WO2023150012A2

WO2023150012A2 - Method and device for predicting risk of foot disease

Info

Publication number: WO2023150012A2
Application number: PCT/US2023/010484
Authority: WO
Inventors: Linh Tung LE; Steve KAUFMAN; Emma Rachel JAY; Quoc-Sy VU; George KENEFATI; Laura SARACHO
Original assignee: Flextrapower, Inc.
Priority date: 2022-02-02
Filing date: 2023-01-10
Publication date: 2023-08-10
Also published as: WO2023150012A3

Abstract

A method is provided for predicting foot disease. The method includes providing a first plurality of temperature sensors positioned relative to a first set of locations on a wearer's first foot and a second plurality of temperature sensors positioned relative to a second set of locations on the wearer's second foot, with the second set of locations being a mirror image of the first set of locations. The method then proceeds to compare a temperature recorded at a first time for each sensor of the second plurality of temperature sensors with a temperature recorded at the first time for the corresponding sensor of the first plurality. Upon identifying a temperature difference greater than a hot spot temperature threshold between a first pair of corresponding sensors, the method may then define a first hot spot risk condition.

Description

METHOD AND DEVICE FOR PREDICTING RISK OF FOOT DISEASE

CROSS REFERENCE TO RELATED APPLICATIONS

[0001] This application takes priority from Provisional Patent Application No. 63/305,940, filed February 2, 2022, the contents of which are incorporated by reference herein.

FIELD OF THE INVENTION

[0002] The invention relates to methods and devices for predicting risk of foot disease, such as diabetic foot ulcerations. Specifically, this disclosure relates to methods based on noninvasive temperature tracking of feet.

BACKGROUND

[0003] Foot ulcers pose a significant health risk, particularly for people with diabetes, who often lose sensation in their feet and thus do not feel the ulcer forming. Diabetic foot ulcers can lead to extended hospitalization, lower limb amputations and even death.

[0004] There have been two main strategies for addressing this grave public health issue for those individuals at high-risk for developing Diabetic foot ulcers. One is to prescribe the use of therapeutic customized shoe insoles to off-load pressure on certain areas of the foot and the second is to encourage frequent visits to healthcare professionals for foot health monitoring.

[0005] While the use of therapeutic customized insoles has been widely adopted to aid in the prevention of Diabetic foot ulcers, patient compliance for using them is often a challenge and caregivers do not have a convenient way to ascertain the level of compliance. Furthermore, the traditional ways of monitoring the foot health of the patient are inconvenient, intermittent, and often inaccurate.

[0006] Further, traditional monitoring is typically limited to temperature monitoring, and does not consider other physiological and environmental factors that may impact foot health. Similarly, existing monitoring does not consider the activity level of a person whose foot is being monitored.

[0007] Further, traditional monitoring methods implement limited methods that are generic across a large number of users. Such methods may use generalized temperature guidelines or pattern-recognition based detection methods. Such methods generate large numbers of false positives. When monitoring methods result in many false positives, users are likely to stop using the methods. Further, where monitoring methods are implemented at a medical facility, such false positives can be mitigated by having a doctor interpret results. However, such monitoring cannot be performed during a user’s normal activity, nor can they be performed while a user is wearing shoes in real time. Were such methods to be implemented at home, the problem of false positives would be exacerbated, as no doctor would be available to interpret results.

[0008] Similarly, traditional monitoring methods cannot be implemented while a user is using therapeutic customized insoles and therefore cannot account for the impact of such insoles on foot health.

[0009] Therefore, a system that can provide the customized therapeutic offloading as well as continuously monitor the foot health of a person's foot and measure compliance in a way that avoids false positives would be beneficial.

SUMMARY

[0010] A method is described herein to output a prediction of a risk of foot disease, while alerting users of such risk. Some embodiments may output a prediction of possible diabetic foot ulceration using interpreted data from two feet, with minimal false positives and high sensitivity.

[0011] In many such embodiments, a patient first receives insoles and downloads a software application, such as for a smartphone. In some such embodiments, the insole may be custom formed to a user’s feet, such as by heat forming.

[0012] The user may then wear the provided insoles every day while the insoles are connected to the software application. [0013] The software application receives temperature data (°C) and battery data (V). In some embodiments, the software application may receive additional sensor data or battery data as well. The software application may then upload the data to a computer server, or may process the data within the application itself.

[0014] The software application may, in some embodiments, then process the raw data as follows:

[0015] 1. Calculate the temperature difference between the right and left feet.

[0016] 2 Check for differences greater than a threshold amount, such as 2.2 °C.

[0017] 3. Note which of these differences occurred during a resting condition.

[0018] 4. Calculate a mean difference between the feet.

[0019] 5. Check whether the mean difference is greater than a threshold amount, such as 1.35 C.

[0020] Then, the algorithm may output the following information:

[0021] Sensor (L or R) T_ was hot, or a specified temperature, at XX:XX.”

[0022] After 48 hours - embodiments may use IMU to know whether shoe is worn to contribute to condition red.

[0023] In some embodiments, the method may leave open variables for IMU X, Y, Z.

[0024] In some embodiments, a method is provided for outputting a prediction based on data from a single foot. Accordingly, the method may output a prediction of possible diabetic foot ulceration using interpreted data from the same foot with minimal false-positives and high sensitivity.

[0025] In some embodiments, a computer-based method is provided for predicting foot disease. The method may include providing a first plurality of temperature sensors positioned relative to a first set of locations on a wearer’s first foot. The method may further include providing a second plurality of temperature sensors positioned relative to a second set of locations on the wearer’s second foot, with the second set of locations being a mirror image of the first set of locations. Accordingly, each sensor of the second plurality of temperature sensors may have a corresponding symmetrically located sensor of the first plurality of temperature sensors.

[0026] The method then proceeds to compare a temperature recorded at a first time for each sensor of the second plurality of temperature sensors with a temperature recorded at the first time for the corresponding sensor of the first plurality. Upon identifying a temperature difference greater than a hot spot temperature threshold between a first pair of corresponding sensors of the first plurality of temperature sensors and the second plurality of temperature sensors, the method may then define a first hot spot risk condition.

[0027] The method may proceed to compare temperatures recorded at a plurality of additional times after the first time for each sensor. Upon determining that a temperature difference between a pair of corresponding sensors remains greater than the hot spot temperature threshold for a first predetermined period of time, the method may define a second hot spot risk condition.

[0028] The method may then output an alert to a user upon defining the second hot spot risk condition.

[0029] In some embodiments, the method further includes providing at least one sensor other than the plurality of temperature sensors for each of the wearer’ s feet. The at least one sensor may comprise one of a force sensor, an inertial measuring unit, and a step-counter. In such an embodiment, upon defining the first hot spot risk condition, the method may determine, based on the at least one sensor other than the plurality of temperature sensors, that the wearer was at rest at the first time, and may then define a resting risk condition. The content of the alert output to the user is then at least partially based on the presence of the resting risk condition.

[0030] In some such embodiments, upon defining the first hot spot risk condition, the method may proceed to determine, based on the at least one sensor other than the plurality of temperature sensors, that the wearer was at rest at a second time prior to the first time. The method may then define the resting risk condition only if the wearer was at rest during both the first time and the second time.

[0031] In some embodiments, the method includes determining that the first hot spot risk condition has not been defined and then proceeds to determine an average temperature for the first time for the first plurality of temperature sensors. The method then determines an average temperature for the first time for the second plurality of temperature sensors.

[0032] Upon determining that a difference between the average temperatures is greater than an average temperature threshold, the method may then define a first average temperature risk condition.

[0033] The method may then proceed with comparing average temperatures for the pluralities of temperature sensors for a plurality of additional times after the first time and upon determining that a difference between the average temperatures remains greater than the average temperature threshold for the first predetermined period of time, the method may define a second average temperature risk condition. The method may then output an alert to the user upon defining the second average temperature risk condition.

[0034] In some such embodiments, the method compares average temperatures for the pluralities of temperature sensors for a plurality of additional times after defining the second average temperature risk condition. The method then outputs an alert to the user upon determining that the temperature difference between the average temperatures remains greater than the average temperature threshold for a second predetermined period of time longer than the first predetermined period of time.

[0035] In some embodiments, the average temperature threshold is lower than the hot spot temperature threshold.

[0036] In some embodiments, the method includes comparing temperatures for pairs of corresponding sensors recorded at a plurality of additional times after defining the second hot spot risk condition. The method then outputs an alert to the user upon determining that the temperature difference between a pair of corresponding sensors remains greater than the hot spot temperature threshold for a second predetermined period of time longer than the first predetermined period of time.

[0037] In some embodiments, the first plurality of temperature sensors are embedded in a first insole for the first foot at a first set of predetermined locations. The second plurality of temperature sensors are embedded in a second insole for the second foot at a second set of predetermined locations. The first set of predetermined locations and the second set of predetermined locations are then mirror images of each other.

[0038] In some embodiments, the method further includes custom forming the first insole and the second insole to the first foot and the second foot respectively by heating the insoles and forming them to the corresponding feet.

[0039] In some embodiments, the method includes first measuring the first foot and the second foot of the wearer and creating the first and second insole by way of an additive manufacturing process based on the measuring of the first foot and the second foot.

[0040] In some embodiments, the method includes providing at least one sensor other than the plurality of temperature sensors for each of the wearer’s feet. The at least one sensor may then comprise one of a force sensor, an inertial measuring unit, and a step-counter. The method then compares the temperatures recorded at the plurality of temperature sensors only upon determining, based on the at least one sensor other than the plurality of temperature sensors, that the plurality of temperature sensors have been positioned relative to the corresponding set of locations.

[0041] In some embodiments, the foot disease to be predicted is a diabetic foot ulceration.

[0042] In some embodiments, a method is provided for predicting foot disease. The method includes providing a plurality of temperature sensors positioned relative to a first set of locations on a wearer’s foot. The method then includes defining a plurality of groups each comprising at least one temperature sensor of the plurality of temperature sensors. Each group corresponds to a zone on the wearer’s foot. [0043] The method then proceeds to compare a first maximum temperature recorded at a first time by any first temperature sensor of the plurality of temperature sensors to a first minimum temperature recorded at the first time by any second temperature sensor of the plurality of temperature sensors to define an ipsilateral temperature difference.

[0044] The method then defines a first ipsilateral hot spot condition where the ipsilateral temperature difference is greater than an ipsilateral difference threshold.

[0045] The method then defines an average temperature at the first time for each group of the plurality of groups and defines an overall average temperature at the first time for the plurality of temperature sensors. The method then defines a first hot zone condition where the average temperature for any first group of the plurality of groups is greater than the overall average temperature by a hot zone threshold.

[0046] The method then outputs an alert to a user based on the definition of either the first ipsilateral hot spot condition or the first hot zone condition.

[0047] In some embodiments, the method defines the average temperature at the first time for each group and defines an overall average temperature only upon determining that the ipsilateral temperature difference is not greater than the ipsilateral difference threshold.

[0048] In some embodiments, the method includes providing at least one sensor other than the plurality of temperature sensors, where the at least one sensor is one of a force sensor, an inertial measuring unit, and a step-counter. The method then determines, based on the at least one sensor other than the plurality of temperature sensors, that the wearer was at rest at the first time, and defines a resting risk condition if the wearer is determined to be at rest and the ipsilateral hot spot condition is defined.

[0049] The alert output to the user may then indicate the presence of the resting risk condition.

[0050] In some embodiments, the method includes comparing a plurality of maximum temperatures recorded at any temperature sensor of the plurality of temperature sensors for a plurality of additional times after the first time to a plurality of minimum temperatures recorded at any temperature sensor of the plurality of temperature sensors for the plurality of additional times. Upon determining that the temperature difference between a maximum temperature and a minimum temperature at a corresponding time remains greater than the ipsilateral difference threshold for a first predetermined period of time, the method defines a second ipsilateral hot spot condition.

[0051] In some embodiments, the method further includes comparing an average temperature for the for any group of the plurality of groups for a plurality of additional times after the first time to an overall average temperature for the plurality of additional times. Upon determining that the average temperature for any group remains greater than the overall average temperature for a first predetermined period of time by the hot zone threshold, the method defines a second hot zone condition.

[0052] In some embodiments, the hot zone threshold is proportional to a standard deviation of the overall average temperature.

[0053] In some embodiments, the method includes comparing the overall average temperature to an ambient temperature and defining an ambient temperature condition upon determining that the overall average temperature is greater than the ambient temperature by more than an ambient temperature threshold.

[0054] In some such embodiments, the method further comprises providing an ambient temperature sensor independent of the plurality of temperature sensors. The ambient temperature sensor is then spaced apart from the plurality of temperature sensors, and the ambient temperature is retrieved from the ambient temperature sensor.

[0055] In some such embodiments, the plurality of temperature sensors are embedded in an insole and the ambient temperature sensor is independent of the insole.

[0056] In some embodiments utilizing an ambient temperature, the method includes providing a wireless interface. The ambient temperature is then retrieved by way of the wireless interface. [0057] In some embodiments utilizing an ambient temperature, the method includes providing at least one sensor other than the plurality of temperature sensors, where the at least one sensor is a force sensor, an inertial measuring unit, or a stepcounter. The method then includes determining, based on the at least one sensor other than the plurality of temperature sensors, that the wearer was at rest at the first time. The method then defines a resting risk condition if the wearer is determined to be at rest and the ipsilateral hot spot condition is defined.

[0058] The alert output to the user is then based on a weighted sum of the ipsilateral hot spot condition, the hot zone condition, the resting risk condition, and the ambient temperature condition.

[0059] In some embodiments, the plurality of temperature sensors is embedded in an insole, and each group of the plurality of groups comprises temperature sensors configured for locating adjacent corresponding zones on the wearer’s foot.

[0060] In some such embodiments, a first group of the plurality of groups is configured for locating adjacent one of the medial plantar artery, the lateral plantar artery, or the calcaneal artery.

[0061] In some embodiments, the method includes providing at least one sensor other than the plurality of temperature sensors, where the at least one sensor is a force sensor, an inertial measuring unit, or a step-counter.

[0062] The method then compares temperatures recorded at the plurality of temperature sensors only upon determining, based on the at least one sensor other than the plurality of temperature sensors, that the plurality of temperature sensors have been positioned relative to the corresponding set of locations.

[0063] In some embodiments, the foot disease to be predicted is a diabetic foot ulceration.

[0064] In some embodiments, the plurality of temperature sensors is embedded in a first insole and the method further includes custom forming the first insole to the wearer’s foot by heating the insole and forming it to the corresponding foot. In some alternative embodiments, the method includes measuring the foot of the wearer and creating the first insole in which the sensors are embedded by way of an additive manufacturing method based on the measuring of the corresponding foot.

[0065] In some embodiments, a method is provided for predicting foot disease, the method including determining whether a wearer is using one or two insoles, with each insole containing a corresponding plurality of temperature sensors.

[0066] upon determining that only a single insole is present, the method proceeds to define a plurality of groups, with each group comprising at least one temperature sensor of the plurality of temperature sensors corresponding to the single insole. Each group of the plurality of groups corresponds to a zone on the wearer’s foot.

[0067] The method then proceeds to compare a first maximum temperature recorded at a first time by any first temperature sensor of the plurality of temperature sensors to a first minimum temperature recorded at the first time by any second temperature sensor of the plurality of temperature sensors to define an ipsilateral temperature difference.

[0068] The method then proceeds to define a first ipsilateral hot spot condition where the ipsilateral temperature difference is greater than an ipsilateral difference threshold.

[0069] If the method determines that two insoles are present, the method proceeds to identify pairs of temperature sensors, such that each temperature sensor of a first plurality of temperature sensors corresponding to a first insole of the two insoles has a symmetrically located temperature sensor of a second plurality of temperature sensors corresponding to a second insole of the two insoles.

[0070] The method then proceeds to compare a temperature recorded at a first time for each sensor of the first plurality of temperature sensors with a temperature recorded at the first time for the corresponding sensor of the second plurality. Upon identifying a temperature difference greater than a hot spot temperature threshold between a first pair of corresponding sensors of the first plurality of temperature sensors and the second plurality of temperature sensors, the method then defines a first hot spot risk condition.

[0071] The method then proceeds to compare temperatures recorded at a plurality of additional times after the first time at the first pair of corresponding sensors. Upon determining that the temperature difference between the first pair remains greater than the hot spot temperature threshold for a first predetermined period of time, the method defines a second hot spot risk condition.

[0072] The method then outputs an alert to a user upon defining either the first ipsilateral hot spot condition or the second hot spot risk condition.

[0073] In some embodiments, a method is provided for predicting foot disease, where the method includes providing a first insole having a first plurality of temperature sensors and providing a second insole having a second plurality of temperature sensors.

[0074] The method then includes custom fitting the first insole to a first foot of a wearer such that the first plurality of temperature sensors is positioned relative to a first set of locations on the wearer’s first foot and custom fitting the second insole to a second foot of the wearer such that the second plurality of temperature sensors is positioned relative to a second set of locations on the wearer’s second foot. The second set of locations is a mirror image of the first set of locations, such that each sensor of the second plurality of temperature sensors has a corresponding symmetrically located sensor of the first plurality of temperature sensors.

[0075] The method then proceeds to compare a temperature recorded at a first time for each sensor of the second plurality of temperature sensors with a temperature recorded at the first time for the corresponding sensor of the first plurality of temperature sensors. Upon identifying a temperature difference greater than a hot spot temperature threshold between a first pair of corresponding sensors of the first plurality of temperature sensors and the second plurality of temperature sensors, the method defines a first hot spot risk condition. [0076] The method then proceeds to compare temperatures recorded at a plurality of additional times after the first time at the first pair of corresponding sensors and upon determining that the temperature difference between the first pair remains greater than the hot spot temperature threshold for a first predetermined period of time, defining a second hot spot risk condition.

[0077] The method then proceeds with outputting an alert to a user upon defining the second hot spot risk condition.

[0078] In some embodiments, a method is provided for predicting foot disease. The method includes providing an insole having a plurality of temperature sensors. Once the insole is provided, the method proceeds with custom fitting the insole to a foot of a wearer such that the plurality of temperature sensors are positioned relative to a first set of locations on the wearer’s foot.

[0079] The method then proceeds with comparing a first maximum temperature recorded at a first time by any first temperature sensor of the plurality of temperature sensors to a first minimum temperature recorded at the first time by any second temperature sensor of the plurality of temperature sensors to define an ipsilateral temperature difference.

[0080] The method the defines a first ipsilateral hot spot condition where the ipsilateral temperature difference is greater than an ipsilateral difference threshold.

[0081] The method then proceeds to define an average temperature at the first time for each group of the plurality of groups and defining an overall average temperature at the first time for the plurality of temperature sensors.

[0082] The method then proceeds with defining a first hot zone condition where the average temperature for any first group of the plurality of groups is greater than the overall average temperature by a hot zone threshold and outputting an alert to a user based on the definition of either the first ipsilateral hot spot condition or the first hot zone condition. BRIEF DESCRIPTION OF THE DRAWINGS

[0083] Figure 1 shows a first embodiment of a device for use in the methods described.

[0084] Figure 2 shows a second embodiment of a device for use in the methods described.

[0085] Figure 3 is a flowchart illustrating a first method for predicting risk of foot disease.

[0086] Figure 4 is a second flowchart illustrating a variation of the method of FIG. 3 with some elements described in more detail.

[0087] Figure 5 is a flowchart illustrating a second method for predicting a risk of foot disease.

[0088] Figure 6 is a second flowchart illustrating a variation of the method of FIG. 5 with some elements described in more detail.

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0089] The description of illustrative embodiments according to principles of the present invention is intended to be read in connection with the accompanying drawings, which are to be considered part of the entire written description. In the description of embodiments of the invention disclosed herein, any reference to direction or orientation is merely intended for convenience of description and is not intended in any way to limit the scope of the present invention. Relative terms such as “lower,” “upper,” “horizontal,” “vertical,” “above,” “below,” “up,” “down,” “top” and “bottom” as well as derivative thereof (e.g., “horizontally,” “downwardly,” “upwardly,” etc.) should be construed to refer to the orientation as then described or as shown in the drawing under discussion. These relative terms are for convenience of description only and do not require that the apparatus be constructed or operated in a particular orientation unless explicitly indicated as such. Terms such as “attached,” “affixed,” “connected,” “coupled,” “interconnected,” and similar refer to a relationship wherein structures are secured or attached to one another either directly or indirectly through intervening structures, as well as both movable or rigid attachments or relationships, unless expressly described otherwise. Moreover, the features and benefits of the invention are illustrated by reference to the exemplified embodiments. Accordingly, the invention expressly should not be limited to such exemplary embodiments illustrating some possible non-limiting combination of features that may exist alone or in other combinations of features; the scope of the invention being defined by the claims appended hereto.

[0090] This disclosure describes the best mode or modes of practicing the invention as presently contemplated. This description is not intended to be understood in a limiting sense, but provides an example of the invention presented solely for illustrative purposes by reference to the accompanying drawings to advise one of ordinary skill in the art of the advantages and construction of the invention. In the various views of the drawings, like reference characters designate like or similar parts.

[0091] Figure 1 shows a first embodiment of a device 100 for use in the methods described. The device shown 100 is a circuit board for embedding into an insole, and has a plurality of sensors TO, Tl, T2, T3, T4, T5. Those sensors T0-T5 are typically connected by wiring on the device 100 to a transmitter (not shown) that can then output any data collected from the sensors to a computer system implementing the methods described below. The sensors may be provided to correspond to specific locations on a wearer’s foot. For example, the temperature sensors may be located to correspond to the wearer’s big toe, heel, etc.

[0092] The plurality of sensors T0-T5 are temperature sensors, and the device shown 100 may further be provided with at least one sensor other than the temperature sensors. The other sensors, not shown, may be one or more of a force sensor, an inertial measuring unit, and a step-counter.

[0093] The device shown 100 is for embedding into an insole. Typically, insoles are provided to users for monitoring in pairs. Accordingly, the device 100 may be paired with a second circuit board for embedding into a second insole. Temperature sensors provided in a second such insole may be located at a set of locations to mirror the locations of the temperature sensors in the first insole. Accordingly each sensor of the second insole would have a corresponding symmetrically located sensor in the first insole.

[0094] The device shown 100 is configured for a first insole for wearing on a wearer’s left foot. The second insole would then be a mirror image of the first insole and would then be for the wearer’s right foot. As discussed in more detail below, the device 100 may be embedded into a customizable insole which may then be heat formed into shape as part of a method for predicting and treating foot disease.

[0095] In some embodiments, instead of the first and second insole being mirror images of each other, the sensors themselves may be located such that they are symmetrically located, or such that the locations are mirror images. As such, a first plurality of temperature sensors may be provided, in some embodiments, embedded in a first insole for the first foot at a first set of predetermined locations. A second plurality of temperature sensors may then be provided, in some embodiments, embedded in a second insole for the second foot at second set of predetermined locations. In such an embodiment, the first set of predetermined locations and the second set of predetermined locations are mirror images of each other. As such, when referencing the sensors or the insoles being mirror images of each other, or symmetric, it will be understood that this may be true for one or both of the predetermined locations for sensors, either in the context of the insoles or taken alone, or for the insoles themselves.

[0096] Figure 2 shows a second embodiment of a device 200 for use in the methods described. As shown, and similar to the first embodiment, the device 200 is a circuit board for embedding into an insole. The circuit board 200 is provided with a plurality of sensors, T0-T17. The plurality of sensors T0-T17 may be temperature sensors and they may be divided into a plurality of defined groups. Each group then comprises at least one temperature sensor and corresponds to a zone of the wearer’s foot.

[0097] In the embodiment shown, a first zone, labeled MPA corresponds to a wearer’s medial plantar artery, and contains temperature sensors TO, Tl, and T2. A second zone, labeled LPA, corresponds to a wearer’s lateral plantar artery, and contains temperature sensors T3, T4, T5, T6, T7, T8, T9, T10, Ti l, and T12. A third zone, labeled CA, corresponds to a wearer’s calcaneal artery, and contains temperature sensors T13, T14, T15, and T17, and a fourth zone, labeled PA, corresponds to a wearer’s peroneal artery, and contains temperature sensor T16.

[0098] Those sensors T0-T17 are typically connected by wiring on the device 200 to a transmitter (not shown) that can then output any data collected from the sensors to a computer system implementing the methods described below.

[0099] In some embodiments, the sensors may be grouped more granularly.

Accordingly, groupings a, b, and c are shown in FIG. 2 as corresponding to subgroupings within the LPA group of temperature sensors. Similarly, groupings La3, La4, La5, and La6 may be considered independently, with each such grouping containing a single corresponding sensor. Such groupings may allow for more granular evaluations of a user’s individual toes.

[00100] In some embodiments, as discussed above with respect to the device 100 of FIG. 1, the device 200 may be provided in pairs. In such scenarios, the device may be embedded in a first insole and may be paired with a second symmetric device. The device shown 200 may then be used in an insole for a wearer’s left foot, and the symmetric second device may be used in an insole for the wearer’s right foot.

[00101] As discussed with respect to the method below, the device 200 of FIG. 2 may also be used in methods where a user has only one foot, and therefore the device may be provided in the context of a single insole.

[00102] The device shown 200 may further be provided with at least one sensor other than the temperature sensors. The other sensors, not shown, may be one or more of a force sensor, an inertial measuring unit, and a step-counter.

[00103] As discussed below, the device 200 may be embedded into a customizable insole which may then be heat formed into shape as part of a method for predicting and treating foot disease. [00104] It is noted that this disclosure references both a user and a wearer, at times. Typically, a wearer of an insole used described herein is a user, in that they are both wearing the insole and using the method for predicting foot disease. In some embodiments, a user may be a third party implementing the method for a patient or family member. In such an embodiment, the wearer may not be the party providing the sensors or receiving alerts indicating risk conditions.

[00105] Figure 3 is a flowchart illustrating a first method for predicting risk of foot disease. As shown, the method initially provides (300) a first plurality of temperature sensors T0-T5 that are positioned relative to a first set of locations on a wearer’s foot. These sensors would typically be provided in the context of a first insole incorporating temperature sensors, such as those shown in the first device 100. The temperature sensors T0-T5 are then positioned relative to the first set of locations by applying the first insole to the wearer’ s first foot.

[00106] The method then proceeds with providing (310) a second plurality of temperature sensors that are positioned relative to a second set of locations on the wearer’s second foot. As discussed above, the second set of locations may be a mirror image of the first set of locations, and the second set of sensors may be provided in the context of a second insole. The first insole may then correspond to a wearer’s left foot and the second insole may then be applied to the wearer’s right foot. Each sensor of the second plurality of temperature sensors may then have a corresponding symmetrically located sensor of the first plurality of temperature sensors T0-T5.

[00107] In some embodiments, in the context of providing the first plurality of temperature sensors and the second plurality of temperature sensors, the method may comprise providing the temperature sensors (at 300, 310) in the respective first and second insoles and providing the insoles as blanks to be molded to a user’s foot. The method may then further comprise custom forming (315) the first insole and the second insole to the first foot and second foot of the wearer respectively by heating the insoles and heat forming them to the corresponding feet. [00108] Once positioned relative to the wearer’s feet, the method may determine (320) that the temperature sensors are applied and may then wake up. Such a check may be in the context of a wake protocol to check whether an insole is being worn, and it may use the sensors other than temperature sensors to detect, for example, acceleration or pressure at the insole. In this way, the method may compare temperatures recorded only upon determining, based on the at least one sensor other than the temperature sensors, that the plurality of temperature sensors have been positioned relative to the corresponding set of locations. Such a check may be repeated at regular intervals until it is determined (at 320) that the device is being worn.

[00109] If the insole is being worn, the wake protocol will wake up a system implementing the method, and the temperature sensors T0-T5 may then begin to record temperature data (330) at various time intervals. For example, the temperature sensors may begin taking readings at 10 minute intervals. The intervals may be adjusted in order to either retrieve more granular data or preserve battery life.

[00110] Once temperature data is recorded at (330), it may be monitored by a processing unit on board the insole or it may be transmitted to an external computer system for processing. Such transmission may be by any standard transmission protocol, such as Bluetooth Low Energy.

[00111] The method then proceeds to implement a contralateral hot-spot protocol. Such a protocol can detect the presence of an elevated temperature by comparing each sensor on one insole to its mirrored counterpart on the other insole. The method therefore compares (at 340) a temperature recorded at a first time for each sensor of the second plurality of temperature sensors with a temperature recorded at the first time for the corresponding sensor of the first plurality.

[00112] A temperature difference may then be recorded (at 350) for each pair of corresponding sensors and the method may then identify (at 360) any temperature difference greater than a hot spot temperature threshold. Upon identifying a temperature difference greater than the hot spot temperature threshold between a first pair of corresponding sensors of the first plurality of temperature sensors and the second plurality of temperature sensors, the method then defines (at 370) a first hot spot risk condition.

[00113] In some embodiments, after identifying a hot spot at the first time, the first hot spot risk condition is defined, placing the method or the sensor into condition yellow. The temperature threshold is defined prior to implementing the method, but may be adjusted for a particular user or for specific scenarios. The temperature threshold may be, for example, 2.2 degrees C.

[00114] The method may then continue to record temperature differences (at 350) and identify (at 360) any temperature differences greater than the hot spot temperature threshold at additional times after the first time. Upon determining (380) that the temperature difference between a pair of corresponding sensors remains greater than the hot spot temperature threshold for a first predetermined period of time, the method defines (390) a second hot spot risk condition. The second hot spot risk condition may be an overall condition yellow for the wearer or user, and may then output an alert (400) to the user upon defining the second hot spot risk condition, or it may be a condition red that triggers an output of an alert.

[00115] In some embodiments, when determining whether a temperature difference remains greater than a temperature threshold, the method may continue to monitor only the pair of sensors that triggered the first hot spot risk condition (at 370). In other embodiments, the method may maintain the first hot spot risk condition if any pair of corresponding sensors indicates a difference greater than the temperature threshold. Accordingly, the first hot spot risk condition may be associated with a specific pair of sensors or it may be more general. In some embodiments, the first predetermined period of time may be, for example two hours, thereby triggering an overall condition yellow as the second hot spot risk condition.

[00116] In some embodiments, as discussed above, at least one sensor other than the plurality of temperature sensors T0-T5 may be provided. The at least one other sensor may be at least one of a force sensor, an inertial measuring unit, and a step counter.

[00117] In such an embodiment, once the first hot spot risk condition is defined (at 370), the method may then proceed to determine, based on the at least one sensor other than the temperature sensors, that the wearer was at rest at the time, and may then define a resting risk condition (at 375). While the determination may be made at 375, the method would typically proceed defining the hot spot (at 370) and monitoring the temperature differential over time (at 380) regardless of the result of such a determination. However, in such an embodiment, any alert output to the user may be based at least partially on the presence or absence of the resting risk condition.

[00118] In some embodiments, the method may proceed to determine, upon defining the first hot spot risk condition (at 370) whether the wearer was at rest at a second time prior to the first time. Such determination may similarly be made based on the at least one sensor other than the temperature sensors. In such an embodiment, the method may define the resting risk condition (at 375) only if the wearer was at rest during both the first time and the second time.

[00119] In some embodiments, the method continues to compare temperatures for pairs of corresponding sensors recorded at a plurality of additional times after defining the second hot spot risk condition (at 390). If the temperature difference between a pair of corresponding sensors remains greater than the hot spot temperature threshold for a second period of time longer than the first period of time, the method may then define a third hot spot risk condition. Such a third hot spot risk condition may cause the method to define an overall condition red, and may alert the user more aggressively than in the case of a condition yellow.

[00120] In some embodiments, the method proceeds to determine whether an average temperature risk condition is present. Accordingly, the method proceeds to determine (at 410) an average temperature for the first time for the first plurality of sensors of the first insole. The method then separately determines (at 420) an average temperature for the first time for the second plurality of sensors for the second insole.

[00121] In some embodiments, the method evaluates the average temperature risk condition only if the first hot spot risk condition is not defined (at 370). In other embodiments, the average temperature risk condition is evaluated constantly and in parallel with the evaluation of the hot spot risk condition.

[00122] Upon determining that a difference between the average temperatures is greater than an average temperature threshold (at 430), the method may then define a first average temperature risk condition (at 440).

[00123] The method may then proceed to compare average temperatures for the pluralities of temperature sensors for a plurality of additional times after the first time. Upon determining that a difference between the average temperatures remains greater than the average temperature threshold for the first predetermined period of time (445), the method may then define a second average temperature risk condition (at 450). As noted above with respect to hot spot risk conditions, the first average temperature risk condition may be a condition yellow in the method associated with the average temperature. The second average temperature risk condition may then be an overall condition yellow for the method. The method may then output an alert to the user (400) upon defining the second average temperature risk condition.

[00124] Typically, the average temperature threshold is lower than the hot spot temperature threshold. Accordingly, the average temperature threshold may be, for example, between 1 and 2 degrees C while the hot spot temperature threshold is above 2 degrees. In some embodiments, the average temperature threshold may be 1.35 degrees C.

[00125] In some embodiments, the method may continue to compare average temperatures for the plurality of temperature sensors for a plurality of additional times after defining the second average temperature risk condition (at 450). In such an embodiment, the method may output an alert to the user (at 400) upon determining that the temperature difference between the average temperatures remains greater than the average temperature threshold for a second predetermined period of time longer than the first predetermined period of time. Where the average temperature has remained elevated for the second predetermined period of time, the method may define an overall condition red, and may alert the user more aggressively than in the case of a condition yellow.

[00126] In the context of this method, several different types of risk conditions can be defined. In some embodiments, these risk conditions fall into three categories: hot spot risk conditions, resting risk conditions, and average temperature risk conditions. Accordingly, the method monitors a wearer’s feet for localized contralateral hot spots and one foot with an elevated mean temperature relative to the other. Where a hot spot is identified, the method further determines if a wearer was at rest.

[00127] For each such risk condition, there may be a first risk condition, which may apply a condition yellow associated with the specific condition. Such a first risk condition, or condition yellow, may be applied as soon as the condition is identified. Accordingly, if a temperature difference above the hot spot temperature threshold is identified between corresponding temperature sensors in the wearer’s two feet, such a corresponding yellow alert may be identified. Similarly, a condition yellow may be associated with resting risk condition, which corresponds to the hot spot temperature risk condition where resting risk is identified, and a condition yellow may be associated with an average temperature risk condition.

[00128] Each of these risk conditions may be evaluated independently and may be monitored by a condition yellow analysis. The condition yellow analysis may then, in some embodiments, weigh the condition yellows, and track the condition yellows over time. As noted above, if any of the individual condition yellows persist over a first period of time, such as for 2 hours, the method as a whole may enter a condition yellow and may trigger an alert to the user.

[00129] Further, if any condition yellow persists for more than a second period of time longer than the first period of time, such as 24 or 48 hours, the method may go into a condition red mode that alerts the user more aggressively. In some embodiments, time periods may be monitored and considered continuously, such that transitions from a localized condition yellow to a method wide condition yellow requires two consecutive hours of a condition yellow. Similarly, a transition to a condition red might then require a consecutive 24 hour or 48 hour period of a condition yellow. In some alternative embodiments, the time periods may be cumulative, such that the method may transition to condition red if a cumulative 24 or 48 hours of condition yellow have passed, even where the condition yellow is not continuous. Further, the time periods recited, namely 2 hours and 24 or 48 hours, are examples, and as such time periods may be varied.

[00130] In some embodiments, a condition yellow alert may be to the wearer of the insoles discussed herein, while a condition red alert may alert may be directed to the user’s doctor or caregiver. In other embodiments, the condition yellow may simply alert the user to the condition while the condition red may alert the user to call an emergency hotline.

[00131] The method described herein may be utilized to predict diabetic foot ulcerations. Alternatively, a similar framework may be used to identify and alert a user to risk associated with other diseases as well. For example, the method may be used to track peripheral neuropathy, charcot, gout conditions, and others.

[00132] Figure 4 is a second flowchart illustrating a variation of the method of FIG. 3 with some elements described in more detail.

[00133] As shown, in the embodiment of FIG. 4 firstly, the software runs the Wake Protocol to check whether the insole is being worn, such as by detecting acceleration or pressure application. If the insole is being worn, the temperature sensors will turn on and start taking readings at 10 minute intervals. This may be done in the firmware.

[00134] Once the temperature sensors are turned on and the communication system, such as a Bluetooth Low Energy (BLE) system starts transmitting data to the smart phone or computer system, the software runs the Contralateral Hot-Spot Protocol. CHSP-1 can detect the presence of an elevated temperature by comparing each sensor on one insole to its mirrored counterpart on the other insole. Every 10 minutes, temperature readings are taken from the 36 total temperature sensors. CHSP-1 takes the difference between each sensor (e.g., T0_L - TO R = TOdiff) and outputs a list (tDiffs) containing number values representing the differential temperatures. At every 10-minute interval, tDiffs will contain a total of 18 indices. The index numbers will correspond with the sensor labels as such:

[00135] [TOdiff, Tldiff, T2diff, T3diff, T4diff, T5diff, T6diff, T7diff, T8diff, T9diff, TIOdiff, Tl ldiff, T12diff, T13diff, T14diff, T15diff, T16diff, T17diff]

[00136] The protocol compares each differential temperature to determine whether it is greater than or equal to the Contralateral Hot-Spot Threshold |chsThresh| (chsThresh may be, for example = 2.2 C) and creates the list chsDiffs as an output. If a differential temperature is > |chsThresh|, chs = TRUE and the value will be placed in its corresponding index position. If a differential temperature is below |chsThresh|, chs = FALSE and a 0 will be placed in its index position. If the value is positive the sensor on the left insole is elevated and if the value is negative the sensor on the right is elevated. If there is at least one contralateral hot-spot detected (T#diff > |chsThresh|), that specific sensor will be put into condition yellow ([T#][L or R]CY) and the Contralateral Hot-Spot Condition Yellow (CHSCY) is triggered.

[00137] Next, is the Resting Temperature Protocol. RTP-1 attributes a Resting attribute (-R) to a hot-spot condition yellow if the reading was taken after a rest interval of at least 10 minutes. It also triggers its own condition yellow (RTCY).

[00138] If there is no hot-spot detected, then the software runs the Mean Temperature Protocol. MTP-1 takes the difference between the mean temperatures of both feet (tmean L - tmean R = LRdiff) and compares the LRdiff to the |meanThresh| (meanThresh may be, for example = 1.35 C). If |LRdiff| > meanThresh and LRdiff > 0, Mean Temperatuer Condition mtc = TRUE and the mean temperature of the left foot is elevated. If |LRdiff| > meanThresh and LRdiff < 0 the mean temperature of the right foot is elevated. If |LRdiff| < meanThresh, mtc = FALSE and neither foot is exhibiting an elevated mean temperature. In the case of an elevated mean foot temperature, the Mean Temperature Condition Yellow (MTCY) is triggered.

[00139] The next protocol, Condition Yellow Analysis, checks whether any of the four Condition Yellow parameters were triggered (HSCY, RTCY, MTCY). This protocol assigns a predetermined weight to each condition yellow.

[00140] The final protocol, Condition Alert Protocol, uses a time-stamped matrix to keep track of the temperature sensors, force sensors, IMU, and step-counter. If any of the individual Condition Yellows (HSCY, RTCY, MTCY) persist for greater than 2 hours, the software goes into Condition Yellow mode and alerts the user to take the Foot Health Assessment (FHA). If any of the individual Condition Yellows (HSCY, RTCY, MTCY) persist for greater than 48 hours (need not be continuous), the software goes into Condition Red mode and alerts the user to call the Emergency Hotline.

[00141] Figure 5 is a flowchart illustrating a second method for predicting a risk of foot disease. The method discussed in reference to FIG. 5 relies on temperature readings for a single foot and the figure thereby illustrates an ipsilateral framework for predicting diabetic foot ulcerations.

[00142] By providing a framework limited to a single foot, the method of FIG. 5 may be applied to wearers having only a single foot, such as in the case of having had a foot amputated. Further, the method may implement several protocols discussed in more detail above with respect to the method of FIG. 3. For example, a wake protocol may be implemented to determine when the method should begin tracking temperature data.

[00143] The method is described generally in the context of the device 200 of FIG. 2. Accordingly, the method first provides (500) a plurality of temperature sensors TOTH and positions those sensors (at 510) relative to a first set of locations on the wearer’s foot. In some embodiments, as discussed above, the device 200 is provided embedded into an insole, and the insole may then be custom formed (515) to the wearer’s feet in order to support the proper positioning of the sensors. [00144] The method then defines (520) a plurality of groups, each comprising at least one temperature sensor of the plurality of temperature sensors. Each group of the plurality of groups corresponds to a zone on the wearer’s foot. As discussed above, such zones may correspond, for example, to a medial plantar artery, a lateral plantar artery, a calcaneal artery, and a peroneal artery.

[00145] As discussed above with respect to the method of FIG. 3, the method may then confirm that the device is worn prior (525) to proceeding. Similarly, the device may record temperature data throughout the process, as discussed above.

[00146] The method then proceeds to compare (530) a first maximum temperature recorded at a first time by any first temperature sensor of the plurality of temperature sensors to a first minimum temperature recorded at the first time by any second temperature sensor of the plurality of temperature sensors. In doing so, the method defines an ipsilateral temperature difference (535).

[00147] The method then determines whether the ipsilateral temperature difference is greater than an ipsilateral difference threshold (at 537). If so, the method then defines (at 540) an ipsilateral hot spot condition. Accordingly, the method identifies an elevated temperature reading by comparing the hottest individual sensor to the coldest individual sensor.

[00148] In some embodiments, as discussed above, at least one sensor other than the plurality of temperature sensors T0-T17 may be provided. The at least one other sensor may be at least one of a force sensor, an inertial measuring unit, and a step counter.

[00149] In such an embodiment, once the ipsilateral hot spot condition is defined (at 540), the method may then proceed to determine (at 545), based on the at least one sensor other than the temperature sensors, that the wearer was at rest at the time, and may then define a resting risk condition (at 550). In such an embodiment, any alert output to the user may be based at least partially on the presence or absence of the resting risk condition. As noted above, the method will typically proceed regardless of whether the user is at rest, but the determination may impact the contents of any alert ultimately issued.

[00150] In some embodiments, the method may proceed to determine, upon defining the ipsilateral hot spot condition (at 540) whether the wearer was at rest at a second time prior to the first time. Such determination may similarly be made based on the at least one sensor other than the temperature sensors.

[00151] In such an embodiment, the method may define the resting risk condition (at 550) only if the wearer was at rest during both the first time and the second time.

[00152] The method may then proceed to define an average temperature (560) at the first time for each group of the plurality of groups and then define (at 570) an overall average temperature at the first time for the plurality of temperature sensors. As discussed above with respect to the method of FIG. 3, the different risk condition determinations may be consecutive, or they may be in parallel.

[00153] The method may then determine whether a difference between the overall average temperature (determined at 570) and an average group temperature (determined at 560) is greater than a hot zone threshold (575). If so, the method may define (at 580) a hot zone condition. In some embodiments, the hot zone threshold may be proportional to a standard deviation of the overall average temperature.

[00154] The method may then output an alert (at 590) to a user based on the definition of either the first ipsilateral hot spot condition or the first hot zone condition.

[00155] In some embodiments, the method defines the average temperature at the first time for each group and defines an overall average temperature only upon determining that the ipsilateral temperature difference is not greater than the ipsilateral difference threshold.

[00156] In some embodiments, the method proceeds with continuing to compare (at 530) a plurality of maximum temperatures recorded at any temperature sensor of the plurality of temperature sensors to a plurality of minimum temperatures recorded at any temperature sensor of the plurality of temperature sensors for a plurality of additional times after the first time. Upon determining that the temperature difference between a maximum temperature and a minimum temperature at a corresponding time remains greater than the ipsilateral threshold for a first predetermined period of time, defining a second ipsilateral hot spot condition.

[00157] Similarly, in some embodiments, the method continues to compare an average temperature for each group (defined at 560) to an overall average temperature (defined at 570) for a plurality of additional times after the first time. Upon determining that the average temperature for any group remains greater than the overall average temperature by the hot zone threshold for a first predetermined period of time, defining a second hot zone condition. Accordingly, as shown in FIG. 3, each risk condition may be modified in terms of severity if the condition persists for an extended period of time.

[00158] As discussed above in reference to the method of FIG. 3, in some embodiments, the user is the wearer. In other embodiments, the user is a caregiver or doctor for the wearer. Accordingly, the user may instruct the wearer in how to properly implement the method and may then assist the wearer, but alerts may then be provided to the user instead of, or in addition to, the wearer. Alternatively, or in addition, the user may be an insurance company, family, friends, or any other party getting notifications.

[00159] In some embodiments, in addition to the hot spot protocol defining a hot spot condition, the resting temperature protocol modifying the hot zone condition, and the hot zone protocol defining the hot zone condition, the method provides an ambient temperature protocol. In such an embodiment, the method may compare (600) the overall average temperature (defined at 570) to an ambient temperature. The method then defines an ambient temperature condition (610) upon determining that the overall average temperature is greater than the ambient temperature (605) by more than an ambient temperature threshold.

[00160] In some embodiments, the method may further comprise providing an ambient temperature sensor independent of the plurality of temperature sensors. The ambient temperature sensor may then be spaced apart from the plurality of temperature sensors, and the ambient temperature may be retrieved from the ambient temperature sensor.

[00161] Accordingly, in some such embodiments, the plurality of temperature sensors may be embedded in an insole, and the ambient temperature sensor may then be independent of the insole. For example, the ambient temperature sensor may clip to an external location on the wearer’s shoe.

[00162] Alternatively, the insole containing the plurality of temperature sensors may further comprise a wireless interface, and the ambient temperature may be retrieved from the wireless interface.

[00163] In some embodiments, the method may track all four conditions defined, namely the hot spot condition, the resting temperature condition, the hot zone condition, and the ambient temperature condition. An alert output to a user may then be based on all four conditions. For example, the alert output to the user may be based on a weighted sum of the four conditions.

[00164] For both the method of FIG. 3 and the method of FIG. 5, the various conditions need not be processed in a specific order. Instead, all conditions may be monitored independently, compared to their respective thresholds, and then weighted and summed in order to generate an overall alert indicating an assessment of overall risk.

[00165] In some embodiments, as discussed in the context of FIG. 3, the plurality of temperature sensors T0-T17 are provided embedded into an insole. Accordingly, each group of the plurality of groups comprises adjacent temperature sensors configured for locating adjacent corresponding zones of the wearer’s foot. Further, the method may comprise providing the temperature sensors in the insole and providing the insole as blanks to be molded to a wearer’s foot. The method may then further comprise custom forming the insole to the foot of the wearer by heating the insole and heat forming it to the corresponding foot.

[00166] Further, in some embodiments, the method may comprise providing the temperature sensors for the insole and custom forming the insole to the foot of the wearer by using additive manufacturing processes, such as 3D printing. As such, the insole may be manufactured in the appropriate shape for use with the corresponding foot.

[00167] In some embodiments, at least one insole containing a corresponding plurality of temperature sensors is first applied to a wearer’s foot or feet. The method then determines whether the wearer is wearing a single insole or two insoles. Accordingly, upon determining that only a single insole is present, the method may then implement the method described above with respect to FIG. 5. However, upon determining that two insoles are present, the method may then instead implement the method described above with respect to FIG. 3.

[00168] It is noted that the devices 100, 200 of FIG. 1 and FIG. 2 are, to an extent, interchangeable. Accordingly, the device 200 of FIG. 2 may be used to implement the method of FIG. 3 where two such insoles are provided. However, the method of FIG. 4 typically requires that temperature sensors be grouped, and therefore may require more temperature sensors than those available in FIG. 1.

[00169] In some embodiments, additional processing may be applied to sensor readings in order to implement the method consistently. For example, temperature outputs may be normalized or weighted in order to provide accurate average temperatures for specific zones as well as for overall temperatures.

[00170] Figure 6 is a second flowchart illustrating a variation of the method of FIG. 5 with some elements described in more detail.

[00171] As shown above in the embodiment of FIG. 4, the algorithm receives raw data from the hardware via a wireless interface, such as BLE and stores it locally in a tabular format, such as CSV. The algorithm sources data from this tabular file.

[00172] As shown in the embodiment of FIG. 4, the software may first run the Wake Protocol to check whether the insole is being worn, such as by detecting acceleration or pressure application. If the insole is being worn, the temperature sensors will turn on and start taking readings at 10 minute intervals. This is done in the firmware. [00173] Once the temperature sensors are turned on and the wireless interface of the system starts transmitting data, As shown in FIG. 6, the software then runs the Hot- Spot Protocol (HSP-1). HSP-1 detects the presence of an elevated temperature reading by comparing the hottest individual sensor (tmax) to the coldest individual sensor (tmin), and representing the difference as the ipsilateral temperature difference (itd). If there is a hot-spot detected (itd > itdThresh), that specific sensor and its respective zone will be put into condition yellow ([T][Zi]CY) and the Hot-Spot Condition Yellow (HSCY) is triggered. Next is the Resting Temperature Protocol (RTP-1). RTP-1 attributes a High Sensitivity attribute (HS) to a hot-spot condition yellow if the reading was taken after a rest interval of at least 10 minutes. It also triggers its own condition yellow (RTCY).

[00174] If there is no hot-spot detected by measuring individual sensors, the software then runs the Hot-Zone Protocol (HZP-1). HZP-1 compares the average temperature reading of the nine zones (M avg, etc.) against the average foot temperature (t avg). If a zone(s) is more than one standard deviation (tsd) above the average foot temperature (threshold= HZthresh), then the respective zone(s) will be put into condition yellow ([Zi]CY) and the Hot-Zone Condition Yellow is triggered (HZCY).

[00175] If there is no hot-spot and no hot-zone detected, then the software runs the Ambient Temperature Protocol (ATP-1). ATP-1 compares the median foot temperature (tmed) against the ambient temperature (amb), the difference is represented by ambient temperature difference (ambd). If there is a significant difference between the median foot temperature and the ambient temperature, then the Ambient Temperature Condition Yellow is triggered (ATCY).

[00176] The next protocol, Condition Yellow Analysis, checks whether any of the four Condition Yellow parameters were triggered (HSCY, RTCY, HZCY, ATCY). This protocol assigns a predetermined weight to each condition yellow.

[00177] The final protocol, Summarized Prediction Protocol, sums each predictor (HS, RT, HZ, AT) and if the sum is equal to or greater than a predetermined threshold, the app will display a true condition yellow (CY). If, for example, only the HS and AT predictors are in condition yellow, the app will not display a condition yellow and will remain in condition green (CG), until the next reading in 10 minutes. This protocol also uses a time-stamped matrix to keep track of the temperature sensors, force sensors, IMU, and step-counter in order to alert a user for condition red (CR), which occurs if and only if a sensor/zone/foot remains in CY continuously for an extended period of time, such as 48 hours.

[00178] The multi-layer algorithm is intended to reduce false-positives and provide a confident prediction to present to users through the app interface.

[00179] While the present invention has been described at some length and with some particularity with respect to the several described embodiments, it is not intended that it should be limited to any such particulars or embodiments or any particular embodiment, but it is to be construed with references to the appended claims so as to provide the broadest possible interpretation of such claims in view of the prior art and, therefore, to effectively encompass the intended scope of the invention. Furthermore, the foregoing describes the invention in terms of embodiments foreseen by the inventor for which an enabling description was available, notwithstanding that insubstantial modifications of the invention, not presently foreseen, may nonetheless represent equivalents thereto.

Claims

What is claimed is:

1. A computer-based method for predicting foot disease comprising: providing a first plurality of temperature sensors positioned relative to a first set of locations on a wearer’s first foot; providing a second plurality of temperature sensors positioned relative to a second set of locations on the wearer’s second foot, the second set of locations being a mirror image of the first set of locations, such that each sensor of the second plurality of temperature sensors has a corresponding symmetrically located sensor of the first plurality of temperature sensors; comparing a temperature recorded at a first time for each sensor of the second plurality of temperature sensors with a temperature recorded at the first time for the corresponding sensor of the first plurality; upon identifying a temperature difference greater than a hot spot temperature threshold between a first pair of corresponding sensors of the first plurality of temperature sensors and the second plurality of temperature sensors, defining a first hot spot risk condition; comparing temperatures recorded at a plurality of additional times after the first time for each sensor and upon determining that a temperature difference between a pair of corresponding sensors remains greater than the hot spot temperature threshold for a first predetermined period of time, defining a second hot spot risk condition; outputting an alert to a user upon defining the second hot spot risk condition.

2. The computer-based method of claim 1 further comprising: providing at least one sensor other than the plurality of temperature sensors for each of the wearer’s feet, the at least one sensor comprising one of a force sensor, an inertial measuring unit, and a step-counter, upon defining the first hot spot risk condition, determining, based on the at least one sensor other than the plurality of temperature sensors, that the wearer was at rest at the first time, and defining a resting risk condition, wherein content of the alert output to the user is at least partially based on the presence of the resting risk condition.

3. The computer-based method of claim 2, wherein, upon defining the first hot spot risk condition, determining, based on the at least one sensor other than the plurality of temperature sensors, that a wearer was at rest at a second time prior to the first time and defining the resting risk condition only if the wearer was at rest during both the first time and the second time.

4. The computer-based method of claim 1 further comprising: determining that the first hot spot risk condition has not been defined; determining an average temperature for the first time for the first plurality of temperature sensors; determining an average temperature for the first time for the second plurality of temperature sensors; upon determining that a difference between the average temperatures is greater than an average temperature threshold, defining a first average temperature risk condition; comparing average temperatures for the pluralities of temperature sensors for a plurality of additional times after the first time and upon determining that a difference between the average temperatures remains greater than the average temperature threshold for the first predetermined period of time, defining a second average temperature risk condition; outputting an alert to the user upon defining the second average temperature risk condition.

5. The computer-based method of claim 4 further comprising: comparing average temperatures for the pluralities of temperature sensors for a plurality of additional times after defining the second average temperature risk condition; and outputting an alert to the user upon determining that the temperature difference between the average temperatures remains greater than the average temperature threshold for a second predetermined period of time longer than the first predetermined period of time.

6. The computer-based method of claim 4, wherein the average temperature threshold is lower than the hot spot temperature threshold.

7. The computer-based method of claim 1 further comprising: comparing temperatures for pairs of corresponding sensors recorded at a plurality of additional times after defining the second hot spot risk condition; and outputting an alert to the user upon determining that the temperature difference between a pair of corresponding sensors remains greater than the hot spot temperature threshold for a second predetermined period of time longer than the first predetermined period of time.

8. The computer-based method of claim 1, wherein the first plurality of temperature sensors are embedded in a first insole for the first foot at a first set of predetermined locations, and wherein the second plurality of temperature sensors are embedded in a second insole for the second foot at a second set of predetermined locations, and wherein the first set of predetermined locations and the second set of predetermined locations are mirror images of each other.

9. The method of claim 8 further comprising custom forming the first insole and the second insole to the first foot and the second foot respectively by heating the insoles and forming them to the corresponding feet.

10. The method of claim 8 further comprising first measuring the first foot and the second foot of the wearer and creating the first and second insole by way of an additive manufacturing process based on the measuring of the first foot and the second foot.

11. The computer-based method of claim 1 further comprising: providing at least one sensor other than the plurality of temperature sensors for each of the wearer’s feet, the at least one sensor comprising one of a force sensor, an inertial measuring unit, and a step-counter, comparing the temperatures recorded at the plurality of temperature sensors only upon determining, based on the at least one sensor other than the plurality of temperature sensors, that the plurality of temperature sensors have been positioned relative to the corresponding set of locations.

12. The computer-based method of claim 1, wherein the foot disease is a diabetic foot ulceration.

13. A computer-based method for predicting foot disease comprising: providing a plurality of temperature sensors positioned relative to a first set of locations on a wearer’s foot; defining a plurality of groups each comprising at least one temperature sensor of the plurality of temperature sensors, each group of the plurality of groups corresponding to a zone on the wearer’s foot; comparing a first maximum temperature recorded at a first time by any first temperature sensor of the plurality of temperature sensors to a first minimum temperature recorded at the first time by any second temperature sensor of the plurality of temperature sensors to define an ipsilateral temperature difference; defining a first ipsilateral hot spot condition where the ipsilateral temperature difference is greater than an ipsilateral difference threshold; defining an average temperature at the first time for each group of the plurality of groups and defining an overall average temperature at the first time for the plurality of temperature sensors; defining a first hot zone condition where the average temperature for any first group of the plurality of groups is greater than the overall average temperature by a hot zone threshold; outputting an alert to a user based on the definition of either the first ipsilateral hot spot condition or the first hot zone condition.

14. The computer-based method of claim 13, wherein the method defines the average temperature at the first time for each group and defines an overall average temperature only upon determining that the ipsilateral temperature difference is not greater than the ipsilateral difference threshold.

15. The computer-based method of claim 13 further comprising: providing at least one sensor other than the plurality of temperature sensors, the at least one sensor comprising one of a force sensor, an inertial measuring unit, and a step-counter, determining, based on the at least one sensor other than the plurality of temperature sensors, that the wearer was at rest at the first time, and defining a resting risk condition if the wearer is determined to be at rest and the ipsilateral hot spot condition is defined, and wherein the alert output to the user indicates the presence of the resting risk condition.

16. The computer-based method of claim 13 further comprising: comparing a plurality of maximum temperatures recorded at any temperature sensor of the plurality of temperature sensors for a plurality of additional times after the first time to a plurality of minimum temperatures recorded at any temperature sensor of the plurality of temperature sensors for the plurality of additional times and, upon determining that the temperature difference between a maximum temperature and a minimum temperature at a corresponding time remains greater than the ipsilateral difference threshold for a first predetermined period of time, defining a second ipsilateral hot spot condition.

17. The computer-based method of claim 13 further comprising: comparing an average temperature for the for any group of the plurality of groups for a plurality of additional times after the first time to an overall average temperature for the plurality of additional times and, upon determining that the average temperature for any group remains greater than the overall average temperature for a first predetermined period of time by the hot zone threshold, defining a second hot zone condition.

18. The computer-based method of claim 13, wherein the hot zone threshold is proportional to a standard deviation of the overall average temperature.

19. The computer-based method of claim 13 further comprising: comparing the overall average temperature to an ambient temperature; and defining an ambient temperature condition upon determining that the overall average temperature is greater than the ambient temperature by more than an ambient temperature threshold.

20. The computer-based method of claim 19 further comprising providing an ambient temperature sensor independent of the plurality of temperature sensors, wherein the ambient temperature sensor is spaced apart from the plurality of temperature sensors, and wherein the ambient temperature is retrieved from the ambient temperature sensor.

21. The computer-based method of claim 20, wherein the plurality of temperature sensors are embedded in an insole and wherein the ambient temperature sensor is independent of the insole.

22. The computer-based method of claim 19 further comprising providing a wireless interface, and wherein the ambient temperature is retrieved by way of the wireless interface.

23. The computer-based method of claim 19 further comprising: providing at least one sensor other than the plurality of temperature sensors, the at least one sensor comprising one of a force sensor, an inertial measuring unit, and a step-counter, determining, based on the at least one sensor other than the plurality of temperature sensors, that the wearer was at rest at the first time, and defining a resting risk condition if the wearer is determined to be at rest and the ipsilateral hot spot condition is defined, wherein the alert output to the user is based on a weighted sum of the ipsilateral hot spot condition, the hot zone condition, the resting risk condition, and the ambient temperature condition.

24. The computer-based method of claim 13, wherein the plurality of temperature sensors is embedded in an insole, and wherein each group of the plurality of groups comprises temperature sensors configured for locating adjacent corresponding zones on the wearer’ s foot.

25. The computer-based method of claim 24, wherein a first group of the plurality of groups is configured for locating adjacent one of the medial plantar artery, the lateral plantar artery, or the calcaneal artery.

26. The computer-based method of claim 13 further comprising: providing at least one sensor other than the plurality of temperature sensors, the at least one sensor comprising one of a force sensor, an inertial measuring unit, and a step-counter, comparing the temperatures recorded at the plurality of temperature sensors only upon determining, based on the at least one sensor other than the plurality of temperature sensors, that the plurality of temperature sensors have been positioned relative to the corresponding set of locations.

27. The computer-based method of claim 13, wherein the foot disease is a diabetic foot ulceration.

28. The computer-based method of claim 13 wherein the plurality of temperature sensors is embedded in a first insole, and further comprising custom forming the first insole to the wearer’s foot by heating the insole and forming it to the corresponding foot.

29. The computer-based method of claim 13 wherein the plurality of temperature sensors is embedded in a first insole, and further comprising first measuring the foot of the wearer and creating the first insole by way of an additive manufacturing method based on the measuring of the corresponding foot.

30. A computer-based method for predicting foot disease comprising: determining whether a wearer is using one or two insoles, each insole containing a corresponding plurality of temperature sensors; upon determining that only a single insole is present: defining a plurality of groups, each comprising at least one temperature sensor of the plurality of temperature sensors corresponding to the single insole, wherein each group of the plurality of groups corresponds to a zone on the wearer’ s foot; comparing a first maximum temperature recorded at a first time by any first temperature sensor of the plurality of temperature sensors to a first minimum temperature recorded at the first time by any second temperature sensor of the plurality of temperature sensors to define an ipsilateral temperature difference; defining a first ipsilateral hot spot condition where the ipsilateral temperature difference is greater than an ipsilateral difference threshold; upon determining that two insoles are present: identifying pairs of temperature sensors, such that each temperature sensor of a first plurality of temperature sensors corresponding to a first insole of the two insoles has a symmetrically located temperature sensor of a second plurality of temperature sensors corresponding to a second insole of the two insoles, comparing a temperature recorded at a first time for each sensor of the first plurality of temperature sensors with a temperature recorded at the first time for the corresponding sensor of the second plurality; upon identifying a temperature difference greater than a hot spot temperature threshold between a first pair of corresponding sensors of the first plurality of temperature sensors and the second plurality of temperature sensors, defining a first hot spot risk condition; comparing temperatures recorded at a plurality of additional times after the first time at the first pair of corresponding sensors and upon determining that the temperature difference between the first pair remains greater than the hot spot temperature threshold for a first predetermined period of time, defining a second hot spot risk condition; outputting an alert to a user upon defining either the first ipsilateral hot spot condition or the second hot spot risk condition. A computer-based method for predicting foot disease comprising: providing a first insole having a first plurality of temperature sensors; providing a second insole having a second plurality of temperature sensors; custom fitting the first insole to a first foot of a wearer such that the first plurality of temperature sensors is positioned relative to a first set of locations on the wearer’s first foot; custom fitting the second insole to a second foot of the wearer such that the second plurality of temperature sensors is positioned relative to a second set of locations on the wearer’s second foot, the second set of locations being a mirror image of the first set of locations, such that each sensor of the second plurality of temperature sensors has a corresponding symmetrically located sensor of the first plurality of temperature sensors; comparing a temperature recorded at a first time for each sensor of the second plurality of temperature sensors with a temperature recorded at the first time for the corresponding sensor of the first plurality of temperature sensors; upon identifying a temperature difference greater than a hot spot temperature threshold between a first pair of corresponding sensors of the first plurality of temperature sensors and the second plurality of temperature sensors, defining a first hot spot risk condition; comparing temperatures recorded at a plurality of additional times after the first time at the first pair of corresponding sensors and upon determining that the temperature difference between the first pair remains greater than the hot spot temperature threshold for a first predetermined period of time, defining a second hot spot risk condition; outputting an alert to a user upon defining the second hot spot risk condition. A computer-based method for predicting foot disease comprising: providing an insole having a plurality of temperature sensors; custom fitting the insole to a foot of a wearer such that the plurality of temperature sensors are positioned relative to a first set of locations on the wearer’ s foot; comparing a first maximum temperature recorded at a first time by any first temperature sensor of the plurality of temperature sensors to a first minimum temperature recorded at the first time by any second temperature sensor of the plurality of temperature sensors to define an ipsilateral temperature difference; defining a first ipsilateral hot spot condition where the ipsilateral temperature difference is greater than an ipsilateral difference threshold; defining an average temperature at the first time for each group of the plurality of groups and defining an overall average temperature at the first time for the plurality of temperature sensors; defining a first hot zone condition where the average temperature for any first group of the plurality of groups is greater than the overall average temperature by a hot zone threshold; outputting an alert to a user based on the definition of either the first ipsilateral hot spot condition or the first hot zone condition.