Systems and methods for the detection of transitions in thermoregulation and for the early detection of changes to health status

Abstract

In some aspects, the disclosed technology generally relates to a system configured for detection of a transition in thermoregulation. In some embodiments, the system may include at least one sensor configured to measure a plurality of heat flux measurements of a subject over time; a processor configured to receive the plurality of heat flux measurements over time, characterize the relationship between heat flux and temperature over time, and detect a transition from a first thermoregulatory control state to a second thermoregulatory control state prior to an onset of fever or infection; and an indicator prompting proposed intervention prior to the onset of fever or infection. The disclosed technology also generally relates, in certain embodiments, to systems for the early detection of fever, particular in sepsis patients, and methods of detecting health anomalies in sepsis patients.

Description

SYSTEMS AND METHODS FOR THE DETECTION OF TRANSITIONS IN THERMOREGULATION AND FOR THE EARLY DETECTION OF CHANGES TO HEALTH STATUSCROSS-REFERENCE TO RELATED APPLICATIONS

[0001] This application claims priority to U.S. Provisional Application No.63 / 711.586, filed October 24, 2024, and U.S. Provisional Application No. 63 / 714,005, filed October 30, 2024, the content of each of which is incorporated by reference in its entirety.BACKGROUNDField of the Disclosed Technology

[0002] The disclosed technology generally relates to sy stems for, wearable devices for, and methods of detecting recognizable features from measurements of emergent properties of a complex adaptive system, such as a biological system, an organism, or for example a human, or a non-biological system. In particular, the disclosed technology relates to systems and methods configured for detection of a transition or transitions in thermoregulation. The disclosed technology also generally relates, in certain embodiments, to systems for the early detection of fever, particular in sepsis patients, and methods of detecting health anomalies in sepsis patients.Description of the Related Art

[0003] Known health monitoring wearable devices may utilize digital temperature sensors to perform high-accuracy measurements of the skin temperature of a user and the temperature of the surrounding environment. However, such know n devices for monitoring users are inadequate. For example, there is a need for improved thermal design to maximize the thermal impedance, or minimize thermal crosstalk, between different temperature sensors in a health monitoring wearable device. Moreover, there is a need for health monitoring wearable devices that are capable of obtaining emergent factors of a user which are indicative of the user’s homeostasis and health state. Further details regarding emergent factors indicative of a user's homeostasis and health state can be found in International Patent Application No. PCT / US2021 / 048053, titled -‘SYSTEMS AND METHODS FOR MEASURING, LEARNING, AND USING EMERGENTPROPERTIES OF COMPLEX ADAPTIVE SYSTEMS” and filed on August 27, 2021, the disclosures of which are incorporated herein by reference. Additionally, further details regarding emergent factors can be found in U.S. Provisional Application No. 63 / 488,892, titled “SYSTEMS AND METHOD FOR DETECTING EMERGENT PROPERTIES AND IMPROVING HEALTH OUTCOMES” and filed on March 7, 2023, the disclosures of which are incorporated herein by reference. Additional details regarding emergent factors can be found in U.S. Provisional Application No. 63 / 679,671, titled “DEVICES AND METHODS FOR OBTAINING EMERGENT FACTORS OF USERS” and filed on January’ 12, 2023, the disclosures of which are incorporated herein by reference.

[0004] A historic perspective sheds light on the manifold advantages of the disclosed technology. Known devices for and methods of monitoring biological systems, and known systems for maintaining or improving health are inadequate. For example, known wearable devices generally exist in the off-the-shelf market; however, many patients and users are excluded from that market. Furthermore, and as a further example, known wearable devices are generally “one size fits all”; however, many patients and users cannot be accommodated by such devices. Additionally, wearable devices generally will accomplish their intended functions only when worn as intended and serve little or no function if not worn substantially continually. There are usually critical moments in which the wearable device should be worn, but off-the-shelf market and one size fits all devices may be unworn at those moments and have features that often motivate patients and users to remove the wearable device.

[0005] The current approach to solving problems in the biological sciences is a bottoms-up approach often referred to as “precision biology.” In its most generalized form precision biology’ couples machine learning with a detailed measurement (“-omics”) of biological parts to ascribe function to parts. This approach is also often referred to as “precision medicine,” especially’ when applied to the discovery, development and delivery of healthcare solutions.

[0006] Precision biology is based on the concept that knowledge gaps are due to a lack of understanding of “parts,” and that detailed measurement and analysis will fill in these knowledge gaps. For example, a basic tool of modem biological sciences is organic chemistry', the study of carbon-containing molecules, and carbon bonded to other key atoms. This is, at least in part, because the genetic, signaling, and structural molecules of living systems consist largely of carbon atoms. Under the precision biology paradigm, function and prediction of function is therefore sought through quantifying these organicchemical attributes in greater detail. However, the art generally fails to recognize that many characteristics of biological systems do not lend themselves to the precision biology paradigm. One such example, where the precision biology paradigm fails, is in the measurement and prediction of emergent properties of complex adaptative (biological) systems. Emergent properties are properties of a system not found in a part, or readily deducible from a detailed inventory and analysis of the parts contained within a system. The precision biology approach--which today has risen to the level of a paradigm-has a blind spot with respect to emergent properties; this blind spot substantially limits advances in the fields of biology and medicine.

[0007] A historic perspective sheds light on the manifold advantages of the current technology, even as all past and cunent understandings of biological systems, and of how to monitor them and maintain or improve health neither anticipate nor render obvious the systems, methods, and uses of the current technology7. Know n devices for and methods of monitoring biological systems, and known systems for maintaining or improving health are inadequate. For example, known wearable devices generally exist in the off-the-shelf market; however, many patients and users are excluded from that market.

[0008] The measurement of human biological systems to understand their function can be traced as far back as Hippocrates in -450 BC. Hippocrates is credited for separating medicine from religion in human biological systems, and thus establishing a physical basis for measuring and diagnosing disease and developing prognosticators. The notion that human biology could be understood through the prism of physical sciences and not religion w as advanced over the ensuing -2,400 years to the beginning of the industrial revolution.

[0009] Informed by advances in the industry, biologists and chemists in the late 19th century and early 20th century began to adopt analogous approaches and technologies to those successfully employed in physics, engineering, and industry. Over the first half of the 20th century7, these approaches were parlay ed into the successful identification of food-derived enzyme cofactors- vitamins; the biological basis of viral and bacterial infections and the means to intercept them-vaccines and antibiotics; and the successful identification of genetic material- DNA, and how genetic information encodes for proteins. These advances contributed to astonishing gains in the understanding of the biological sciences and medicine.

[0010] In the most general sense, the tools and reasoning that drove industrialization were then, and are now still, employed to solve biological problems. Atthe core of the reasoning is a form of reductionism that is instantiated in the scientific method in the generalized hypothesis of “what part is ascribed to what function.”

[0011] A precision approach to learning would be most predictive when there is a simple and orderly relationship between a part and its function. Such examples in non-biological systems might include a tire on a bicycle, or in a biological system, a gene and protein critical for energy synthesis and life itself. In these instances, the measurement of the tire or the gene would be expected to correlate with the function of the system. The precision biology approach has its greatest positive predictive value in non-biological systems that are designed and engineered by humans, as these systems, by definition, follow a 1 : 1 relationship between parts and function. The precision biology approach also has value in biological systems where there is a hypothesized and measurable relationship between a part and its function. However, the precision biology approach would lose its positive predictive value in biological systems when there is not a 1:1 relationship between a part and its function. The instance where there is no discernable relationship between a part and its function is the case where a part, or two or more parts, form a new structure or perform a new function not readily predictable or discernable from the part or parts alone. This property, the ability of one or more parts to form a structure or perform a function not resident in the / a part alone, is its “emergent structure or function” and collectively its “emergent property or properties.”

[0012] The current precision biology approach to understanding the function of biological and complex non-biological systems is limited by the inability to measure, quantity, predict, control, maximize, design, and engineer complex adaptive biological and non-biological systems based on their emergent properties. These limitations are observed at nearly all hierarchies of biological systems, including the biosphere itself.

[0013] The precision biology approach is limited in understanding biological and human function. The parts-based approach implicitly considers the biological system or human as a self-contained collection of parts from which function is to be sorted and calculated. It embodies a pre-vitamin paradigm and ironically is limited today by an incomplete inventory of the parts responsible for function. Until relatively recently, the precision biology7approach in humans omitted -1-10 trillion bacteria that form the human microbiome. The precision biology' approach also discounts or omits in their entirety other parts and the context in which they exist. Examples would include food. While there are estimated to be over 30,000 plant-derived small molecules called phytonutrients in the human diet, the function of only <0.1% of these phytonutrients-the vitamins-areunderstood. Additionally, the precision biology approach discounts the criticality and importance of certain classes of enzymes and deprioritizes their study. This would include but is not limited to those in metabolism that interact with substances derived from the milieu exterior, such as oxidoreductase enzy mes. When applied to medicine, the precision biology paradigm oversimplifies the complexity of biological systems. It is very limited in its ability to diagnose and develop treatments to disease when the function it seeks to understand is emergent in origin.

[0014] The precision biology approach is also limited in understanding the health of a species or collection of species and resources. The precision biology7approach considers health as the null case or absence of disease obtained through a process of disease elimination. Today, human health is a concept, not an actuality. It should be noted that this was / is not always the case in many non-reductionist cultures. The concept of health as an energy state-essentially an emergent property-independent from disease is common to many eastern cultures and religions, chakras, reiki, prana, chi, can be traced to 400 BC, and more recently in the West as elan vital in the 1900s. Health is essentially the baseline of function of a biological system, and may also be referred to as homeostasis. But homeostasis is an emergent property: a complex interplay7of many parts to produce interchangeable forms and functions that are not resident in or discernable by the precision biology approach. The precision biology approach significantly fails in an open system in which homeostasis (health) is dependent upon the complex interaction of the milieu interior and milieu exterior. As a result, disease measures are used to define the absence of health. Disease measures are very7poor surrogates for absence of health in that they substantially lag changes in health or ‘‘health capacity”: the resilience (adaptivity) of a system expressed primarily by its ability to persist or achieve some core function.

[0015] The precision biology approach is also limited in “genetic engineering” and industrial biology. The absence of a 1 : 1 relationship between the change of a gene and the intended outcome frequently results in the generation of non-homeostatic (un-healthy) states inconsistent with the intended new (synthetic function) or viability.

[0016] The precision biology7approach is also limited in terms of its implementation. It requires highly specialized and expensive equipment for measurement. The precision biology7approach is limited in terms of learning rate. It results in an unmanageable number of false (positive) discoveries and discounts the possibility of unexpected outcomes, in other words, “unintended consequences”. The cost, risk and time to learn are very high and increasing consistent with Eroom’s Law. The precision biologyapproach is limited by its invasiveness and ethicality. Whereas emergent properties are often quantifiable from the exterior, the precision biology approach typically involves invasive tests or experimental euthanasia that can be unethical, injurious or lethal- all of which reduce the practicality of gaining frequent and sufficient measurements. Without large sample sizes and real human test data, it is extremely difficult to obtain the necessary statistical power to differentiate good hypotheses from bad. This exacerbates the problems of false discovery and further slows the learning rate of the biological sciences generally. The precision biology approach is limited by its silence on anthropocentric effects on biological function. It considers that DNA contains all the relevant biological information, and that function cascades forthwith. It does not consider other physical or biological information systems such as temperature, inter- / intra-species dependencies, gravity, magnetic fields, currents, populations, and the like all of which have undergone dramatic changes in the last 100 years of the “anthropocene.” The precision biology' approach is also limited by the conjecturing of a "paradigm" that “DNA is the book of life’' is “truth” despite evidence to the contrary. Despite these clear limitations to the precision biology approach / paradigm, there is dogmatic continuation of this approach as a series of “-omics” revolutions. Because there may be an infinite set of taxonomies of parts, the parts-based approach is essentially inexhaustible and therefore, non-falsifiable: there is no means by which the precision biology paradigm can prove itself wrong. This non-falsifiability has been made worse by modem machine learning tools. It is now conjectured that the knowledge gap in the precision biology approach is not the approach, but insufficiencies in analytical methods to understand the parts. While machine learning tools will certainly have utility' for those problems solvable by the precision biology approach, more analysis and data gathering has never supplanted the need for new measurements that make visible what has been hidden. The precision biology' approach simply does not measure or acknowledge emergent properties of biological systems by which the essence of life is defined.

[0017] Life exists and persists across a wide range of dynamic environmental conditions. Diverse forms of life can be found in extreme temperatures, pressures, pH conditions, and chemical solutions. Yet common to all living organisms is the emergent property of extracting energy' from their environment and employing that energy' in accordance with a metabolic strategy' that “fits” their environment. While there are nearly as many such metabolic strategies as there are species, all must obey basic thermodynamic principles of heat transfer and therefore must be thermally appropriate for their environment. In other words, in order to persist, all must have a proper “heat fit” with theirenvironment. Should a living organism lose the ability to maintain its “heat fit” within its environment, its metabolism will fail and it will no longer persist (i.e., it will die). This basic principle of heat fit governs all living things, from primitive bacteria to plants to organisms as complex as human beings. Therefore, effective maintenance or regulation of a living organism’s heat fit depends on the efficient design and execution of its respective metabolic strategy in the face of dynamic changes in its environment. Because extracting replacement energy from the environment has a metabolic cost of its own, the aspects of the metabolic strategy that have the most potential for exhausted energy pose the most risk to the organism maintaining its heat fit.

[0018] What is needed, therefore, is a new way to measure, quantify, and interpret emergent properties of biological and non-biological systems to understand the function of complex adaptive systems, enabling prediction, optimization, design, and engineering of biological and non-biological systems. This way should be considered as part of a “consilience approach” that considers the totality of all biological and non-biological parts and systems and their emergent properties within.

[0019] New systems, devices and methods are needed to understand, with greater accuracy, accessibility, scalability and more readily, the function of complex adaptive systems. Such systems, devices and methods would, ideally, enable prediction, optimization, design, and engineering of biological and even non-biological systems, and would consider the totality of all biological and non-biological parts and systems.SUMMARY

[0020] The present disclosure relates, in certain embodiments, to a system configured for detection of a transition in thermoregulation in a subject, the system comprising: at least one sensor configured to measure a plurality of heat flux measurements of the subject over time; a processor configured to receive the plurality of heat flux measurements over time, characterize the relationship between heat flux and temperature over time, and detect a transition from a first thermoregulatory control state to a second thermoregulatory control state prior to an onset of fever or infection; and an indicator prompting proposed intervention prior to the onset of fever or infection. The transition from the first thermoregulatory control state to the second thermoregulatory control state may be indicative of a change to an adaptive control system of the subject. An emergent condition may be identified based on the indicated change to the adaptive control system. The heat flux measurements of a subject over time may include at least one of the following: coretemperature measurements; skin temperature measurements; or ambient temperature measurements. The heat flux measurements may include at least two of the following: core temperature measurements; skin temperature measurements; or ambient temperature measurements. A recognized change in the plurality of heat flux measurements may correspond to the transition from the first thermoregulatory control state to the second thermoregulatory control state. The recognized change in the plurality’ of heat flux measurements may correspond to a recognized change in the relationship between the skin temperature measurements, and the ambient temperature measurements.

[0021] The present disclosure relates, in certain embodiments, to a method for detection of a transition in thermoregulation in a subject, the method comprising: measuring a plurality of heat flux measurements of a subject over time; processing the plurality of heat flux measurements over time; recognizing the transition from a first thermoregulatory control state to a second thermoregulatory control state prior to an onset of fever or infection; and administering an intervention prior to an onset of a fever or an infection. The heat flux measurements over time may include at least one of the following: core temperature measurements; skin temperature measurements; or ambient temperature measurements. The heat flux measurements over time include at least two of the following: core temperature measurements; skin temperature measurements; or ambient temperature measurements. The transition from the first thermoregulatory control state to the second thermoregulatory control state may be identified based a change in an adaptive control system of the subject. The method may further comprise a step of identifying an emergent condition based on the identified change in the adaptive control system. A recognized change in the plurality of heat flux measurements may corresponds to the transition from the first thermoregulatory control state to the second thermoregulatory control state. The recognized change in the plurality of heat flux measurements may correspond to a recognized change in the relationship between the plurality of skin temperature measurements, and the plurality of ambient temperature measurements.

[0022] The present disclosure relates, in certain embodiments, to a system for identifying a control state of thermoregulation of a subject, the system comprising: at least one sensor configured to measure a plurality of heat flux measurements of a subject over time; a processor configured to receive the plurality of heat flux measurements, characterize the relationship between heat flux and temperature over time, and detect a transition from a first thermoregulatory control state to a second thermoregulatory control state prior to an onset of fever or infection; and an intervenor that intervenes thermoregulation of the subj ectprior to an onset of a fever or an infection. The transition from the first thermoregulatory control state to the second thermoregulatory control state may identify an adaptive control system of the subject. An emergent condition may be identified based on the identified adaptive control system. The plurality of heat flux measurements over time include at least one of the following: a plurality of core temperature measurements; a plurality7of skin temperature measurements; or a plurality of ambient temperature measurements. A recognized change in the plurality of heat flux measurements may correspond to the transition from the first thermoregulatory control state to the second thermoregulatory control state. The recognized change in the plurality7of heat flux measurements may correspond to a recognized change in the relationship between the plurality7of skin temperature measurements, and the plurality of ambient temperature measurements.

[0023] The present disclosure relates, in certain embodiments, to a system for treating a change in thermoregulation in a subject, the system comprising: at least one sensor configured to measure a plurality7of heat flux measurements of a subject; a processor configured to receive the plurality of heat flux measurements, characterize the relationship between heat flux and temperature over time, and detect a transition from a first thermoregulatory7control state to a second thermoregulatory' control state prior to an onset of fever or infection; and an administrator of treatment to the subject prior to an onset of a fever or an infection. The transition from the first thermoregulatory control state to the second thermoregulatory7control state may7identify an adaptive control system of the subject. An emergent condition may be identified based on the identified adaptive control system. The plurality7of heat flux measurements over time may include at least one of the following: core temperature measurements; skin temperature measurements; or ambient temperature measurements. The plurality of heat flux measurements over time include at least two of the following: core temperature measurements; skin temperature measurements; or ambient temperature measurements. A recognized change in the plurality of heat flux measurements may correspond to the transition from the first thermoregulatory control state to the second thermoregulatory control state. The recognized change in the plurality of heat flux measurements may correspond to a recognized change in the relationship betw een the plurality of skin temperature measurements, and the plurality of ambient temperature measurements.

[0024] The systems, devices, kits, and methods disclosed herein each have several aspects, no single one of which is solely responsible for their desirable attributes. Without limiting the scope of the claims, some prominent features will now be discussedbriefly. Numerous other examples are also contemplated, including examples that have fewer, additional, and / or different components, steps, features, objects, benefits, and advantages. The components, aspects, and steps may also be arranged and ordered differently. After considering this discussion, and particularly after reading the section entitled “Detailed Description,” one will understand how the features of the devices and methods disclosed herein provide advantages over other known devices and methods.

[0025] It is to be understood that any features of the device and / or of the array disclosed herein may be combined together in any desirable manner and / or configuration. Further, it is to be understood that any features of the method of using the device may be combined together in any desirable manner. Moreover, it is to be understood that any combination of features of this method and / or of the device and / or of the array may be used together, and / or may be combined with any of the examples disclosed herein. Still further, it is to be understood that any feature or combination of features of any of the devices and / or of the arrays and / or of any of the methods may be combined together in any desirable manner, and / or may be combined with any of the examples disclosed herein.

[0026] It should be appreciated that all combinations of the foregoing concepts and additional concepts discussed in greater detail below are contemplated as being part of the inventive subj ect matter disclosed herein and may be used to achieve the benefits and advantages described herein.BRIEF DESCRIPTION OF THE DRAWINGS

[0027] Features of examples of the present disclosure will become apparent by reference to the following detailed description and drawings, in which like reference numerals correspond to similar, though perhaps not identical, components. For the sake of brevity, reference numerals or features having a previously described function may or may not be descnbed in connection with other drawings in which they appear.

[0028] Figure 1 is a schematic diagram that illustrates changes in autonomic control of thermoregulation preceding fever in a sepsis patient, along with an depiction of an example of a device for the early detection of fever, based on observed patterns of heat elimination, according to the present disclosure.

[0029] Figures 2A-2D illustrate the general principles of thermoregulation and how they are used in the disclosed technology. In particular, Figure 2A schematically depicts how core temperature is maintained by the feedback / control of heat generation and heat elimination: Figure 2B schematically depicts a principle mode of control of coretemperature; Figure 2C schematically depicts the main and auxiliary feedback loop between core, skin, and ambient temperatures; and Figure 2D depicts an example of a device for the early detection of fever, based on observed patterns of heat elimination, according to the present disclosure.

[0030] Figure 3 schematically illustrates a specialized platform designed to monitor and analyze thermoregulation of individuals and groups according to some embodiments of the disclosed technology.

[0031] Figure 4 shows a comparison of thermoregulatory data, and rhythms within such data, for a healthy person versus a hospitalized immunocompromised oncology patient.

[0032] Figure 5 shows a comparison of thermoregulatory data, and rhythms within such data, for a hospitalized immunocompromised oncology patient with neutrophil count and core body temperature.

[0033] Figure 6 schematically illustrates platform communication links and databases used in the disclosed technology, and shows that such links and databases may be secured consistent with best practices and standards.

[0034] Figure 7 illustrates the hardware schematic of the patient wearable device according to some embodiments of the disclosed technology7.

[0035] Figure 8, in the left panel, depicts a single patient summary view according to some embodiments of the disclosed technology; Figure 8, in the right panel, shows the automated triage view for multiple patients under care, according to some embodiments of the disclosed technology.

[0036] Figure 9 depicts a division of the thermoregulatory7plane into zones in the analysis of rhythm (left panel) and instability (right panel), according to certain embodiments of the disclosed technology.

[0037] Figure 10 shows thermoregulation data measured from a sepsis patient.

[0038] Figure 11 shows the same thermoregulation data as in Figure 10, analyzed and displayed in a different way than in Figure 10.

[0039] Figures 12A, 12B and 12C show heat flux patterns for likely sepsis events.

[0040] Figure 13 shows thermoregulation data and leukocyte readings measured in a patient who is experiencing sepsis, had chemotherapy, and was isolated in room in a cancer recovery ward.

[0041] Figure 14 shows experimental data gathered from monitoring individuals who were not experiencing fever when being monitored.

[0042] Figure 15 shows experimental data gathered from monitoring individuals who were experiencing fever when being monitored.

[0043] Figure 16 illustrates how the determination of fever is made using measurements from an example embodiment of a device of the present disclosure.

[0044] Figure 17 illustrates the utility of an example embodiment of a device of the present disclosure for detecting fevers.

[0045] Figure 18 illustrates the high detection capabilities of a device of the present disclosure.DETAILED DESCRIPTION

[0046] All patents, applications, published applications and other publications referred to herein are incorporated herein by reference to the referenced material and in their entireties. If a term or phrase is used herein in a way that is contrary7to or otherw ise inconsistent with a definition set forth in the patents, applications, published applications and other publications that are herein incorporated by reference, the use herein prevails over the definition that is incorporated herein by reference.Overview of Disclosed Technology

[0047] Phenotype in biology generally relates to the entire expression of processes of the body of a biological entity. Usually, a subset of the expression is captured by a device. In medical applications, it is useful to reduce the full phenotype down to interpretable metrics (e.g., aspects or feature library). Thus, in some aspects, the disclosed technology creates a library of computations that can run across data and output value that a clinician or patient can look at and determine what it means if it goes up or down (i.e., can interpret it). To do so, the disclosed technology first has to sort through individuals to determine what their phenotypes are, including quantifying the full expression of individuals and then sort or segment the population based on certain aspects of phenotype and identifying outliers (or anomalies).

[0048] In some embodiments, sorting is an informational action that requires a single number on which the sorting is based. Each of the individual sorting processes is likely to be noisy and therefore inaccurate on its own, but in the context of an application where the statistics has been run, it can determine, for example, which aspect is an outlierfor that patient and how many of the aspects are considered outliers, and can then alert based on the determination. The weaknesses of any aspect may lessen when various aspects are used together. In some embodiments, the disclosed technology can answer any question about health outcomes of patients in real time.

[0049] In some embodiments, a criterion used to identify outliers may be chosen based on how it connects to the general medical context of the patient and / or whether it can be related to any action a doctor would take given the lead time that is in place currently. In some embodiments, a criterion used to identify’ outliers may be an emergent value as the disclosed technology' leams the patient and their manners of progression.

[0050] In the medical practice, there is a dichotomy of health and disease. Doctors may be concerned about what to monitor next. The disease may have a measurement that it is defined by, and the monitoring paradigm is that clinicians take the measurement defined by the disease and then measure it a lot. For example, the mechanism for changes in core temperature involves changes in peripheral temperatures as there are mechanistic connections between core temperature and peripheral temperature. Thus, if the clinicians are concerned about core temperature, the clinicians can measure periphery temperature instead.

[0051] In some embodiments, the disclosed technology utilizes the paradigm that there are healthy patterns that have to be disrupted before the disease can start to emerge. Thus, all of the core temperature measurements can serve as disease measures and reveal disease progressions, and the peripheral temperature measurements can serve as health measures that quantify healthy patterns that must be disrupted for a new state to emerge. In some embodiments, metrics used for early detection of diseases are connected to necessary preconditions that had to have occurred in order for the diseases to emerge. In some embodiments, the metrics may be based on the assumption that disease progression is likely to have the same aspects every time. In some embodiments, the disclosed technology detects diseases early (e.g., 4-6 day in advance of disease onset) in a much simpler manner compared to prior art methods. For example, the disclosed technology may detect if a patient exhibited a circadian rhythm (one of the characteristics of homeostasis) but the circadian rhythm ceases to exist, or if a patient’s data (plotted, for example, as heat vs. ambient temperature) was consistently within a given range that indicates normal behavior but then begins to exhibit anomalies and starts to exit the range gradually. In some embodiments, the disclosed technology quantifies aspects of doctors’ qualitative judgmentregarding disease progression, but sticks with clinician's vocabulary and workflow. In some embodiments, the disclosed technology can solve the problem of self-reporting.

[0052] In some aspects, the disclosed technology provides methods of assessing health or disease progression early and systems and devices for quantifiable aid in assessing disease progress early. In some embodiments, the automating process of the disclosed technology creates the initial assessment and then leads to patient interview initiation. In some embodiments, additional data may be provided after initial diagnosis to aid in the assessment. In some embodiments, the disclosed technology further provides a recommendation for action. In some embodiments, the disclosed technology7is based on characterizing the relationship between heat and temperature of the patient over time. In some embodiments, the disclosed technology is based on characterizing the relationship between skin temperature of the patient and air temperature. In some embodiments, the disclosed technology provides a platform for non-hospital (or remote) physiologic monitoring of immunocompromised patients at risk of infection leading to sepsis.

[0053] In some aspects, the disclosed technology7provides a system configured for detection of a transition in thermoregulation. The system may comprise at least one sensor configured to measure a plurality7of heat flux measurements of a subject over time. The system may further comprise a processor configured to receive the plurality7of heat flux measurements over time, characterize the relationship between heat flux and temperature over time, and detect a transition from a first thermoregulatory control state to a second thermoregulatory7control state prior to an onset of fever or infection. In some embodiments, the transition from the first thermoregulatory7control state to the second thermoregulatory control state is indicative of a change to an adaptive control system of the subject. In some embodiments, an emergent condition is identified based on the indicated change to the adaptive control system. The system may further comprise an indicator prompting proposed intervention prior to the onset of fever or infection.

[0054] In some embodiments, the heat flux measurements over time include at least one of the following: core temperature measurements; skin temperature measurements; or ambient temperature measurements. In some embodiments, the heat flux measurements include at least two of the following: core temperature measurements; skin temperature measurements; or ambient temperature measurements. In some embodiments, a recognized change in the plurality7of heat flux measurements corresponds to the transition from the first thermoregulatory control state to the second thermoregulatory control state. In some embodiments, the recognized change in the plurality of heat flux measurementscorrespond to a recognized change in the relationship between the skin temperature measurements, and the ambient temperature measurements.

[0055] In some aspects, the disclosed technology provides a method for detection of a transition in thermoregulation. The method may comprise measuring a plurality of heat flux measurements of a subject over time. The method may further comprise processing the plurality of heat flux measurements over time. The method may further comprise recognizing the transition from a first thermoregulatory control state to a second thermoregulatory control state prior to an onset of fever or infection. In some embodiments, the transition from the first thermoregulatory control state to the second thermoregulatory control state is identified based a change in an adaptive control system of the subject. The method may further comprise identifying an emergent condition based on the identified change in the adaptive control system. The method may further comprise administering an intervention prior to an onset of a fever or an infection.

[0056] In some embodiments, the heat flux measurements over time include at least one of the following: core temperature measurements; skin temperature measurements; or ambient temperature measurements. In some embodiments, the heat flux measurements include at least two of the following: core temperature measurements: skin temperature measurements; or ambient temperature measurements. In some embodiments, a recognized change in the plurality of heat flux measurements corresponds to the transition from the first thermoregulatory control state to the second thermoregulatory control state. In some embodiments, the recognized change in the plurality of heat flux measurements correspond to a recognized change in the relationship between the skin temperature measurements, and the ambient temperature measurements.

[0057] In some aspects, the disclosed technology provides a system for identifying a control state of thermoregulation of a subject. The system may comprise at least one sensor configured to measure a plurality of heat flux measurements of a subject over time. The system may further comprise a processor configured to receive the plurality of heat flux measurements, characterize the relationship between heat flux and temperature over time, and detect a transition from a first thermoregulatory control state to a second thermoregulatory7control state prior to an onset of fever or infection. In some embodiments, the transition from the first thermoregulatory control state to the second thermoregulatory control state identifies an adaptive control system of the subject. In some embodiments, an emergent condition is identified based on the identified adaptive control system. Thesystem may further comprise an intervenor that intervenes thermoregulation of the subject prior to an onset of a fever or an infection.

[0058] In some embodiments, the plurality of heat flux measurements over time include at least one of the following: a plurality of core temperature measurements; a plurality of skin temperature measurements; or a plurality of ambient temperature measurements. In some embodiments, a recognized change in the plurality of heat flux measurements corresponds to the transition from the first thermoregulatory control state to the second thermoregulatory control state. In some embodiments, the recognized change in the plurality of heat flux measurements correspond to a recognized change in the relationship between the plurality of skin temperature measurements, and the plurality of ambient temperature measurements.

[0059] In some aspects, the disclosed technology provides a system for treating a change in thermoregulation. The system may comprise at least one sensor configured to measure a plurality7of heat flux measurements of a subject. The system may further comprise a processor configured to receive the plurality of heat flux measurements, characterize the relationship between heat flux and temperature over time, and detect a transition from a first thermoregulatory control state to a second thermoregulatory control state prior to an onset of fever or infection. In some embodiments, the transition from the first thermoregulatory control state to the second thermoregulatory control state identifies an adaptive control system of the subject. In some embodiments, an emergent condition is identified based on the identified adaptive control system. The system may further comprise an administrator of treatment to the subject prior to an onset of a fever or an infection.

[0060] In some embodiments, the plurality of heat flux measurements over time include at least one of the following: core temperature measurements; skin temperature measurements; or ambient temperature measurements. In some embodiments, the plurality of heat flux measurements over time include at least two of the following: core temperature measurements; skin temperature measurements; or ambient temperature measurements. In some embodiments, a recognized change in the plurality of heat flux measurements corresponds to the transition from the first thermoregulatory control state to the second thermoregulatory control state. In some embodiments, the recognized change in the plurality of heat flux measurements correspond to a recognized change in the relationship between the plurality of skin temperature measurements, and the plurality of ambient temperature measurements.

[0061] In some embodiments, the disclosed technology provides an augmentation, rather than replacement, of core temperature measurements. Then clinicians can jettison the core temperature measurements when they are convinced that the disclosed metrics are better.Definitions

[0062] ‘'Analysis,” as used herein, refers to any description of characteristics or features of any observed sequence of information. Types of analysis include, but are not limited to, analyzing raw measurements such as wherein the numerical values of raw measurements can be used directly as features; resampled measurements such as wherein a set of raw measurements are grouped by and represented by the mean value of the group or some other group statistic; distributional representation of measurements such as wherein the distribution of a collection of measurements may be represented in regularly spaced bins or irregular bins which have been determined by some other process such as a Gaussian Mixture model; statistical tests over sets of measurements such as the Hartigan DIP test of multimodality or Stationarity tests which can be used to detect changes over time; fit parameters from physical models such as a 3-compartment model of body heat content, and extensions thereof or fitting hemodynamic parameters of human circulatory system: parameters of universal mathematical models such as those which cannot be reduced to any simple parameter of a physical model and which may include non-physical control parameters which summarize structure in the dataset, including, for example, Bifurcation parameter of conjugate logistic map and Eigenvalues of a hessian matrix of a "sloppy" physical model fit.

[0063] “Biological system,” as used herein, refers to any network of biologically relevant entities. In its broadest aspect, a biological system is any network of chemical reactions which exists as a persistent non-equilibrium configuration by its own devices. Biological systems encompass and span differing scales and are determined based different structures depending on the nature of the biological system. Examples of a biological system on a large scale include, for example, a population of microscopic organisms, a homogenous population of similar organisms living in proximity to one another (for example, a cell culture or a community7of humans), a heterogeneous population of organisms living in a single ecosystem, biological networks. Examples of biological systems on a smaller scale include an individual organism, for example a single mammalsuch as a human, an organ or tissue system within such an organism, cellular organelle systems, or artificial life systems.

[0064] ‘'Data stream,’’ as used herein, refers to a sequence of digitally encoded coherent signals (packets of data or data packets) used to transmit or receive information that is in the process of being transmitted. A data stream may be a set of extracted information from a data provider, and may comprise, for example, a sequence of ordered lists of elements (representing different signal components) and an associated sequence of timestamps.

[0065] “Disease,” as used herein, broadly refers to any condition that causes pain, dysfunction, distress, or death to the person afflicted. Thus, disease may include one or more injuries, disabilities, disorders, syndromes, infections, isolated symptoms, deviant behaviors, and atypical variations of structure and function. Diseases may affect biological organisms not only physically, but also mentally. Thus, in the case of a human afflicted with a disease, contracting and living with a disease can alter the affected person's perspective on life. Examples of diseases include those identified and classified on the World Health Organization’s 10th revision of the International Statistical Classification of Diseases and Related Health Problems (ICD-10). Such diseases that may affect humans include, infectious and parasitic diseases, neoplasms, diseases of the blood and blood-forming organs, disorders involving the immune mechanism, endocrine diseases, nutritional diseases, metabolic diseases, mental and behavioral disorders, diseases of the nervous system, diseases of the eye and adnexa, diseases of the ear and mastoid process, diseases of the circulatory system, diseases of the respiratory system, diseases of the digestive system, diseases of the skin and subcutaneous tissue, diseases of the musculoskeletal system and connective tissue, diseases of the genitourinary system, diseases associated with pregnancy, childbirth and the puerperium, diseases originating in the perinatal period, congenital malformations, deformations and chromosomal abnormalities, as well as injuries, poisoning, and consequences of external causes.

[0066] “Energy expenditure,” as used herein, in its most general sense, relates to the measurement of parameters that reflect heat or work in a biological system. “Energy expenditure” also refers to an entropy producing (irreversible) outlay of free energy to power an adaptive task within a biological system. An energy expenditure is largely irreversible (entropy-producing) so it represents energy' which cannot be retrieved for other tasks. “Energy homeostasis” or “homeostatic control of energy’ balance.” as used herein,refers to a biological process that involves the coordinated homeostatic regulation of food intake (energy inflow) and energy expenditure (energy outflow).

[0067] ‘'Emergent factor” or '‘emergent property” as used herein, refer to properties of a system not found in a part, or readily deducible from a detailed inventory and analysis of the parts contained within a system. They may be revealed by events, deviations from norm or other time dependent features in some measurable parameter of the system. This property, the ability- of one or more parts to form a structure or perform a function not resident in the / a part alone, is its “emergent structure or function” and collectively its “emergent property7or properties.” Emergent properties may be observed directly or indirectly. Examples of emergent properties include amphotericity, conductivity, solvation capacity, ion mobility, oxidation-reduction potential, ligand association, hydration, electrolysis, thermal conductivity, heat capacity, thermal absorptivity, adhesion, cohesion, transparency, turbidity, incompressibility, polarity, dipolarity , dipole moment, diamagnetism, voltage range of the liquid phase, temperature range of the liquid phase, abundancy, and speciation, flux of energy, momentum, particles or other substances. Emergent factors also include thermoregulation and heat elimination, either as an absolute, static value of heat elimination or as aperiodic function, for example a circadian periodicity of heat elimination.

[0068] “Feature,” as used herein, refers to any descriptive aspect, characteristic, attribute, quality, trait or property of a sequence, sub-sequence or datum of information. Examples of features include, but are not limited to, Chaotic, Repeating, Predictable, Spirals, Meanders, Rotations, Orbits, Dense / Diffuse, Symmetric / Asymmetric, Regular / Irregular / Intermittent, Periodic / Aperiodic, Cyclical, Similar / Dissimilar, Dynamic / Static, Rate of change, Direction of change, Inflections, Sequential, State Transitions, Anomalies / Outliers, Interruptions / Breaks, Oscillating / Persistent, Damped / Undamped, Increasing / Decreasing, Improving / Declining, Intersecting / Non-intersecting, Linear / Non-linear, Homogenous / Diverse, Monotonic / Polytonic, Serial / Out of order, Balanced / Imbalanced, Long / Short, Range, Modes / Medians / Averages / Standard Deviations, Equilibrium / Non-equilibrium, Stable / Unstable, Controlled / Uncontrolled, Homeomorphic / Isomorphic, Monomodal / Multimodal, Bounded / Unbounded, Trending, Exceeding / Not Exceeding a Threshold, Rising / F ailing, Growing / Shrinking, Speeding up / Slowing down, Constant / / Fluctuating, Peak / V alley, Zenith / Nadir, Asymptotic, Sudden, Steep / Gradual. Logistical / Polynomial mapping, Discrete / Continuous / Spaced / Discontinuous, Proportional, Gains / Losses,Energetic / Active / Inactive, Complexity / Simplicity, Attractors / Repellers, States, State transitions, Curves, Manifolds, Trajectories. Inflation / Deflation, Fractals, Momentum, Iterations, Dissipating / Developing, Presence / Absence, Perturbations, Variations / Invariation, Limited / Unlimited, Converging / Diverging, Velocity, Derivatives / Integrals, Exponential, Minimum / Maximum, Forward / Reverse / Inverse, Pulsing, Coalescing, Saturated / Unsaturated, Gain, Gradients, Deep / Shallow, Bifurcations / Splits, Points / Lines / Surfaces, Early / Late, and Distributed / Grouped.

[0069] “Forecasting,” as used herein, refers to any prediction of future data points within a time series based on what comes before the future data points.

[0070] “Health,” as used herein, refers to the baseline of function of a biological system, and may also be referred to as homeostasis. Health is not merely the absence of disease because health is an affirmative state independent of disease. Health is related to the ability of a biological system or organism to successfully adapt to a variety of challenges without significant loss of function. Physiologists, for example, may describe health as the sufficiency of a form of stored energy they call physiologic reserve — the ability of a human to positively respond to a stress. Physicists, as another example, may describe health as a capacity to incorporate, transform, and dissipate energy to persist. Cell biologists, as another example, may describe health as the baseline state of homeostasis — the ability of a cell or tissue to auto-regulate. Biochemists, as another example, may describe health as the control of anabolic and catabolic reactions in a metabolic network critical to biological function.

[0071] “Health capacity,” as used herein, is the resilience (adaptivity) of a system expressed primarily by its ability to persist or achieve some core function. The adjectives associated with high or low health capacity are it' and ‘frail,' respectively. Low health capacity- “Frailty”- increases the risk of disease or injury and the ability’ to withstand external stresses. Disease diminishes function such that health capacity may be diminished as a result. High health capacity “Fitness"’- decreases the risk of injury’ and increases the ability to perform and to withstand external stresses. Early interception of disease can preserve and maintain health capacity and careful management of health capacity can prevent disease. Health capacity may be considered a correlation of a state, or energy budget, with a function of a biological system that defines the ability of the biological system to persist. Health capacity may be comprised of several quantities which may not necessarily be compared in the same manner or reduced to a single score. Data analytics may be used to discover the relationship between raw measurements and an abstract healthcapacity score. Dimensionality reduction or machine learning methods may be used to leam health capacity scores based on the raw measurement time series data and to predict adaptation and health outcomes.

[0072] “Health capacity rules,” as used herein, refers to the minimal set of attributes of an "energy budget” required to confer “health capacity.”

[0073] “Homeostasis,” as used herein, refers to processes and mechanisms for the regulation of the internal environment of a biological system, generally to limit variability of a state and / or maintain the status of a state. An example of a homeostasis mechanism at the organismal level is sweating, which serves to reduce temperature. An example of a homeostasis mechanism at the biochemical and cellular level is redox control and its regulation of metabolism.

[0074] “Infection,” as used herein, refers to an invasion of a biological system, typically of an organism, by one or more agents (or pathogens) that are not generally associated with the biological system. The agent is often a disease-causing agent. Infection also includes the propagation and multiplication of the agent, and the reaction of host biological system or organism. Infection also includes the generation of toxins, by or as a proximal cause of, the agent. Infectious disease, sometime referred to as “transmissible disease” or “communicable disease,” is a disease state resulting from an infection. Pathogens include, but are not limited to. viruses and related agents such as viroids and prions, bacteria, fungi which may be further classified, for example, as Ascomycota, including yeasts such as Candida, filamentous fungi such as Aspergillus, Pneumocystis species, and dermatophytes, Basidiomycota, including the human-pathogenic genus Cryptococcus, parasites which may be further classified, for example, as unicellular organisms (including, for example, malaria, Toxoplasma, Babesia). Macroparasites (including worms or helminths) such as nematodes such as parasitic roundworms and pinworms, tapeworms (cestodes), and flukes (trematodes, such as schistosomiasis), arthropods such as ticks, mites, fleas, and lice, can also cause human disease, which conceptually are similar to infections. Invasion of an animal body, such as a human body, by macroparasites may also be termed infestation but is consider, as used herein, to be a form of infection.

[0075] “Inflammation,” as used herein, refers to a particular, generic set of biological responses of body tissues to stimuli, such as pathogens, damaged cells, or irritants. Inflammation (and the associated condition, pre-inflammation) is a response involving immune cells, blood vessels, and molecular mediators that, at least in part, servesto eliminate the initial cause of cell injury, clear out necrotic tissues damaged from the original insult and initiate tissue repair. Signs of inflammation include increased heat, pain, redness, swelling, and loss of function. Inflammation may be considered a mechanism of innate immunity, as compared to adaptive immunity', which would be specific to a particular pathogen. Inflammation may be classified as acute or chronic. Acute inflammation is the initial response of the body to a stimuli and may be achieved by the increased movement of plasma and leukocytes (especially granulocytes) from the blood into the injured tissues. A series of biochemical events propagates and matures the inflammatory response, involving the local vascular system, the immune system, and various cells within the injured tissue. Chronic inflammation, often termed prolonged inflammation, may cause a progressive shift in the type of cells present at the site of inflammation, such as mononuclear cells, and is characterized by substantially simultaneous destruction and healing of tissue.

[0076] ‘‘Metabolism,” as used herein, refers to transformation of energy by¬ converting chemicals and energy into cellular components (anabolism) and decomposing organic matter (catabolism). Living things require energy to maintain internal organization (homeostasis) and to produce the other phenomena associated with life.

[0077] “Modeling,” as used herein, refers to any descriptive representation or understanding of the processes or operation of biological systems which approximate such real world processes or operations.

[0078] “Motifs,” as used herein, refers to any repeated subsequences of information.

[0079] “Oncogenesis,” as used herein, refers to the formation of a cancer, whereby normal cells are transformed into cancer cells, also termed “tumorigenesis” or “carcinogenesis”. The process is characterized by changes at the cellular, genetic, and epigenetic levels and abnormal cell division. Mutations in DNA and epimutations disrupt processes involved in the programming and regulation of the normal balance between proliferation and programmed cell death.

[0080] “Response (to stimuli),” as used herein, refers to an action or modification in a biological system that results from external stimulus. A response may take any of several forms. For example, in the case of a unicellular organism, it may be the contraction resulting from exposure to the presence of chemicals in the environment. As another example, response may be a complex set of reactions involving all the senses ofmulticellular organisms. A response is often expressed by motion; for example, the leaves of a plant turning toward the sun (phototropism), and chemotaxis.Detecting Emergent Properties and Improving Health Outcomes

[0081] The generation, analysis, and use of data relating to the health condition or health capacity of biological systems (e.g., a human user) has been explored. More specifically, the use of sensors, and combinations of sensors, for capturing data related to the health capacity of biological systems has also been explored. Health capacity can refer to the resilience (adaptivity) of a system expressed primarily by its ability' to persist or achieve some core function. To assess the health capacity of a system, one may interpret the emergent factors of the system. Emergent factors may refer to events, deviations from norm or other time dependent patterns in some measurable parameter of the system that can be observed directly or indirectly. Emergent factors or properties may also refer to properties of a biological system that are not readily predictable from the functions of the component parts of the system. Examples of emergent properties can include amphotericity, conductivity, solvation capacity, ion mobility, oxidation-reduction potential, ligan association, hydration, electrolysis, thermal conductivity, heat capacity, thermal absorptivity, adhesion, cohesion, transparency, turbidity', incompressibility', polarity, dipolarity, dipole movement, diamagnetism, voltage range of the liquid phase, temperature range of the liquid phase, abundancy, and speciation, flux of energy, momentum, particles or other substances, heat elimination, either as an absolute, statis value of heat elimination or as a periodic function, for example, a circadian periodicity' of heat elimination.

[0082] Physicists have encountered the problem of emergent factors before (e.g., magnetism) and have concluded that it may be advantageous to identify a thermodynamic parameter which summarizes the order, rather than to attempt to measure molecular details of that order directly. In fact, all order is associated with missing energy. (See, for example, https: / / en.wikipedia.org / wiki / Latent_heat). For example, when studying complex materials, physicists look for anomalous specific heats as the bellwether of hidden organization. Landau defined the order parameter (See, for example, https: / / en.wikipedia.org / wiki / Landau_theory): a useful mathematical device which quantifies the thermodynamic character and robustness of the underlying order. Our insight is based, in part, on the concept that the organization of living systems has associated thermodynamic signatures analogous to order parameters. And, only these biological orderparameters will enable highly accurate learning with small sample sizes. Furthermore, it is likely that such a thermal signature may inform us of the robustness of biological order, physiologic reserve and health state.

[0083] The underlying health condition can be monitored or assessed by use of a wearable device that can collect and / or monitor the health capacity of biological systems. It may include at least one wearable thermodynamic sensor that can be configured to measure an emergent factor of the human, wherein the emergent factor is the temporal alignment of heat production and heat elimination of the human, the temporal alignment relating to the circadian rhythm of the human, and based on the emergent factor, generate measured data comprising heat flux data over time. The wearable device may also capture heat flux data, wherein at least one health capacity is a basal metabolic status, and at least one emergent factor is the temporal alignment of heat production and heat elimination of the biological system. The wearable device may include an array of sensors that record health metrics and capture the data. In some embodiments, the wearable device includes at least one pair of wearable thermodynamic sensors that are placed symmetrically, about an axis of symmetry of a subject. This at least one pair of wearable thermodynamic sensors may be configured to capture heat flux data from biological compartments, located symmetrically with respect to an axis of symmetry of the subject, and allow for substantially simultaneous monitoring of the symmetric biological compartments. Each of the symmetrically placed sensors may include an array of sensors that record health metrics and capture the data essentially substantially simultaneously. The wearable device may continuously record select “energy signatures1’ metrics or indicators of health for the subject. In some embodiments, the wearable device requires low cost and low power, enabling accessibility and continuous data capture in real-time. In some embodiments, the wearable device comprises at least one multi-modality sensor system that measures electrochemical, mechanical, structural, thermal, and / or energetic properties reflective of homeostasis and cell physiology. The wearable device can comprise any number of sensors.

[0084] In some aspects, the disclosed wearable device is designed and configured to quantify physiologic energy outputs (for example, peripheral heat and physical activity). This device is benchmarked against gold-standard physiologic endpoints in multiple human studies. Metrics for such benchmarking involve a signal with high accuracy with training sets as small as 25 samples. A robust structure is identified inhuman heat signatures and serves as a direct measure of the autonomic processes underlying homeostasis (i.e., biological organization). Specifically, the device provides a means forthe non-invasively detection of a thermal signature of an inflammatory cascade before any change in core temperature. This observation has ramifications from the perspectives of thermal physics, and transformational biological applications.

[0085] In some aspects, the wearable device described herein utilizes a physical model of temperature homeostasis, inspired by the function of the hypothalamus, to interpret the health significance of an individual’s thermal signature. By measuring the principal data streams which the hypothalamus integrates (heat and body temperature), the device allows for the characterizing of the basis of homeostasis and physiologic reserve -including differences between the sexes - and for defining gender-specific metrics that are relevant to trauma injury' treatment. The wearable device continuously and contextually measures these principal data streams moderated by the hypothalamus, and provides a means for characterizing both individuals and gender groups by measuring their thermal signature to assess what we call a thermoregulatory phenotype.

[0086] In some aspects, the disclosed technology is based, in part, on the utilization of a novel physical model of temperature homeostasis, providing a means for understanding and / or interpreting the health significance of an individual’s thermal signature (thermal phenoty pe) and for acting upon that interpretation in a variety7of ways. The non-invasive wearable device continuously senses thermal signature of body heat, and requires no charge or battery replacement for periods as long as several months. Because the disclosed technology measures body heat, which is fundamentally related to temperature homeostasis, it avoids challenges in using the typical molecular biomarker.

[0087] In some aspects, the disclosure provides devices and methods for continuously and contextually characterizing an individual’s metabolic state by measuring their thermal signature to assess what is referred to as a thermoregulatory phenotype. Changes relative to this phenotype are sensitive indicators of change in health state. The device is designed and configured such that it delivers, in human use, general associations between an individual's thermal signature and physiologic reserve. Additional information is available within the thermal signature to an actionable assessment of health. Clinical studies are designed to gather data that will serve as a novel vital sign of homeostasis as well as an aggregate health signature, with applicability to early detection of many disease states, management of individual wellness.

[0088] The Scholander-Irving model depicts a pattern of changes of resting metabolic of an endothermic homeotherm over a range of ambient temperatures. Per Scholander and Laurence Irving were interested in researching how warm-blooded birdsand mammals maintain body temperature. With such interest, they discovered warmblooded birds and mammals maintain body temperature by balancing their rate of metabolic heat production and the rate of heat lost to the environment.

[0089] However, in relation to humans, one may have limited knowledge regarding their health capabilities, health status, disease state, general state of health, etc. One may gain limited insight into these areas of knowledge only with sophisticated physiologic measurement tools, to which few may have access.

[0090] Emergent factors or emergent properties are identified and selected, for measurement, based on various criteria. Generally speaking, emergent factors that may be directly measured are preferred over emergent factors that may only be measured indirectly. Techniques used to measure (directly or indirectly) that are less invasive are preferred over techniques that are more invasive. Measurements that are reliable and associated with a single emergent factor, rather than multiple emergent factors, are preferred.Example System for Detecting Transitions in Thermoregulation

[0091] One objective of the disclosed technology is to fill a gap in the delivery of healthcare by engineering a purpose-built wearable that detects infection early where it starts (e.g., outside of the hospital), enabling effective treatment, and prevention of sepsis for which there are no approved therapies. It is estimated that up to 87% of cases of infection leading to sepsis start outside of hospitals.

[0092] Most patients at risk of infection leading to sepsis (e g., those who are immunocompromised) are in home or post-acute care locations that lack sophisticated monitoring technology or high touch medical services critical to early detection and treatment. In almost every case, infection is detected and treated late, if at all, when patients manifest overt signs and symptoms necessitating hospitalization. The late onset of symptoms introduces a delay in detection resulting in a missed opportunity to treat a pathogen early with effective therapies and avoid progression to sepsis where only- supportive therapies exist. Current data suggests that for every hour of delay in treatment the risk of death increases 4-9%. Today, sepsis is the leading cause of 30-day hospital readmissions in the United States, and the leading cause of death in immunocompromised patients.

[0093] One goal of the disclosed technology is to provide to patients, physicians, and health systems a new non-invasive, remote, broad-spectrum physiologic monitoring technology that continuously measures and detects changes in thermoregulationthat precede the first sign of infection, fever, to automate the detection of infection, enabling more timely treatment with known and effective therapies.

[0094] In some aspects, the disclosed technology provides an ultra-compact, always-on, wearable medical device linked to a cloud-based platform by a mobile application intended for the continuous measurement and analysis of changes in patterns of thermoregulation that precede changes in core body temperature to aid healthcare professionals in the early detection of infection and sepsis in immunocompromised patients.

[0095] In some embodiments, the disclosed device provides for more effective treatment or diagnosis of life-threatening or irreversibly debilitating human disease or conditions. As sepsis leading to infection is a leading cause of death and disability’ in immunocompromised patients, the disclosed device enables the early detection of infection in ambulator}' and hospitalized patients by detecting changes in patterns of thermoregulation which precede the current gold standard- elevation of core temperature, fever. By detecting infection earlier than existing devices, time-dependent treatments can be employed earlier, improving health outcomes.

[0096] In some embodiments, the disclosed device is a broad-spectrum measurement and analysis device that can detect infection before fever. An essential feature is its accessible deployment across home / post-acute care / hospital settings where gaps in healthcare exist, to capture the pre-clinical / prodromal phase of disease, essential to interception.

[0097] In some embodiments, the disclosed device is a non-invasive device that can detect infection in immunocompromised patients prior to fever that can be readily deployed across non-hospitalized and hospitalized care settings.

[0098] In some embodiments, the disclosed device offers significant advantages over existing approved or cleared alternatives, including the potential, compared to existing approved alternatives, to reduce or eliminate the need for hospitalization, improve patient quality of life, facilitate patients’ ability to manage their own care (such as through self-directed personal assistance), or establish long term clinical efficiencies. In comparison to Sepsis ImmunoScore (the only FDA approved device that allegedly “identifies patients at risk for having or developing sepsis” to this date), the use of the disclosed device is not dependent upon hospitalization. The disclosed device has the ability to detect infection where the majority of cases start, for example, in non-hospital settings. The disclosed device can be worn by patients at home, enabling detection andinterception of infection via continuous monitoring outside of hospital stays, with an expected reduction in (re)hospitalization. In addition, as the principal components of the Sepsis ImmunoScore are core temperature and endogenous pyrogen, the disclosed device will detect infection leading to sepsis earlier, even in emergency or hospital settings. The disclosed device is also noninvasive, does not require the collection of specialized blood tests, does not require access to a patient’s medical data or EMR, and does not employ complex artificial intelligence algorithms.

[0099] In some embodiments, the disclosed device provides continuous monitoring in settings where many immunocompromised patients are susceptible to infection and where gaps in care exist. By providing an always-on, simple-to-use wearable and medical alert system, the disclosed device provides patients with the possibility of earlier treatment leading to improved outcomes.

[0100] In some embodiments, the disclosed device provides a simple, scalable solution for the early detection of infection in non-hospitalized patients who are immunocompromised and at a higher risk of infection leading to sepsis.

[0101] In some embodiments, the disclosed device targets the medical problem of infection leading to sepsis. Sepsis is the leading cause of death worldwide, and the leading cause of hospital readmissions in the United States resulting in significant morbidity and mortality. There is an unmet medical need of immunocompromised patients, e.g. cancer chemotherapy patients, transplant patients, patients with AIDS, patients with autoimmune disorders, patients with chronic illness(es), and the elderly who are frail with multimorbidity, at an exceptionally high risk of infection leading to sepsis. Although changes in thermoregulation can be measured in a hospital setting through a variety means including, for example, clinical exam, blood tests, imaging studies, etc., there does not exist a remote physiologic monitoring system to detect changes in thermoregulation in non-hospital settings where most cases originate.

[0102] Prior art approaches to the detection of infection in immunocompromised patients focus on the measurement of core temperature. Elevation in core temperature, that is, fever, is a late indicator of infection. Elevated core temperature occurs after the pathogen-triggered systemic cytokine in llammatoiy / i mmune response that alters brain hypothalamic set point. What is needed is a new way to detect changes in physiology that occur prior to fever.

[0103] Figure 1 is a schematic diagram that illustrates changes in autonomic control of thermoregulation precede fever and sepsis. Fever is a late-stage clinical sign ofinfection. The use of changes in core temperature as an indication of infection is especially problematic in patients with low white blood cell counts being treated for cancer, so called neutropenic fever. Febnle neutropenia in these populations rises to the level of a medical emergency that requires urgent evaluation (within 1 hour) and remains a significant cause of morbidity, mortality' and cost burden in patients with cancer. The urgency is brough about because fever is a late indicator of infection. It occurs after pathogen exposure, triggering of the innate and adaptive immune systems, activation of the neuroendocrine system ultimately leading to a change in hypothalamic core temperature set point. The approach of the disclosed technology is to detect infection early by the measurement of changes in thermoregulation that are responsible for, and therefore definitionally precede changes in core temperature that result in fever.

[0104] Thus, in some aspects, the disclosed technology provides a patient wearable and a software platform, i.e., a remote physiologic / patient monitor, to measure known changes in thermoregulation that occur during infection prior to fever. Thermoregulation a homeostatic process that maintains a steady internal body temperature despite changes in external conditions. The mechanism of thermoregulation involves afferent sensing, central control, and efferent responses. Peripheral and central thermoreceptors sense an increase or decrease in body temperature and send this information to the hypothalamus. The body then responds with multiple mechanisms to either dissipate or generate heat based on the body's needs. Based on this approach, the clinical hypothesis is that changes in the regulation of core temperature will precede its consequence, fever, and that this data will aid physicians in early treatment of infection leading to sepsis. In addition, data obtained from this approach may lead to subsequent insights and hypotheses concerning: i) discernment of chemotherapy — versus pathogenic — ever for which the treatments are different, and ii) the diagnosis of classes of pathogens based thermoregulatory patterns.

[0105] Figures 2A-2D illustrate the general principles of thermoregulation and how they are used in the disclosed technology. Figure 2A illustrates that humans are endotherms that regulate temperature (homeostasis) to a setpoint of 37°C. This is sometimes depicted as a ‘’balance” to suggest the presence of feedback control mechanisms. Critically, the stability of core temperature is accomplished by a balance between generation and elimination of heat. Each individual possesses a “way” they individually balance energy, referred to herein as their thermoregulatory phenotype.

[0106] Figure 2B illustrates that going beyond the metaphor of “balance”, physiologists have determined that humans achieve temperature homeostasis by generating a surfeit of heat and controlling its release. The skin is the principal organ / site of heat release, but the skin of the periphery serves as a special zone of thermoregulatory control. Peripheral skin has anatomically differentiated zones characterized by specialized hairless structures that contain arteriovenous anastomoses under neuroendocrine control. Vasomotor control of these anastomoses provides the physiologic means whereby the heat release is gated. This control is orchestrated centrally from the brain- specifically the hypothalamus.

[0107] Figure 2C illustrates that the regulatory' control of core temperature relies on information feedback in the neuroendocrine system. Afferent signals, including core and peripheral temperature, are integrated in the hypothalamus to regulate the efferent output signals necessary to achieve temperature homeostasis. Because ambient temperature strongly influences the rate of the flow of heat from the skin, ambient temperature also is implicitly a part of this control loop.

[0108] Figure 2D illustrates that the disclosed device is designed and engineered based on the above established principles: 1) one goal is to produce a data stream from a non-invasive measurement of temperature homeostasis; 2) a strategy' is to measure and characterize heat elimination not at the core, but at the periphery where the brain’s dynamic regulatory control is most clearly’ expressed; 3) an approach is to continuously measure both peripheral skin and ambient temperature, the combination of which is sensitive to local heat elimination and reveals hypothalamic control; 4) the disclosed device uses basic temperature sensing hardware to achieve this, along with standard microprocessor and communications functionality and 5) a plan, substantiated by human clinical data, is to demonstrate that our device records changes in the brain’s control of temperature homeostasis, thermoregulation, which precede fever.

[0109] In some embodiments, the disclosed remote physiologic monitoring system that measures thermoregulation and generates clinically meaningful actionable alerts meets the following criteria, also summarized in Table 1 :1. Measure the physical components of thermal state — heat and temperature.2. Measure at an anatomic location that is sensitive to the brain's control of heat elimination.3. Have an intuitive display of data / derived metrics that are clinically actionable for the ty pical physician.4. Be engineered to deliver continuous awareness of thermoregulatory state, enabling timely intervention.Table 1: Essential system requirementsAttribute Category RationaleHeat and temperature are distinct but intimately related physical parameters. It is not possible to interpret the full significance of one to the Sensitive to both heatPhysics thermoregulatory process without simultaneous and temperatureknowledge of the other. This is related to a deep concept in thermodynamics, where all critical parameters come in pairs.The regulatory aspect of thermoregulation must Measurement at a be foremost. Measurement near an peripheral (skin) Biology’ & autonomic / anatomical control point will thermoregulatory Medicine maximize the signal of the regulatory activity control point relative to random ambient noise or other extraneous thermal details.Mere measurement is not sufficient. The Intuitive data displayinformation contained in the measurement must of changes inInformatics be delivered to clinicians in a timely and legible thermoregulation thatmanner, which does not require extensive, and / or are readily actionablespecialized analysis.Because infection and sepsis are time-dependent phenomenon, a product for the interception of Continuous, remoteEngineering infection must be automated, continuous and and automatedwork in remote contexts in order to enable timelyintervention.

[0110] In some embodiments, each of the attributes in Table 1 is incorporated into the disclosed medical device platform for remote physiologic monitoring of immunocompromised patients at risk of infection leading to sepsis. In some embodiments, the disclosed medical device includes four components. See Figure 3, the center of which is the non-invasive patient wrist-worn wearable. The wearable can continuously measure heat and temperature in proximity to the arteriovenous anastomoses located on the palms of the hands. By linking the data obtained from the wearable via a gateway to the cloud, physicians may be provided with a way to see changes in patterns of thermoregulation that occur prior to fever. These features meet the attributes described in Table 1.[OHl] In some embodiments, the disclosed platform is designed to implement the following requirements:1. Continuous monitoring of thermoregulation2. Automated analysis of thermoregulatory physiologic parameters3. Tools to aid healthcare professionals in the early detection of infection or sepsis in immunocompromised patients4. Simple and robust solutions for patient self-management5. Simple and robust solutions for healthcare professionals to support their patients using the disclosed wearable device.

[0112] In some embodiments, the disclosed platform is designed to deliver on the following objectives:1. FDA class 2-compliant wearable device — produced with an ISO 13548 certified manufacturer — for the measurement of ambient and peripheral skin temperature.2. Measurement data collection that is privacy-ensured.3. High-performance time-series analysis of the measurement data.4. Scalability and fault-tolerant reliability at all points of the system.5. Secure, privileged-only access to data and analysis in aid of health professionals.

[0113] Figure 3 schematically illustrates a specialized platform designed to monitor and analyze thermoregulation of individuals and groups according to some embodiments of the disclosed technology. The disclosed technology prioritizes safety and efficiency. The disclosed technology employed a comprehensive systems design approach, incorporating input from various healthcare professionals who work with high-risk patients. Through clinical trials, the disclosed technology ensured seamless integration with the healthcare professionals’ existing workflows and needs. In some embodiments, the platform comprises four primary functional components:1. Wearable Device: Continuously captures temperature and motion data, forming the basis of our thermoregulatory time series. For example, it may monitor patients and record measurement data 24 hours a day for up to over one year.2. Mobile Applications (e.g., iOS and / or Android): Reads data from the wearable device and faithfully transmits the data to the database used in the disclosed technology. For example, it may securely transmit measurement data without including any personally identifiable information (PII).3. Cloud Platform: Houses secure databases for analytics. In some embodiments, it:a. Ingests data from all the mobile applicationsb. Encrypts the data within raw measurement and analytics databases c. Computes automated analysis of the thermoregulatory’ physiologic parametersd. Hosts the access-controlled clinician portals (for each unique healthcare organization using the wearable device).4. Clinician Portals: Hosted on the cloud platform with protected access for healthcare professionals. Provides data access on a population or individual patient.

[0114] In some embodiment, such structure of the platform allows for robust data collection and analysis while maintaining strict security and privacy standards. In some embodiments, the softwares implemented by the disclosed technology follow IEC 62304 guidance on Medical Device Software Life Cycle.

[0115] In some embodiments, the mobile application may serve as a communications gateway. In some embodiments, there is no data shared with the patient on the communications gateway because the requirement is to aid the healthcare professional in decision. The patient may be given confirmation of the data transfer status and corresponding instructions. In some embodiments, the mobile application communicates with the cloud using authenticated cloud APIs over a TLS secured connection.

[0116] In some embodiments, the data is received by a load-balanced cloud service that reliably writes the raw- data into a secured database. This service and database may be implemented on AWS S3.

[0117] In some embodiment, the disclosed platform scales to support millions of monitored patients across multiple healthcare organizations, each with their own privacy and security policy requirements. This may be enabled by a modular distributed architecture approach. The disclosed platform may also scale based on component level scalability, where each component is independently customized and load balanced. The following is a summary of how each component is designed to scale, in some embodiments:1. Wearable Devices: These are deployed and replaceable on-demand by healthcare professionals. The wearable will store measurement data until a transmission completes successfully so a continuous connection to the mobile application is not required.2. Mobile Application Gateway: The application passes along all data from a wearable to the cloud. It does not change the data at all, and the applicationwill ensure that the data is successfully received by the cloud into a secure database.3. Cloud Platform: As shown in Figure 3, the cloud includes sub-components that perform independent computation or data management functions. Each of the cloud components is dynamically scalable - developed as interoperable cloud services using leased HIPAA AWS resources. The operations team can monitor each of the cloud sub-components and will either automatically or manually scale up / down.4. Clinician Portals: The portal provides personalized data views to clinicians - and may be fully managed by the operations team. The portal is implemented within the cloud platform (e.g., an AWS cloud platform) and can be automatically scaled based on the views requested by all clinician end-users.Example Data Measured by the System

[0118] In some embodiment, the intended use population are immunocompromised patients at high risk for infection leading to sepsis. Patterns of thermoregulation derived from the disclosed wearable may be compared with gold standard clinical indices of immunodeficiency and fever. For example. Figures 4 and 5 show representative data obtained from one patient among several patients that were undergoing elective bone marrow transplant, were hospitalized and w ere at high risk of infection. The patient experienced multiple episodes of clinically relevant fever and w as treated and recovered from a blood-bom bacterial infection. A time series of core temperature and leukocyte count are compared with thermoregulatory rhythm and anomalies obtained from the disclosed platform. The hypothesis was that change in thermoregulation as represented by changes in thermoregulatory rhythm and / or stability w ould occur prior to clinical fever.

[0119] Figure 4 show s a comparison of thermoregulatory rhythms of a healthy person versus hospitalized immunocompromised oncology patient. The thermoregulatory rhythms were obtained from the disclosed device for two subjects over more than 3 weeks. The upper panel of Figure 4 represents a healthy control, and the lower panel of Figure 4 is a hospitalized patient undergoing an elective bone marrow' transplant. Once values for temperature and heat are obtained, they are plotted as a time series in a 2 * 2 grid representing an individual thermoregulatory rhythm, the autonomic feedback control system described in Figure 2C. The variation in color connotes one of fourthermoregulatory states. Initial inspection reveals a periodic rhythm for the healthy subject (upper panel). In contrast, the rhythm for a hospitalized patient undergoing treatment (lower panel) starts regular and becomes irregular. Black regions connote when the subject is not wearing the device, i.e., “off wrist.”

[0120] In the healthy subject, while there is a readily identifiable rhythm, there are substantial variations in any 24-hour interval. These systematic variations arise because the energy load on core temperature, e.g., work, sleep, diet, ambient temperature, etc., vary daily. This data view may be referred to as a depiction of a thermoregulatory phenotype, connoting how a person adjusts the flow of energy to achieve temperature homoeostasis. See also Figure 2A.

[0121] In contrast to the healthy subject, the hospitalized subject initially has a very regular rhythm, which deteriorates in about 12 days into hospitalization, remains irregular for about 10 days and recovers some periodicity7thereafter. The initial highly regular pattern is explained by hospital residence where energy7load, e.g., sleep, work, diet and ambient temperature, etc., is highly controlled. The abrupt loss and subsequent recovery of rhythm may be explained by neutropenic fever and infection followed by successful treatment. See Figure 5 for additional details.

[0122] Figure 5 shows a comparison of thermoregulatory7rhythms of hospitalized immunocompromised oncology patient with neutrophil count and core body temperature. Data obtained from the disclosed device (third and fourth panels from the top) versus values obtained for core temperature (first panel from the top) and leukocyte (WBC) count (second panel from the top) for a hospitalized patient undergoing a bone marrow transplant. There is a substantial loss of thermoregulatory7rhythm on around 5 / 22 / 24 that precedes neutropenic fever by about 4 days which occurs on 5 / 26 / 24 (third panel from the top). To the calculation of rhythm, thermoregulatory stability is also computed (shown in the fourth panel from the top). Briefly , values for temperature and heat are obtained, and plotted in reference to normal values shown in light blue which were obtained for more than 250 subjects. Values that fall outside of the normal plot of heat versus temperature (the normal thermoregulatory zone) are designated as instability. The variations in color, dark blue or red, connotes one of two unstable thermoregulatory^ states. Comparing the first and second panels with the fourth panel, a positive correlation betw een the occurrence of neutropenic fever and loss of thermoregulatory stability can be observed. The loss of stability substantially precedes fever by about 28 hours. Additionally, the loss of stability remains throughout the duration of the febrile episode and persists beyond the recovery ofnormal core temperature. Return to the normal thermoregulatory' zone was correlated to clinical parameters of successful treatment and recovery (data not shown). The instabilities (shown in the fourth panel) that occurs on 5 / 14 / 24 and 5 / 15 / 24 correlate to an elevation of core temperature (shown in the first panel). The instabilities were associated with administration of CART cell therapy.Example Data Path

[0123] Figure 6 schematically illustrates that all platform communication links and databases used in the disclosed technology' are secured following the latest best practices and standards. The data path shown in Figure 6 includes generating, transmitting, computing, and displaying data from the wearable to the physician. The physician portal may utilize the analysis results based on the access-protected measurement data in the database used in the disclosed technology7. In some embodiments,1. The wearable generates data for the system. It does so by continuously measuring and recording peripheral skin and ambient temperature.2. The mobile application transmits data, without any modifications, from the wearable to the cloud used in the disclosed technology. This is conducted securely.3. The cloud platform receives the data from all the disclosed mobile applications and securely stores the data in databases.4. The cloud platform automatically analyzes the database-stored measurement data and records the results in an analytics database.5. The cloud platform provides healthcare organizations with access to protected web portals, enabling clinicians to view the results of their patient population as recorded within the analytics database.

[0124] In some embodiments, the disclosed technology ensures secure communication between core components, protecting against data breaches and unauthorized access. In some embodiments, the disclosed technology adheres to a robust security' policy. In some embiments, the disclosed technology can be achieved using art recognized commercial standards for communications. In some embodiments, the system's architecture allow s for seamless updates to implementation methods as superior solutions emerge, without compromising data integrity or analytical results, including historical information. In some embodiments, the mobile application gateway and cloud platform communicate securely, adhering to CMS recommendations and federal data transitrequirements outlined in NIST SP 800-52 Revision 2. In some embodiments, clinician access to the measured data is strictly controlled, limiting visibility to only those wearable devices associated with the specific clinician and their healthcare organization. In some embodiments, clinicians interact with a secure w eb portal hosted on the cloud infrastructure used by the disclosed technology (e.g., an AWS cloud infrastructure). This setup ensures all clinician-related computations occur within a protected cloud environment, keeping raw data and results contained within the platform. In some embodiments, access to personalized portals is granted through secure username-password credentials, and the approval and revocation of these access credentials for each clinician is managed.

[0125] In some embodiments, to ensure data privacy and security, all communication links between the key components are secured against data theft and unauthorized interpreters. In some embodiments, the system is designed to allow updating the implementations methods used when better solutions become available. This will not affect the integrity of the data and analysis, including any existing data.

[0126] In some embodiments, communication between the wearable and the mobile application gateway is accomplished using the highest level of the Bluetooth Low Energy Secure Connection standard (Bluetooth 5.1 / 5.2). For example, it may use a Federal Information Processing Standards (FIPS) compliant algorithm called Elliptic Curve Diffie Hellman (ECDH).

[0127] In some embodiments, communication between the mobile application gateway and the cloud platform is secured using IETF TLS - the Internet Engineering Task Force, Transport Layer Security. This is consistent with CMS recommendation and federal data transit mandate in NIST SP 800-52 Revision 2.

[0128] In some embodiments, to further protect data, all data sent from the wearable is devoid of any ePHI. Access to the data via the clinician portal may be privileged by restricting access to only the wearable devices associated with the clinician and their healthcare organization. The clinician may use a secure w eb portal that is hosted from the cloud used in the disclosed technology. Thus, all computation required by the clinician may be performed within a protected cloud platform - the raw data and results remain within the cloud platform. The clinician may gain access to their personalized portal using TLS secured username-password credentials. The portal access credentials for each clinician may be subject to approval and removal.Example Design and Specification of the Wearable

[0129] In some embodiments, the disclosed wearable device and platform is purposefully designed and engineered for the early detection of infection leading to sepsis in non-hospitalized settings. In some embodiments, the disclosed wearable device is also readily deployable within hospital settings. In some embodiments, the primary benefit of early detection is derived from the measurement of thermoregulation at an anatomic control point whose change precedes fever. In some embodiments, the disclosed wearable device is designed for simplicity of use as both a remote physiologic monitoring technology and as an adjunct to in-hospital monitoring of vital signs. See Table 2 for the design benefits.Table 2: Design benefits.Attribute Benefit UsersFDA-approved medical device Proven safe &effectiveMeasurement of thermoregulation Early detectionPatients / family Wearable Non-hospital Physicians One year battery life, does not need Compliance Nurses recharging IT Personnel Automated EfficientLow cost, effortless for users Scalable

[0130] In some embodiments, the disclosed wearable device has three types of users: patients, healthcare providers, and managers of healthcare information technologies.

[0131] In some embodiments, the disclosed wearable device is developed to comply with harmonized standards recognized by the International Standards Organization (ISO) and the US Food and Drug administration (FDA). These standards relate to effectiveness regarding electrical safety, mechanical safety, software safety, and biocompatibility. See Table 3.Table 3: StandardsISO 14971 Shelf lifeFCC Rules CFRno. 47, Part 15 Subparts B and C Section 15.247 AIM 7351731 RFID ImmunityANSI IEEE C63.27 Wireless coexistenceANSI / ISA 62443-2-1 CybersecurityISO / IEC 27001 CybersecurityTable 3: StandardsIEC 62304:2015 Software Lifecycle ProcessesISO 10993-1:2018 Biological evaluation of medical devicesISO 14971:2019 Application of risk management to medical devicesISO 10993-5 CytotoxicityISO 10993-10:2010 Tests for irritation and skin sensitizationISO 20417:2021Packaging. Markings and Instructions for Use

[0132] Figure 7 illustrates the hardware schematic of the patient wearable device according to some embodiments of the disclosed technology, including the specific hardware and placement for all hardware components related to physiologic measurement sensors, patient / clinician usability, required functionality, and safety / reliability. An engineering design challenge was to develop a safe, ultra-lightweight, dependable thermoregulation monitor that is exceptionally user-friendly. A primary design challenge was to create a dependable, small wearable that accurately measures both skin and ambient temperatures, suitable for both in-hospital and everyday use. To make it practical to use the device, an affordable, mass-producible compact device that also ensured thermal isolation for each temperature sensor, despite having an loT board and battery between them, is needed. In some embodiments, the technical solution is to use a highly compact custom loT board with Osram’s pre-calibrated temperature sensors attached to flexible circuit wings, achieving sufficient thermal isolation using air gaps and foam. A second engineering challenge was the data communication challenge, and the technical solution utilizes a low-energy Bluetooth antenna-in-a-chip to keep things compact. In some embodiments, the battery and loT board design does not exceed 3 milliwatts even when all components are powered on.

[0133] In addition, since health professionals may want to ensure that "anyone physically and / or mentally capable can easily remove the wearable." a strap that is easy to attach and remove may be used in the disclosed w earable. For safety and biocompatibility, the strap may use only ISO 10993-5 & 10993-10 materials for the external surfaces. Such material selection supports the use of 30% isopropyl alcohol every 12 hours. In some embodiments, the strap material includes an FDA-approved biocompatible elastomeric material. In some embodiments, all materials in contact with the patient are FDA-approved biocompatible materials. The external monitor housing components may include an FDA-approved biocompatible injection molded plastic.

[0134] In some embodiments, the wearable has two parts that contact a patient’ s skin: One is a round sensor unit that is fully enclosed with FDA-biocompatible thermoplastic, and second, a strap that is specifically designed for ease of removal - even for a frail patient - that is also manufactured with FDA-biocompatible thermoplastic.

[0135] To avoid disturbing patients, a feature may be implemented that allows data transfer by gently tapping the wearable with a device that hosts the disclosed mobile application, which introduced the need for a Near Field Communication (NFC) coil and associated loT board components. Additionally, the enclosure of the wearable device may be designed with specific mechanical snaps and an O-ring to achieve IP67 dirt and water protection. In some embodiments, the device incorporates the O-ring to prevent dirt and moisture ingress per IP67 rating.

[0136] In some embodiments, the wearable device incorporates two temperature sensors for monitoring the patient’s skin temperature and the ambient temperature surrounding the patient. In some embodiments, the device measures temperature at two points, the top and bottom of the device, corresponding to skin and ambient temperature, respectively. By subtracting the two temperatures, a temperature gradient, which is driven by body heat and sensitive to changes in heat elimination, is quantified. Given that heat leaves the body in a variety' of forms, an accurate measure of total body heat elimination may not be obtainable in a wearable form. Without being bound by theory, the focus of the disclosed technology on measuring insensible heat loss near an autonomic control point is not because it is an accurate measure of Total Energy Expenditure (TEE), but because it is an informative signal of thermoregulation.

[0137] In some embodiments, the wearable device further incorporates an inertia measurement unit (IMU) to monitor and collect patient activity data. In some embodiments, the wearable device incorporates a central processing unit that manages all device functions. In some embodiments, the device incorporates an ultra-Low Energy Bluetooth module and near-field communication antenna (NFC) for communicating with the disclosed mobile application and for patient ease-of-use. In some embodiments, the external housings snap together permanently to enclose the PCBA and battery (therefore, no user access to internal components). In some embodiments, the device is held in place and presents the skin temperature side of the device to the patient via an adjustable band that allows the patient to wear the device on either wrist.

[0138] In some embodiments, the device incorporates a lithium-ion, non-rechargeable primary battery to power all electrical functions. The CR2032 battery may besealed and cannot be accessed by the patient. In some embodiments, the device is intended to be used by a single patient and the clinician receives a non-PHI unique patient identifier during the provisioning process.

[0139] In some embodiments, the wearable may use the 5.1 / 5.2 Bluetooth standard for ultra-low energy data transfer. In some embodiments, the wearable may use Near Field Communication (NFC) to manually initiate a data transfer via the disclosed mobile application by simply tapping the wearable to a smartphone that has the disclosed mobile application. The NFC tap-to-transfer feature can make it easier for healthcare professionals to assist patients.Example Data Views and Physician Portal

[0140] The disclosed technology can aid physicians in decision support by detecting changes from baseline patterns of thermoregulation that may indicate early signs of infection or sepsis. To that end, views of data which enable a physician to explore and analyze patient data may be provided.

[0141] In some embodiments, there are two primary data views which highlight two distinct aspects of thermoregulation for a single patient. Both take the form of time series bar charts with a bar for each hour. The first depicts the rhythm of thermoregulation. The principal feature of this display is a circadian rhythm. The second display depicts anomalies of thermoregulation as compared to the normal baseline. These two views are natural complements of each other.

[0142] In some embodiments, in addition to the above data view for a single patient, a group view for multiple patients may be provided, by aggregating each patient’s data into a concise pie chart which can be displayed in a grid layout. The pie chart provides a summary of each patient’s state, and a comparison to the recent past without the full detail of the time series representation which is included in the single patient data views.

[0143] The phy sician portal may be designed to be intuitive and simple to use. In some embodiments, there are two modes a clinician can use: the population mode for a rapid '‘triage” of a patient care group, or the patient mode for rapid “assessment” of a single patient.

[0144] For example, clinicians interact with a secure web portal as described in Figure 6. In this clinical portal, a physician can view a group of patients under their care, a view that is called “automated triage.” Values computed in this view may be based on thermoregulatory stability. Figure 8, left panel, depicts a single patient summary viewaccording to some embodiments of the disclosed technology. The outer circle of the pie chart is obtained by summing the time a subject is in a region of stability or instability over 24 hrs. The inner circle of the pie chart is a reference value for the same subject obtained as rolling average of values obtained over 7 previous days. In this example the daily and weekly values are the same. Figure 8, right panel, shows the automated triage view for multiple patients under care, according to some embodiments of the disclosed technology. The physician can use the default value for a particular parameter or set their own threshold value for automated alerts. In this view the “alert” is indicated by the “red dot” contained within a subject’s pie chart data representation.

[0145] The physician portal may also include patient views of thermoregulatory rhythm (representative views are shown in Figures 4 and 5).Analysis and Display of Thermoregulation Data

[0146] An objective in building the aforementioned bar chart visualization is to gather several attributes necessary for effective analysis of thermoregulation into a single figure. These attributes include:1. Date and time as the pn mary independent axis2. A coarse mechanism for illustrating changing relationship between heat and temperature3. A way of embedding our knowledge of normal patterns and baselines

[0147] Consistent with these attributes, a display according to some embodiments of the disclosed technology may depict two key aspects of thermoregulation: 1) its rhythm, and 2) its stability over time. For example, the space of the 2-dimensional thermoregulatory plane may be divided into zones which represent distinct modes of thermoregulation. The distribution of a collection of measurements among a set of categories may be depicted with a bar chart. A stacked bar chart may be a particularly effective way to depict changes in thermoregulation over time. Detailed definitions of the thermoregulatory zones may be different for the rhythm and stability plots but the process for generating the plots may be the same in each case. In some embodiments, the process for generating the plots include:1. Each measurement is labelled by its zone according to the algebraic inequalities listed in Table 4A and Table 4B.2. For each hour, the number of measurements in each zone is counted.3. The count in each zone is converted into a percentage of time spent in that zone.4. A stacked bar representation of the percentages is constructed using the color maps depicted in Figure 9.5. The above steps are repeated for each hour of data and the bars are arranged horizontally to depict the passage of time.Table 4A: Rhythm Table 4B: StabilityDetermine the color associated with each Determine the color of each point in the data point in the rhythm plot using the stability plot using the following logic following logic: IF heat <= y3(Ts) THEN color = royal blue IF heat > yl(Ts) AND heat > y2(Ts) THEN IF heat > y3(Ts) AND heat <=y4(Ts) color = yellow THEN color = light blueIF heat > yl(Ts) AND heat <= y2(Ts) IF heat > y3(Ts) AND heat > y4(Ts) THEN THEN color = orange color = RedIF heat <= y l(Ts) AND heat > y2(Ts) y3(Ts) and y4(Ts) are the two black lines THEN color = light blue shown in Figure 9, right panel. In some IF heat <= y l(Ts) AND heat <= y2(Ts) embodiments, at least one of the two black THEN color = dark blue lines may be linear.yl(Ts) and y2(Ts) are the two black linesshown in Figure 9, left panel. In someembodiments, at least one of the two blacklines may be linear.

[0148] Figure 9 depict the division of the thermoregulatory plane into zones in the analysis of rhythm (left panel) and instability (right panel), according to some embodiments of the disclosed technology. Plotted on the X-axis is skin temperature and on the Y-axis is heat (approximated by skin temperature minus ambient temperature). The specific locations of the boundaries between zones were chosen based on observation of a large number of human subjects and encode the understanding of the baseline pattern. Specifically, the boundaries in the stability plot (right panel) surround the vast number of measurements of thermoregulations derived by the disclosed device. In this sense, the stability plot shows the natural range of thermoregulation in light blue. By contrast, the rhythm plot (left panel) simply divides the normal range of thermoregulation into four zones which meet at a central point.

[0149] Using the disclosed wearable device that can detect pattern changes in a person’s baseline thermal signature and based on the fact that thermal signatures have an underlying pattern related to normal circadian rhythm, the disclosed methods for analysis and display of thermoregulation data can be configured to detect changes in circadianrhythm that far precede other pattern anomalies in thermal signature. The following demonstrates that by examining sepsis trials data, it is possible to not only detect infection (e.g., sepsis) based on a characteristic ‘"J” curve on a triangle plot (where the curve reflects the generation of a fever), but also detect other patterns even before a fever is generated, sometimes days before a fever. Those patterns are disruptions in the periodicity of circadian rhythm.

[0150] Figure 10 shows thermoregulation data measured from a sepsis patient. The top panel in Figure 10 is the core temperature, which has a huge scatter because of the manual nature of the measurement. It is difficult to pull any trend information out prior to the big spike in temperature late in the infection. The four panels below are all based on data measured by the disclosed wearable device. The second and third panels are raw data from heat and skin temperature, respectively. The fourth and fifth panels are circadian rhythm fits over the skin temperature. Specifically, the fourth panel illustrates by a vertical line the daily range of the the amplitude of the skin temperature, and the fifth panel illustrates by a vertical line the daily mesor (a mean value based on the distribution of values across the cycles of the circadian rhythm, computed using a cosine function) of the skin temperature. What is revealed by the data is that the raw data, and the circadian metrics computed over it, show a profound change as much as about 6 days before the clinical detection. To depict the time lead, the clinical detection is highlighted in red and the likely detection is highlighted in green. Interestingly, the detection is very close to the lonely high core temperature measurement, which may not be a mere coincidence. The disclosed device may be very useful in disambiguating real sentinel signs of infection from mere noise and aiding in decision support.

[0151] The analysis shown in Figure 10 is an explicit circadian analysis of the skin temperature signal. In this case, it can be observed that the circadian rhythm changes as much as about 6 days before the fever shows up in core temperature. Therefore, a cosine wave was fitted to the circadian rhythm of skin temperature, and a drop in amplitude around the time the signal changes can be observed. These amplitude metrics can be made statistically rigorous. Here they are plotted with error bars. This particular fit was performed using a rolling 72-hour window of the data and the fitting was performed using the function curve_fit out of the python package scipy. Based on this stream of circadian metrics, anomaly detection can be incorporated into the automated triage function.

[0152] Figure 11 shows the same thermoregulation data as in Figure 10, but analyzed and displayed in a different way. Here, rather than performing a circadian rhythmfitting procedure, the bar chart type depiction of rhythm and anomalies are examined. This creates a striking visual representation of the individual’s circadian rhythm. An increase in the appearance of one color or another over time indicates that the individual’s pattern has shifted. The boundaries of the four zones can be seen in the triangle plot in the upper right comer. These zone boundaries are chosen by matching the slopes of the upper edges of the triangle and having them intersect at a point. In this case, the data show that in the days before the red out-of-triangle anomaly, there was extra yellow in the in-triangle bar charts. This is easier to see than from a distance than the subtle change in skin temperature in the raw time series trace.

[0153] Figures 12A, 12B and 12C show likely sepsis events. In-triangle rhythm and out-of-triangle anomalies are shown together to enable a highly complementary combination of analysis. The in-triangle rhythm or pattern is an expression of health. In this case, it is captured by a course division of the triangle into four zones. The interplay between these zones is simple to display in these bar charts and expresses a large portion of a blob-shaped pattern versus a boomerang-shaped pattern in the triangle-based plots. The out-of-triangle data points indicate anomalies. A darker red indicates when the patient goes further outside on the red side of the triangle. While the examples shown here are diverse, the general behavior is that the in-triangle rhythm breaks before a patient’s data leaves the triangle.

[0154] Based on the data measured by the disclosed device, the disclosed technology reveals several distinct signs that are observed to precede fever. These signs are:1. Persistent stay outside the right edge of triangle2. Persistent rightward shift of energy signature3. Increased occupation of the boomerang notch4. Observation of J-curve pattern5. Deterioration of circadian rhythm.

[0155] The disclosed technology also reveals several signs that could be derived from core temperature measurements:6. Decrease in variability of core temperature7. Rising trend in core temperature8. Recent transient core temperature spike above 38.5 °C9. Sustained core temp above 38.5 °C

[0156] The aforementioned signs are nine distinct aspects of thermoregulatory phenotype. Not only the measurement and analysis of the first five signs can be automated, but also analysis of the last four signs can be automated within the disclosed technology with the input of temperature data. For example, application software of the disclosed technology could prompt users to check their core temperatures periodically (e.g., while transferring data, on a preset schedule, or when prompted by alerts based on anomalies detected). This core temperature data could be used to detect clinical fever according to standard definition. Meanwhile, a stack of thermoregulatory phenotype scores, which are consumer health metrics, can be displayed. Only metric number 9 has medical content relevant to the FDA, but the other metrics are present whether or not the core temperature readings are input to the application. The first five metrics may be computed even when no core temperature measurement has been input.

[0157] Figure 13 shows thermoregulation data and leukocyte readings measured in a patient who had real sepsis, was in cancer recovery ward, had chemotherapy and was kept in an isolated room. The first panel of Figure 13 shows two measurements of core temperature of the patient. The nurses took core temperature by an invasive measurement. From beginning to first green line, the core temperature first stays fairly constant, then they start to exhibit a bit more range and climb up higher. The horizontal red line is considered a clinical fever baseline. The data exhibit clinical fever on the 14th or 15th of May 2024, come back down, dip, and then spike right before the second green line. The spike before the first green line is the first time the core temperature approaches a fever and just crosses the line briefly. Between the green lines the core temperature is in the acceptable range, but it starts to slowly rise again and then hits and stays above clinical fever at the horizontal red line. The vertical red line indicates the point at which doctors decided to take a laboratory sample and then immediately applied antibiotics, causing the core temperature to come under control again. Without being bound by theory, when the control system of the patient fails, the patient has fever. In other words, when core temperature shows fever, something is already wrong.

[0158] The second panel of Figure 13 shows leukocyte readings of the patient. The leukocyte readings show a dip, consistent with simultaneous occurrence of the chemotherapy that compromised the patient’s immune system, resulting in an infection and ultimately the fever. The third and fourth panels of Figure 13 show heat and skin temperature of the patient, respectively. The heat and skin temperature exhibit regular, periodicity patterns, unlike the core temperature. Without being bound by theory, theperiodicity is related to circadian rhythm and also depends on metabolism (e.g., eating, digesting, storing, etc.). The first green line on May 21, 2024 indicates the first time the patient had fever, and in the meanwhile the patient had symptoms of swelling (edema) so the wearable device was took off and the data were lost. However, it can be observed that between the time before the first green line and the time after the first green line, the pattern goes from regular to irregular.

[0159] The fifth and sixth panels of Figure 13 show amplitude and mesor of the skin temperature, respectively, where the horizontal line represents the mean and the extended bars represent the max / min of the data. The data go from steady and well-regulated to less regulated and volatile. There is an artificial drop in the data between the two green lines due to the wearable device being taken off. After the second green line, the mean temperature of skin goes up. In some embodiments, the amplitude may be used as the leading indicator of fever according to the disclosed technology.

[0160] Between the second green line and the red line is where the “J” curve is observed. Instead of the core temperature being controlled on daily cycle, what can be observed is the system failing and going into a failure cycle (e.g., at the first green line). Without being bound by theory, the skin is part of the core temperature regulatory system, and the core temperature will lag in infection because of some multi-day process where the patient doesn’t feel right. Therefore, in some embodiments, the disclosed technology detects a change or transition in in the control system in how the body regulates temperature (homeostatic regulation). In some cases, transition of the thermoregulation system from one state to another signals not a failure of the adaptive control system but a shift in how it is controlling the homeostatic. In some cases, the transition is the earliest time an emergent condition can be detected. In some cases, changes in homeostasis are preceded in changes in the homeostatic state. In some cases, the disclosed technology is not detecting the change in homeostasis, but rather, the change in control system for homeostasis. In some cases, the “J” curve represents moving to a different mode of the control system where the core temperature is forced to rise.Example; Early Detection of Fever in Sepsis Patients

[0161] In some aspects, the disclosed technology7relates to a method of early detection of fever, especially in sepsis patients.

[0162] In certain embodiments, the method is a method for the assessment of fever in a monitored subject: obtaining heat flux data for the subject, wherein the data isbased at least in part on skin temperature and ambient temperature measurements that are collected substantially continuously and automatically; determining whether the heat flux data falls within a predetermined regions designated as (i) positive for fever, (ii) indeterminant for fever, or (iii) negative for fever; and reporting the designation (i) positive for fever, (ii) indeterminant for fever, or (iii) negative for fever as an assessment of fever in the monitored subject. In certain embodiments, the heat flux data is substantially based on skin temperature and ambient temperature measurements. In certain embodiments, the heat flux data is not based on core temperature measurements. In certain embodiments, the assessment of fever is provided earlier in the progress of disease than an assessment based on core temperature measurements alone. In certain embodiments, the subject is an immune-compromised patient. In certain embodiments, the reporting is provided to a health care professional.

[0163] To verify that methods of early assessment or detection of fever is reliable, non-invasive, and substantially continuous, a method according to the present disclosure were as reliable known methods based on core temperature measurement, an example of the present method was compared to a method in which the at least two of the segments were labeled according to the maximum core temperature (max(Tc)) measured within the segment with one of the following designations: a first label designation where max(Tc) > 38.5°C, a second label designation where max Tc) < 38.5°C and max(Tc) > 37.5°C, or a third label designation where max(Tc) > 37.5°C; and reporting the designations for the at least tw o segments as an early assessment of fever in the monitored subject. Results of the method of early assessment or detection of fever according to the present disclosure showed this method to be at least as reliable as methods that would require the non-substantially continuous, invasive detection of core temperature.

[0164] Preferably, the labeling is of at least four of the segments. The first label designation is positive as to fever. The second label designation is of early fever temperature elevation. The third designation is negative as to fever. The subject may be an immune-compromised patient. The method may also include a step wherein the reporting is provided to a health care professional.

[0165] In some embodiments, an objective of the disclosed technology is to provide patients, physicians, and health systems with a new non-invasive temperature monitoring system, device and method that continuously measures and detects changes inthermoregulation. The disclosed technology may be configured to help detect some fevers earlier and determine timely treatment options with known and effective therapies.

[0166] There is an unmet clinical need for hospitalized sepsis patients to have fevers detected before it is too late. For immunocompromised patients, especially sepsis patients, detecting fever early is critical because this is frequently the only clinical sign of a treatable life-threatening infection (see A. G. Freifeld et al., “Clinical Practice Guideline for the Use of Antimicrobial Agents in Neutropenic Patients with Cancer: 2010 Update by the Infectious Diseases Society of America,” Clin. Infect. Dis., vol. 52, no. 4, pp. e56-e93, 2011, doi: 10.1093 / cid / cir073). Delay in diagnosis of fever and treatment of infection significantly increases the rate of mortality, and rapid inter ention is essential. The majority of patients who develop fever during neutropenia have no identifiable site of infection and no positive culture results. Medical societies, including for example the Infectious Diseases Society of America, recommend that every patient with fever and neutropenia receive empirical antibiotic therapy urgently (for example, within two hours) after presentation because infection may progress rapidly in these patients. See A. G. Freifeld et al., “Clinical Practice Guideline for the Use of Antimicrobial Agents in Neutropenic Patients with Cancer: 2010 Update by the Infectious Diseases Society of America,” Clin. Infect. Dis., vol. 52, no. 4, pp. 61, 2011.

[0167] To better avoid the risks associated with the use of indwelling blood catheters or urinary catheters for immunocompromised patients, the existing standard of care involves the use of interval non-invasive measurement of core temperature. While conceptually simple, interval thermometry is, in practice, subject to significant limitations. The most significant of these limitations are critical gaps in patient data. A typical standard, applicable for in-hospital oncology settings, is the periodic non-invasive measurement of the core temperature of a patient, typically once every four to eight hours, with a threshold for diagnosis of fever set at 38°C. See C. Flora et al., “High-frequency temperature monitoring for early detection of febrile adverse events in patients with cancer,” Cancer Cell, vol. 39, no. 9, pp. 1167-1168, 2021). This standard of care practice has been established based on clinical yield and nursing workload, but it is prone to missing fevers that arise between measurements. Moreover, vital parameters are often not measured or monitored in accordance with doctor instructions. See L. S. van Galen et al., “Delayed Recognition of Deterioration of Patients in General Wards Is Mostly Caused by Human Related Monitoring Failures: A Root Cause Analysis of Unplanned ICU Admissions,” PLoS ONE, vol. 11, no. 8, p. e0161393, 2016. Therefore, while core temperaturemeasurement is a standard of care for confirming the presence or absence of fever, it is burdensome to measure at a high frequency and with high confidence.

[0168] Known devices and methods to address the need for earlier fever detection have severe disadvantages in sepsis patients. For example, interval monitoring is prone to missed measurements and places a substantial burden on both patients and healthcare workers; invasive probes pose significant risks for immunocompromised patients while also limiting patient activities and movement; adhesive patches may be less accurate than other methods, and the risk of skin injury poses significant risks for immunocompromised patients. See M. Qi, Y. Qin, S. Meng, N. Feng, and Y. Meng, “Risk factors for medical adhesive-related skin injury at the site of peripherally inserted central venous catheter placement in patients with cancer: a single-centre prospective study from China,’’ BMJ Open, vol. 14, no. 3, p. e080816, 2024; see also J. F. Pires-Junior, T. C. M. Chianca, E. L. Borges, C. Azevedo, and G. P. R. Simino, “Medical adhesive-related skin injury in cancer patients: A prospective cohort study,” Rev. Lat.-Am. Enferm, vol. 29, p. e3500, 2021). These devices and methods also limit patient activities, such as bathing, and ingestible sensors are not indicated for those who weigh less than 80 pounds or for those who are “physiologically unsound” or pose other challenges.

[0169] New methods for measuring the onset of fever, or otherwise derive a surrogate measure of core temperature, is needed. Such methods would be, preferably, non-invasive, continuous, automated, operator independent, and have an acceptable false positive rate, with a low false negative rate to identify treatable fevers quickly and successfully. For immunocompromised patients, such methods would preferably identify fever early and thus save lives.

[0170] The disclosed technology, in certain embodiments, uses a complementary technique to detect clinically important fevers before such fevers might otherwise be found using interval core temperature measurements. This technology can supplement, but need not replace, the current standard of care - core temperature measurement.

[0171] In some preferred embodiments, the disclosed technology includes non-invasive wearable devices, preferably worn on or near the wrist, that measure changes in heat elimination. Such measurement of heat elimination serves as a surrogate for changes in temperature homeostasis which, in turn, lead to fever. More specifically, the hypothalamus manages core temperature by regulating peripheral blood flow and, in turn, regulates heat elimination. This occurs at specialized anatomic sites: arteriovenousanastomoses, or the connections between arteries and veins. See, e.g., N. A. S. Taylor, M. J. Tipton, and G. P. Kenny, “Considerations for the measurement of core, skin and mean body temperatures,” J. Therm. Biol., vol. 46, pp. 72-101, 2014. When ambient temperature is lower than core temperature, and when arteries and / or veins are vasoconstricted, heat is conserved, and core temperature is elevated. Conversely, when arteries and / or veins are vasodilated, heat is eliminated more quickly and core temperature decreases. Because the flow of heat is dependent upon a temperature difference between ambient temperature and core temperature, measuring both skin temperature and ambient temperature is a viable way to characterize this control mechanism and its relationship to changes in core temperature that result in fever. The non-invasive wearable devices disclosed herein close the gaps in interval core temperature measurement. They are also amenable to automation, predictive analytics, and for providing alters to healthcare workers.

[0172] In certain embodiments, the disclosed technology includes embodiments useful for monitoring fever in immunocompromised patients. Such patient may be hospitalized. Such monitoring preferably supplements routine core temperature monitoring. In some preferred embodiments, the devices measure physiologic signals associated with autonomic core temperature regulation in the body, enabling the detection of fevers that might otherwise be missed or might otherwise be detected later with routine core temperature monitoring alone. In some preferred embodiments, the devices provide monitoring updates at regular (for example, at 10-minutes, 15 -minute, or 20-minute intervals) and produce one of three possible outputs: (1 ) the patient is not currently showing signs that indicate that core temperature is elevated (“negative”); (2) the patient is currently showing signs that may be indicative of elevated core temperature (“indeterminate”); and (3) the patient is currently showing strong signs of elevated core temperature that require further confirmation (“positive”).

[0173] In a preferred embodiment, the device is an ultra-compact, always-on, wearable medical device specifically designed with the needs of immunocompromised patients, and the healthcare workers who care for them, in mind.

[0174] The disclosed technology differs from other known devices that measure temperature at the skin, at least one of several ways. The disclosed device is unique in the way that it accounts for the thermal physics and physiology of the body. To detect fever, a device must measure both skin temperature and a temperature gradient. Each measurement is preferably substantially uncontaminated by heat from the device itself. The disclosed technology can accomplish this property by using a two-sensor design. In a preferredembodiment, one sensor monitors the temperature of the skin (Twrist) while a second sensor monitors the ambient temperature of the air on the top surface of the device (Tair). The difference between the two temperatures approximates a temperature gradient (h = Twrist~ Tair) which is closely related to heat elimination. The sensors are preferably attached to flexible circuit wings, and sufficient thermal isolation is achieved using air gaps and foam. In preferable battery and board designs, the power usage does not exceed three milliwatts when all components are powered on.

[0175] Advantages of the disclosed technology include one or more of the following: the ambient and skin temperature sensors are accurate to within ±0.1 °C from -25°C to 55°C, to within ±0.2°C from -20°C to 60°C, or to within ±0.1°C from -20°C to 50°C. These high levels of accuracy have been verified by using a test setup calibrated to National Institute of Standards and Technology (“NIST”) standards with verification equipment calibrated by an ISO / IEC-17025 accredited laboratory.

[0176] Another aspect of the disclosed technology is the location at which the disclosed device is placed on the body. A richer stream of information than has been available from more stable temperature measurements closer to the core is drawn by measuring at the inside of the wrist where the mechanisms of autonomic control are located. See N. A. S. Taylor, M. J. Tipton, and G. P. Kenny. “Considerations for the measurement of core, skin and mean body temperatures.” J. Therm. Biol., vol. 46, pp. 72-101, 2014. To access the information, a rapid sampling rate is used, and measurements are collected more than once per minute.

[0177] In this manner, the disclosed systems and methods may be compared to a thermometer in the way in which a continuous glucose monitor (CGM) would be compared to a blood glucose meter. For example, just as a CGM uses a peripheral measure of glucose in the interstitial fluid as an approximation of blood glucose, the disclosed device uses peripheral measures of skin temperature and heat as an approximation of core temperature; just as a CGM provides higher sampling frequency than is typically achieved using a blood glucose meter and finger sticks, the disclosed device provides a higher sampling frequency than is typically achieved with traditional temperature monitoring; just as CGMs were initially introduced to supplement measurements collected with a blood glucose meter, the disclosed device is intended to supplement and not replace conventional core temperature measurement.

[0178] In some embodiments, the disclosed system and methods comprise an ultra-low energy Bluetooth module and near-field communication antenna (NFC) for communicating and transferring patient data. The disclosed device uses the 5.1 / 5.2 Bluetooth standard for ultra-low energy data transfer. The wearable also supports the use of NFC to manually initiate a data transfer. The device supports encry pted data transfer using a Federal Information Processing Standards (FIPS) compliant algorithm called Elliptic Curve Diffie Hellman (ECDH). Results from the device can be displayed in active patient monitoring software and can be transmitted to the Electronic Health Record.

[0179] The innovative hardware and placement of the disclosed device have the potential to make continuous skin temperature and heat elimination measurements at the periphery a clinically actionable vital sign.

[0180] In some preferred embodiments, the disclosed system and method comprises a lithium-ion, non-rechargeable primary battery to power all electrical functions. A CR2032 battery7is suitable and is commonly used in consumer applications, and is sealed and cannot be accessed by the patient. Batteries are chosen to optimize life; a battery is preferably selected to provide for months of use. In some embodiments, the disclosed device comprises an O-ring to prevent dirt and moisture ingress in accordance w ith its IP67 rating. The device is held in place and presents the skin temperature side of the device to the patient via an adjustable band that allows the patient to wear the device on either wrist.

[0181] In some embodiments, the disclosed device further comprises an inertial measurement unit (IMU) which may be used in the future to monitor and collect patient activity7data, but this data is not used at this time for the device that is the subject of this breakthrough designation request.

[0182] The disclosed device is a single-patient, single-use device; after the device has been used by a single patient, it should be discarded. The physician and patient health care team receives a non-PHI unique patient identifier during the provisioning process. The performance of the disclosed device has been, and is, demonstrated by studies.

[0183] In 2021, data from 30 healthy subjects (the “Kochhar Study”) showed a pattern that suggested that some fevers may be detectable with the device, although no fevers were observed in this study. See Figure 14. In 2022, data from six subjects with induced fever (the “LPS” study) further suggested that the disclosed device could be used detect fever. See Figure 17. In 2024, we conducted our first study with continuous core temperature monitoring in a clinical context (the “Neutropenic Fever Study”), validating the correlation between fever and measurements from the disclosed device in wild-typefevers in individuals with neutropenia. Based on this experience, we have designed the device with detection boundaries that enable the detection of some fevers that might otherwise be missed or might otherwise be detected later with routine core temperature monitoring alone. See Figure 16. The data gathered to date provides a reasonable expectation of technical and clinical success for this approach, see Tables 5 and 6, and Figure 18, and further studies will be conducted to confirm that the device is safe and effective for this use.

[0184] The unique capabilities of the disclosed device enable identification of a threshold that is useful for the detection of fever. The threshold is related to the standard fever threshold, but with an empirically derived correction for the effects of ambient temperature. The existence of the threshold was identified in preliminary studies in 2021 and 2022, and it is illustrated with clinical data described below.

[0185] Figure 14 shows experimental data gathered from monitoring individuals who were not experiencing fever (the Kochhar Study). The y-axis is heat ( / i), and the x-axis is temperature of the skin (Twrist). In healthy individuals who are not experiencing fever, the points do not extend beyond a boundary that appears in the data near Twrist= 37°C and h =0°C. Skin temperature differs from core temperature by virtue of the influence of ambient temperature. Ambient temperature is usually lower than both core (Tc) and skin temperatures, such that the influence of the ambient temperature is to decrease skin temperature. Exposure to lower ambient temperatures results in a linear decrease in skin temperature. As shown in Figure 14, This effect is most visible at the high end of the skin temperature distribution producing a boundary when plotting h = Twrist— Tairagainst Twrist. The consistency of the results observed in the Kochhar Study, and illustrated in Figure 14, supports the hypothesis that individuals experiencing fever show' detectable differences in measurements made by the disclosed system and method.

[0186] Figure 15 shows experimental data gathered from monitoring individuals who were experiencing fever (the LPS study). The y-axis is heat (h), and the x-axis is temperature of the skin (Twrist). In the LPS study, two injections of lipopolysaccharide w ere administrated, separated by seven days to induce fevers of about six hours in duration. As shown in Figure 15, the disclosed device measurements associated with the periods of induced fever tended towards the right-hand region of the plot and crossed the empirical boundary that appears in the data from typical measurements that were observed when fever was not induced. As shown in Figure 15, each of these subjectshas a distribution of data in the normal state (shown as blue points) which tends to appear to the left of the green line, which represents the boundary’ described in Figure 14. Each subject had two injections of lipopolysaccharide separated by seven days w hich induced a fever for about six hours each. The measurements taken by the disclosed system and method device during these periods are plotted as red points connected by a red line. In every case of the eight injections represented here (two injections are shown in each plot), the febrile state resulted in points near and over the typical boundary observed in the non-febrile data.

[0187] This boundary is generally respected in a normal state of thermoregulation. However, fever results in measurements that cross this boundary. This boundary is interpreted as a continuation of the well-known fever threshold into the periphery', where skin temperature ‘’splits the difference’’ between elevated core temperature and lower ambient temperatures. This new threshold amounts to a one-parameter model, where only the slope of the threshold in the plane of heat and skin temperature must be determined empirically. This boundary may be defined as:(1) h = - 1.6 ■ (Twrist- 37.44°C)

[0188] In addition, a second cutoff has been selected to define an indeterminate or equivocal region. This boundary' may be defined as:(2) h = - 1.6 ■ (Twrist- 36.97°C)

[0189] Together, equations (1) and (2) produce the decision boundaries and zones shown in Fig 41.

[0495] Figure 16 illustrates an example of how' an early determination of fever may be made using measurements from an example embodiment of the disclosed device. The y-axis is heat (h), calculated as Twrist - Fair; the x-axis is temperature of the skin (Twrist). Figure 16 shows data collected substantially' continuously and automatically, and also shows decision boundaries used with measurements from the disclosed device to enable the early detection of fever. Such early detection might be missed or detected only later in disease progression when using routine, intermittent core temperature monitoring alone. As shown in Figure 16, when a point Twrist, h) is above and to the right of the line defined by equation (1), it is in the so-called “Positive Region” and the patient is currently showing strong signs of elevated core temperature that require further confirmation. When (Twrist' ) is inthe region between the lines defined by equations (1) and (2), it is in the so-called “Indeterminate” region, meaning that the patient is currently showing signs thatmay be indicative of elevated core temperature. When (Twrist, h) is below and to the left of the line defined by equation (2). it is in the so-called "‘Negative Region,” and the patient is not currently showing signs that indicate that core temperature is elevated. Applying these boundaries to the data collected in the Neutropenic Fever Study, the first study with continuous core temperature monitoring in a clinical context, illustrates the utility in detecting fevers.

[0496] Figure 17 illustrates the utility of an example embodiment of a device for detecting fevers. The y-axis is heat (h), and the x-axis is temperature of the skin (Twrist). The figure shows measurements made by the disclosed device and the decision boundaries, demonstrating utility for the detection of fever, and preferably for the early detection of fever.

[0497] The shaded areas depict the ‘'indeterminate” region illustrated in Figure 16. Each row corresponds to an example patient from the Neutropenic Fever Study, and each column shows one of the three results from left to right: negative, indeterminate, and positive. The white points represent individual device measurements. Generally, elevation of core temperature will result in an elevation of skin temperature, but with significant variability in the measurement. Appropriately accounting for heat makes it possible to detect likely elevations in core temperature.

[0498] In a study which has so far enrolled n = 27 patients, oncology patients admitted for care during neutropenic windows of their treatment are monitored, as they are at high risk of infection and fever. Consequently, these patients have interval core temperature monitoring as part of their standard care. A comparison of the core temperature (Tc) and data from the disclosed device establishes that the disclosed technology shows correlation, suggesting a reasonable expectation of technical and clinical success.

[0190] Difficulties with using core temperature measurement in the reference method include is in the comparison of the disclosed continuous temperature measurement with a much sparser interval time series of core temperature. To establish a comparison, the following procedure was implemented:1. Segment the full time series into four-hour periods2. Label each segment according to the maximum core temperature (max(Tc)) measured within that segment, where:a. If max(Tc) > 38.5°C. the patient is said to have a “concerning fever.”b. Otherwise, if 38.5°C > max(Tc) > 37.5 °C, the patient is said to have "pre-fever elevation.”c. Otherwise, if max(Tc) < 37.5°C the patient is said to have "‘no fever.”3. Identify the region associated with even' measurement from the disclosed device according to Figure 16.a. If any measurement is in the '‘Positive Region,” the result is “Positive.”b. Otherwise, if any measurement is in the “Indeterminate Region,” the result is “Indeterminate .”c. Otherwise, all measurements are in the “Negative Region,” so the result is “Negative.”

[0191] The “pre-fever elevation” and “concerning fever” thresholds will usefully bracket the clinical fever threshold of 38°C. These temperature thresholds have been chosen to mimic the way physicians interrogate core temperature elevation, namely by tracking the rise of temperature before and after the 38°C fever boundary. The results are shown in Table 5.Table 5: Pilot Study ResultsReference Method: Core Temperature Concerning Pre-Fever No Total Fever Elevation FeverTest Positive 92 85 21 198 Method:Indeterminate 36 151 171 358 EnerjiDevice Negative 40 362 1245 1647Total 168 598 1437 2203

[0192] One objective of the disclosed technology is to provide low-latency detection of fever with high Positive Predictive Value (PPV) while also maintaining a high Negative Predictive Value (NPV). Specifically, the objectives are:Metric Name Objective Description Rationale PPVi Near or greater Of points testing positive, Positive detection must be than 90% percentage that correspond trustworthyto max(Tc) > 37.5°CMetric Name Objective Description Rationale PPV2Near or greater Of points testing as Indeterminate results are not than 50% indeterminate, percentage associated with an alarm or that correspond to alert, so we allow a lower max(Tc) > 37.5°C predictive valueNPV Near or greater Of points testing negative, Although the device is not than 95% percentage that correspond intended to replace interval to max(Tc) > 38.5°C core temperature monitoring, negative detection must be trustworthy Determined Near or greater Percentage of points testing Users will only perceive the than 90% either positive or negative system as worth using if it (not indeterminate) regularly produces determinate results

[0193] Additionally, two primary performance metrics may be optimized in accordance with the objectives listed above. These are:Metric Name Objective Description Rationale PPAi Maximize this Of points that correspond to Negative detection must be metric max(Tc) > 38.5°C trustworthy, and concerning percentage that are not fevers should be detected as labeled 'no fever’ either “positive” or “indeterminate” PPA2Maximize this Of points that correspond to Negative detection must be metric max(Tc) between 37.5°C trustworthy, detecting preand 38.5°C, percentage that fever elevation is clinically are not labeled ‘no fever’ valuable

[0194] PPV and NPV are related to the incidence of elevated temperature and its corresponding prevalence in the dataset. It is reported that fever accounts for about 25% of admitted days. See K. B. Laupland, R. Shahpori, A. W. Kirkpatrick, T. Ross, D. B. Gregson, and H. T. Stelfox, “Occurrence and outcome of fever in critically ill adults,” Crit. Care Med., vol. 36, no. 5, pp. 1531-1535, 2008. Pilot data shows concerning fever in about 10% of admitted days. This raises the possibility that the disclosed device may have stronger performance in hospital environments with higher incidence of infection than in the hematology ward used for this study, where patients are shielded from pathogen exposure and the incidence is lower. Here, PPV and NPV are estimated based on the prevalence of pre-fever elevation and concerning fever in study data.Table 6: Summary of examples of the performance of the disclosed device Metric Name ResultPPVi 177 / 198=89.4%PPV2 187 / 358=52.2%NPV 1607 / 1647=97.6% Determined 1845 / 2203=83.7% PPAi 128 / 168=76.2%PPA 236 / 598=39.5%2

[0195] In addition to showing valuable PPV and NPV performance, the disclosed device shows high capability7to distinguish individuals with concerning fever from individuals without concerning fever.

[0196] Figure 18 illustrates the high detection capabilities of the disclosed technology. Thus, Figure 18 shows certain receiver operating characteristics (ROC) analysis using various potential fever detection boundaries. The y axis shows true positive rate, and the x axis shows false positive rate. The high detection capability of the device can be demonstrated by simulating different cutoffs by varying the intercept of the boundary line with the Twrist-axis (where h = 0) to generate a receiver operating characteristics (ROC) curve. Using the pilot data, this results in an area under the receiver operating characteristics curve (AUC) of 0.83. This strong detection capability7and the other results above demonstrate a reasonable likelihood of technical and clinical success. In the future, the selected boundaries in equations (1) and (2) will be validated prospectively.

[0197] In some preferred embodiments, the advantages of the disclosed technology can further include a short detection lead time and lifesaving impact.

[0198] In a critical care situation where a serious risk of infection exists, core temperature monitoring is the standard of care. However, the complexity of the measurement, other emergencies, shift changes, and shortages of qualified staff limit the availability of high quality core temperature data. A four-hour cadence is often cited as best practice, but this may not be achieved in practice. In many situations, the reality on the ground might create gaps as long as 12 hours between temperature measurements, where even in unstable patients, more than 10% of patients received only two temperature measurements per day. Indeed, even within our own protocolized study at a well-funded research hospital, where four-hour cadence is the goal, more than 15% of the intervals aregreater than six hours. See Ghosh E, Eshelman L, Yang L, Carlson E, Lord B. Description of vital signs data measurement frequency in a medical / surgical unit at a community hospital in United States. Data Brief. 2017 Nov 21;16:612-616.

[0199] To estimate the improvement in detection time which may be possible with the disclosed devices, high and low estimates of the real -world temperature monitoring interval (i.e., 4hrs, 12hrs) were used. Assuming that the onset of fever is not correlated with the measurement intervals, the average fever will go undetected for a period of time that is half the measurement interval. This sets the upper limit on our detection lead time, L. This lead time is further limited by PPA. Lead time was estimated by the equation:Interval(3) L - - PPA2

[0200] Using the estimate of PPA1 from Table 6, above (about 76% of concerning fevers are identified as either “indeterminate” or “positive”), the detection lead time estimated from equation (3) may be about 90 minutes when a four- hour core temperature monitoring interval is achieved or about 4.5 hours when core temperature is monitored at 12-hour intervals. If only “positive” results are considered, the estimated PPA is 92 / 168 = 54.8%, and corresponding the average detection lead time may be about one hour when a four-hour core temperature monitoring interval is achieved or about three hours when core temperature is monitored at 12-hour intervals.

[0201] In vulnerable populations, including the populations described above, earlier detection of fever saves lives. For example, in the context of sepsis, delay in administration of antibiotics is associated with higher risk-adjusted in-hospital mortality', with one publication estimating the odds ratio at 1.04 per hour; 95% CI, 1.03 to 1.06; P<0.001. See S. C. W. et al., “Time to Treatment and Mortality during Mandated Emergency Care for Sepsis,” N. Engl. J. Med., vol. 376, no. 23, pp. 2235-2244, 2017. Even with frequent core temperature monitoring at intervals of four hours, use of the disclosed device reduces average fever detection lead time by up to an hour, up to 90 minutes, up to two hours, or longer. Therefore, by detecting some concerning fevers in immunocompromised hospitalized patients significantly sooner than they would otherwise be detected using interval core temperature monitoring alone, the disclosed device can prompt important and potentially life-saving interventions, providing for more effective treatment or diagnosis of diseases or conditions.

[0202] In some preferred embodiments, the advantages of the disclosed technology can further include providing more effective treatment or diagnosis of lifethreatening or irreversibly debilitating human diseases or conditions.

[0203] Patients at risk of infection include those who are immunocompromised, and infection is a leading cause of death and disability in immunocompromised patients. The current standard of care for detecting infection in immunocompromised patients is the measurement of core temperature. The use of changes in core temperature as an indication of infection is especially problematic in patients with low white blood cell counts being treated for cancer - also referred to as neutropenic fever. See A. G. Freifeld et al., “Clinical Practice Guideline for the Use of Antimicrobial Agents in Neutropenic Patients with Cancer: 2010 Update by the Infectious Diseases Society of America,’7Clin. Infect. Dis., vol. 52, no. 4, pp. e56-e93, 2011. Febrile neutropenia in these populations rises to the level of a “medical emergency that requires urgent evaluation (within 1-hr). . . and remains a significant cause of morbidity, mortality and cost burden in patients with cancer.’’ See C. C. Braga, R. A. Taplitz, and C. R. Flowers, “Clinical Implications of Febrile Neutropenia Guidelines in the Cancer Patient Population,” J. Oncol. Pr., vol. 15, no. 1, pp. 25-26, 2019.

[0204] Even with interval core temperature measurement, in many cases, infection is detected and treated late, when patients manifest overt signs and symptoms. The late onset of symptoms introduces a delay in detection, resulting in a missed opportunity to treat a pathogen early with effective therapies and avoid progression to sepsis where only supportive therapies exist. For example, in the context of sepsis, delay in administration of antibiotics is associated with higher risk-adjusted in-hospital mortality, with one publication estimating the odds ratio at 1.04 per hour; 95% confidence interval, 1.03 to 1.06; P<0.001 (see S. C. W. et al., “Time to Treatment and Mortality during Mandated Emergency Care for Sepsis,” N. Engl. J. Med., vol. 376, no. 23, pp. 2235-2244, 2017, doi: 10.1056 / nejmoal703058).

[0205] In immunocompromised patients, fever leads to life-threatening or irreversibly debilitating human disease or conditions, and sepsis is a leading cause of death in immunocompromised patients. See NIH, National Institute of General Medical Sciences, Sepsis, available at https: / / www.nigms.nih.gov / education / fact-sheets / Pages / sepsis.aspx (last visited on Sept. 23, 2024). Detecting fever early can provide for more effective treatment or diagnosis for these patients.

[0206] In assessing the effectiveness, the FDA recommends:[. . .] a sponsor should demonstrate a reasonable expectation that the device could provide for more effective treatment or diagnosis of the disease or condition identified in the proposed indications for use. This includes a reasonable expectation that the device could function as intended (technical success) and that a functioning device could more effectively treat or diagnose the identified disease or condition (clinical success). Mechanisms for demonstrating a reasonable expectation of technical and clinical success could include literature or preliminary data (bench, animal, or clinical). For example, a sponsor might provide preliminary bench data to support the potential for technical success and literature to support that a given principle of operation could more effectively treat or diagnose the identified disease or condition.

[0207] The level and type of evidence needed to determine whether a device is reasonably expected to '‘provide for more effective treatment or diagnosis" may vary depending on the intended use of the device, its technology and features, and the available standard of care alternatives. When evaluating this part of the first criterion, FDA considers the totality of information regarding the proposed device, its function, potential for technical success, potential for clinical success, potential for a clinically meaningful impact, and its potential benefits and risks. The determination of whether a device is reasonably expected to “provide for more effective treatment or diagnosis'’ is based upon all these factors

[0208] See “Breakthrough Devices Program,” U.S. Food and Drug Administration, Final Guidance Document FDA-2017-D-5966, Sep. 2023. Available: https: / / www.ida. go / regulatoty-information / search-xda-guidance- documents.-breaklhrough-devices-prograiu) .

[0209] As noted above, interval core temperature measurements leave critical gaps in monitoring immunocompromised patients. The disclosed device is designed with thermal and safety characteristics to close these gaps. Preliminary performance assessments demonstrate a reasonable expectation of technical and clinical success. The principle of operation, performance data available, limitations of existing alternatives, and the totality of information available demonstrate there is a reasonable expectation the disclosed device will detect a significant portion of clinically meaningful fevers in immunocompromised patients earlier than interval core temperature measurements alone.

[0210] By detecting fever in immunocompromised patients earlier, the disclosed device has the potential to prompt important and potentially life-saving interventions in this vulnerable patient population, thereby providing for more effective treatment or diagnosis of life-threatening or irreversibly debilitating human diseases or conditions.

[0211] The disclosed devices further provide significant advantages over existing approved or cleared alternatives. Existing approaches to addressing the need for earlier fever detection have severe disadvantages, particularly when used for immunocompromised patients. The disclosed device minimizes or substantially eliminates these disadvantages, and is preferably designed to exhibit an excellent safety profile when used by immunocompromised patients. During IRB studies, the device has now been worn by immunocompromised patients for a total of more than 400 person-days, with no adverse events that are attributable to wearing the device. It presents a new opportunity to meet a critical and currently unmet need for this patient population.

[0212] The disclosed technology’ is intended, in certain embodiments, for use to monitor fever in immunocompromised patients who are hospitalized, as a supplement to routine core temperature monitoring. By enabling the detection of fevers that might otherwise be missed or detected later with routine core temperature monitoring alone, the disclosed technology has potential to prompt important and potentially life-saving interventions in this vulnerable patient population, providing for more effective treatment or diagnosis of diseases or conditions.Additional Notes

[0213] It should be appreciated that all combinations of the foregoing concepts and additional concepts discussed in greater detail below (provided such concepts are not mutually inconsistent) are contemplated as being part of the inventive subject matter disclosed herein. In particular, all combinations of claimed subject matter appearing at the end of this disclosure are contemplated as being part of the inventive subject matter disclosed herein. It should also be appreciated that terminology explicitly employed herein that also may appear in any disclosure incorporated by reference should be accorded a meaning most consistent with the particular concepts disclosed herein.

[0214] Reference throughout the specification to “one example’’, “another example”, “an example”, and so forth, means that a particular element (e.g., feature, structure, and / or characteristic) described in connection with the example is included in atleast one example described herein, and may or may not be present in other examples. In addition, it is to be understood that the described elements for any example may be combined in any suitable manner in the various examples unless the context clearly dictates otherwise.

[0215] It is to be understood that the ranges provided herein include the stated range and any value or sub-range within the stated range, as if such value or sub-range were explicitly recited. For example, a range from about 2 nm to about 20 nm should be interpreted to include not only the explicitly recited limits of from about 2 nm to about 20 nm, but also to include individual values, such as about 3.5 nm, about 8 nm, about 18.2 nm, etc., and sub-ranges, such as from about 5 nm to about 10 nm, etc. Furthermore, when “about’7and / or “substantially” are / is utilized to describe a value, this is meant to encompass minor variations (up to + / - 10%) from the stated value.

[0216] While several examples have been described in detail, it is to be understood that the disclosed examples may be modified. Therefore, the foregoing description is to be considered non-limiting.

[0217] While certain examples have been described, these examples have been presented by way of example only, and are not intended to limit the scope of the disclosure. Indeed, the novel methods and systems described herein may be embodied in a variety of other forms. Furthermore, various omissions, substitutions and changes in the systems and methods described herein may be made without departing from the spirit of the disclosure. The accompanying claims and their equivalents are intended to cover such forms or modifications as would fall within the scope and spirit of the disclosure.

[0218] Features, materials, characteristics, or groups described in conjunction with a particular aspect, or example are to be understood to be applicable to any other aspect or example described in this section or elsewhere in this specification unless incompatible therewith. All of the features disclosed in this specification (including any accompanying claims, abstract and drawings), and / or all of the steps of any method or process so disclosed, may be combined in any combination, except combinations where at least some of such features and / or steps are mutually exclusive. The protection is not restricted to the details of any foregoing examples. The protection extends to any novel one, or any novel combination, of the features disclosed in this specification (including any accompanying claims, abstract and drawings), or to any novel one, or any novel combination, of the steps of any method or process so disclosed.

[0219] Furthermore, certain features that are described in this disclosure in the context of separate implementations can also be implemented in combination in a single implementation. Conversely, various features that are described in the context of a single implementation can also be implemented in multiple implementations separately or in any suitable sub-combination. Moreover, although features may be described above as acting in certain combinations, one or more features from a claimed combination can, in some cases, be excised from the combination, and the combination may be claimed as a subcombination or variation of a sub-combination.

[0220] Moreover, while operations may be depicted in the drawings or described in the specification in a particular order, such operations need not be performed in the particular order shown or in sequential order, or that all operations be performed, to achieve desirable results. Other operations that are not depicted or described can be incorporated in the example methods and processes. For example, one or more additional operations can be performed before, after, simultaneously, or between any of the described operations. Further, the operations may be rearranged or reordered in other implementations. Those skilled in the art will appreciate that in some examples, the actual steps taken in the processes illustrated and / or disclosed may differ from those show n in the figures. Depending on the example, certain of the steps described above may be removed or others may be added. Furthermore, the features and attributes of the specific examples disclosed above may be combined in different ways to form additional examples, all of which fall within the scope of the present disclosure. Also, the separation of various system components in the implementations described above should not be understood as requiring such separation in all implementations, and it should be understood that the described components and systems can generally be integrated together in a single product or packaged into multiple products. For example, any of the components for an energy storage system described herein can be provided separately, or integrated together (e.g., packaged together, or attached together) to form an energy storage system.

[0221] For purposes of this disclosure, certain aspects, advantages, and novel features are described herein. Not necessarily all such advantages may be achieved in accordance with any particular example. Thus, for example, those skilled in the art will recognize that the disclosure may be embodied or carried out in a manner that achieves one advantage or a group of advantages as taught herein without necessarily achieving other advantages as may be taught or suggested herein.

[0222] Conditional language, such as “can,” “could,” “might,” or “may,” unless specifically stated otherwise, or otherwise understood within the context as used, is generally intended to convey that certain examples include, while other examples do not include, certain features, elements, and / or steps. Thus, such conditional language is not generally intended to imply that features, elements, and / or steps are in any way required for one or more examples or that one or more examples necessarily include logic for deciding, with or without user input or prompting, whether these features, elements, and / or steps are included or are to be performed in any particular example.

[0223] Conjunctive language such as the phrase “at least one of X, Y, and Z,” unless specifically stated otherwise, is otherwise understood with the context as used in general to convey that an item. term. etc. may be either X. Y, or Z. Thus, such conjunctive language is not generally intended to imply that certain examples require the presence of at least one of X, at least one of Y, and at least one of Z.

[0224] Language of degree used herein, such as the terms “approximately,” “about,” “generally,” and “substantially” represent a value, amount, or characteristic close to the stated value, amount, or characteristic that still performs a desired function or achieves a desired result.

[0225] The scope of the present disclosure is not intended to be limited by the specific disclosures of preferred examples in this section or elsewhere in this specification, and may be defined by claims as presented in this section or elsewhere in this specification or as presented in the future. The language of the claims is to be interpreted broadly based on the language employed in the claims and not limited to the examples described in the present specification or during the prosecution of the application, which examples are to be construed as non-exclusive.

Claims

WHATIS CLAIMED IS:

1. A system configured for detection of a transition in thermoregulation in a subject, the system comprising:at least one sensor configured to measure a plurality of heat flux measurements of the subj ect over time;a processor configured to receive the plurality of heat flux measurements over time, characterize the relationship between heat flux and temperature over time, and detect a transition from a first thermoregulatory control state to a second thermoregulatory control state prior to an onset of fever or infection; andan indicator prompting proposed intervention prior to the onset of fever or infection.

2. The system of claim 1, wherein the transition from the first thermoregulatory control state to the second thermoregulatory control state is indicative of a change to an adaptive control system of the subject.

3. The system of claim 2. wherein an emergent condition is identified based on the indicated change to the adaptive control system.

4. The system of claim 3, wherein the heat flux measurements of a subject over time include at least one of the following:core temperature measurements;skin temperature measurements; orambient temperature measurements.

5. The system of claim 3, wherein the heat flux measurements include at least two of the following:core temperature measurements;skin temperature measurements; orambient temperature measurements.

6. The system of either claim 4 or claim 5, wherein a recognized change in the plurality of heat flux measurements corresponds to the transition from the first thermoregulatory control state to the second thermoregulatory control state.

7. The system of claim 6, wherein the recognized change in the plurality of heat flux measurements correspond to a recognized change in the relationship between the skin temperature measurements, and the ambient temperature measurements.

8. A method for detection of a transition in thermoregulation in a subject, the method comprising:measuring a plurality of heat flux measurements of a subject over time; processing the plurality of heat flux measurements over time; recognizing the transition from a first thermoregulatory control state to a second thermoregulatory control state prior to an onset of fever or infection; and administering an intervention prior to an onset of a fever or an infection.

9. The method of claim 8, wherein the heat flux measurements over time include at least one of the following:core temperature measurements;skin temperature measurements; orambient temperature measurements.

10. The method of claim 8. wherein the heat flux measurements over time include at least two of the following:core temperature measurements;skin temperature measurements; orambient temperature measurements.

11. The method of either claim 9 or claim 10. wherein the transition from the first thermoregulatory control state to the second thermoregulatory control state is identified based a change in an adaptive control system of the subject.

12. The method of claim 11, further comprising identifying an emergent condition based on the identified change in the adaptive control system.

13. The method of claim 12, wherein a recognized change in the plurality of heat flux measurements corresponds to the transition from the first thermoregulatory control state to the second thermoregulatory control state.

14. The method of claim 13, wherein the recognized change in the plurality’ of heat flux measurements correspond to a recognized change in the relationship between the plurality of skin temperature measurements, and the plurality of ambient temperature measurements.

15. A system for identifying a control state of thermoregulation of a subject, the system comprising:at least one sensor configured to measure a plurality of heat flux measurements of a subject over time;a processor configured to receive the plurality of heat flux measurements, characterize the relationship between heat flux and temperature over time, anddetect a transition from a first thermoregulatory' control state to a second thermoregulatory control state prior to an onset of fever or infection; andan intervenor that intervenes thermoregulation of the subject prior to an onset of a fever or an infection.

16. The system of claim 15, wherein the transition from the first thermoregulatory control state to the second thermoregulatory control state identifies an adaptive control system of the subject.

17. The system of claim 16, wherein an emergent condition is identified based on the identified adaptive control system.

18. The system of claim 17, wherein the plurality' of heat flux measurements over time include at least one of the following:a plurality’ of core temperature measurements;a plurality' of skin temperature measurements; ora plurality of ambient temperature measurements.

19. The system of claim 18, wherein a recognized change in the plurality of heat flux measurements corresponds to the transition from the first thermoregulatory control state to the second thermoregulatory^ control state.

20. The system of claim 19, wherein the recognized change in the plurality' of heat flux measurements correspond to a recognized change in the relationship between the plurality of skin temperature measurements, and the plurality of ambient temperature measurements.

21. A system for treating a change in thermoregulation in a subject, the system comprising:at least one sensor configured to measure a plurality of heat flux measurements of a subject;a processor configured to receive the plurality' of heat flux measurements, characterize the relationship between heat flux and temperature over time, and detect a transition from a first thermoregulatory control state to a second thermoregulatory control state prior to an onset of fever or infection; andan administrator of treatment to the subject prior to an onset of a fever or an infection.

22. The system of claim 21, wherein the transition from the first thermoregulatory control state to the second thermoregulatory control state identifies an adaptive control system of the subject.

23. The system of claim 22, wherein an emergent condition is identified based on the identified adaptive control system.

24. The system of claim 23, wherein the plurality of heat flux measurements over time include at least one of the following:core temperature measurements;skin temperature measurements; orambient temperature measurements.

25. The system of claim 23, wherein the plurality of heat flux measurements over time include at least two of the following:core temperature measurements;skin temperature measurements; orambient temperature measurements.

26. The system of claim 24 or claim 25, wherein a recognized change in the plurality7of heat flux measurements corresponds to the transition from the first thermoregulatory control state to the second thermoregulatory control state.

27. The system of claim 26, wherein the recognized change in the plurality of heat flux measurements correspond to a recognized change in the relationship between the plurality7of skin temperature measurements, and the plurality7of ambient temperature measurements.

28. A method for the assessment of fever in a monitored subject:obtaining heat flux data for the subject, wherein the data is based at least in part on skin temperature and ambient temperature measurements that are collected substantially7continuously and automatically;determining whether the heat flux data falls within a predetermined regions designated as (i) positive for fever, (ii) indeterminant for fever, or (iii) negative for fever; andreporting the designation (i) positive for fever, (ii) indeterminant for fever, or (iii) negative for fever as an assessment of fever in the monitored subject.

29. The method of claim 28, wherein the heat flux data is substantially based on skin temperature and ambient temperature measurements.

30. The method of claim 28, wherein the heat flux data is not based on core temperature measurements.

31. The method of claim 28, wherein the assessment of fever is provided earlier in the progress of disease than an assessment based on core temperature measurements alone.

32. The method of any of claims 28-31, wherein the subject is an immune-compromised patient.

33. The method of any of claims 28-32, wherein the reporting is provided to a health care professional.

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