, Listeria monocytogenes, Vibrio cholerae, Vibrio parahaemolyticus, Mycobacterium tuberculosis, Mycobacterium leprae, Helicobacter pylori, Bordetella pertussis, Legionella pneumophila, Shigella spp., Yersinia pestis, Francisella tularensis, Brucella spp., Borrelia burgdorferi, Chlamydia trachomatis, Chlamydia pneumoniae, Coxiella burnetiid, Rickettsia rickettsia, Rickettsia prowazekii, Bartonella henselae, Burkholderia pseudomallei, Burkholderia mallei, Acinetobacter baumannii, Moraxella catarrhalis, Nocardia spp., Propionibacterium acnes, Actinomyces spp., Treponema pallidum, Treponema denticola, Fusobacterium spp., Porphyromonas spp., Prevotella spp., Bacteroides fragilis, Bacteroides thetaiotaomicron, Capnocytophaga spp., Pasteurella multocida, Actinobacillus spp., Streptobacillus moniliformis, Erysipelothrix rhusiopathiae, Lactobacillus spp., Corynebacterium diphtheriae, Corynebacterium jeikeium, Nocardia asteroids, Mycoplasma pneumoniae, Ureaplasma urealyticum, Legionella longbeachae, Legionella bozemanii, Legionella dumoffli, Legionella micdadei, Legionella anisa, Legionella feeleii, Legionella gormanii, Legionella jordanis, Legionella londiniensis, Legionella maceachernii, Legionella oakridgensis, Legionella quateirensis, Legionella rubrilucens, Legionella sainthelensi, Legionella steigerwaltii, Legionella taurinensis, and Legionella wadsworthii, and the fungi include Candida albicans, Aspergillus fumigatus, Cryptococcus neoformans, Histoplasma capsulatum, Blastomyces dermatitidis, Coccidioides immitis, Candida glabrata, Candida tropicalis, Candida parapsilosis, Candida krusei, Trichophyton rubrum, Trichophyton mentagrophytes, Microsporum canis, Epidermophyton floccosum, Pneumocystis jirovecii, Fusarium solani, Fusarium oxysporum, Rhizopus oryzae, Mucor spp., Scedosporium prolificans, Sporothrix schenckii, Paracoccidioides brasiliensis, Candida dubliniensis, Candida lusitaniae, Candida guilliermondii, Candida kefyr, Candida famata, Candida lipolytica, Candida utilis, Candida zeylanoides, Candida rugosa, Candida norvegensis, Candida pelliculosa, Candida sake Candida stellatoidea, Candida zonata, Aspergillus flavus, Aspergillus niger, Aspergillus terreus, Candida haemulonii, Candida orthopsilosis, Candida metapsilosis, Candida auris, Trichosporon asahii, Trichosporon cutaneum, Trichosporon mucoides, Trichosporon ovoides, Trichosporon asteroid, Geotrichum candidum, Geotrichum capitatum, Paecilomyces spp., Acremonium spp., Alternaria spp., Cladosporium spp., Penicillium spp., Aspergillus nidulans, Aspergillus versicolor, Exophiala dermatitidis, Exophiala jeanselmei, Exophiala spinifera, Exophiala xenobiotica, Candida utilis var. utilis, Candida glabrata var. bracarensis, Trichosporon dohaense, Trichosporon domesticum, Trichosporon japonicum, Trichosporon moniliiforme, Trichosporon mucoidum, Trichosporon pullulans, Rhizomucor pusillus, Rhizomucor variabilis, Cunninghamella bertholletiae, Cunninghamella echinulate, Cunninghamella blakesleeana, Absidia corymbifera, Mucor circinelloides, Mucor racemosus, Saksenaea vasiformis, Rhizopus microspores, and Rhizopus spp (see col. 9, lines 17-28 – “In some embodiments, the sensor for detecting a particular type of VOCs present at a tissue site may be a chemical gas sensor which may detect different gases in an area, especially those gases which might be harmful to humans or animals. The chemical gas sensors may comprise many kinds of materials such as, for example, polymers, semiconductors, carbon graphites, and organic/inorganic composites which have been used as sensing materials to detect the targeted gases based on various sensing techniques and principles. Such chemical gas sensors may include, for example, acoustic wave gas sensors, resistive gas sensors, photoelectric gas sensors, and optical gas sensors”, col. 12, line 58-col. 13, line 21 – “For example, the sensor device 305 may comprise a first VOC sensor 310 and a second VOC sensor 315 configured to detect and/or measure one or more particular VOCs found in gases emitted from the tissue site. In one example embodiment, either one of the VOC sensors may be a FAIMS sensor available from Owlstone Medical Ltd. In another example embodiment, either one of the VOC sensors may be a sensor available from Alphasense similar to the FAIMS sensor. The FAIMS sensor in some embodiments may provide outputs or fingerprints associated with various VOCs indicative of protease levels which can be used to identify normal wound healing or non-healing wound conditions as described above. The FAIMS sensor in some other embodiments may provide other outputs or fingerprints associated with other VOCs indicative of other biomarkers which can be used to identify normal wound healing or non-healing wound conditions. Additionally or alternatively, the sensor device 305 may be configured to detect and/or measure other parameters or variables, such as, for example, pH of wound exudates, temperature, oxygen concentration, humidity, glucose levels within wound exudates, among others. For example, the sensor device 305 may further comprise a pH sensor 320 and a humidity/temperature sensor 325. Thus, in some embodiments, the sensor device 305 may include one or more individual sensors, such as a VOC sensor, pH sensor, blood sensor, glucose sensor, growth factor sensor, or another type of sensor. Additionally, the sensor device 305 may include one or more sensors for detecting and/or measuring various electrolyte levels at a tissue site through electrical resistance sensing”, and claim 3).
Regarding claim 20, Locke et al. discloses the sensor array is disposed within one of a wearable device, a portable device, a disposable device, and a wound dressing, (see col. 2, lines 1-18 – “For example, in some embodiments, a system for treating a tissue site may include a dressing, a negative-pressure source, a container, and a sensor module. The dressing may be adapted to be placed on the tissue site, and the negative-pressure source may be adapted to be fluidly coupled to the dressing. The container may be adapted to be fluidly coupled to the dressing and to the negative-pressure source and to receive fluid from the tissue site. The sensor module may be adapted to be exposed to gas associated with the fluid from the tissue site. The sensor module may comprise a first sensor configured to detect a condition of the tissue site and to generate a first output based on the detected condition. The first sensor may be configured to detect a first volatile organic compound. Additionally, the sensor module may further comprise a second sensor configured to detect a second volatile organic compound. In some embodiments, the sensor module may be positioned on the container” and col. 9, lines 34-38 – “The diagnostic module 160 may also be positioned at other points in the therapy system 100 such as, for example, as a component attached to the fluid conductor 116 or a component of the dressing interface 123”).
Regarding claim 21, Locke et al. discloses the at least one processor is disposed in a remote device (see col. 13, lines 47-51 – “The communications module 330 of the diagnostic module 160 may be configured to transmit and receive data to/from one or more other components of the therapy unit 101, such as the controller 130, or a separate remote device 350 such as, for example, a cell phone”).
Regarding claim 22, Locke et al. discloses the sensor array is disposed within the wound dressing (see col. 9, lines 34-38 – “The diagnostic module 160 may also be positioned at other points in the therapy system 100 such as, for example, as a component attached to the fluid conductor 116 or a component of the dressing interface 123”), and the system further comprises:
a negative pressure source (105) to apply negative pressure to the wound to promote healing (see col. 17, lines 42-45 – “The controller 130 may also use feedback from the diagnostic module 160 to vary the level of negative pressure supplied by the negative-pressure source 105 to the tissue site 415”).
Regarding claim 23, Locke et al. discloses the at least one processor is further configured to: adjust a rate of the negative pressure source based on the information from the sensor array (see col. 17, lines 42-45 – “The controller 130 may also use feedback from the diagnostic module 160 to vary the level of negative pressure supplied by the negative-pressure source 105 to the tissue site 415”).
Regarding claim 24, Locke et al. discloses the at least one processor is further configured to: determine a treatment for the wound based on the information from the sensor array (see col. 16, lines 17-24 – “Furthermore, in some embodiments, the controller 130 may be programmed to automatically direct that one or more types of therapy to the tissue site 415 could be initiated, adjusted, or stopped. In some embodiments, the controller 130 may automatically make changes to one or more forms of therapy, and thus the adjustments to the therapy may be triggered independently of an operator of the therapy system 100”).
Regarding claim 25, Locke et al. discloses an apparatus comprising:
a memory device containing software executable by at least one processor (see col. 4, lines 57-65 – “Some components of the therapy system 100 may be housed within or used in conjunction with other components, such as sensors, processing units, alarm indicators, memory, databases, software, display devices, or user interfaces that further facilitate therapy. For example, in some embodiments, the negative-pressure source 105 may be combined with the controller 130, the first sensor 135, the second sensor 140, the regulator 165, and other components into a therapy unit 101”) to cause the at least one processor to:
receive, from sensor array (310, 315, 320, 325), information pertaining to detection of one or more gases emanating from one or more pathogens in a wound that produce an infection, wherein the sensor array includes sensing materials that change one or more properties in response to a presence of the one or more gases (see col. 9, lines 17-28 – “In some embodiments, the sensor for detecting a particular type of VOCs present at a tissue site may be a chemical gas sensor which may detect different gases in an area, especially those gases which might be harmful to humans or animals. The chemical gas sensors may comprise many kinds of materials such as, for example, polymers, semiconductors, carbon graphites, and organic/inorganic composites which have been used as sensing materials to detect the targeted gases based on various sensing techniques and principles. Such chemical gas sensors may include, for example, acoustic wave gas sensors, resistive gas sensors, photoelectric gas sensors, and optical gas sensors” and col. 12, line 58-col. 13, line 21 – “For example, the sensor device 305 may comprise a first VOC sensor 310 and a second VOC sensor 315 configured to detect and/or measure one or more particular VOCs found in gases emitted from the tissue site. In one example embodiment, either one of the VOC sensors may be a FAIMS sensor available from Owlstone Medical Ltd. In another example embodiment, either one of the VOC sensors may be a sensor available from Alphasense similar to the FAIMS sensor. The FAIMS sensor in some embodiments may provide outputs or fingerprints associated with various VOCs indicative of protease levels which can be used to identify normal wound healing or non-healing wound conditions as described above. The FAIMS sensor in some other embodiments may provide other outputs or fingerprints associated with other VOCs indicative of other biomarkers which can be used to identify normal wound healing or non-healing wound conditions. Additionally or alternatively, the sensor device 305 may be configured to detect and/or measure other parameters or variables, such as, for example, pH of wound exudates, temperature, oxygen concentration, humidity, glucose levels within wound exudates, among others. For example, the sensor device 305 may further comprise a pH sensor 320 and a humidity/temperature sensor 325. Thus, in some embodiments, the sensor device 305 may include one or more individual sensors, such as a VOC sensor, pH sensor, blood sensor, glucose sensor, growth factor sensor, or another type of sensor. Additionally, the sensor device 305 may include one or more sensors for detecting and/or measuring various electrolyte levels at a tissue site through electrical resistance sensing”); and
analyze the information from the sensor array to identify the one or more pathogens and determine a presence of the infection in the wound, wherein the one or more pathogens are identified based on time-dependent patterns of changes of the one or more properties indicating corresponding pathogens (see Figure 6 and col. 9, line 51-col. 10, line 9 – “Wound protease activity often times is a very useful measurement of how the healing of a wound is progressing. During the initial inflammation stage of the wound healing process, there may be a higher level of protease activity. Referring to FIG. 6, protease levels initially increase rapidly in the normal course of wound healing. For example, the protease levels may peak at about the third day, but begin to reduce by about the fifth day. Thus, a directionally-changing level of protease activity may be a good indicator of normal wound healing. Thus, a directionally-changing activity from a rapidly increasing level to a decreasing level may be an indicator of normal wound healing that a device such as the diagnostic module 160 is capable of detecting by sensing one or more VOCs. However, if the level of activity increases rapidly to an abnormally high level or if the duration of the raised activity continues beyond the initial stage, it may be a good indicator that the wound is not healing as efficiently as desired. More specifically, increased levels of MMPs, often times MMP-2 and MMP-9 proteases, are commonly found in non-healing wounds. Thus, elevated protease activity may be an indicator of poor wound progress, and a device, such as the diagnostic module 160 capable of detecting the levels of the wound proteases via one or more VOCs, may be a useful tool for providing real-time feedback of wound healing to a clinician” and col. 20, lines 44-53 – “The systems, apparatuses, and methods described herein may provide significant advantages. For example, the ability to detect the status of a wound would be of great benefit, as healing progress may be tracked, and accordingly, treatment may be optimized to expedite closure of the tissue site. By analyzing fluid drawn off from the wound for wound factors associated with the different stages of healing, wound healing progress can be assessed. Additionally, indications of infection may be identified, thus allowing the opportunity for prompt intervention”).
Regarding claim 27, Locke et al. discloses a negative pressure source (105) applies negative pressure to the wound to promote healing, and the software further causes the at least one processor to:
adjust a rate of the negative pressure source based on the information from the sensor array (see col. 17, lines 42-45 – “The controller 130 may also use feedback from the diagnostic module 160 to vary the level of negative pressure supplied by the negative-pressure source 105 to the tissue site 415”).
Regarding claim 28, Locke et al. discloses the software further causes the at least one processor to:
determine a treatment for the wound based on the information from the sensor array (see col. 16, lines 17-24 – “Furthermore, in some embodiments, the controller 130 may be programmed to automatically direct that one or more types of therapy to the tissue site 415 could be initiated, adjusted, or stopped. In some embodiments, the controller 130 may automatically make changes to one or more forms of therapy, and thus the adjustments to the therapy may be triggered independently of an operator of the therapy system 100”).
Claim Rejections - 35 USC § 103
The text of those sections of Title 35, U.S. Code not included in this action can be found in a prior Office action.
Claim(s) 4, 19, and 26 is/are rejected under 35 U.S.C. 103 as being unpatentable over Locke et al., further in view of Chen et al. (US Publication No. 2020/0211707 A1) (previously cited).
Regarding claims 4, 19, and 26, it is noted Locke et al. does not specifically teach the analyzing step comprises: analyzing the electrical signals by a machine learning model to correlate the time-dependent patterns of changes of the one or more properties to patterns of the corresponding pathogens. However, Chen et al. teaches the analyzing step comprises: analyzing the electrical signals by a machine learning model to correlate the time-dependent patterns of changes of the one or more properties to patterns of the corresponding pathogens (see [0004] – “The processor is configured to calculate at least one feature value according to the current physiological data, and input the feature value into a machine learning model to determine one of categories including at least two of uninfected, fungal infected, contaminated bacteria infected, Gram-negative infected, and Gram-positive infected”). It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the method, system, and apparatus of Locke et al. to include the analyzing step comprises: analyzing the electrical signals by a machine learning model to correlate the time-dependent patterns of changes of the one or more properties to patterns of the corresponding pathogens, as disclosed in Chen et al., so as to predict types of pathogens in patients with septicemia and distinguish between categories including at least two of uninfected, fungal infected, contaminated bacteria infected, Gram-negative infected, and Gram-positive infected (see Chen et al.: Abstract).
Response to Arguments
As noted above, Applicant’s amendments to the claims are sufficient to overcome the rejection of claims 1, 3-16, and 18-24 under 35 U.S.C. 101. However, the amendments are not sufficient to overcome the rejection of claims 25-28 under 35 U.S.C. 101.
Applicant's arguments filed 12/26/2025 have been fully considered but they are not persuasive.
In response to applicant's argument that the references fail to show certain features of the invention, it is noted that the features upon which applicant relies (i.e., Locke does not describe sensors that can detect physiological status such as heart rate, blood oxygen, etc., which requires the sensor being attached to the body of the patient) are not recited in the rejected claim(s). Although the claims are interpreted in light of the specification, limitations from the specification are not read into the claims. See In re Van Geuns, 988 F.2d 1181, 26 USPQ2d 1057 (Fed. Cir. 1993).
Moreover, Applicant’s argument appears to rely on a mischaracterization of the variety of sensors that Locke describes and/or what the broadest reasonable interpretation of the claimed “sensor array comprising… one or more physiological sensors… each physiological sensor is configured to detect physiological status… wherein the physiological status of the subject comprises one or more parameters selected from heart rate, pulse rate, respiratory rate, blood oxygen saturation, blood pressure, hydration level, brain activity, cranial pressure, and skin and body temperature”. In addition to the VOC gas sensors, Locke describes sensors configured to detect other parameters or variables including, pH, temperature, oxygen concentration, humidity, glucose levels, blood sensor, growth factor sensor, or sensors for detecting and/or measuring electrolyte levels at a tissue site through electrical resistance sensing (see col. 13, lines 8-21). Locke further describes the parameters including pH of wound exudates, O2 concentration of tissue at the tissue site, temperature, humidity within the dressing, glucose level in wound exudates, as well as others (see col. 19, lines 5-10). The description of the sensors in Locke is clearly sufficient to read on physiological sensors configured to detect physiological status at the tissue site, wherein the physiological status comprises at least one of blood oxygen saturation (i.e. oxygen concentration), hydration level (i.e. humidity), and skin/body temperature.
In response to Applicant’s argument that Locke does not describe time-dependent patterns of changes of the one or more properties, the Examiner respectfully disagrees and points to Figure 6, which shows how protease activity (as sensed by the VOC sensors) changes over time in both a normal healing wound and a non-healing wound. Locke also describes throughout the description tracking sensor measurements over time to determine the status of the wound at a present time as well as a healing trend of the tissue site to determine a progression of wound healing (see e.g., col. 9, line 51-col. 10, line 8 and col. 15, lines 27-52).
Conclusion
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to DEVIN B HENSON whose telephone number is (571)270-5340. The examiner can normally be reached M-F 7 AM ET - 5 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, Robert (Tse) Chen can be reached at (571) 272-3672. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/DEVIN B HENSON/ Primary Examiner, Art Unit 3791