Systems and methods for extracting insights by analyzing behaviors exhibited by non-human animals

Abstract

A system for identifying an anomaly in behavior of a non-human animal, the system comprising processing circuitry configured to: provide a behavior baseline comprising first information regarding normal behavior of the non-human animal for a given period of time during which no anomaly occurs; obtaining data regarding a series of consecutively identified behaviors of the non-human animal identified within the second time period; an action is performed when the data does not conform to the behavior baseline, thereby indicating an anomaly in the non-human animal behavior.

Description

Technical Field

[0001] The presently disclosed subject matter relates to extracting insights by analyzing behaviors exhibited by non-human animals. Background Art

[0002] The ongoing challenge to the caregivers of non-human animals is that non-human animals cannot communicate by explaining their feelings and / or emotions. Non-human animals cannot explain any details about their conditions to their caregivers, or even cannot point out any specific pain caused by any reason. Caregivers can only identify when non-human animals suffer pain by monitoring the behavior of non-human animals. Most importantly, animals cannot be constantly monitored by their caregivers. Even if animals can communicate, in most cases, it is impossible to extract insights (such as one or more of the following: identifying behavioral patterns, identifying behavioral baselines, identifying the connection between behaviors, identifying the condition / health of animals, or identifying behavioral abnormalities) from the behavior of animals in real time or even near real time. Therefore, for example, it takes time to identify the abnormal behavior of any individual animal, because the caregiver needs to observe the abnormal behavior first, and then determine whether it is abnormal. Even when noticed, in many cases, the caregiver will allocate extra time to find out that the abnormal behavior is not temporary, but due to disease, infection, itching or some other situations that require intervention (an example of intervention is behavior modification, medical examination or treatment). It can be readily appreciated that in some cases, the longer it takes to identify a medical condition requiring intervention, the more difficult it is to treat the medical condition, and in extreme cases, the window of time for treating the medical condition may close.

[0003] For example, pets such as dogs or cats may suffer from pruritus (itching) due to various reasons associated with skin health (e.g., skin diseases, allergies, etc.) and / or several different parasitic infections. In many cases, animal caregivers (e.g., pet owners) may not notice the pruritus because pet owners may need some time to realize that their pets are showing abnormal or pathological (rather than normal) behaviors, such as increased or abnormal scratching, shivering, barking, combing, etc. In some cases, pet owners may only find the pruritus after skin injuries have occurred, which brings great discomfort to the animal. Even when excessive scratching, shivering, barking, combing, etc. are noticed, pet owners may decide to wait longer to ensure that the pruritus will not subside on its own without treatment. Therefore, pet owners may need quite a long time to take their pets to the veterinarian for intervention (such as behavior modification, medical examination and / or treatment). By the time treatment can be applied, the problem may have become worse and even more difficult to solve.

[0004] In some cases, a particular type of intervention may not resolve a problem for a non-human animal. Likewise, it may be difficult to determine the effectiveness of an intervention due to the lack of ability to communicate with the non-human animal and the inability of the animal caregiver to constantly monitor the animal. As a result, the intervention may be ineffective, or only partially effective, and it may take a long time to learn that an intervention (such as behavior modification or therapy) did not resolve the problem. In view of this fact, and by the time the appropriate intervention is identified, the non-human animal may suffer for a long period of time until the appropriate intervention is identified and the problem is resolved. A related situation may occur when a caregiver does not comply or is unable to comply with the care requirements to resolve the problem. This lack of treatment compliance may not be apparent to the veterinarian unless the caregiver provides timely updates on the animal's status.

[0005] Another challenge is when a new intervention (such as a new behavior modification approach or a new treatment) is developed and its efficacy needs to be determined. For example, when a new drug is developed, it needs to be tested to determine whether the new drug is effective and how well it performs relative to existing and potential competing interventions (such as competing treatments).

[0006] One thing all of these situations have in common is that the measurement of the behavior of non-human animals requires subjective observation, such as documentation by the non-human animal's caregiver. Current technology enables the determination of animal behavior through objective monitoring and analysis of animal movement data (and / or other types of data, such as body position data) acquired over time, for example, by a three-dimensional accelerometer that records specific movements made by the animal. One example is Sure Petcare's (hereinafter referred to as "Animo"). An activity and behavior monitoring device that is attached to a dog, such as on a dog collar. Understand and accurately interpret your dog's unique patterns. Delivers insights into a dog's activity and sleep patterns and translates movements into named behaviors, such as shivering, scratching, and barking, that may indicate potential deviations from normal movement (health). The dog's movement is measured in three-dimensional space (3D accelerometer). The dog's movement is recorded at time intervals, and for each time interval, the movement data acquired within such time interval can be characterized as named behaviors. The characterized behaviors can include any one or more of the following (whether alone or in combination): shivering, grooming, scratching, resting, sleeping, high activity, medium activity, low activity, barking, calorie consumption, walking, running, sitting, lying down, jumping, chewing, sniffing, licking, etc. Utilizing this technology can help identify valuable information (such as one or more of the following: behavior patterns, behavior baselines, connections between behaviors, animal condition / health, effects of treatment, or behavioral abnormalities) by analyzing the identified behaviors of non-human animals in an objective manner that does not rely on subjective human observation of the behavior of non-human animals.

[0007] It can be used to provide information useful both for research and development (e.g., for testing the effects of drugs, discovering new correlations between behavior and the health status of animals, etc.) and for consumers (providing pet owners with insights into the health status of their pets, improving communication between pet owners and veterinarians, etc.). It will be appreciated that information can be provided in different ways for various purposes. For example, for research and development purposes, by using The data available is substantially more sophisticated than what would be provided to a consumer who sees the naming behavior of the representation. Most consumers will not be able to understand the The raw data collected, and the data provided to the consumer may therefore be processed or analyzed to provide clearer insights to the consumer.

[0008] It is important to note that devices that monitor the movement of non-human animals and characterize behavior are also available for animals other than dogs, such as cattle. However, due to the inherent differences between different types of animals, there are significant differences in the devices and the algorithms used on the data collected thereby. For example, a dog moves much more flexibly than a cow (imagine a cow scratching the way a dog does), and therefore the raw accelerometer data includes different types of physical movements than, for example, a cow might make.

[0009] Therefore, there is a need in the art for new systems and methods for extracting insights (such as one or more of the following: identifying behavioral patterns, identifying behavioral baselines, identifying connections between behaviors, identifying the condition / health of the animal, or identifying behavioral anomalies) by analyzing behaviors exhibited by non-human animals. Summary of the invention

[0010] According to a first aspect of the subject matter of the present disclosure, a system for identifying anomalies in the behavior of a non-human animal is provided, the system comprising a processing circuit configured to: provide a behavioral baseline comprising first information about normal behavior of the non-human animal within a given time period in which no anomalies occur; obtain data about a series of consecutively identified behaviors of the non-human animal identified within a second time period; and perform an action when the data does not conform to the behavioral baseline, thereby indicating an anomaly in the behavior of the non-human animal.

[0011] In one embodiment of the disclosed subject matter and / or embodiments thereof, for each normal behavior, the information about the normal behavior includes: (a) an indication of the type of behavior, and (b) one or more of the following: (i) a normal frequency range for the behavior, (ii) a normal duration range for the behavior, (iii) a normal intensity range for the behavior, and (iv) a normal score range for a score calculated for the behavior.

[0012] In one embodiment of the disclosed subject matter and / or embodiments thereof, the processing circuit is further configured to analyze the data to determine a cause of the anomaly.

[0013] In one embodiment of the presently disclosed subject matter and / or embodiments thereof, the cause is one or more of: itching, heart problems, nervous system problems, obesity, diabetes, separation anxiety, arthritis, ear inflammation, musculoskeletal problems.

[0014] In one embodiment of the disclosed subject matter and / or embodiments thereof, the continuously identified behavior is determined based on analysis of three-dimensional (3D) accelerometer data acquired by a 3D accelerometer included in a device attached to the non-human animal.

[0015] In one embodiment of the subject matter of the present disclosure and / or its embodiments, the behavioral baseline is an animal-specific behavioral baseline determined using baseline creation data, the baseline creation data comprising a baseline series of continuously identified baseline behaviors of the non-human animal identified over a third time period that the non-human animal is considered to behave normally.

[0016] In one embodiment of the presently disclosed subject matter and / or embodiments thereof, the action is triggering an alarm to a caregiver of the non-human animal.

[0017] In one embodiment of the presently disclosed subject matter and / or embodiments thereof, the caregiver is an owner of the non-human animal, a veterinarian of the non-human animal, or a trainer of the non-human animal.

[0018] In one embodiment of the presently disclosed subject matter and / or embodiments thereof, the alert includes an indication of a potential cause of the anomaly.

[0019] In one embodiment of the presently disclosed subject matter and / or embodiments thereof, normal behavior and continuously identified behaviors include one or more of the following: shivering, grooming, scratching, resting, sleeping, high activity, medium activity, low activity, barking, calorie burning, walking, running, sitting, lying down, jumping, chewing, sniffing, or licking.

[0020] In one embodiment of the presently disclosed subject matter and / or embodiments thereof, the information about normal behavior includes a sleep score.

[0021] In one embodiment of the disclosed subject matter and / or embodiments thereof, the processing circuit is further configured to provide one or more abnormality prevention recommendations to a caregiver of the non-human animal based on historical behavioral data associated with the non-human animal.

[0022] According to a second aspect of the subject matter of the present disclosure, a system for monitoring the effectiveness of treatment of one or more causes of abnormalities in the behavior of a non-human animal is provided, the system comprising a processing circuit configured to: provide a behavioral baseline comprising first information regarding normal behavior of the non-human animal within a given time period in which no abnormalities occur; obtain second information of a second series of continuously identified behaviors of the non-human animal identified within a second time period after the treatment is applied to the non-human animal; and perform an action when a trend of one or more parameters calculated based on the second information does not converge to the behavioral baseline.

[0023] In one embodiment of the subject matter of the present disclosure and / or its embodiments, for each normal behavior, the first information about the normal behavior includes: (a) an indication of the type of behavior, and (b) one or more of the following items: (i) a normal frequency range for the behavior, (ii) a normal duration range for the behavior, (iii) a normal intensity range for the behavior, and (iv) a normal score range for the score calculated for the behavior.

[0024] In one embodiment of the disclosed subject matter and / or embodiments thereof, the continuously identified behavior is determined based on analysis of three-dimensional (3D) accelerometer data acquired by a 3D accelerometer included in a device attached to the non-human animal.

[0025] In one embodiment of the subject matter of the present disclosure and / or its embodiments, the behavioral baseline is an animal-specific behavioral baseline determined using baseline creation data, the baseline creation data comprising a baseline series of continuously identified baseline behaviors of the non-human animal identified over a third time period that the non-human animal is considered to behave normally.

[0026] In one embodiment of the presently disclosed subject matter and / or embodiments thereof, the action is triggering an alarm to a caregiver of the non-human animal.

[0027] In one embodiment of the presently disclosed subject matter and / or embodiments thereof, the caregiver is an owner of the non-human animal, a veterinarian of the non-human animal, or a trainer of the non-human animal.

[0028] In one embodiment of the presently disclosed subject matter and / or embodiments thereof, normal behavior and continuously identified behaviors include one or more of the following: shivering, grooming, scratching, resting, sleeping, high activity, medium activity, low activity, barking, calorie burning, walking, running, sitting, lying down, jumping, chewing, sniffing, or licking.

[0029] In one embodiment of the presently disclosed subject matter and / or embodiments thereof, the first information about normal behavior comprises a sleep score.

[0030] According to a third aspect of the subject matter of the present disclosure, there is provided a system for monitoring the effectiveness of a treatment for one or more causes of abnormalities in the behavior of a non-human animal, the system comprising a processing circuit configured to: provide a successful treatment behavior baseline comprising first information regarding normal behavior of the non-human animal over multiple time periods after application of treatment for the one or more causes of abnormalities in the behavior of the non-human animal; obtain second information regarding a series of consecutive identified behaviors of the non-human animal identified over a given time period after application of treatment for an itch-causing infection to the non-human animal; and perform an action when the series of consecutive identified behaviors of the non-human animal over a time period in a time period corresponding to the given time period do not meet the successful treatment behavior baseline.

[0031] In one embodiment of the subject matter of the present disclosure and / or its embodiments, for each normal behavior, the first information about the normal behavior includes: (a) an indication of the type of behavior, and (b) one or more of the following items: (i) a normal frequency range for the behavior, (ii) a normal duration range for the behavior, (iii) a normal intensity range for the behavior, and (iv) a normal score range for the score calculated for the behavior.

[0032] In one embodiment of the disclosed subject matter and / or embodiments thereof, the continuously identified behavior is determined based on analysis of three-dimensional (3D) accelerometer data acquired by a 3D accelerometer included in a device attached to the non-human animal.

[0033] In one embodiment of the subject matter of the present disclosure and / or embodiments thereof, the successful treatment behavior baseline is an animal-specific successful treatment behavior baseline determined using baseline creation data, the baseline creation data comprising a baseline series of continuously identified baseline behaviors of the non-human animal identified within a third time period after application of treatment for one or more causes of abnormality in the behavior of the non-human animal.

[0034] In one embodiment of the presently disclosed subject matter and / or embodiments thereof, the action is triggering an alarm to a caregiver of the non-human animal.

[0035] In one embodiment of the presently disclosed subject matter and / or embodiments thereof, the caregiver is an owner of the non-human animal, a veterinarian of the non-human animal, or a trainer of the non-human animal.

[0036] In one embodiment of the presently disclosed subject matter and / or embodiments thereof, normal behavior and continuously identified behaviors include one or more of the following: shivering, grooming, scratching, resting, sleeping, high activity, medium activity, low activity, barking, calorie burning, walking, running, sitting, lying down, jumping, chewing, sniffing, or licking.

[0037] In one embodiment of the presently disclosed subject matter and / or embodiments thereof, the first information about normal behavior comprises a sleep score.

[0038] According to a fourth aspect of the subject matter of the present disclosure, a method for identifying anomalies in the behavior of a non-human animal is provided, the method comprising: providing, by a processing circuit, a behavioral baseline comprising first information about normal behavior of the non-human animal within a given time period in which no anomalies occur; obtaining, by the processing circuit, data about a series of continuously identified behaviors of the non-human animal identified within a second time period; and performing, by the processing circuit, an action when the data does not conform to the behavioral baseline, thereby indicating an anomaly in the behavior of the non-human animal.

[0039] In one embodiment of the disclosed subject matter and / or embodiments thereof, for each normal behavior, the information about the normal behavior includes: (a) an indication of the type of behavior, and (b) one or more of the following: (i) a normal frequency range for the behavior, (ii) a normal duration range for the behavior, (iii) a normal intensity range for the behavior, and (iv) a normal score range for a score calculated for the behavior.

[0040] In one embodiment of the disclosed subject matter and / or embodiments thereof, the method further comprises analyzing, by the processing circuitry, the data to determine a cause of the anomaly.

[0041] In one embodiment of the presently disclosed subject matter and / or embodiments thereof, the cause is one or more of: itching, heart problems, nervous system problems, obesity, diabetes, separation anxiety, arthritis, ear inflammation, musculoskeletal problems.

[0042] In one embodiment of the disclosed subject matter and / or embodiments thereof, the continuously identified behavior is determined based on analysis of three-dimensional (3D) accelerometer data acquired by a 3D accelerometer included in a device attached to the non-human animal.

[0043] In one embodiment of the subject matter of the present disclosure and / or its embodiments, the behavioral baseline is an animal-specific behavioral baseline determined using baseline creation data, the baseline creation data comprising a baseline series of continuously identified baseline behaviors of the non-human animal identified over a third time period that the non-human animal is considered to behave normally.

[0044] In one embodiment of the presently disclosed subject matter and / or embodiments thereof, the action is triggering an alarm to a caregiver of the non-human animal.

[0045] In one embodiment of the presently disclosed subject matter and / or embodiments thereof, the caregiver is an owner of the non-human animal, a veterinarian of the non-human animal, or a trainer of the non-human animal.

[0046] In one embodiment of the presently disclosed subject matter and / or embodiments thereof, the alert includes an indication of a potential cause of the anomaly.

[0047] In one embodiment of the presently disclosed subject matter and / or embodiments thereof, normal behavior and continuously identified behaviors include one or more of the following: shivering, grooming, scratching, resting, sleeping, high activity, medium activity, low activity, barking, calorie burning, walking, running, sitting, lying down, jumping, chewing, sniffing, or licking.

[0048] In one embodiment of the presently disclosed subject matter and / or embodiments thereof, the information about normal behavior includes a sleep score.

[0049] In one embodiment of the disclosed subject matter and / or embodiments thereof, the method further includes providing, by the processing circuitry, one or more abnormality prevention recommendations to a caregiver of the non-human animal based on historical behavioral data associated with the non-human animal.

[0050] According to a fifth aspect of the subject matter of the present disclosure, a method for monitoring the effect of treatment of one or more causes of abnormalities in the behavior of a non-human animal is provided, the method comprising: providing, by a processing circuit, a behavioral baseline comprising first information about the normal behavior of the non-human animal within a given time period in which no abnormalities occur; obtaining, by the processing circuit, second information of a second series of continuously identified behaviors of the non-human animal identified within a second time period after the treatment is applied to the non-human animal; and performing an action by the processing circuit when a trend of one or more parameters calculated based on the second information does not converge to the behavioral baseline.

[0051] In one embodiment of the subject matter of the present disclosure and / or its embodiments, wherein for each normal behavior, the first information about the normal behavior includes: (a) an indication of the type of behavior, and (b) one or more of the following items: (i) a normal frequency range for the behavior, (ii) a normal duration range for the behavior, (iii) a normal intensity range for the behavior, and (iv) a normal score range for the score calculated for the behavior.

[0052] In one embodiment of the disclosed subject matter and / or embodiments thereof, the continuously identified behavior is determined based on analysis of three-dimensional (3D) accelerometer data acquired by a 3D accelerometer included in a device attached to the non-human animal.

[0053] In one embodiment of the subject matter of the present disclosure and / or its embodiments, the behavioral baseline is an animal-specific behavioral baseline determined using baseline creation data, the baseline creation data comprising a baseline series of continuously identified baseline behaviors of the non-human animal identified over a third time period that the non-human animal is considered to behave normally.

[0054] In one embodiment of the presently disclosed subject matter and / or embodiments thereof, the action is triggering an alarm to a caregiver of the non-human animal.

[0055] In one embodiment of the presently disclosed subject matter and / or embodiments thereof, the caregiver is an owner of the non-human animal, a veterinarian of the non-human animal, or a trainer of the non-human animal.

[0056] In one embodiment of the presently disclosed subject matter and / or embodiments thereof, normal behavior and continuously identified behaviors include one or more of: shivering, grooming, scratching, resting, sleeping, high activity, moderate activity, low activity, barking, calorie burning, walking, running, sitting, lying down, jumping, chewing, sniffing, or licking.

[0057] In one embodiment of the presently disclosed subject matter and / or embodiments thereof, the first information about normal behavior comprises a sleep score.

[0058] According to a sixth aspect of the subject matter of the present disclosure, there is provided a method for monitoring the effects of one or more causes of abnormalities in the behavior of non-human animals, the method comprising: providing, by a processing circuit, a successful treatment behavior baseline comprising first information regarding normal behavior of the non-human animal over multiple time periods after application of treatment for the one or more causes of abnormalities in the behavior of the non-human animal; obtaining, by the processing circuit, second information regarding a series of consecutive identified behaviors of the non-human animal identified over a given time period after application of treatment for an infection causing itching to the non-human animal; and performing an action by the processing circuit when the series of consecutive identified behaviors of the non-human animal over a time period corresponding to the given time period in the time period do not meet the successful treatment behavior baseline.

[0059] In one embodiment of the subject matter of the present disclosure and / or its embodiments, for each normal behavior, the first information about the normal behavior includes: (a) an indication of the type of behavior, and (b) one or more of the following items: (i) a normal frequency range for the behavior, (ii) a normal duration range for the behavior, (iii) a normal intensity range for the behavior, and (iv) a normal score range for the score calculated for the behavior.

[0060] In one embodiment of the disclosed subject matter and / or embodiments thereof, the continuously identified behavior is determined based on analysis of three-dimensional (3D) accelerometer data acquired by a 3D accelerometer included in a device attached to the non-human animal.

[0061] In one embodiment of the subject matter of the present disclosure and / or embodiments thereof, the successful treatment behavior baseline is an animal-specific successful treatment behavior baseline determined using baseline creation data, the baseline creation data comprising a baseline series of continuously identified baseline behaviors of the non-human animal identified within a third time period after application of treatment for one or more causes of abnormality in the behavior of the non-human animal.

[0062] In one embodiment of the presently disclosed subject matter and / or embodiments thereof, the action is triggering an alarm to a caregiver of the non-human animal.

[0063] In one embodiment of the presently disclosed subject matter and / or embodiments thereof, the caregiver is an owner of the non-human animal, a veterinarian of the non-human animal, or a trainer of the non-human animal.

[0064] In one embodiment of the presently disclosed subject matter and / or embodiments thereof, normal behavior and continuously identified behaviors include one or more of the following: shivering, grooming, scratching, resting, sleeping, high activity, medium activity, low activity, barking, calorie burning, walking, running, sitting, lying down, jumping, chewing, sniffing, or licking.

[0065] In one embodiment of the presently disclosed subject matter and / or embodiments thereof, the first information about normal behavior comprises a sleep score.

[0066] According to a seventh aspect of the subject matter of the present disclosure, there is provided a non-transitory computer-readable storage medium having a computer-readable program code embodied therewith, the computer-readable program code being executable by at least one processing circuit of a computer to perform a method for identifying anomalies in the behavior of a non-human animal, the method comprising: providing, by the processing circuit, a behavioral baseline comprising first information about normal behavior of the non-human animal within a given time period in which no anomalies occur; obtaining, by the processing circuit, data about a series of continuously identified behaviors of the non-human animal identified within a second time period; and performing, by the processing circuit, an action when the data does not conform to the behavioral baseline, thereby indicating an anomaly in the behavior of the non-human animal.

[0067] According to an eighth aspect of the subject matter of the present disclosure, a non-transitory computer-readable storage medium is provided, which has a computer-readable program code embodied therein, and the computer-readable program code is executable by at least one processing circuit of a computer to perform a method for monitoring the effect of treatment of one or more causes of abnormalities in the behavior of non-human animals, the method comprising: providing, by the processing circuit, a behavioral baseline comprising first information about normal behavior of the non-human animal within a given time period in which no abnormalities occur; obtaining, by the processing circuit, second information of a second series of continuously identified behaviors of the non-human animal identified within a second time period after the treatment is applied to the non-human animal; and performing an action by the processing circuit when a trend of one or more parameters calculated based on the second information does not converge to the behavioral baseline.

[0068] According to a ninth aspect of the subject matter of the present disclosure, there is provided a non-transitory computer-readable storage medium having a computer-readable program code embodied therewith, the computer-readable program code being executable by at least one processing circuit of a computer to perform a method for monitoring the effect of a treatment for one or more causes of abnormalities in the behavior of a non-human animal, the method comprising: providing, by the processing circuit, a successful treatment behavior baseline comprising first information about normal behavior of the non-human animal over multiple time periods after application of treatment for the one or more causes of abnormalities in the behavior of the non-human animal; obtaining, by the processing circuit, second information about a series of continuously identified behaviors of the non-human animal identified within a given time period after application of treatment for an infection causing itching to the non-human animal; and performing an action by the processing circuit when a series of continuously identified behaviors of the non-human animal within a time period corresponding to the given time period in the time period does not meet the successful treatment behavior baseline. BRIEF DESCRIPTION OF THE DRAWINGS

[0069] In order to understand the subject matter of the present disclosure and to see how it may be put into practice, the subject matter will now be described, by way of non-limiting example only, with reference to the accompanying drawings, in which:

[0070] Figure 1is a schematic diagram of an operating environment for a system for extracting insights from the behavior of non-human animals in accordance with the presently disclosed subject matter;

[0071] Figure 2 is a block diagram schematically illustrating one example of a system according to the disclosed subject matter;

[0072] Figure 3 is a flow chart illustrating one example of a sequence of operations performed for extracting insights from the behavior of a non-human animal in accordance with the presently disclosed subject matter;

[0073] Figure 4 is a flow chart illustrating one example of a sequence of operations performed for monitoring the effects of an intervention performed on a non-human animal in accordance with the presently disclosed subject matter;

[0074] Figure 5 is another flow chart illustrating another example of a sequence of operations performed for monitoring the effects of an intervention performed on a non-human animal in accordance with the presently disclosed subject matter;

[0075] Figures 6a to 9e An exemplary graphical user interface (GUI) shown to a dog's caregiver in accordance with the disclosed subject matter is shown:

[0076] Figure 6a A GUI is shown indicating that a dog is suffering from excessive shivering;

[0077] Figure 6b Shown is shown in the Figure 7a Shivering was measured in the dogs over a one-month period of treatment;

[0078] Figure 7a and Figure 7b A GUI is shown indicating that the dog was suffering from excessive shaking and scratching prior to the intervention and the effect of the intervention;

[0079] Figures 8a to 8e A GUI is shown indicating that the dog suffered from excessive shivering and decreased sleep quality prior to the intervention and the effects of the intervention;

[0080] Figures 9a to 9e A GUI is shown indicating that the dog suffered from excessive shivering prior to the intervention and the effect of the intervention;

[0081] Figure 10a to Figure 10g each showing a diagram of the value of a parameter determined during an experiment in which animals have been monitored during the day and during the night in both the infection and non-infection phases;

[0082] Figures 11a to 11d each showing a graph of the course of the average number of events per hour between Day 8 and Day 24 of an exemplary study discussed herein;

[0083] Fig.12 A graph showing minutes of scratching per month by skin disease diagnosis as observed in an exemplary study discussed herein;

[0084] Fig.13 A graph showing average minutes of scratching per day by skin disease diagnosis as observed in an exemplary study discussed herein;

[0085] Fig.14 a graph showing average minutes of shivering per day by skin disease diagnosis as observed in an exemplary study discussed herein;

[0086] Fig.15 A graph showing average minutes of grooming per day by skin disease diagnosis as observed in an exemplary study discussed herein;

[0087] Fig.16 a graph showing the average number of minutes of nightly rest per night by skin disease diagnosis as observed in an exemplary study discussed herein;

[0088] Fig.17 a graph showing average sleep ratio per night by skin disease diagnosis as observed in an exemplary study discussed herein;

[0089] Fig.18 A graph showing the average number of minutes of scratching per day observed in an exemplary study as discussed herein;

[0090] Fig.19 a graph showing the average number of minutes of shivering per day observed in an exemplary study as discussed herein;

[0091] Fig. 20 a graph showing the average minutes of grooming per day observed in an exemplary study as discussed herein; and

[0092] Fig.21 A graph showing the average number of minutes of nightly rest per night observed in an exemplary study as discussed herein. DETAILED DESCRIPTION

[0093] In the following detailed description, many specific details are set forth to provide a thorough understanding of the subject matter of the present disclosure. However, it will be appreciated by those skilled in the art that the subject matter of the present disclosure can be practiced without these specific details. In other examples, well-known methods, processes, and components are not described in detail to avoid obscuring the subject matter of the present disclosure.

[0094] In the figures and description set forth, like reference numerals indicate those components that are common to different embodiments or configurations.

[0095] Unless otherwise expressly stated, as will be apparent from the following discussion, it should be recognized that terms such as "providing," "obtaining," "executing," "analyzing," and the like, utilized throughout the specification discussion, include actions and / or processes of a computer to manipulate data and / or transform data into other data, the data being represented as physical quantities, such as electronic quantities, and / or the data representing physical objects. The terms "computer," "processor," "processing circuit," and "controller" should be broadly interpreted to cover any kind of electronic device with data processing capabilities, including, by way of non-limiting example, but not limited to, personal desktop / laptop computers, servers, computing systems, communication devices, smart phones, tablet computers, smart TVs, processors (e.g., digital signal processors (DSPs), microcontrollers, field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), etc.), a group of multiple physical machines that share the execution of various tasks, virtual servers co-resident on a single physical machine, any other electronic computing device, and / or any combination thereof.

[0096] Operations according to the teachings herein may be performed by a computer specially constructed for the required purpose, or by a general purpose computer specially configured for the required purpose by a computer program stored in a non-transitory computer readable storage medium. The term "non-transitory" as used herein excludes transitory propagating signals, but otherwise includes any volatile or non-volatile computer memory technology suitable for the application.

[0097] As used herein, the phrases "for example," "such as," "for example," and variations thereof describe non-limiting embodiments of the subject matter of the present disclosure. References in the specification to "one instance," "some instances," "other instances," or variations thereof mean that a particular feature, structure, or characteristic described in conjunction with the embodiment(s) is included in at least one embodiment of the subject matter of the present disclosure. Therefore, the appearance of the phrases "one instance," "some instances," "other instances," or variations thereof do not necessarily refer to the same embodiment(s).

[0098] It should be appreciated that, unless expressly stated otherwise, certain features of the subject matter of the present disclosure described in the context of separate embodiments for clarity may also be provided in combination in a single embodiment. Conversely, various features of the subject matter of the present disclosure described in the context of a single embodiment for brevity may also be provided individually or in any suitable sub-combination.

[0099] In embodiments of the presently disclosed subject matter, the comparison may be performed Figures 3 to 5 The stages shown in FIG. 1 may be fewer, more, and / or different stages. In embodiments of the subject matter of the present disclosure, the steps may be performed in a different order. Figures 3 to 5 One or more of the stages shown in the figure and / or one or more groups of stages may be performed simultaneously. Figure 2 A general schematic diagram of a system architecture according to an embodiment of the disclosed subject matter is shown. Figure 2 Each module in may be comprised of any combination of software, hardware, and / or firmware that performs the functions as defined and explained herein. Figure 2 The modules in the system may be concentrated in one location or dispersed in more than one location, as described in detail herein. In other embodiments of the subject matter of the present disclosure, the system may include more Figure 2 There may be fewer, more, and / or different modules shown in FIG.

[0100] Any reference to a method in the specification shall apply mutatis mutandis to a system capable of performing the method and shall apply mutatis mutandis to a non-transitory computer-readable medium storing instructions which, once executed by a computer, result in the performance of the method.

[0101] Any references to a system in the specification shall apply mutatis mutandis to a method that may be performed by the system and shall apply mutatis mutandis to a non-transitory computer-readable medium storing instructions that may be performed by the system.

[0102] Any reference to a system in the specification shall apply mutatis mutandis to a system capable of executing instructions stored in a non-transitory computer readable medium, and shall apply mutatis mutandis to a method executable by a computer reading the instructions stored in a non-transitory computer readable medium.

[0103] With this in mind, turn your attention to Figure 1 , which is a schematic diagram of an operating environment for a system for extracting insights from the behavior of non-human animals in accordance with the presently disclosed subject matter.

[0104] According to the disclosed subject matter, using an animal monitoring device 12 (such as Sure Petcare's (hereinafter referred to as "Animo")) monitors non-human animals 10 (such as pets, including dogs and cats, but not limited thereto). For example, the animal monitoring device 12 can be attached to the animal's collar (as shown in the figure), or in any other way that enables the animal monitoring device 12 to collect data that enables the behavior of the non-human animal to which it is attached to be characterized over time. It should be noted that although the animal monitoring device 12 is attached to the non-human animal 10 in the figure, in some cases, the animal monitoring device 12 can be a device that does not need to be attached to the non-human animal 10. One example is a monitoring device that utilizes an external camera that can monitor the animal's environment in order to identify the animal and characterize its behavior over time. Other examples of non-wearable monitoring devices include connected feeding and drinking stations, microphones (which can identify sounds made by non-human animals 10, such as barking, howling, etc.), scales, gates, etc., each of which can be used to characterize the behavior of the non-human animal 10. It should be noted that in some cases, a combination of wearable and non-wearable devices can be used to determine behavior.

[0105] As indicated herein, the animal monitoring device 12 is configured to characterize the behavior of the non-human animal 10 monitored thereby over time. Some exemplary behaviors that the animal monitoring device 12 may identify include: shivering, grooming, scratching, resting, sleeping, high activity, medium activity, low activity, barking, calorie burning, walking, running, sitting, lying down, jumping, chewing, sniffing, licking, etc. and combinations thereof. However, it should be noted that the animal monitoring device 12 may be configured to identify only a portion of these behaviors, additional behaviors above the behaviors listed above, or combinations thereof.

[0106] In some cases, animal monitoring device 12 may include a three-dimensional (3D) accelerometer, and in such cases, behaviors may be identified by analyzing data acquired by the 3D accelerometer, as each behavior has a corresponding manifestation in the acquired acceleration data.

[0107] Animal monitoring device 12 may optionally also include a location-determining device (not shown), such as a Global Navigation Satellite System (GNSS) receiver, or any other device capable of determining the geographic location of animal monitoring device 12. Using the location-determining device, animal monitoring device 12 may track the location of non-human animals 10 monitored thereby over time.

[0108] In some cases, the animal monitoring device 12 may also measure (using various sensors) and optionally monitor biometric and other information associated with the non-human animal 10, such as temperature, hormone levels, blood oxygen, electrocardiogram (ECG) data, food and / or water intake, urine output, blood pressure, other blood chemistries (such as electrolytes), respiratory rate, heart rate, deoxyribonucleic acid (DNA) data, facial recognition data, etc. It should be noted that in some alternative or additional cases, all or part of the biometric material may be measured and monitored by sensors included in another device (not shown) other than the animal monitoring device 12. Such other device may also optionally be attached to the non-human animal 10 in various ways (e.g., attached to a collar of the non-human animal 10).

[0109] In some cases, animal monitoring devices 12 are located outside of system 100, which is a separate entity that is communicatively connected to the animal monitoring devices. In this case, information related to the behavior of each non-human animal 10 and position information (hereinafter referred to as "position information") determined using a positioning determination device are sent to system 100. However, in some cases, system 100 can be part of animal monitoring devices 12, so that each animal monitoring device or some of the animal monitoring devices in animal monitoring devices 12 is an independent unit capable of performing the operations of system 100, as described in detail herein.

[0110] In those cases where the animal monitoring device 12 is external to the system 100, the transmission may be directly from the animal monitoring device 12 to the system 100 (e.g., when the animal monitoring device 12 has internet connectivity). Alternatively, the information about the behavior and, optionally, the location information of each non-human animal 10 may be transmitted indirectly from the animal monitoring device 12 to the system 100. In these cases, the information about the behavior and, optionally, the location information of each non-human animal 10 may be transmitted from the animal monitoring device 12 to an intermediate device (e.g., any device with internet connectivity, including, for example, a smartphone), from which the information is transmitted to the system 100. The information about the behavior and, optionally, the location information of each non-human animal 10 may be transmitted from the animal monitoring device 12 to the intermediate device via a short-range connection, such as a Bluetooth Low Energy (BLE) connection. This configuration supports lower energy consumption of the animal monitoring device 12, which in turn enables longer recharging cycles thereof.

[0111] The system 100 is configured to extract insights (such as one or more of: identifying behavioral patterns, identifying behavioral baselines, identifying connections between behaviors, identifying the condition / health of the animal, or identifying behavioral anomalies) from the behavior of the non-human animal 10 by analyzing the behavior of the non-human animal 10 as determined by the animal monitoring device 12 (optionally together with location information), and as described herein, in particular with reference to Figure 3 Once an insight that action is required (such as when an anomaly is identified in the behavior of the non-human animal 10), the system 100 can be configured to perform an action, such as triggering an alert to a caregiver of the non-human animal 10 in question (such as its owner and / or its veterinarian and / or its trainer). The alert can be provided to the caregiver via an animal caregiver device 15, such as a smartphone, personal computer, laptop, smart watch, or any other type of device by which an alert can be provided to the caregiver of the non-human animal.

[0112] Additionally, or alternatively, the system 100 can be configured to monitor the effectiveness of an intervention (such as behavior modification or treatment), for example, in response to a health condition (note that the health condition can be a physical health condition, such as itching, etc., or a mental health condition, such as anxiety) or abnormal behavior of the non-human animal 10, as described herein, in particular with reference to Figures 4 to 5 For example, when an abnormality is identified (e.g., based on analysis of the behavior of the non-human animal 10), in many cases the abnormality has a cause. The cause of the abnormality can be, for example, itching, heart problems, neurological problems, obesity, diabetes, separation anxiety, arthritis, musculoskeletal problems, etc. When the cause of the abnormality is identified, in many cases the non-human animal 10 receives treatment, such as medication, anti-parasitic products (e.g., Fluralaner formulations such as Merck Animal Health's ) or other types of intervention. Such intervention (such as behavior modification or treatment) should gradually or, in some cases, immediately stop the abnormality in the behavior of the non-human animal 10. The system 100 can analyze the behavior of the non-human animal 10 after the intervention and verify whether the behavior of the non-human animal 10 gradually decreases or immediately stops being abnormal after the intervention (e.g., after providing treatment or at least prescribing it).

[0113] In some cases, when the intervention does not show the expected effect (e.g., gradually reduce or immediately stop the abnormality), the system 100 can perform actions, such as triggering an alarm to the caregiver of the non-human animal 102 (such as its owner and / or its veterinarian and / or its trainer). The alarm can be provided to the caregiver via an animal caregiver device 15, such as a smart phone, personal computer, laptop, smart watch, or any other type of device through which an alarm can be provided to the caregiver of the non-human animal 10.

[0114] In some cases, the system 100 may enable communication between an owner of a non-human animal 10 and other entities, such as a veterinarian of the non-human animal 10 or veterinary clinic staff. For example, an owner of a non-human animal 10 may add a note via a suitable device, such as a smartphone, a personal computer, a laptop, a smartwatch, or any other type of device on which an application supporting uploading of such notes is installed. Such notes may be sent to a veterinarian of the non-human animal 10 via a suitable device, such as a smartphone, a personal computer, a laptop, a smartwatch, or any other type of device on which an application supporting receiving such notes is installed. Additionally, or alternatively, the veterinarian of the non-human animal 10 may send information, such as notes, prescriptions, reminders, etc., to the owner of the non-human animal 10. In more general cases, the system 100 may enable communication between various animal caregiver devices 15, such as an animal caregiver device 15 of a veterinarian of the non-human animal 10 or veterinary clinic staff, and an animal caregiver device 15 of an owner of a non-human animal 10.

[0115] The system 100 may additionally or alternatively generate reports and various recommendations, such as training or dietary recommendations. The system 100 may optionally utilize additional equipment for these purposes, including, for example, bowl / water consumption information of the non-human animal 10 obtained from a suitable bowl of the non-human animal 10 that can monitor food and / or water consumption. The system 100 may also optionally assist a trainer of the non-human animal 10 in understanding the historical behavior of the non-human animal 10 and optionally create a recommendation / training plan for the non-human animal 10. In some cases, the system 100 may also track the results and achievements of the training plan and optionally adjust it accordingly.

[0116] Having described the operating environment of system 10, attention is turned to Figure 2 , which is a block diagram schematically illustrating one example of a system for extracting insights from the behavior of non-human animals according to the presently disclosed subject matter.

[0117] According to the disclosed subject matter, system 100 includes processing circuitry 130. Processing circuitry 130 may be one or more processing units (e.g., central processing units), microprocessors, microcontrollers (e.g., microcontroller units (MCUs)), or any other computing device or module, including multiple and / or parallel and / or distributed processing units, suitable for independently or collaboratively processing data to control relevant system 100 resources and implement operations related to the resources of system 100.

[0118] The processing circuit 100 may include an insight identification module 140 and / or an intervention effect monitoring module 150. The insight identification module 140 is configured to extract insights from the behavior of non-human animals (such as pets, including dogs, cats, etc.), as particularly referred to herein. Figure 2 The intervention effect monitoring module 150 is configured to monitor the effect of the intervention on the behavior of the non-human animal, as described herein, in particular with reference to Figure 3 and Figure 4 Further detailed.

[0119] The system 100 may also include a network interface 110 (e.g., a network card, a WiFi client, a LiFi client, a 3G / 4G client, or any other component) that enables the system 100 to communicate with various systems over a network, such as external systems that can provide the system 100 with behavioral data characterizing the behavior of one or more non-human animals over time, and optionally provide location data indicating the location of the non-human animals over time. An example of such an external system is an animal monitoring device 12, such as Sure Petcare's It should be noted that in some cases, animal monitoring devices 12 (such as Sure Petcare's ) can provide behavioral data, and optionally location data, to the system 100 directly (via a network connection such as WiFi or cellular communications) or indirectly via a user device such as a smartphone, laptop, smart speaker, smart watch, etc., to which the animal monitoring device 12 can be connected via a relatively short-range connection such as Bluetooth Low Energy (BLE). On the other hand, in other cases, the system 100 can be independent of any external system in that it can be incorporated into an animal monitoring device 12 such as Sure Petcare's ) (and in this case it may not require a network interface, or a relatively short-range connection such as Bluetooth Low Energy (BLE) may be sufficient).

[0120] The system 100 may also include or be otherwise associated with a data repository 120 (e.g., a database, a storage system, a memory including a read-only memory - ROM, a random access memory - RAM, or any other type of memory, etc.), which is configured to store data, for each non-human animal 10 being monitored, optionally including, among other things: the breed of the non-human animal 10, the age of the non-human animal 10, the gender of the non-human animal 10, medical information of the non-human animal 10 (previous illnesses, medications received, etc.), special notes related to the non-human animal 10, dislikes, the name of the non-human animal 10, reports generated for the non-human animal 10, information about the monitoring device attached to the non-human animal 10 (such as the hardware / firmware / software version of the device, etc.), information about the past behavior of the non-human animal 10 (such as shivering, grooming, scratching, resting, sleeping, high activity, medium activity, low activity, barking, calorie burning, walking, running, sitting, lying down, jumping, chewing, sniffing, licking, etc.), behavioral baselines defining expected normal behavior of the non-human animal 10, information of the caregiver of the non-human animal 10 (e.g., the animal's owner, the animal's veterinarian, the animal's trainer, etc.), information of the medical condition of the non-human animal 10 (allergies, heart problems, neurological problems, diabetes, obesity, musculoskeletal problems, etc.), successful intervention behavioral baselines defining expected changes in the behavior of the non-human animal 10 over time after intervention (such as behavior modification or treatment) when behavioral abnormalities (e.g., abnormal behavior patterns, abnormal combinations of behaviors, etc.) are identified, location information indicating the location of the non-human animal 10 over time, etc. The data repository 120 may also be configured to enable retrieval and / or updating and / or deletion of the stored data. Note that in some cases, data repository 120 may be distributed, and system 100 may access information stored thereon, for example, via a wired or wireless network to which system 100 is connected (eg, via its network interface 110 ).

[0121] Now turn your attention to Figure 3 , which is a flow chart illustrating one example of a sequence of operations performed for extracting insights from the behavior of non-human animals in accordance with the presently disclosed subject matter.

[0122] According to some examples of the disclosed subject matter, system 100 can be configured to perform insight identification process 200 , such as using insight identification module 140 .

[0123] To this end, system 100 may be configured to provide a behavioral baseline that includes information about normal behavior of non-human animal 10 over a given period of time when no abnormalities have occurred (block 210 ).

[0124] As indicated herein, the animal monitoring device 12 is configured to characterize the behavior of the non-human animal 10 monitored thereby over time. For example, 3D accelerometer data may be acquired continuously and analyzed in time windows (e.g., every three / five / ten seconds) in order to determine the behavior of the animal during the analyzed time period. Some exemplary behaviors that may be identified by the animal monitoring device 12 include: shivering, grooming, scratching, resting, sleeping, high activity, medium activity, low activity, barking, calorie burning, walking, running, sitting, lying down, jumping, chewing, sniffing, licking, etc. This information may be used in order to create a behavioral baseline, e.g., as further detailed herein (while noting that the behavioral baseline may alternatively be determined in other ways, or it may be received from another system).

[0125] It should be noted that in some cases, the behavioral baseline can be associated with a subset of one or more of the available behaviors (available to the system 100), or a combination of some or all of the available behaviors. Thus, a baseline can be provided for a single behavior (e.g., a sleep baseline (sleep can be defined, for example, by a sleep score), a scratching baseline, a shivering baseline, etc.) or a combination of behaviors (e.g., a sleep and shivering baseline, a sleep and scratching baseline, etc.). It should be noted that in this case, when no abnormalities occur that may affect these behaviors, the behavioral baseline will be constructed based on information associated with such a subset of behaviors (while other abnormalities that do not affect those behaviors may occur because they will not affect the baseline based on behaviors not affected by such abnormalities).

[0126] It should also be noted that the baseline may vary depending on the time of day, season, type of activity performed by the animal (sleeping, barking, running), different time periods covered by the baseline (e.g., 1 hour, 12 hours, 24 hours, one week, one month, one year, etc.). In some cases, multiple baselines may exist and be used depending on the time of day (e.g., daytime baseline and nighttime baseline), season (summer baseline, winter baseline, spring baseline, and fall baseline), type of activity performed by the animal (barking baseline, sleeping baseline, running baseline, etc.), etc.

[0127] The behavioral baseline may be an animal-specific behavioral baseline determined using baseline creation data that includes a baseline series of consecutively identified baseline behaviors of the non-human animal identified over a time period during which the non-human animal is believed to be behaving normally (i.e., it is not sick, not suffering from an itch, etc.). In other words, system 100 may determine a behavioral baseline using information about the behavior of non-human animal 10 over a given time period as determined using information acquired by animal monitoring device 12. As indicated herein, it is noted that the behavioral baseline may be determined in other ways (e.g., the behavioral baseline may be determined based on human observations of the animal), or a combination of data from animal monitoring device 12 and human observations may be used to obtain and or improve the baseline.

[0128] Note that in some cases, the behavioral baseline may be a general baseline determined for a group of non-human animals 10 rather than for a specific animal. The group may be non-human animals of the same breed / type / size / etc.

[0129] Furthermore, in some cases, system 100 may use a general baseline for newly monitored non-human animals 10, and may refine such baseline as specific behavioral data is collected by animal monitoring device 12 attached to the newly monitored non-human animal 10. More generally, it is noted that in some cases, the behavioral baseline may be updated or refined over time as more data is collected by animal monitoring device(s) 12. It is noted that this may be necessary because the behavioral patterns of non-human animals may change between seasons, as they age, due to injuries, etc.

[0130] It should be noted that in some cases, various parameters may have an impact on the expected behavioral baseline, such as the location of the non-human animal 10 (city / town / rural / village), the age of the non-human animal 10, the age of the owner of the non-human animal 10, etc. In such cases, multiple general baselines (which are not animal-specific) may exist, and a particular non-human animal 10 may be associated with a selected baseline based on the relevant parameters.

[0131] For each normal behavior, the information about the normal behavior included in the behavioral baseline may include: (a) an indication of the type of behavior (e.g., the name of the behavior, a graph indicating the type of behavior, a digital signal characterizing the type of behavior, or any other data that enables the behavior to be distinguished from other behaviors), and (b) one or more of the following: (i) a normal frequency range for the behavior (e.g., the number of times the behavior can be expected to be seen during a given time period), (ii) a normal duration range for the behavior (e.g., how long the behavior can be expected to last), (iii) a normal intensity range for the behavior (e.g., how intense the behavior can be expected), (iv) a normal score range for scores calculated for the behavior (e.g., a score range for sleep scores calculated for non-human animals 10), (v) a normal time window during which the behavior is expected to occur, etc.

[0132] As a specific example, a behavioral baseline may define that a non-human animal10 is expected to sleep between 8-11 hours, rest between 4-6 hours, groom between 15-45 minutes, shiver between 10-20 minutes, scratch between 20-40 minutes, be at high activity between 30-60 minutes, be at medium activity between 45-90 minutes, be at low activity between 1-3 hours, and eat between 10-30 minutes, all within a 24 hour period. As a further example, a behavioral baseline may also define normal grooming and scratching intensity ranges, frequencies, and durations.

[0133] For example, a behavioral baseline may also define the normal duration of each occurrence of one or more behaviors, such as scratching. Thus, a baseline may define that scratching occurs between 20-40 minutes during a 24-hour period, whereas each single scratching behavior that occurs during a 24-hour period occurs continuously for between 5-45 seconds.

[0134] The behavioral baseline may also define a range of sleep scores calculated for sleep behavior between 75-85 points out of 100. It is noted that the sleep score may be determined based on a measure of the duration and frequency of behaviors that may be associated with interruptions to sleep and a measure of the duration of uninterrupted sleep (generally, the longer the duration of uninterrupted sleep, the higher the sleep score). It is noted in this regard that the sleep score enables abnormalities to be highlighted because the behavior of the non-human animal 10 is expected to change less frequently than during the day when the non-human animal 10 is more active, assuming that the non-human animal 10 does not have a medical condition that requires intervention. If the non-human animal 10 does not have a medical condition that requires intervention, it is expected to be less active during sleep time, and its behavior is expected to be quiet or less interrupted (in a sense that it is not expected to be subject to many interruptions caused by grooming or shivering), and if the non-human animal 10 is more active than usual during these times (e.g., shivering and / or grooming more than usual), it may enable the identification of a medical condition that requires intervention.

[0135] The system 100 is also configured to obtain data regarding a series of continuously identified behaviors of the non-human animal 10 identified during a second time period that is not the time period based on which the behavioral baseline is determined (if determined) (block 220). The continuously identified behaviors may be determined based on an analysis of three-dimensional (3D) accelerometer data acquired by a 3D accelerometer included in an animal monitoring device 12 attached to the non-human animal 10.

[0136] The series of consecutive identified behaviors may be analyzed to determine whether the series of consecutive identified behaviors conform to a behavioral baseline, and if they do not conform to the behavioral baseline, the system 100 is configured to perform an action, thereby providing insights associated with the behavior of the non-human animal (e.g., indicating an abnormality in the behavior of the non-human animal 10) (block 230). The action may trigger an alert to a caregiver of the non-human animal 10, such as an owner of the non-human animal 10 and / or a veterinarian of the non-human animal 10 and / or a trainer of the non-human animal 10.

[0137] In some cases, an alert may be provided to the owner of the non-human animal 10, suggesting a visit to a veterinarian. In some cases, the owner or caregiver of the non-human animal may contact a veterinarian based on the owner's review of the alert from the system. Using the system 100, the veterinarian may view objectively monitored data, rather than just the (subjective) description of the owner of the non-human animal 10, which may be very helpful to the veterinarian.

[0138] In this regard, it is noteworthy that currently veterinarians do not have the ability to identify abnormalities in the behavior of non-human animals 10, except by being notified by the owner of the non-human animal 10, such as through traditional written or verbal sources (or in those cases where the veterinarian can observe the non-human animal 10). Being able to be provided with information about abnormalities in the behavior of non-human animals 10 treated by a veterinarian (note that when a veterinarian is mentioned herein, it is not necessarily limited to a specific veterinarian, but rather it can be any veterinarian from a clinic that treats non-human animals 10) is very important and can result in saving the life of the non-human animal 10, preventing (or at least reducing) undue suffering of the non-human animal 10, etc. This is emphasized given that abnormalities in the behavior of the non-human animal 10 can be identified even before it is noticed by the owner of the non-human animal 10. It should also be noted that providing veterinary clinics and / or veterinarians with information that can promote proactiveness of the veterinary clinics and / or veterinarians (e.g., by inviting owners of non-human animals 10 to examine the non-human animals 10, etc.) provides the veterinary clinics and / or veterinarians with added value that is perceived by their clients (owners of non-human animals 10).

[0139] In addition, and although not shown in the figures, a veterinary clinic in which one or more veterinarians are providing treatment to multiple non-human animals 10 may find great value in being able to obtain detailed reports on the behavior of the non-human animal(s) 10 being treated in the veterinary clinic. Having such reports may enable better monitoring of the medical condition of the non-human animal(s) 10, which may enable the clinic to proactively identify abnormalities that require intervention, etc. Reports may be provided for various segments of the non-human animals 10, such as for non-human animal(s) 10 treated by a particular veterinarian, for non-human animal(s) 10 that meet particular conditions (such as age, sex, location, etc.), for non-human animal(s) 10 that exhibit a particular behavior or combination of behaviors, etc. In some cases, reports may be generated based on data acquired during a selected time period (e.g., during the past 24 hours, during the past week, during the past month, etc.), and in some cases, the reports may show trends in various behaviors over such time periods. It will be appreciated that the system 100 can be configured to generate any of the above-described reports or any other reports based on data (including location data) obtained by an animal monitoring device 12 attached to the non-human animal 10 and / or data obtained by other devices (such as a bowl of the non-human animal 10 that can monitor food and / or water consumption, a tracking device that monitors the animal's location, an implant that monitors the animal's biometric data, animal data from a database or the like, etc.).

[0140] It should be noted that such reports can be provided through a communication link between the output of the system 100 and the veterinary practice management software and hardware. This can link the output to the medical record of the non-human animal 10 at the veterinary clinic and facilitate communication with the veterinary clinic personnel.

[0141] It should be further noted that some reports may enable various comparisons between different non-human animal 10 populations, such as a comparison between a "normal" non-human animal 10 population (which has not been diagnosed as having any disease) and a population of non-human animals 10 suffering from itching for various reasons, or a comparison between a population of non-human animals 10 suffering from a particular disease and a population of non-human animals 10 suffering from itching for various reasons.

[0142] Returning to and continuing the example provided herein, in order to determine whether the series of continuously identified behaviors of the non-human animal 10 conforms to the behavioral baseline, the time spent by a given animal during the second time period for each type of behavior can be summarized (as indicated by the series of continuously identified behaviors obtained at block 220) and compared with the corresponding expected range. If the time spent by the animal for each type of behavior is not within the expected range based on the behavioral baseline, an abnormality is identified. Similarly, for each behavior associated with the expected intensity range of the behavioral baseline, any deviation from the expected intensity range can be identified as an abnormality. In addition, when the baseline defines a sleep score range, the actual sleep score calculated for the non-human animal 10 can be compared thereto, and when the sleep score calculated for the non-human animal 10 deviates from the sleep score range, an abnormality is identified.

[0143] It is important to note that use of the insight identification process 200 enables a reduction in the time required to identify insights (including early detection of health conditions / abnormalities in the behavior of the non-human animal 10) because in many cases, caregivers of the non-human animal 10 are unable to notice a change in behavior until the change in behavior is much more significant than a change in behavior that could be identified by the system 100 as an insight (e.g., an abnormality).

[0144] In one particular study, staff at a veterinary clinic chose to call a dog owner after observing unusual scratching or shivering alerts over multiple days (provided to the staff via system 100). This enabled the staff to gain insights that might otherwise have been missed without having that essential information provided to them via system 100.

[0145] In some cases, the system 100 is also configured to analyze the data obtained at block 220 to determine a cause of an insight (e.g., a cause of an identified abnormality) (block 240). Some exemplary causes of abnormalities identified as insights may include one or more of: skin diseases (such as allergies / atopic dermatitis), ear infections, parasitic infestations (scratching, grooming, shivering, decreased sleep scores), obesity (objective control of activity and feeding), diabetes (decreased sleep scores), separation anxiety (increased barking), arthritis and other problems of the musculoskeletal system (changes in activity patterns), or any pathological changes that affect any physiological activity of the non-human animal 10.

[0146] It will be appreciated that different causes of abnormalities will manifest themselves in different ways in the behavioral data of the non-human animal 10. For example, pruritus will result in a certain type of abnormality (such as lower than expected sleep scores, excessive scratching, increased nighttime grooming, some combination, etc.), while arthritis will result in another type of abnormality (such as lower than expected high activity). The type and nature of the pruritus or arthritis identified can further assist the veterinarian in assessing the possible underlying causes of the pathological condition(s).

[0147] In the event that the system 100 determines a factor or possible underlying cause that led to an insight (e.g., a cause of an identified abnormality), the alert provided to the caregiver of the non-human animal 10 may include an indication of the cause of the insight, which the caregiver may use to monitor the non-human animal 10, treat the non-human animal 10, consult with a veterinarian, etc.

[0148] In some cases, the system 100 can utilize location information obtained by the animal monitoring device 12 (and more specifically by the location determination device) to provide evidence for a potential cause of an insight. For example, if the non-human animal 10 is located in a known flea risk area, the cause of the insight can be identified as flea infestation. As another example, if the owner of the non-human animal 10 is not taking it for a walk, or has changed its walking routine, the cause of the anomaly can be identified as a missed walk or a changed walking routine. It should be noted that these are merely examples, and location can also be used to determine the cause of the insight in other ways.

[0149] It is also important to note that in some cases, if the location information can be used to explain the insight, the system 100 can be configured to not perform the action at block 230 because there may be no need to provide an alert to the caregiver of the non-human animal 10. For example, if the non-human animal 10 takes a longer walk than usual, which results in an anomaly in the behavior of the non-human animal 10 (e.g., excessive resting during a certain period of time after such a walk) - there may be no need to alert the caregiver of the anomaly because it can be explained by the longer than usual walk.

[0150] In some cases, the system 100 may also be configured to provide one or more abnormality prevention recommendations to a caregiver of the non-human animal 10 based on historical behavioral data associated with the non-human animal 10 (block 250). Thus, if analysis of past behavioral data of the non-human animal 10 indicates that the non-human animal 10 suffers from allergies at certain times of the year (e.g., during the spring), the system 100 may provide abnormality prevention recommendations to the caregiver to initiate preventive interventions (such as behavioral modification or therapy) to prevent allergies at the appropriate time (e.g., at the beginning of spring). It should be noted that in some cases, block 250 may be performed separately and independently of the insight identification process 200.

[0151] In some cases, historical behavioral data associated with non-human animal 10 may be used to adapt the behavioral baseline to past changes in the behavior of non-human animal 10 over time. For example, if non-human animal 10 sleeps more during the winter, the baseline may be adjusted to reflect the fact that non-human animal 10 sleeps more during the winter than during the summer.

[0152] It should also be noted that reference Figure 3 , some blocks may be integrated into one merged block, or may be broken down into several blocks and / or other blocks may be added. In addition, in some cases, the blocks may be executed in an order different from that described herein. It should also be noted that some blocks are optional. It should also be noted that although the flow charts are also described with reference to the system elements that implement them, this is by no means restrictive, and the blocks may be executed by elements other than those described herein.

[0153] Go to Figure 4 , shows a flow chart illustrating one example of a sequence of operations performed for monitoring the effects of an intervention (such as behavior modification or therapy) on a non-human animal in accordance with the presently disclosed subject matter.

[0154] According to certain examples of the subject matter of the present disclosure, system 100 can be configured to perform intervention (such as behavior modification or treatment, including medical treatment and / or changed diet, and / or more exercise, etc.) effect monitoring process 300, for example using intervention effect monitoring module 150.

[0155] To this end, system 100 may be configured to provide a behavior baseline (block 310 ) that includes normal behavior information about non-human animal 10 over a given time period in which no abnormalities in the behavior of non-human animal 10 occur, similar to the behavior baseline discussed with reference to block 210 .

[0156] The system 100 is also configured to obtain information about a series of continuously identified behaviors of the non-human animal 10 identified within a second time period after intervention is provided to the non-human animal 10 (block 320), similar to the information about a series of continuously identified behaviors of the non-human animal 10 discussed with reference to block 220, except that the series of continuously identified behaviors of the non-human animal 10 in block 320 are identified within a time period after intervention is provided to the non-human animal 10.

[0157] As can be appreciated, when an intervention is provided to a certain non-human animal 10, it is expected to have a positive impact on the abnormality in the behavior of the non-human animal 10. Therefore, the system 100 can be configured to perform an action (block 330) when the trend of one or more parameters calculated based on the information obtained at block 320 has not converged to the behavioral baseline provided at block 310. The action can be to trigger an alarm to the caregiver of the non-human animal 10 (such as the owner of the non-human animal 10 and / or the veterinarian of the non-human animal 10 and / or the trainer of the non-human animal 10). If necessary, such an alarm can enable the intervention to be adjusted or additional or alternative interventions (e.g., alternative treatments) to be provided to the non-human animal 10.

[0158] It is noted that the behavioral baseline may be animal specific, or it may be a generic behavioral baseline that may optionally be determined using expert estimates. In some cases, a variety of generic baselines may exist, each of which may be associated with a set of parameters, such as specific breed(s), specific age range(s), specific animal size(s), specific medical diagnosis, etc. In such cases, a specific non-human animal 10 may be associated with a selected generic baseline that is selected from a collection of available baselines based on a match between the parameters of the specific non-human animal 10 and the parameters of the baselines in the collection.

[0159] It should be noted that in some cases, it may not be possible to obtain an animal-specific baseline (e.g., for an animal that is new to using Animo). In this case, the intervention effect monitoring process 300 can still be performed using a general behavioral baseline, or even without using a baseline, simply by ensuring that a positive trend can be observed from the information obtained at block 320.

[0160] It is also important to note that the reference Figure 4 , some blocks may be integrated into one merged block, or may be broken down into several blocks and / or other blocks may be added. It should also be noted that although the flow charts are also described with reference to system elements implementing them, this is by no means restrictive, and the blocks may be executed by elements other than those described herein.

[0161] Figure 5is another flow chart illustrating another example of a sequence of operations performed for monitoring the effects of an intervention on a non-human animal in accordance with the presently disclosed subject matter.

[0162] According to some examples of the disclosed subject matter, system 100 can be configured to perform another intervention effect monitoring process 400, such as using intervention effect monitoring module 150. A veterinarian or animal health provider will determine the specific details of the intervention, and system 100 can then objectively measure the implementation and results of the intervention.

[0163] To this end, the system 100 can be configured to provide a successful intervention behavior baseline (block 410) that includes information about the normal behavior of the non-human animal 10 over multiple time periods after providing an intervention (such as behavior modification or treatment, including medical treatment and / or a modified diet, and / or more exercise, etc.) to address one or more causes of abnormality in the behavior of the non-human animal 10. It is important to note in this regard that a successful intervention is expected to result in a gradual improvement in the condition of the non-human animal over time until full recovery and return to normalcy. Thus, the successful intervention behavior baseline can define an expected pattern of improvement in behavioral changes that the non-human animal is expected to exhibit when a successful intervention is provided to the non-human animal.

[0164] Note that in some cases, multiple successful intervention behavior baselines may exist, each associated with a specific cause of abnormality in the behavior of the non-human animal 10. For example, a first successful intervention behavior baseline may be associated with pruritus, while a second successful intervention behavior baseline may be associated with arthritis.

[0165] It is important to note that different animals may respond differently to the same treatment. Thus, the successful intervention behavior baseline may be an animal-specific successful intervention behavior baseline determined using baseline creation data that includes a baseline series of continuously identified baseline behaviors of the non-human animal 10 identified over multiple time periods after providing an intervention (such as behavior modification or therapy) to address one or more causes of an abnormality in the non-human animal 10. In other words, the successful intervention behavior baseline may be determined by the system 100 using information of the behavior of the non-human animal 10 over each of the multiple time periods, as determined using information obtained by the animal monitoring device 12. As indicated herein, it is important to note that the successful intervention behavior baseline may be determined in other ways (e.g., the successful intervention behavior baseline may be determined based on human observations of the non-human animal 10 or a combination of human observations and monitoring data).

[0166] Note that in some cases, the successful intervention behavior baseline may be a general baseline determined for a group of non-human animals 10 rather than for a specific animal. The group may be non-human animals of the same breed / type / size / etc.

[0167] In addition, in some cases, the system 100 may use a general successful intervention behavior baseline for a newly monitored non-human animal 10, and after providing intervention (such as behavior modification or therapy) to address one or more causes of abnormalities in the behavior of the non-human animal 10, if the intervention is successful, such baseline may be improved when specific behavioral data is collected by the animal monitoring device 12 attached to the newly monitored non-human animal 10 (because the successful treatment behavior baseline is required to reflect improvements in behavior when successful intervention is provided).

[0168] For each normal behavior in each time period, the information about the normal behavior included in the successful intervention behavior baseline may include: (a) an indication of the type of behavior (e.g., the name of the behavior, a description of the behavior, a graph indicating the type of behavior, a digital signal characterizing the type of behavior, or any other data that enables the behavior to be distinguished from other behaviors), and (b) one or more of the following: (i) a normal frequency range for the behavior during the corresponding time period (e.g., the number of times the behavior can be expected to be seen during the corresponding time period after the intervention), (ii) a normal duration range for the behavior during the corresponding time period (e.g., how long the behavior can be expected to last during the corresponding time period), (iii) a normal intensity range for the behavior during the corresponding time period (e.g., how intense the behavior can be expected during the corresponding time period), and (iv) a normal score range for the behavior calculated for the corresponding time period (e.g., a score range for the sleep score calculated for the corresponding time period for the non-human animal 10).

[0169] As a specific example, a successful intervention behavioral baseline may define that a non-human animal 10 is expected to sleep between 6-9 hours, rest between 3-4 hours, groom between 1-2 hours, shiver between 1-2 hours, scratch between 1-2 hours, be high activity for 20-40 minutes, be moderate activity for 1-2 hours, be low activity for 2-4 hours, and eat for 10-20 minutes, all during the first 24 hours after the intervention, during the first 24 hours after the intervention. The successful intervention behavioral baseline may also define a normal range of grooming and scratching intensities for the 24 hours.

[0170] A successful intervention behavior baseline may also define the normal duration of each occurrence of one or more behaviors, such as scratching. Thus, a successful intervention behavior baseline may define scratching to occur between 1-2 hours during a 24-hour period following intervention, whereas each scratching behavior that occurs during the 24-hour period occurs continuously for between 10-90 seconds.

[0171] The successful intervention behavior baseline may also define a sleep score range calculated for sleep behavior during the first 24 hours after the intervention, such as 60-75 out of 100. Note that the sleep score may be determined based on measurements of duration and frequency of behaviors that may be associated with interruptions of sleep, as well as measurements of duration of uninterrupted sleep (such that the longer the duration of uninterrupted sleep, the higher the sleep score).

[0172] Continuing with this example, a successful intervention behavioral baseline may define that over the next 24 hours after the intervention (i.e., 24 to 48 hours after the intervention), the behavior of a particular non-human animal 10 is expected to show improvement over the first 24 hours after the intervention. Sleeping is expected to be between 8-11 hours, resting is between 4-6 hours, grooming is between 15-45 minutes, shivering is between 10-20 minutes, scratching is between 20-40 minutes, high activity is between 30-60 minutes, moderate activity is between 45-90 minutes, low activity is between 1-3 hours, and eating is between 10-30 minutes, all during the first 24 hours after the intervention. A successful intervention behavioral baseline may also define a normal grooming and scratching intensity range for those next 24 hours, which may be expected to be lower than the normal grooming and scratching intensity range for the first 24 hours. In addition, a successful intervention behavior baseline can be defined as during those next 24 hours (i.e., 24 to 48 hours after the intervention), scratching behavior occurs within 0.5-1.5 hours, but each scratching behavior that occurs during this time period occurs continuously between 5-60 seconds. A successful intervention behavior baseline can also be defined as a sleep score range calculated for sleep behavior during the next 24 hours (i.e., 24 to 48 hours after the intervention) that is expected to be between 70-85 points out of 100.

[0173] It should be noted that although only two time periods are provided for the successful intervention behavior baseline in the above example, this is by no means limiting, and the successful intervention behavior baseline may include more than two time periods.

[0174] The system 100 is also configured to obtain information about a series of consecutive identified behaviors of the non-human animal identified within a given time period after providing an intervention (e.g., behavior modification or treatment) related to itch relief to the non-human animal (block 420). The consecutive identified behaviors may be determined based on an analysis of three-dimensional (3D) accelerometer data acquired by a 3D accelerometer included in an animal monitoring device 12 attached to the non-human animal 10.

[0175] The series of consecutively identified behaviors may be analyzed to determine whether the series of consecutively identified behaviors of the non-human animal during a time period in the time period corresponding to the given time period do not meet the successful intervention behavior baseline, and if they do not meet the successful intervention behavior baseline, the system 100 is configured to perform an action, thereby indicating that the intervention was not performed as expected (block 430). The action may trigger an alarm to a caregiver of the non-human animal 10, such as the owner of the non-human animal 10 and / or a veterinarian of the non-human animal 10 and / or a trainer of the non-human animal 10.

[0176] Continuing with the example provided herein, in order to determine whether a series of continuously identified behaviors of a non-human animal 10 conforms to a successful intervention behavior baseline, the time spent by a given animal during each of a plurality of time periods exhibiting each type of behavior may be summarized (as indicated by the series of continuously identified behaviors obtained at block 220) and compared to the corresponding expected range for the corresponding time period. If the time spent by the animal in each relevant behavior classification is not within the expected range for the corresponding time period, the intervention was not performed as expected. Similarly, for each behavior associated with the expected intensity range of the successful intervention behavior baseline, any deviation from the expected intensity range at the corresponding time period may indicate that the intervention was not performed as expected. In addition, when the successful intervention behavior baseline defines a sleep score range for each time period, the actual sleep score calculated for the non-human animal 10 during the corresponding time period may be compared thereto, and when the sleep score calculated for the non-human animal 10 deviates from the sleep score range, insights indicating abnormalities and potential pathological conditions may be identified.

[0177] The successful intervention behavior baseline may be animal specific, or it may be a generic successful intervention behavior baseline that may optionally be determined using an expert's estimate of expected successful intervention outcomes. In some cases, a variety of generic successful intervention behavior baselines may exist, each of which may be associated with a set of parameters, such as specific breed(s), specific age range(s), specific animal size(s), specific medical diagnosis, etc. In such a case, a specific non-human animal 10 may be associated with a selected generic successful intervention behavior baseline that is selected from a collection of available successful intervention behavior baselines based on a match between the parameters of the specific non-human animal 10 and the parameters of the successful intervention behavior baselines in the collection.

[0178] It should be noted that in some cases, animal-specific baselines may not be available (e.g., for animals that are new to using Animo). In such cases, the intervention effectiveness monitoring process 400 may still be performed using a general successful intervention behavior baseline, or even without a baseline, simply by ensuring that a positive trend can be observed from the information obtained at block 420.

[0179] It is important to note that use of the intervention effectiveness monitoring process 300 and / or another intervention effectiveness monitoring process 400 can reduce the time required after treatment initiation to identify that an intervention provided to the behavior of a non-human animal 10 is not performing as expected because, in many cases, a caregiver of the non-human animal 10 is unable to notice behavioral changes that are expected to occur when the intervention is successful until those behavioral changes are much more pronounced than behavioral changes that the system 100 can identify as abnormal.

[0180] It should be noted that when any type of baseline is mentioned herein, the baseline can be a dynamic baseline calculated based on a specific time period (e.g., a specific number of days / weeks / months / etc.), which can optionally be a rolling time window during which the non-human animal 10 performs normally.

[0181] It is also important to note that the reference Figure 5 , some blocks may be integrated into one merged block, or may be broken down into several blocks and / or other blocks may be added. It should also be noted that although the flow charts are also described with reference to system elements implementing them, this is by no means restrictive, and the blocks may be performed by elements other than those described herein.

[0182] 6-9 illustrate exemplary graphical user interfaces (GUIs) presented to a dog's caregiver in accordance with the presently disclosed subject matter. Figure 6a A GUI is shown indicating that a dog named "Evya" suffers from excessive shivering (based on the Evya is a 16-year-old mixed-breed dog who suffers from recurrent otitis externa (inflammation of the ear). Figure 6b A GUI is shown showing the shivering measurements of Evya over a period of one month while Evya was being treated (based on the data collected by the collar attached to Evya). Device). As can be seen, Evya began intervention (medical treatment) on March 19, 2020, and by March 21, 2020, substantial improvement was recorded, indicating that Evya's shivering amount returned to normal levels at that time period. Prior to the improvement, during a 9-day period (marked by the dots above the measured amount in the graph), Evya exhibited excessive shivering, indicating that it was suffering from ear inflammation. Among other things, this example shows that the systems and methods of the present disclosure can be used both to alert caregivers of activities that may require intervention, and also to track interventions to see if they are successful.

[0183] Figure 7a and Figure 7bA GUI is shown indicating that the dog suffered from excessive shaking and scratching prior to the intervention, and the effects of the intervention. The information presented is associated with a 5-year-old beagle named "Loui". On January 26, 2020, Loui was brought in for surgery for lip fold dermatitis. The surgery was uneventful, and Loui was discharged wearing an Elizabethan collar (cone). Following the surgery and as a result of wearing the Elizabethan collar, Loui was shaking and scratching excessively for 8 days (as shown in Figure 1). Figure 7a and Figure 7b , which shows the With the Elizabethan collar, Loui was unable to bite her paws, which caused her a lot of discomfort, such as Figure 7a and Figure 7b , with the midpoints indicating days when Loui scratched more than usual. Following surgery (January 26, 2020), Loui did not sleep well and spent a lot of time scratching and shivering (but not grooming - as the Elizabethan collar prevents grooming). On July 2, 2020, the Elizabethan collar was removed, and Loui exhibited excessive grooming (compensatory grooming). Loui was treated with steroids and antihistamines to prevent excessive scratching and grooming, and on July 4, 2020, Loui's shivering and scratching behavior (based on the The information obtained by the device) is restored to normal levels, such as Figure 7b can be seen in.

[0184] Figures 8a to 8e A GUI is shown indicating that the dog suffered from excessive shivering and decreased sleep quality prior to the intervention and the effects of the intervention. The information presented is associated with a female mixed breed dog named "Sky". Sky had an ear infection beginning on May 1, 2020 and received an intervention (medical treatment) for the infection on May 4, 2020. Figure 8a As you can see in the , on May 1, 2020, Sky’s sleep score (based on the sound from the collar attached to Sky) was 92 out of 100, compared to the average sleep score of 92 out of 100. The information obtained by the device) dropped to 70 out of 100. In addition, Figure 8b As can be seen in the video, Sky also began to shiver more than usual on the same day (based on the Device information). Figure 8c As can be seen in the following day (May 2, 2020), Sky’s sleep score dropped further to 51 out of 100, and he also exhibited excessive shaking and scratching (based on the Device information). Figure 8dAs can be seen in the video, on the second day (May 3, 2020), Sky's scratching value returned to the normal range, while Sky was still shaking more than usual. Figure 8e As can be seen in the video, on May 4, 2020, Sky's behavior (based on the The information obtained by the device) returns to normal.

[0185] Figures 9a to 9e A GUI is shown indicating that a dog suffered from excessive shivering prior to an intervention and the effects of the intervention. The information presented is associated with a dog named "Maple," a 4-year-old cocker spaniel who suffered from recurrent otitis externa (inflammation of the ear). On October 31, 2019, Maple's owner complained of an inflamed ear during a visit to the veterinarian. Figure 9a As can be seen in the video, on October 24, 2019, Maple began to shiver more than normal (based on the information obtained by the device). Figure 9b and 9c Prior to the veterinary visit, excessive shivering also occurred on October 25, 26, and 28, 2019 (based on the presence of a collar attached to Maple). After visiting the doctor and starting intervention (medical treatment) for the ear inflammation, the shivering decreased and returned to normal levels on November 2, 2019.

[0186] like Figure 9d and Fig.9e As can be seen in the , ear inflammation recurred which caused Maple to have excessive shivering on November 20, 2019 and November 21, 2019. On November 21, 2019, Maple was prescribed a different treatment which rapidly reduced the excessive shivering such that on November 22, 2019, no excessive shivering was identified, indicating a successful intervention.

[0187] Before continuing with these figures, attention is directed to another exemplary case study conducted according to the teachings herein. This case study used a three-dimensional accelerometer, cloud data logging, and a data presentation app ( app) to assist in the medical management and early outbreak detection associated with chronic canine skin diseases. Medical management of chronic canine pruritic skin diseases is challenging and often frustrating. Getting early warning of an outbreak, having the dog owner adhere to the recommended treatment regimen, and maintaining close patient monitoring are factors that can greatly improve outcomes. Mobile monitoring using an accelerometer and on a smartphone-based app ( Cloud data logging, data analysis, and data presentation on an app (but not limited to) optionally combined with automated real-time communications with the veterinary clinic can help address these challenges and provide opportunities for improved medical management.

[0188] In this case study, a neutered, 9-year-old male pug weighing 6 kg was under medical management for dermatology and participated in a larger clinical study evaluating accelerometer technology with the owner's informed consent. The dog had previously been diagnosed with chronic pruritus with previous outbreaks and was referred to a veterinary dermatologist. The dog's pruritus was suspected to be atopic dermatitis associated with allergy to environmental allergens. The dog was also known to have previously suffered from otitis externa, which resolved with treatment. The analyzed accelerometer data provided warning of the dog's pruritus outbreak before the owner observed overt clinical signs. Based on this alert, communication was initiated between the veterinarian and the dog's owner, which resulted in a revision of the pruritus management regimen and improvement in clinical signs.

[0189] In conclusion, analyzed accelerometer data combined with data communications are a valuable adjunct to the ongoing management of chronic pruritic skin diseases in dogs.

[0190] Back to the picture, Figure 10a to Figure 10g Figures showing the values ​​of the parameters determined during the test, during which the animals were monitored during the day and during the night in the flea infestation period and the flea non-infestation period. A more detailed description of the test is provided below. The information shown in each figure is based on an analysis of the behavior of eight dogs during the infestation period (wherein they were infected with C. felis fleas) and the non-infestation period (wherein they were not infected with C. felis fleas).

[0191] Fig.10a The amount of grooming (minutes per hour) during the following periods is shown: (a) during the day when the dog is not infected with C.felis fleas, (b) at night when the dog is not infected with C.felis fleas, (c) during the day when the dog is infected with C.felis fleas, and (d) at night when the dog is infected with C.felis fleas. Looking at this information, it can be appreciated that when infected with C.felis fleas, the dog's grooming time during the day and at night is longer than when the dog is not infected with C.felis fleas. It can also be appreciated that the difference during the night is much more significant. At night, when the dog is not infected with C.felis fleas, they groom less than 1 minute per hour. When the dog is infected with C.felis fleas, most dogs groom much more.

[0192] Fig.10bThe amount of barking (in minutes per hour) during the following periods is shown: (a) during the day when the dog was not infested with C. felis fleas, (b) during the night when the dog was not infested with C. felis fleas, (c) during the day when the dog was infested with C. felis fleas, and (d) during the night when the dog was infested with C. felis fleas. Looking at this information, it can be appreciated that when infested with C. felis fleas, the dog barks less during the day and barks more during the night when compared to the amount of barking when the dog was not infested with C. felis fleas.

[0193] Fig.10c The amount of scratching (minutes per hour) during the following periods is shown: (a) during the day when the dogs were not infested with C. felis fleas, (b) during the night when the dogs were not infested with C. felis fleas, (c) during the day when the dogs were infested with C. felis fleas, and (d) during the night when the dogs were infested with C. felis fleas. Thus, it can be seen that the dogs that were not infested with fleas scratched less at night.

[0194] Fig.10d Shown is the amount of shivering (in minutes per hour) during: (a) daytime when the dog was not infested with C. felis fleas, (b) nighttime when the dog was not infested with C. felis fleas, (c) daytime when the dog was infested with C. felis fleas, and (d) nighttime when the dog was infested with C. felis fleas. Looking at this information, it can be appreciated that the dog engaged in shivering for a longer period of time during the night when infested with C. felis fleas than during the night when the dog was not infested with C. felis fleas.

[0195] Fig.10e The amount of rest (in minutes per hour) during (a) the day when the dogs were not infested with C. felis fleas, (b) the night when the dogs were not infested with C. felis fleas, (c) the day when the dogs were infested with C. felis fleas, and (d) the night when the dogs were infested with C. felis fleas. Thus, it can be seen that the dogs that were not infested with fleas rested more at night.

[0196] Fig.10fShown are the amount of high activity (minutes per hour) during the following periods: (a) during the day when the dog was not infested with C. felis fleas, (b) during the night when the dog was not infested with C. felis fleas, (c) during the day when the dog was infested with C. felis fleas, and (d) during the night when the dog was infested with C. felis fleas. Looking at this information, it can be appreciated that when infested with C. felis fleas, the dog engaged in less high activity during the day than when the dog was not infested with C. felis fleas.

[0197] Figure 10g The amount of low activity (in minutes per hour) during the following periods is shown: (a) during the day when the dogs were not infested with C. felis fleas, (b) at night when the dogs were not infested with C. felis fleas, (c) during the day when the dogs were infested with C. felis fleas, and (d) at night when the dogs were infested with C. felis fleas. Looking at this information, it can be appreciated that when infested with C. felis fleas, the dogs engaged in more low activity during the night when compared to the amount of low activity during the night when the dogs were not infested with C. felis fleas. This reduced rest may further lead to a reduction in high activity time during the day in flea-infested dogs (see Fig.10f ).

[0198] Having described these figures, attention is now directed to some studies conducted in relation to the subject matter of the present disclosure. It should be noted that these are merely examples and should not be used to limit the scope of the remainder of the detailed description.

[0199] Example Study 1:

[0200] List of abbreviations:

[0201] 2. In the morning BW weight CAS Chemical Abstracts Service D Research Day n number NA not applicable pm After noon C.felis Ctenocephalides felis

[0202] Overview:

[0203] This study evaluated the feline flea (C. felis) model using experimental infection with the flea C. felis. equipment Suitability for monitoring the health of the dog.

[0204] Materials and methods: A total of 8 Healthy dogs with the device were included in the study. After a 17-day adaptation period, a behavioral baseline was established for behavioral parameters such as activity, rest, scratching, grooming and shivering, and all dogs were infected with 80 C.felis. Four days after the infection, fleas were removed and fleas were counted. Two weeks after the first infection, a second infection with 100 fleas was performed, and then fleas were removed and fleas were counted. The behavioral parameters during the days of infection were compared with the established behavioral baseline. If the infection with 100 fleas is not enough to cause significant behavioral changes compared to the behavioral baseline, a third infection with 120 fleas is planned.

[0205] After the first infestation with 80 fleas, the changes in the number of fleas and behavioral parameters were not so obvious for all dogs when evaluated. After the first infestation with 100 C.felis, some behaviors were significantly different from the established baseline. Significant changes were obtained in the paired t-test for grooming and resting (day and night), barking and high activity (day), scratching, shivering and low activity (night). Therefore, the third infestation with 120 fleas was omitted.

[0206] All dogs remained in good clinical health throughout the study.

[0207] As described in more detail herein, an infestation of at least 100 fleas evokes significant changes in behavioral parameters such as grooming and resting during the day and night.

[0208] Test article (test product): is an activity and behavior monitoring device that understands and accurately interprets your dog's unique patterns. Delivers insights into your dog's activity and sleep patterns, as well as behaviors that indicate potential problems (health conditions), such as shivering, scratching, and barking. From the moment it is attached to a dog’s collar, its suite of adaptive algorithms begins to learn the animal’s unique movement patterns, which are specific to each dog; accurately interpreting them and reporting the corresponding types of activity and behavior, such as to SURE Petcare – A smartphone app (hereinafter referred to as the "app"), or via any other output device by which notifications can be provided to the animal caregiver / veterinarian.

[0209] Test system:

[0210]

[0211] Research Process

[0212] Animal Management, Feeding and Water:

[0213] Feed the dogs, provide toys, water, appropriate temperature and lighting conditions, and maintain a socially stable dog group.

[0214] Animal Health

[0215] Clinical examination:

[0216] All dogs were clinically examined by a veterinarian on the day of inclusion (study day 1) and on the last day of the recovery period (study day 26). The clinical examination included measurement of rectal temperature and assessment of the cardiovascular system (auscultation, capillary refill), respiratory system (auscultation), superficial lymph nodes (e.g., mandibular lymph nodes), and signs of lameness or discomfort. Particular attention was paid to the skin and coat (e.g., hair loss, shedding).

[0217] General Health Observation (GHO):

[0218] From the beginning of the acclimation period until the end of the animal period, general health observations (general condition and appetite) were performed twice daily, once in the morning and, except for study schedules, a second time in the afternoon.

[0219] Document any unusual observations. Perform clinical examination and treatment of animals showing illness or distress at the discretion of the Study Director.

[0220] Observations of unusual reactions to test items:

[0221] During the general health observation, the animals were also checked for proper placement of collars and equipment, as well as possible reactions to the test articles or their “attachments.”

[0222] Observation of abnormal reactions after flea infestation:

[0223] Following each flea infestation, animals were continuously monitored within the first hour. Over the next 4 days, dogs were examined for symptoms associated with local irritation and / or reaction, including erythema, scaling / scaling, dry skin, skin cracking, edema, hair loss, blistering, exudation, urticaria, and wheals. For each time point, each assessment parameter was scored as absent (A), slightly changed (B), moderately changed (C), or severely changed (D).

[0224] Group Assignment

[0225] From the 10 dogs that started the adaptation phase (see Table 1), 8 dogs were selected based on the data recorded during the adaptation phase (baseline) and behavior of clinical health status. Two dogs ("Flash" and "Pablo") were identified as reserve animals because their temperaments were more nervous than the other dogs. All 8 dogs participating in the study formed the study population. There was no distinction into study groups. Therefore, randomization was not applicable.

[0226] Management of test items

[0227] all The devices were applied to the collars of individual animals according to the manufacturer's instructions. The devices were applied to all 10 dogs selected for the acclimation period 17 days before the first infection (study day 0).

[0228] Table 1: Assignment of test articles to study animals (n=10)

[0229]

[0230] 1 Reserve Animals

[0231] Flea Infestation

[0232] The first flea infestation was performed on study day 0 (n=80 fleas). Based on the results of the first infestation, a second infestation was performed with 100 fleas on study day 14. The third infestation with 120 fleas was omitted.

[0233] All dogs were infested with the following parasite species: C. felis: Live, unfed, male and female adult fleas, ≤4 weeks of age. The fleas were applied directly to the fur along the topline, sides of the body, and / or head of each dog.

[0234] Assessment of parasite burden

[0235] 96 hours after each infestation, fleas were removed and the number of fleas (ie, parasite count) for each dog was counted and recorded.

[0236] For parasite counts, each dog's entire body was carefully examined and fleas were collected by combing the dog's coat with a flea comb. The removed fleas were counted. The dogs were evaluated in a non-systematic order as they "arrived".

[0237] Data collection and processing

[0238] By using Equipment to collect data (see Table 1 for the allocation of animals and equipment). In addition, other behavioral characterization devices may be used with appropriate modifications.

[0239] From the From the moment it is attached to your dog's collar, The acceleration data will be recorded continuously. Both contain a 3-axis accelerometer sensor and an integrated non-volatile memory. The memory is capable of storing data for a period of up to 2 weeks. Each includes a set of implemented algorithms that begin to understand the animal's unique movement patterns; accurately interpret them into dog states (e.g. shivering, grooming, scratching, resting, sleeping, high activity, medium activity, low activity, barking, calorie consumption, walking, running, sitting, lying down, jumping, chewing, sniffing, licking, etc.) and send them to a smartphone (Apple iPhone) application (App) Report the corresponding activity and behavior type. Connect to SUREPetcare via Bluetooth Low Energy (BLE) app, but this is not limiting and the connection can be established in other ways. Individual activity and behavior profiles are generated via the SUREPetcare app.

[0240] A minimum period of 7 days is used to understand the dog's "normal" activity level (its behavioral baseline), but other amounts of time may be used to collect behavioral baseline data.

[0241] Once Animo is attached to the dog, data collection is a continuous process. The data collected at each meaningful time period (e.g. 10 seconds, 15 seconds, 30 seconds, 1 minute, etc.) is analyzed and categorized into behaviors.

[0242] During the adaptation period in this example, 18 days of The data is collected and transferred to a data cloud environment. Based on this data, a normal behavior pattern for each dog is defined, also referred to herein as a "behavioral baseline."

[0243] During the animal stage, select the time interval data after infection, the data collected continuously, and carry out data evaluation with the segmentation of 24 hours (09:00-09:00 of the second day in the morning), maximum 4 days (24 hours).Based on these data, determine the behavior pattern after infection (infection 1, infection 2).

[0244] Animal health parameters

[0245] Depending on the data packet after infection, the most appropriate parameters for monitoring the health status of the animal are identified.

[0246] Key features of the Sure Petcare app include:

[0247] Activity: Set and monitor your daily activity goals, and view activity reports by day, week, month and year.

[0248] Calories: Track calories burned by your dog and compare to recommended daily goals based on breed, age and weight.

[0249] Sleep Quality: Hourly reports of sleep quality throughout the night; a poor night's sleep may be an indicator of stress, discomfort, or illness.

[0250] Behavior tracking: Events showing increased barking, scratching, or shaking.

[0251] Activity

[0252] Tracks the total time in hours and minutes your dog is active each day. Activity is categorized as walking, running, or any other movement, such as shaking.

[0253] Calories

[0254] Calorie calculation is based on an industry standard calculation that takes into account the dog's weight. Calories burned are tracked for each type of movement your dog makes. In addition to weight, the app also takes into account spay / neuter status and age.

[0255] Sleep quality

[0256] Poor sleep quality may be a symptom of stress, discomfort, need for intervention, or illness. The app can identify if the dog's sleep quality last night or the previous few nights was far below normal and compare the sleep quality data to the dog's average sleep quality data. The dog's sleep hours are individually defined within the app (e.g., 0 p.m. to 5 a.m.). The individual dog's sleep hours can be adjusted based on their typical sleep patterns and timing. Alternatively, the dog's sleep hours can be determined based at least in part on data collected by Animo.

[0257] track

[0258] Accurately detect when a dog is barking, scratching or shaking. The amount of these behaviors is tracked by the device and compared to normal or typical behavior (e.g., baseline). The dog's resting time is continuously tracked by the App throughout the day.

[0259] The following parameters were selected to characterize the health status (health condition) of the dogs: resting, barking, grooming, scratching, shivering, low activity, medium activity and high activity.

[0260] Statistical analysis

[0261] Assessment of adequacy of infection

[0262] Each dog participating in the study was considered fully infested when approximately 50% of the number of fleas used for infestation were retrieved 4 days after infestation.

[0263] Data Analysis

[0264] The data for each parameter is evaluated based on daily events.

[0265] Data interpreted from each infestation ("Infestation") were compared to the behavioral baseline ("Uninfested"). After the first infestation with 80 fleas, less difference was detected compared to data based on an infestation of 100 fleas.

[0266] Each The implemented algorithms continuously track various behavioral states (e.g. shivering, grooming, scratching, resting, sleeping, high activity, medium activity, low activity, barking, calorie burning, walking, running, sitting, lying down, jumping, chewing, sniffing, licking, etc.). The following parameters are used for statistical analysis of the number of events:

[0267] Rest Low: Absolute number (accuracy 0.01) and continuous duration of sleep episodes per 24 hours.

[0268] Rest High: The absolute number of events where the dog’s head does not touch the ground.

[0269] Rest: The sum of Rest High and Rest Low.

[0270] Barking: Absolute number of incidents per 24 hours (09:00 am to 09:00 pm).

[0271] Grooming: absolute number of events per 24 h (09:00 am to 09:00 pm), time of maximum grooming period (Tmax) and number of consecutive grooming phases per 24 h.

[0272] Scratching: absolute number of events per 24 h (09:00 am to 09:00 pm), time of maximum scratching period (Tmax), and number of consecutive scratching phases per 24 h.

[0273] Shivering: Absolute number of shivering episodes (events) per 24 hours (eg 09:00 AM to 09:00 AM) (accuracy 0.01).

[0274] Low activity: absolute number of events per 24 hours (09:00 am to 09:00 pm), time of longest period with low activity (Tmax) and number of consecutive low activity phases per 24 hours.

[0275] High activity: absolute number of events per 24 hours (09:00 am to 09:00 pm), time of longest period with high activity (Tmax), and number of consecutive high activity phases per 24 hours.

[0276] Time of day is defined as follows:

[0277] Daytime is the time from 7 am to before 7 pm.

[0278] Night time is the time from 7pm to before 7am.

[0279] The observation period started on Study Day -16 and ended on Study Day 18 (9 AM), with infestations occurring on Study Day 0 (between 9 AM and 10 AM) and Study Day 14 (between 9 AM and 10 AM). After the first infestation, fleas were removed.

[0280] Days on which infestation or flea removal was performed were not considered for statistical analysis.

[0281] therefore, Infection status is defined as follows:

[0282] Uninfected: Study Day -15 to Study Day -1, Study Day 5 to Study Day 13

[0283] Infection: Study Day 1 to Study Day 3, Study Day 15 to Study Day 17

[0284] The average number of events per hour was determined for each dog, parameter, date, time of day, and infection status.

[0285] Generalized linear models were applied to investigate the following effects on the average number of events per hour (α = 0.05):

[0286] Status (infected / uninfected)

[0287] Time of day (day / night)

[0288] Status and time of day interaction

[0289] Additionally, the mean number of events per hour was determined for each dog, parameter, time of day, and infection status.

[0290] Separate analyses were performed for each time of day to investigate possible effects of infection status. A two-sided t-test (α=0.05) for paired samples was used for each dog to compare the mean number of events during the infection period with the mean number of events during the non-infection period.

[0291] result

[0292] Animal Health

[0293] Clinical examination

[0294] No abnormalities were detected in any of the dogs (8 enrolled plus 2 reserve animals) during clinical examinations on Study Day 1 and at the end of the animal period (Study Day 26).

[0295] General health observation

[0296] General behavior and appetite of all animals were normal throughout the animal study period.

[0297] Observation of abnormal reactions after flea infestation

[0298] Four days after the first flea infestation (n=80 fleas), mild erythema appeared in three dogs (Anton, Mable, Paul), which remained until the day before the second infestation (n=100 fleas). Mild erythema appeared in three dogs (Lolly, Mable, Maggie) on the 2 days, 3rd and 4th day after the second infestation. Itching was observed in Lolly and Mable. Mable also had localized hair loss four days after the second infestation (study day 18).

[0299] Description of the study population

[0300] Determination of body weight

[0301] The body weights of the eight dogs included in the study ranged from 10.4 kg to 14.9 kg on study day 1 and from 10.0 kg to 14.4 kg at the end of the animal period, with all but one dog experiencing a weight loss of up to 5%.

[0302] Table 2 Individual body weight and body weight summary

[0303]

[0304] Age and gender distribution

[0305] For age and gender distribution, see Table 3 .

[0306] Table 3 Individual age and sex of the studied animals

[0307]

[0308] mn: neutered males, fn: neutered males, N: number

[0309] Adequacy of infection

[0310] If 50% of the fleas were retrieved after 4 days of infection, the infection was considered adequate. Due to pair housing during the first infection, the flea distribution became uneven in both dogs before the evaluation. Therefore, several dogs were under-infested. In addition, the data collected on the animal well-being parameters indicated no behavioral changes that could be statistically evaluated.

[0311] During the second infection period, dogs were housed individually and the data collected were deemed suitable for statistical evaluation.

[0312] Table 4 lists the number of individual fleas retrieved from the individual dogs 4 days after the respective infestations.

[0313] Table 4: Number of fleas counted during assessment

[0314]

[0315] The number of fleas recollected from one animal (Anton) was slightly below the 50% threshold. As the actual flea count of 46 was only slightly below (<10%) the expected minimum number of 50 fleas in an individual animal, the flea infestation was considered sufficient for study purposes. It was decided not to exclude Anton's data from further statistical evaluation.

[0316] Animal health parameters

[0317] The hourly event means are summarized for each parameter and each combination of time of day and infestation status (after infestation with 100 fleas) in Table 5, and the results of the effects investigated using generalized linear models are summarized in Table 6. The results of paired t-tests performed separately for each time of day are summarized in Table 7.

[0318] Table 5: Mean and standard deviation of average events per hour

[0319]

[0320] Table 6: Generalized Linear Model Results

[0321]

[0322] Table 7: Results of paired t-tests for each time of day

[0323]

[0324] Generalized linear models revealed highly significant differences between daytime and nighttime observations for all parameters (p<0.0001, indicated in bold).

[0325] For grooming, a significant difference was observed between the infected and uninfected study periods (p<0.0001), which was similar during day and night, so no significant interaction was observed. Separate analysis of day and night events confirmed this observation (day: p=0.0017, night: p=0.0069). Fig.10a A graphical display of the average number of events observed is given in .

[0326] For barking, the difference between the infected and uninfected study periods was not significant, and no significant interaction was observed between condition and time of day. However, separate analyses of daytime and nighttime events revealed a significant difference between the infected and uninfected study periods during the day (p = 0.0017). Fig.10b A graphical display of the average number of events observed is given in .

[0327] For scratching, the difference between the infected and uninfected study periods was not significant, but the interaction between condition and time of day was significant (p = 0.0194), as there was slightly more scratching during the day when uninfected and slightly more scratching at night when infected. Separate analysis of daytime and nighttime events confirmed that the difference at night was significant (p = 0.0066). Fig.10c A graphical display of the average number of events observed is given in .

[0328] For shivering, the difference between the infected and uninfected study periods was not significant, but since there was no difference during the day, but shivering was slightly more at night when infected, the interaction between status and time of day was significant (p = 0.0102). Separate analysis of daytime and nighttime events confirmed that the difference was significant at night (p = 0.0098). Fig.10d A graphical display of the average number of events observed is given in .

[0329] For rest, the difference between the infected and uninfected study periods was not significant, but the interaction between state and time of day was significant (p<0.0001) due to slightly more rest during the day when infected and slightly less rest at night when infected. When daytime and nighttime events were analyzed separately, significant differences between the infected and uninfected study periods were observed during both daytime and nighttime (daytime: p=0.0298, nighttime: p=0.0017). Fig.10e A graphical display of the average number of events observed is given in .

[0330] For high activity, a significant difference was observed between the infected and uninfected study periods (p<0.0001), this difference was very large during the day (higher activity when uninfected), but not during the night, so the interaction was also significant (p<0.0001). Separate analysis of daytime and nighttime events confirmed that the difference during the daytime was significant (p=0.0004). In the above discussion Fig.10f A graphical display of the average number of events observed is given in .

[0331] For hypoactivity, a significant difference was observed between the infected and uninfected study periods (p=0.0130). More hypoactivity was observed during the day when uninfected and more hypoactivity was observed at night when infected, and this interaction was also significant (p=0.0042). Separate analysis of daytime and nighttime events revealed no significant differences during the daytime, but significant differences at night (p=0.0247). In the above discussion Figure 10g A graphical display of the average number of events observed is given in .

[0332] Discussion and Conclusion

[0333] As shown in this example study, changes in the dog's behavior as monitored by the Animo device can be evoked by an infestation of C. felis fleas. Changes in grooming behavior, resting, and activity patterns become apparent, especially at night. For example, an infestation dose of 100 fleas produced the above-described traceable differences. Therefore, the behavior monitored by the Animo device can be used as a proxy for possible changes in the dog's health status.

[0334] Example Study 2:

[0335] Glossary of abbreviations and definitions of terms

[0336]

[0337] Overview

[0338] This study evaluated The therapeutic effect of Fluralaner on the health status of dogs artificially infested with C. felis fleas (n=100).

[0339] Materials and methods: A total of 12 equipment Healthy dogs were enrolled in the study. The dogs wore Animo for 4 days -- in part to establish baseline data. All dogs were infected with 100 C. felis.

[0340] Four days after infection (96 hours), all dogs were given an oral commercial antiparasitic product Chewable tablets for dogs (Fluralaner). The day of treatment was defined as study day 0. Seven days after treatment, the therapeutic effect of the therapy was evaluated by removing all fleas from the animals and counting them.

[0341] To evaluate To demonstrate the preventive effect of the treatment, a second infection with 100 C. felis was performed on study day 20. Before each infection (study day -1 and study day 20) and during a period of four days after each infection, the skin and fur were examined for changes / abnormal reactions. From the beginning of the adaptation period until the end of the animal phase, Behavioral parameters of well-being such as grooming, activity level, scratching, and shivering were continually assessed.

[0342] Statistical evaluations were performed for the following parameters: grooming, high activity, moderate activity, low activity, resting, scratching, and shivering, comparing the following time periods: "Untreated / Baseline" (Study Day -8 to Study Day -4), "Infected" (Study Day -4 to Study Day 0), "Treatment" (Study Day 0 to Study Day 4), and "Protected" (Study Day 20 to Study Day 24).

[0343] result:

[0344] All animals were healthy throughout the study. Fluralaner for dogs) or No adverse reactions were observed after using the device (Animo).

[0345] The therapeutic efficacy against C. felis evaluated seven days after treatment was 100%. The preventive efficacy against C. felis evaluated 24 days after treatment and 4 days after reinfestation of fleas was 100%.

[0346] Flea infestation had an effect on dog behavior, including grooming at night (p=0.0167) and resting at night (p=0.0303), grooming during the day (p=0.1095), low activity at night (p=0.0755), and scratching at night (p=0.1242).

[0347] No direct treatment effects on dog behavior could be observed, but trends were seen for lower activity at night (p=0.1343), rest during the day (p=0.1260), and rest at night (p=0.0869).

[0348] Long-term treatment effects were observed on dog behaviors, including grooming at night (p = 0.0161), low activity at night (p = 0.0412), and rest at night (p = 0.0001). These results suggest that Fluralaner was well tolerated in all dogs participating in this study. When administered to dogs artificially infested with C. felis fleas (n=100), the (preventive) administration had a significant effect on grooming, resting and scratching behavior, as monitored by the Animo device. The differences in behavior as monitored by the Animo device were more pronounced in preventive (as shown by the "protection" period) administration than in therapeutic (as shown by the "treatment" period) administration.

[0349] Test article (test product)

[0350]

[0351]

[0352] Test system

[0353] Research animals

[0354] On the first day of adaptation (study day -8), 15 Twelve of the animals were selected for the study.

[0355] Table 8: Animal details

[0356]

[0357] No.: number, ID: identification, D: study day, Mn: neutered male, Fn: neutered female

[0358] Research Process

[0359] Animal management, feed and water

[0360] Feed the dogs, provide toys, water, appropriate temperature and lighting conditions, and maintain a socially stable dog group.

[0361] Animal Health

[0362] Clinical examination

[0363] On study day 6 and the last day of the recovery period (study day 38), all dogs underwent a clinical examination. The clinical examination included measurement of rectal body temperature and evaluation of abnormalities of the cardiovascular system (auscultation, capillary refill), respiratory system (quality of breathing), superficial lymph nodes (Lnn. mandibulares), and signs of lameness and discomfort. Particular attention was paid to the skin / coat (hair loss, hair loss). The examination was performed by a veterinarian.

[0364] General Health Watch (GHO)

[0365] General health observations (general condition and appetite) were performed twice daily from the start of acclimatization until the end of the animal period.

[0366] Observation of abnormal reactions after test article administration

[0367] Following test article administration and during general health observations, animals were checked for abnormal reactions or signs of illness (remaining feed after feeding time).

[0368] Observation of abnormal reactions after flea infestation

[0369] Following each flea infestation (study day 0 and study day 20), animals were monitored within the first hour and continuously for the next 4 days (i.e., 24, 48, 72, and 96 hours after treatment). All dogs were examined for symptoms associated with local irritation and / or reaction, including erythema, flaking / scaling, dry skin, skin cracking, edema, hair loss, blistering, exudation, urticaria, and wheals. For each time point, each assessment parameter was scored as absent (A), slightly changed (B), moderately changed (C), or severely changed (D).

[0370] Concomitant medication

[0371] From the start of the study (study day -8) until the end of the animal phase (study day 38), all dogs received no medication that could interfere with the study objectives. During the study, no animals were removed from the study, died unexpectedly, or were euthanized.

[0372] Determination of body weight

[0373] Body weights were determined on the day of inclusion (study day -6) and on the day of determination of individual flea burdens after the second infestation (study day 24). Weighing was performed after feeding and after determination of individual flea burdens.

[0374] Group Assignment

[0375] 15 wear Twelve of the dogs were included in the study, which were selected based on clinical health, previous study experience and behavior in their social group. All animals participating in the study formed the study group. No distinction was made into study groups. No randomization was performed. All animals were uniquely identified by microchip number.

[0376] Management of test items

[0377]

[0378] Table 9: Individual Dosages

[0379]

[0380] Flea Infestation

[0381] All dogs were infected with C. felis (n=100) twice. The first infection was performed on study day -4, and the second infection was performed on study day 20. All dogs were infected with the following species of parasites: C. felis (isolate SHM19): live, unfed adult male and female fleas, age ≤ 4 weeks. The fleas were applied directly to the fur along the topline of each uninfected conscious dog.

[0382] Assessment of flea burden

[0383] After each infestation, individual flea burdens were determined for all dogs. Evaluations after the first infestation were performed seven days after treatment (Study Day 7) to assess Evaluation after the second infection was performed on study day 24, 96 hours after the second infection, to assess the efficacy of the treatment. The preventive treatment effect of the dog was evaluated by 1:10. At these time points, fleas were removed and the number of live fleas (i.e., parasite count) was counted and recorded for each dog. For parasite counts, each dog was carefully examined and fleas were collected by combing the dog's fur with a flea comb. The removed fleas were counted. The dogs were evaluated in a non-systematic order when they arrived. For the calculation of efficacy, the number of dead fleas was ignored.

[0384] Data collection and processing

[0385] All data is collected using As used herein, is an activity and behavior monitoring device that learns and accurately interprets your dog’s unique patterns. Delivers insights into your dog's activity and sleep patterns, as well as behaviors that may indicate potential issues (health conditions), such as shivering, scratching, and barking.

[0386] In this example, once the device is attached to the collar, data collection can be a continuous process. Data collection can also be near-continuous. Each interval of a meaningful time period (e.g., 10 seconds, 15 seconds, 30 seconds, 1 minute, etc.) is classified as a behavior.

[0387] If the dog begins to show significant changes in behavior, including barking, scratching, grooming, and / or shaking, An alarm may be sent. In addition, both long-term and short-term changes in the dog's sleep may be monitored. A decrease in quality may be a symptom of disease or other environmental factors that disturb the dog (health condition) at night.

[0388] In this example, the following time intervals for continuously collected data were predetermined during the animal phase: Infection 1, following infection until treatment (Study Day -4 09:00 AM–Study Day 0 09:00 AM), Treatment 1 (Therapeutic) (Study Day 0 09:00 AM–Study Day 4 09:00 AM), and Treatment 2 (Prophylactic) (Study Day 20 09:00 AM–Study Day 24 09:00 AM).

[0389] Animal health parameters

[0390] The following features of the Sure Petcare app are included in the features used to monitor the health status of animals after artificial flea infestation:

[0391] Activity: Set and monitor daily activity goals and view activity reports by day, week, month and year. Behavior Tracking: Shows events of increased grooming.

[0392] Activity

[0393] The total time in hours and minutes that the dogs were active each day was tracked, so it could be inferred whether the animals were getting enough exercise to lead a healthy lifestyle. Activity was categorized as walking, running, or any other movement, such as shaking.

[0394] Behavior Tracking

[0395] Accurately detect when a dog is barking, scratching, or shaking. Significant increases in any of these behaviors are tracked by the device and compared to normal behavior (also referred to herein as the "behavior baseline"). The dog's resting time is continuously tracked by the App during the day.

[0396] In this example, the following parameters were selected (alone or in combination) to characterize the health of the dog: grooming, high activity, low activity, resting, scratching, shivering, and medium activity.

[0397] No additional parameters were selected in this example, but other parameters could be used.

[0398] Statistical analysis

[0399] Justification for sample size

[0400] The number of animals included in the study was 12 dogs. Assuming a standard deviation of 0.5, ten dogs were sufficient to detect a mean difference of 0.5 using a paired t-test with a power of 1-β=0.8 and a significance level of α=0.025 (one-sided). This estimate corresponds to the results obtained for low activity at night in "Example Study 1", see above for details. This sample size is also large enough to detect larger differences, as observed for grooming during the day (mean difference of 1.0, standard deviation of 0.9), grooming at night (mean difference of 0.85, standard deviation of 0.65), and high activity during the day (mean difference of 2.0, standard deviation of 1.0).

[0401] To compensate for possible dropouts due to insufficient infection, 12 dogs were included in the study.

[0402] Description of the study group

[0403] Descriptive analyses of the study population were performed with respect to initial age and weight on Study Day 3 (clinical examination) using appropriate statistical parameters.

[0404] Data Analysis

[0405] The aim of this analysis was to investigate possible changes in individual behavior regarding flea infestation after treatment with Preventive efficacy of chewable tablets.

[0406] The device records the following parameters based on daily events (meaningful time intervals such as 10 seconds, 15 seconds, 30 seconds, 1 minute, etc.): grooming, barking, scratching, shivering, resting, high activity, medium activity and low activity.

[0407] The following parameters were selected for evaluation:

[0408] Main parameters:

[0409] Grooming: Absolute number of events.

[0410] Secondary parameters:

[0411] High Activity: The sheer number of events.

[0412] Low Activity: The absolute number of events.

[0413] Additional parameters were also monitored:

[0414] Rest: Absolute number of events

[0415] Scratching: Absolute number of incidents

[0416] Shivering: Absolute number of events

[0417] Moderate activity: absolute number of events

[0418] Events are aggregated hourly.

[0419] Observations from 7:00 PM to 6:00 AM are classified as "night" observations, and observations from 7:00 AM to 6:00 PM are classified as "day" observations. Daytime and nighttime observations will be analyzed separately.

[0420] Observations were also categorized into study periods as follows:

[0421] · “Untreated period”: before the first infection on study day -4;

[0422] “Infection period”: between the first infection on Study Day -4 and the first treatment on Study Day 0;

[0423] · “Treatment Period”: between the first treatment on Study Day 0 and Study Day 4;

[0424] • “Protection period”: between the second infection on study day 20 and the determination of individual flea burdens on study day 24.

[0425] For each dog and parameter as well as time of day (night / day) and study period (untreated / infected / treated / protected period), the average number of events per hour was determined.

[0426] For each parameter and time of day (night / day), study periods were compared pairwise using t-tests for paired observations (two-sided, α=0.05):

[0427] "Infected period" versus "untreated period" to demonstrate the effects of flea infestation on dog behavior

[0428] "Infection period" versus "treatment period" to investigate possible therapeutic effects of treatment on dog behavior

[0429] · "Infestation period" versus "protection period" to investigate whether the effects of treatment on dog behavior persist if flea infestation is present after treatment.

[0430] For grooming, high activity, low activity, and rest, the average number of events per hour was determined for each study day (Study Day -8 vs. Study Day 24) and time of day (night / day), and the results were displayed graphically.

[0431] Description of the study group

[0432] Twelve dogs were included in the study. There were no dropouts during the study period, so data from all 12 dogs were used for statistical analysis.

[0433] The mean age of the study group was 3.5 ± 1.2 years, and the age of the dogs ranged from 2 to 5 years. The mean body weight on study day -6 was 13.0 ± 2.0 kg, with a range of body weights from 10.0 to 16.5 kg.

[0434] Genders within the study group were almost evenly distributed. Seven of the 12 dogs (58%) were male and neutered. Five of the 12 dogs (42%) were female and neutered.

[0435] Animal Health

[0436] Clinical examination

[0437] During clinical examination on study day-6, no symptoms were observed that would interfere with the study objectives. No changes were observed regarding the skin and coat, and all animals were found to be healthy. Therefore, all animals were included in the study.

[0438] At the end of the animal period (study day 38), all animals were examined again. All animals were healthy throughout the study.

[0439] Observation of abnormal reactions after test article administration

[0440] No abnormal reactions were observed in any of the animals following test article administration. No animal suffered from illness or discomfort requiring veterinary assistance.

[0441] Observation of abnormal reactions after flea infestation

[0442] In all animals, at all time points, before and after infection on study day 0 and study day 20, each parameter was examined and scored as A (no change).

[0443] Concomitant medication

[0444] From the beginning of the study to the end of the animal phase, the dogs received no medications that could interfere with the study objectives. After the second flea infestation, no live fleas were found in any of the dogs. Therefore, there was no need to treat fleas with other licensed products.

[0445] Determination of body weight

[0446] Body weights assessed on Study Day -6 and Study Day 24 hours are shown in Table 10:

[0447] Table 10: Weight

[0448]

[0449] No.: number, ID: identification, D: study day, Mn: neutered male, Fn: neutered female

[0450] Assessment of parasite burden

[0451] No live fleas were found on any dog ​​during the evaluations on study day 7 and study day 24 hours. One and two live fleas were found on two dogs (Anton and Humpty, respectively) at study day 24 hours (see Table 11). The treatment efficacy against C. felis was 100% seven days after treatment. The preventive efficacy against C. felis was 100% 24 days after treatment and 4 days after reinfestation.

[0452] Table 11: Determination of flea counts at study day 7 and study day 24 hours

[0453]

[0454] No.: number, D: research day, E: (T) :Therapeutic efficacy, E (P) : Preventive efficacy

[0455] Animal health parameters

[0456] Provided below are detailed results for each dog, time of day, study period and observed parameters. Table 12 below summarizes the average number of events per hour for each parameter, time of day and study period. After infection, a significant increase in the main parameter grooming was observed. During the day, the frequency of grooming increased further in the first few days after treatment and then slowly declined. During the night, the frequency of grooming decreased after treatment and was comparable to before infection during the protection period. No changes in high activity were observed during the night. During the day, high activity decreased after infection and further decreased after treatment, and then increased again during the protection period.

[0457] A significant change in low activity was observed during the night. Low activity increased after infection, then decreased after treatment and was comparable to pre-infection during the protection period. No changes in low activity were observed during the day. Among the additional parameters observed, a significant change in rest at night was seen. The time spent resting decreased significantly after infection, returned almost to pre-infection duration after treatment, and increased further during the protection period.

[0458] Table 12: Average number of events per hour

[0459]

[0460] These observations were confirmed by the results of statistical analysis.

[0461] The p values ​​obtained from the comparison of the infection period with the untreated period, the treated period and the protected period are summarized in Table 13. Significant results at the significance level of α=0.05 (two-sided) are marked with an asterisk (*).

[0462] Table 13: Results of pairwise comparisons during the study period

[0463]

[0464] *Significant results at α=0.05 significance level (two-sided) Flea infestation affected dog behaviors, including grooming at night (p=0.0167), resting at night (p=0.0303), grooming during the day (p=0.1095), low activity at night (p=0.0755), and scratching at night (p=0.1242).

[0465] After treatment, a trend towards low activity at night (p=0.1343), rest during the day (p=0.1260) and rest lw at night (p=0.0869) was seen.

[0466] Long-term treatment effects on dog behavior were observed for grooming at night (p=0.0161), low activity at night (p=0.0412), and rest at night (p=0.0001).

[0467] exist Fig.11a (Combing), Fig.11b (High Activity), Fig.11c (low activity) and Fig.11d (Break) shows the course of the average number of events per hour between Study Day -8 and Study Day 24, including both daytime and nighttime results.

[0468] Discussion and Conclusion

[0469] All animals were treated with the medium-sized dog The soft chew treatment was well tolerated. No adverse events were observed throughout the animal period.

[0470] As described above, statistically significant changes were observed for the animal well-being parameters, night grooming and night rest. Night grooming: increased after flea infestation, decreased during the protection period (study day 20 to study day 24) compared to the infestation period. Night rest: decreased after flea infestation, increased immediately after treatment, increased during the protection period compared to the infestation period.

[0471] Changes were also observed for animal well-being parameters, grooming during the day, low activity at night and scratching at night. Grooming during the day: increased after flea infestation. Low activity at night: increased after flea infestation, decreased immediately after treatment and decreased during the protection period compared to the infestation period. Scratching at night: increased after flea infestation.

[0472] These results further indicate that Suitable for detecting changes in animal well-being parameters including grooming, resting, high activity, scratching and low activity in dogs when experimentally infected with C. felis.

[0473] Statistical results:

[0474] Description of study groups: Gender, initial age, weight:

[0475]

[0476]

[0477]

[0478] Average number of events per hour for each dog, time of day, study period and parameter:

[0479]

[0480]

[0481]

[0482]

[0483]

[0484]

[0485]

[0486] Comparison of study period, time: daytime, parameter: grooming

[0487]

[0488]

[0489]

[0490] Dependent variable: Grooming Grooming

[0491]

[0492] Comparison of study periods, time: nighttime, parameter: grooming

[0493]

[0494]

[0495]

[0496]

[0497] Dependent variable: Grooming Grooming

[0498]

[0499] Comparison of study periods, time: daytime, parameter: high activity

[0500]

[0501]

[0502]

[0503] Dependent variable: High activity

[0504]

[0505]

[0506] Comparison of study periods, time: nighttime, parameter: high activity

[0507]

[0508]

[0509]

[0510] Dependent variable: High activity

[0511]

[0512] Comparison of study periods, time: daytime, parameter: low activity

[0513]

[0514]

[0515]

[0516]

[0517] Dependent variable: Low activity

[0518]

[0519] Comparison of study periods, time: nighttime, parameter: low activity

[0520]

[0521]

[0522]

[0523]

[0524] Dependent variable: Low activity

[0525]

[0526] Comparison of study period, time: daytime, parameter: rest

[0527]

[0528]

[0529]

[0530]

[0531] Dependent variables: RestLow rest low

[0532]

[0533] Comparison of study periods, time: nighttime, parameter: rest

[0534]

[0535]

[0536]

[0537] Dependent variables: RestLow rest low

[0538]

[0539]

[0540] Comparison of study periods, time: daytime, parameter: scratching

[0541]

[0542]

[0543]

[0544] Dependent variables: scratch scratch

[0545]

[0546] Comparison of study periods, time: nighttime, parameter: scratching

[0547]

[0548]

[0549]

[0550] Dependent variables: scratch scratch

[0551]

[0552] Comparison of study periods, time: nighttime, parameter: shivering

[0553]

[0554]

[0555]

[0556]

[0557] Dependent variables: scratch scratch

[0558]

[0559] Comparison of study periods, time: daytime, parameter: moderate activity

[0560]

[0561]

[0562]

[0563]

[0564] Dependent variable: Mid medium activity

[0565]

[0566] Comparison of study periods, time: nighttime, parameter: moderate activity

[0567]

[0568]

[0569]

[0570]

[0571] Dependent variable: Mid medium activity

[0572]

[0573] Daily means each study day and time of day:

[0574]

[0575]

[0576]

[0577] Example Study 3

[0578] background:

[0579] Dog skin diseases are often associated with pruritus, which can lead to skin trauma, skin damage and impaired resting profile for both the owner and the dog. Market research of dog owners shows that their dog's resting profile is a significant concern. Flea and tick infestations are common causes of skin diseases and may also cause pruritus. Managing canine pruritus is an ongoing requirement with the potential for recurrences or "breakouts" and the need to manage anti-itch treatments to deliver effective dosage regimens.

[0580] (provided as a non-limiting example) is a 3-dimensional accelerometer device that detects changes in dog movement (behavior) and enables tracking of these changes over time. This study demonstrates the use of ANIMO's output to provide veterinarians with valuable health profiles to document dog treatment progress and allow dog owners to see improvements in their dog's movement profile in the case of treatment for skin disease. Dogs wearing ANIMO require an initial 14-day calibration fit prior to initiating monitoring to normalize to the expected movement profile of the individual dog.

[0581] The dogs in this study were also prescribed or other flea / tick medications as a precaution for pruritus caused by ectoparasites or skin allergies triggered by ectoparasites. The study clinic is located in Florida, USA, an endemic high-risk area for fleas. Flea / tick medications were prescribed prior to the start of the study and were at the discretion of the veterinarian. The chewable tablets (manufactured by Merk Animal Health) are labeled to provide up to 12 weeks of flea and tick protection in a single dose. A key benefit of this extended protection is that dog owners increase their compliance with their veterinarian's recommendations for year-round flea and tick protection by receiving 12 consecutive weeks of treatment without the need for monthly re-dosing. This increased compliance is expected to deliver health benefits to dogs treated with Bravecto when compared to dogs treated monthly with flea / tick products or not treated with flea / tick products.

[0582] Dogs enrolled in the field trial wore ANIMO and were examined by a veterinary dermatologist for any cause of itching. The behavior of all dogs was tracked over a 4-month period following enrollment.

[0583] As further described below, this exemplary study illustrates the ability to analyze ANIMO delivered data showing detectable movements (including sleeping, shivering, grooming, and scratching) of dogs receiving treatment for itch and / or flea infestation, and derive useful insights therefrom. As an example, this study illustrates the use of ANIMO delivered data reports as early warning indicators of itch recurrence (e.g., "outbreaks") in dogs with allergic conditions. As another example, this study illustrates the ability to assess comparative rest profiles of dogs with confirmed skin allergic disease using ANIMO activity data profiles over a period of several months following treatment for itch. As another example, this study illustrates the ability to assess owner self-reported compliance with recommended flea and tick treatments, and the possible role of owner compliance in dog comfort.

[0584] Overview of the study:

[0585] Thirty-six dogs were enrolled in the Bravecto group and one dog discontinued during the trial. Sixty dogs were enrolled in the other treatment group and seven discontinued during the trial. A total of 96 dogs were enrolled, of which nine discontinued, resulting in 87 dogs (including 36 (41%) Bravecto and 51 (59%) other treatments) completing the trial.

[0586] During the study, owners maintained notes of medications administered to their dogs and other relevant behaviors during the study period as diary notes inserted into the notes field in the app. This is an example of increased communication between pet owners and caregivers.

[0587] Owners were asked to sync ANIMO readings daily and this happened automatically as long as the ANIMO and app were within Bluetooth range and the phone had internet connectivity. However, there were reports of owners failing to sync for more than 72 hours. These were monitored weekly and owners were contacted to have them sync. Any owner who failed to sync after more than 14 days was at risk of data loss and there were occasional data loss throughout the trial. Several enrolled dogs were eliminated from the trial due to failure to sync data. All owners who completed the trial were asked to return for a final check and complete an end-of-study questionnaire.

[0588] The alarms received during the trial were monitored and each owner was contacted. In this example study, the alarms indicated scratching or shivering, or possibly both.

[0589] Scratch analysis for dermatological diagnosis

[0590] Several dogs with multiple alarms and / or recurrence of clinical signs as observed by the owner were taken to the veterinarian for reexamination. On average, the amount of scratching by dogs with atopic dermatitis as detected by the ANIMO monitor was similar to that of dogs with allergic dermatitis (about 6 minutes per day). The "suspected allergy" dogs scratched 2-5 minutes more per day than the other dogs, and this remained consistent from month to month. When the scratching time for each dog was added up each month, the atopic dogs scratched 20-30 minutes more per month than the allergic dermatitis dogs, although this difference was clinically insignificant when considered on a daily basis.

[0591] Table 14 below shows the average scratching time per day (in minutes) for skin disease diagnoses:

[0592]

[0593] In this regard, please also turn your attention to Fig.12 and Fig.13 , which show a graph of the average minutes of scratching per month by dermatological diagnosis and a graph of the average minutes of scratching per day by dermatological diagnosis, respectively, as observed in the study.

[0594] Shiver Analysis by Dermatological Diagnosis

[0595] For the analysis of shivering data, dogs with atopic dermatitis and allergic dermatitis shivered an average of 3-4 minutes per day. When the shivering time for each dog was added up each month, the dogs with allergic dermatitis shivered approximately 20-30 minutes more per month compared to the dogs with atopic dermatitis who shivered less than 1 minute per day.

[0596] Table 15 below shows the average daily shivering time (in minutes) by skin disease diagnosis:

[0597]

[0598]

[0599] In this regard, attention is also turned to Fig.14 , which shows a graph of the average number of minutes of shivering per day by dermatological diagnosis as observed in the study.

[0600] Grooming analysis for dermatological diagnosis

[0601] The average amount of grooming time per dog per day was approximately 25-35 minutes. There did not appear to be much difference in this variable between dogs with atopic dermatitis compared to those with allergic dermatitis. Dogs with otitis externa (inflammation limited to the ear) had the least amount of grooming per day as measured by ANIMO.

[0602] Table 16 below shows the average daily grooming time (in minutes) by skin disease diagnosis:

[0603]

[0604] In this regard, attention is also turned to Fig.15 , which shows a graph of average minutes of grooming per day by dermatological diagnosis as observed in the study.

[0605] Nighttime rest through dermatological diagnosis

[0606] Dogs with atopic dermatitis consistently had the lowest mean number of minutes of nightly rest, while dogs with “suspected allergies” had the highest mean number of minutes of nightly rest. For dogs diagnosed with both atopic dermatitis and atopic dermatitis, nightly rest averaged 6.9–7.3 hours.

[0607] Table 17 below shows the average nighttime rest time (in hours) per night by skin disease diagnosis:

[0608]

[0609] In this regard, attention is also turned to Fig.16 , which shows a graph of the average number of minutes of nighttime rest per night by dermatological diagnosis as observed in the study.

[0610] Sleep ratio by dermatological diagnosis

[0611] Actual to reported sleep ratios (i.e., actual dog sleep hours per night as determined by Animo data, divided by reported sleep hours as reported by dog ​​owners using the app) for the different dermatologic diagnoses were very similar, suggesting that, on average, dogs had similar amounts of sleep quality regardless of itch diagnosis. A sleep ratio of 1 indicates that Animo recorded the dog sleeping for the entire period identified as sleep time by the owner. A number less than one indicates that the dog was awake for some portion of the sleep time.

[0612] Table 18 below shows the average nighttime rest time (in hours) per night by skin disease diagnosis:

[0613]

[0614] In this regard, attention is also turned to Fig.17 , which shows a graph of the average sleep ratio per night by dermatology diagnosis as observed in the study.

[0615] Overview of clinical signs in all dogs during the entire study period

[0616] All dogs, regardless of dermatologic diagnosis or flea / tick medication assignment, were grouped into a single graph to visualize the scratching patterns observed over the 120-day study period ( Fig.18 Shown are the average number of minutes of scratching per day during the 120-day study period), shivering patterns ( Fig.19 Shown are the mean number of minutes of shivering per day during the 120-day study period), grooming patterns ( Fig. 20 Shown are the average number of minutes of grooming per day) and nighttime resting patterns during the 120-day study period ( Fig.21 The mean number of minutes of nighttime rest per night during the 120-day study period is shown). As a group, the amount of each behavior exhibited by the dogs over time was consistent. A best fit line was applied to the data to demonstrate this consistency. For shivering and grooming, the best fit line increased slowly over time, but the average scratching and nighttime rest did not seem to change much over time. Early in the study, when the dogs were seen in the dermatology clinic (Days 0 and 14), they were treated for pruritus. After the initial treatment, changes in shivering and grooming correlated with a gradual recurrence of pruritus over time.

[0617] Scratching, shivering and total alarm counts monitored over 120 days

[0618] Seventy-seven dogs completed the full 120 days of study monitoring. These animals were used to compare the number of alerts generated by Animo during the study. Ten dogs were dropped from this analysis because they participated in the study for less than 120 days, ranging from 91-119 days. Alerts were triggered by the Animo App's interpretation of the recorded data, indicating deviations from expected baseline data. Alerts were classified into categories based on an algorithm that interprets the recorded data.

[0619] Scratch alarm

[0620] Over the 120 days, 537 scratching alarms were generated by 77 dogs. Each dog in this study generated 0-29 alarms over the 120 days, with an average of 7.4 scratching alarms per dog in total. 17 / 77 dogs (22%) did not generate any scratching alarms at all, and 60 / 77 dogs (78%) generated 1 or more alarms.

[0621] When the number of scratch alerts was placed into a range, it was clear that most dogs diagnosed with atopic dermatitis produced very few scratch alerts (0 or 1-5) over the entire study period. Dogs diagnosed with atopic dermatitis were more likely to produce 1-15 scratch alerts over the same period. The difference in the number of scratch alerts produced between atopic dermatitis and atopic dermatitis was statistically significant. The scratch alert patterns were similar between dogs assigned to the Bravecto and Monthly flea / tick medication groups. The differences between the means for dogs prescribed the different flea / tick medications were not statistically significant.

[0622] Table 19 shows the scratching alert generated by the skin disease diagnosis:

[0623]

[0624] Shiver Alert

[0625] Over a 120-day period, 672 shivering alarms were generated by 77 dogs. The dogs in this study generated 0-32 alarms over a 120-day period, with an average of 8.6 shivering alarms per dog in total. 7 / 77 dogs (9%) did not generate any shivering alarms at all, and 70 / 77 dogs (91%) generated 1 or more alarms. The shivering alarm patterns were similar in dogs diagnosed with allergic dermatitis and atopic dermatitis.

[0626] Table 20 shows the shivering alert generated by the skin disease diagnosis:

[0627]

[0628] Total Alarm

[0629] Canine behaviors that trigger scratching alarms can occur independently of canine behaviors that produce shivering alarms. If there is some shared commonality that a particular movement by one dog might produce a scratching alarm, while a similar movement by another dog might produce a shivering alarm, we created a “total alarm” category that was the sum of the scratching alarm and the shivering alarm.

[0630] Over the 120 days, 1209 total alarms were generated by 77 dogs. The dogs in this study generated 0-57 total alarms over the 120 days, with an average of 16.8 total alarms per dog. 4 / 77 dogs (5%) did not generate any total alarms, meaning they did not generate scratching or shaking alarms during the study period. The dogs that did not generate alarms were from the allergic dermatitis group (n=2), the atopic dermatitis group (n=1), and the otitis externa group (n=1). Over the study period, 73 / 77 (95%) dogs generated 1 or more alarms. The allergic dermatitis dogs had the highest proportion of 1-10 total alarms, while the atopic dermatitis dogs had the highest proportion of 11-20 total alarms, which is similar to the pattern we saw when we looked at scratching alarms alone.

[0631] Table 21 shows the total alerts generated by skin disease diagnosis:

[0632]

[0633] On average, dogs with allergic dermatitis generated slightly more than half the scratch alarms generated by dogs with atopic dermatitis (63%; 5.6 / 8.9), but the average number of shiver alarms was similar (9.2 vs. 8.3).

[0634] Table 22 shows the average number of alerts by dermatological diagnosis over a 120-day period:

[0635] n Scratch alarm Shiver Alert Total Alarm Allergic dermatitis 39 5.6 9.2 14.7 Atopic dermatitis 30 8.9 8.3 17.3 external otitis 6 5.5 10.5 16.0 Suspected allergy 2 9.0 1.0 10.0

[0636] It should be understood that the subject matter of the present disclosure is not limited in its application to the details set forth in the description contained herein or the details shown in the accompanying drawings. The subject matter of the present disclosure can have other embodiments and can be practiced and executed in various ways. Therefore, it should be understood that the wording and terminology adopted herein are for descriptive purposes and should not be regarded as limiting. Therefore, those skilled in the art will recognize that the concepts on which the present disclosure is based can be easily used as a basis for designing other structures, methods and systems to perform several purposes of the subject matter of the present disclosure.

[0637] It will also be understood that the system according to the subject matter of the present disclosure can be implemented at least in part as a suitably programmed computer. Likewise, the subject matter of the present disclosure foresees a computer program readable by a computer for performing the disclosed method. The subject matter of the present disclosure also foresees a machine-readable memory tangibly embodying a machine-executable program of instructions for performing the disclosed method.

Claims

1. A system for identifying anomalies in the behavior of a non-human animal, the system comprising a processing circuit configured to: providing a behavioral baseline, the behavioral baseline comprising first information about normal behavior of the non-human animal during a given period of time without abnormality occurring; obtaining data regarding a series of consecutively identified behaviors of the non-human animal identified during a second time period; An action is performed when the data does not conform to the behavioral baseline, thereby indicating an abnormality in the non-human animal's behavior.

2. The system according to claim 1, wherein for each normal behavior, the information about the normal behavior comprises: (a) an indication of the type of behavior, and (b) one or more of the following: (i) a normal range of frequencies for the behavior, (ii) a normal range of durations for the behavior, (iii) a normal range of intensities for the behavior, (iv) a normal range of scores calculated for the behavior. 3 . The system of claim 1 , wherein the processing circuit is further configured to analyze the data to determine a cause of the anomaly.

4. The system of claim 3, wherein the cause is one or more of: itching, heart problems, nervous system problems, obesity, diabetes, separation anxiety, arthritis, ear inflammation, musculoskeletal problems.

5. The system of claim 1, wherein the continuously identified behavior is determined based on an analysis of three-dimensional (3D) accelerometer data acquired by a 3D accelerometer included in a device attached to the non-human animal.

6. A system according to claim 1, wherein the behavioral baseline is an animal-specific behavioral baseline determined using baseline creation data, wherein the baseline creation data includes a baseline series of continuously identified baseline behaviors of the non-human animal identified within a third time period during which the non-human animal is considered to behave normally.

7. The system of claim 1, wherein the action is triggering an alarm to a caregiver of the non-human animal.

8. The system of claim 7, wherein the caregiver is an owner of the non-human animal, a veterinarian of the non-human animal, or a trainer of the non-human animal.

9. The system of claim 7, wherein the alert includes an indication of a potential cause of the anomaly.

10. The system of claim 1, wherein the normal behavior and the continuously identified behavior include one or more of: shivering, grooming, scratching, resting, sleeping, high activity, moderate activity, low activity, barking, calorie burning, walking, running, sitting, lying down, jumping, chewing, sniffing, or licking.

11. The system of claim 1, wherein the information about the normal behavior includes a sleep score.

12. The system of claim 1, wherein the processing circuit is further configured to provide one or more abnormality prevention recommendations to a caregiver of the non-human animal based on historical behavioral data associated with the non-human animal.

13. A system for monitoring the effectiveness of a treatment for one or more causes of abnormality in behavior of a non-human animal, the system comprising processing circuitry configured to: providing a behavioral baseline, the behavioral baseline comprising first information about normal behavior of the non-human animal during a given period of time without abnormality occurring; obtaining second information of a second series of successively identified behaviors of the non-human animal identified within a second time period after applying the treatment to the non-human animal; An action is performed when a trend of one or more parameters calculated based on the second information does not converge to the behavioral baseline.

14. The system according to claim 13, wherein for each normal behavior, the first information about the normal behavior comprises: (a) an indication of the type of behavior, and (b) one or more of the following: (i) a normal range of frequencies for the behavior, (ii) a normal range of durations for the behavior, (iii) a normal range of intensities for the behavior, (iv) a normal range of scores calculated for the behavior.

15. The system of claim 13, wherein the continuously identified behavior is determined based on analysis of three-dimensional (3D) accelerometer data acquired by a 3D accelerometer included in a device attached to the non-human animal.

16. A system according to claim 13, wherein the behavioral baseline is an animal-specific behavioral baseline determined using baseline creation data, the baseline creation data including a baseline series of continuously identified baseline behaviors of the non-human animal identified within a third time period during which the non-human animal is considered to behave normally.

17. The system of claim 13, wherein the action is triggering an alarm to a caregiver of the non-human animal.

18. The system of claim 17, wherein the caregiver is an owner of the non-human animal, a veterinarian of the non-human animal, or a trainer of the non-human animal.

19. The system of claim 13, wherein the normal behavior and the continuously identified behavior include one or more of: shivering, grooming, scratching, resting, sleeping, high activity, moderate activity, low activity, barking, calorie burning, walking, running, sitting, lying down, jumping, chewing, sniffing, or licking.

20. The system of claim 13, wherein the first information about the normal behavior comprises a sleep score.

21. A system for monitoring the effectiveness of a treatment for one or more causes of abnormality in behavior of a non-human animal, the system comprising processing circuitry configured to: providing a successful treatment behavior baseline comprising first information regarding normal behavior of the non-human animal over a plurality of time periods after application of treatment for the one or more causes of abnormality in the behavior of the non-human animal; obtaining second information of a series of consecutively identified behaviors of the non-human animal identified within a given time period after applying a pruritus-causing infection treatment to the non-human animal; An action is performed when the series of consecutively identified behaviors of the non-human animal during a time period in the time period corresponding to the given time period does not meet the successful treatment behavior baseline.

22. The system according to claim 21, wherein for each normal behavior, the first information about the normal behavior comprises: (a) an indication of the type of behavior, and (b) one or more of the following: (i) a normal range of frequencies for the behavior, (ii) a normal range of durations for the behavior, (iii) a normal range of intensities for the behavior, (iv) a normal range of scores calculated for the behavior.

23. The system of claim 21, wherein the continuously identified behavior is determined based on analysis of three-dimensional (3D) accelerometer data acquired by a 3D accelerometer included in a device attached to the non-human animal.

24. A system according to claim 21, wherein the successful treatment behavior baseline is an animal-specific successful treatment behavior baseline determined using baseline creation data, the baseline creation data including a baseline series of continuously identified baseline behaviors of the non-human animal identified within a third time period after applying the treatment to the one or more causes of the abnormality in the behavior of the non-human animal.

25. The system of claim 21, wherein the action is triggering an alarm to a caregiver of the non-human animal.

26. The system of claim 25, wherein the caregiver is an owner of the non-human animal, a veterinarian of the non-human animal, or a trainer of the non-human animal.

27. The system of claim 21, wherein the normal behavior and the continuously identified behavior include one or more of: shivering, grooming, scratching, resting, sleeping, high activity, moderate activity, low activity, barking, calorie burning, walking, running, sitting, lying down, jumping, chewing, sniffing, or licking.

28. The system of claim 21, wherein the first information about the normal behavior comprises a sleep score.

29. A method for identifying anomalies in the behavior of a non-human animal, the method comprising: providing, by the processing circuit, a behavioral baseline, the behavioral baseline comprising first information regarding normal behavior of the non-human animal within a given time period without abnormality occurring; obtaining, by the processing circuit, data regarding a series of consecutively identified behaviors of the non-human animal identified during a second time period; An action is performed by the processing circuit when the data does not conform to the behavioral baseline, thereby indicating an abnormality in the behavior of the non-human animal.

30. The method of claim 29, wherein for each normal behavior, the information about the normal behavior comprises: (a) an indication of the type of behavior, and (b) one or more of the following: (i) a normal range of frequencies for the behavior, (ii) a normal range of durations for the behavior, (iii) a normal range of intensities for the behavior, (iv) a normal range of scores calculated for the behavior.

31. The method of claim 30, further comprising analyzing, by the processing circuitry, the data to determine a cause of the anomaly.

32. The method of claim 31, wherein the cause is one or more of: itching, heart problems, nervous system problems, obesity, diabetes, separation anxiety, arthritis, ear inflammation, musculoskeletal problems.

33. The method of claim 29, wherein the continuously identified behavior is determined based on an analysis of three-dimensional (3D) accelerometer data acquired by a 3D accelerometer included in a device attached to the non-human animal.

34. The method of claim 29, wherein the behavioral baseline is an animal-specific behavioral baseline determined using baseline creation data, the baseline creation data comprising a baseline series of continuously identified baseline behaviors of the non-human animal identified over a third time period during which the non-human animal is considered to behave normally.

35. The method of claim 29, wherein the action is triggering an alarm to a caregiver of the non-human animal.

36. The method of claim 35, wherein the caregiver is an owner of the non-human animal, a veterinarian of the non-human animal, or a trainer of the non-human animal.

37. The method of claim 35, wherein the alert includes an indication of a potential cause of the anomaly.

38. The method of claim 29, wherein the normal behavior and the continuously identified behavior include one or more of: shivering, grooming, scratching, resting, sleeping, high activity, moderate activity, low activity, barking, calorie burning, walking, running, sitting, lying down, jumping, chewing, sniffing, or licking.

39. The method of claim 29, wherein the information about the normal behavior includes a sleep score.

40. The method of claim 29, further comprising providing, by the processing circuit, one or more abnormality prevention recommendations to a caregiver of the non-human animal based on historical behavioral data associated with the non-human animal.

41. A method for monitoring the effectiveness of a treatment for one or more causes of abnormality in behavior of a non-human animal, the method comprising: providing, by the processing circuit, a behavioral baseline, the behavioral baseline comprising first information regarding normal behavior of the non-human animal within a given time period without abnormality occurring; obtaining, by the processing circuit, second information of a second series of consecutively identified behaviors of the non-human animal identified within a second time period after applying the treatment to the non-human animal; An action is performed, by the processing circuit, when a trend of one or more parameters calculated based on the second information does not converge to the behavioral baseline.

42. The method according to claim 41, wherein for each normal behavior, the first information about the normal behavior comprises: (a) an indication of the type of behavior, and (b) one or more of the following: (i) a normal range of frequencies for the behavior, (ii) a normal range of durations for the behavior, (iii) a normal range of intensities for the behavior, (iv) a normal range of scores calculated for the behavior.

43. The method of claim 41, wherein the continuously identified behavior is determined based on an analysis of three-dimensional (3D) accelerometer data acquired by a 3D accelerometer included in a device attached to the non-human animal.

44. A method according to claim 41, wherein the behavioral baseline is an animal-specific behavioral baseline determined using baseline creation data, wherein the baseline creation data includes a baseline series of continuously identified baseline behaviors of the non-human animal identified within a third time period during which the non-human animal is considered to behave normally.

45. The method of claim 41, wherein the action is triggering an alarm to a caregiver of the non-human animal.

46. ​​The method of claim 45, wherein the caregiver is an owner of the non-human animal, a veterinarian of the non-human animal, or a trainer of the non-human animal.

47. The method of claim 41, wherein the normal behavior and the continuously identified behavior include one or more of: shivering, grooming, scratching, resting, sleeping, high activity, moderate activity, low activity, barking, calorie burning, walking, running, sitting, lying down, jumping, chewing, sniffing, or licking.

48. The method of claim 41, wherein the first information about the normal behavior comprises a sleep score.

49. A method for monitoring the effectiveness of a treatment for one or more causes of abnormality in behavior of a non-human animal, the method comprising: providing, by processing circuitry, a successful treatment behavior baseline comprising first information regarding normal behavior of the non-human animal over a plurality of time periods after application of treatment for the one or more causes of abnormality in the behavior of the non-human animal; obtaining, by the processing circuit, second information of a series of consecutively identified behaviors of the non-human animal identified within a given time period after applying a pruritus-causing infection treatment to the non-human animal; An action is performed by the processing circuit when the series of consecutively identified behaviors of the non-human animal during a time period in the time period corresponding to the given time period does not meet the successful treatment behavior baseline.

50. The method according to claim 49, wherein for each normal behavior, the first information about the normal behavior comprises: (a) an indication of the type of behavior, and (b) one or more of the following: (i) a normal range of frequencies for the behavior, (ii) a normal range of durations for the behavior, (iii) a normal range of intensities for the behavior, (iv) a normal range of scores calculated for the behavior.

51. The method of claim 49, wherein the continuously identified behavior is determined based on an analysis of three-dimensional (3D) accelerometer data acquired by a 3D accelerometer included in a device attached to the non-human animal.

52. A method according to claim 49, wherein the successful treatment behavior baseline is an animal-specific successful treatment behavior baseline determined using baseline creation data, wherein the baseline creation data includes a baseline series of continuously identified baseline behaviors of the non-human animal identified within a third time period after applying the treatment to the one or more causes of the abnormality in the behavior of the non-human animal.

53. The method of claim 49, wherein the action is triggering an alarm to a caregiver of the non-human animal.

54. The method of claim 53, wherein the caregiver is an owner of the non-human animal, a veterinarian of the non-human animal, or a trainer of the non-human animal.

55. The method of claim 49, wherein the normal behavior and the continuously identified behavior include one or more of: shivering, grooming, scratching, resting, sleeping, high activity, moderate activity, low activity, barking, calorie burning, walking, running, sitting, lying down, jumping, chewing, sniffing, or licking.

56. The method of claim 49, wherein the first information about the normal behavior comprises a sleep score.

57. A non-transitory computer readable storage medium having computer readable program code embodied therewith, the computer readable program code being executable by at least one processing circuit of a computer to perform a method for identifying anomalies in behavior of a non-human animal, the method comprising: providing, by the processing circuit, a behavioral baseline, the behavioral baseline comprising first information about normal behavior of the non-human animal within a given time period without abnormality; obtaining, by the processing circuit, data regarding a series of consecutively identified behaviors of the non-human animal identified during a second time period; An action is performed by the processing circuit when the data does not conform to the behavioral baseline, thereby indicating an abnormality in the behavior of the non-human animal.

58. A non-transitory computer readable storage medium having computer readable program code embodied therewith, the computer readable program code being executable by at least one processing circuit of a computer to perform a method for monitoring the effectiveness of a treatment for one or more causes of abnormality in behavior of a non-human animal, the method comprising: providing, by the processing circuit, a behavioral baseline, the behavioral baseline comprising first information about normal behavior of the non-human animal within a given time period without abnormality; obtaining, by the processing circuit, second information of a second series of consecutively identified behaviors of the non-human animal identified within a second time period after applying the treatment to the non-human animal; An action is performed, by the processing circuit, when a trend of one or more parameters calculated based on the second information does not converge to the behavioral baseline.

59. A non-transitory computer readable storage medium having computer readable program code embodied therewith, the computer readable program code being executable by at least one processing circuit of a computer to perform a method for monitoring the effectiveness of a treatment for one or more causes of abnormality in behavior of a non-human animal, the method comprising: providing, by the processing circuit, a successful treatment behavior baseline comprising first information regarding normal behavior of the non-human animal over a plurality of time periods after application of treatment for the one or more causes of abnormality in the behavior of the non-human animal; obtaining, by the processing circuit, second information of a series of consecutively identified behaviors of the non-human animal identified within a given time period after applying a pruritus-causing infection treatment to the non-human animal; An action is performed by the processing circuit when the series of consecutively identified behaviors of the non-human animal during a time period in the time period corresponding to the given time period does not meet the successful treatment behavior baseline.

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