NZ726936B2 - Systems and methods for providing animal health, nutrition, and/or wellness recommendations - Google Patents
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- NZ726936B2 NZ726936B2 NZ726936A NZ72693615A NZ726936B2 NZ 726936 B2 NZ726936 B2 NZ 726936B2 NZ 726936 A NZ726936 A NZ 726936A NZ 72693615 A NZ72693615 A NZ 72693615A NZ 726936 B2 NZ726936 B2 NZ 726936B2
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Classifications
-
- A—HUMAN NECESSITIES
- A01—AGRICULTURE; FORESTRY; ANIMAL HUSBANDRY; HUNTING; TRAPPING; FISHING
- A01K—ANIMAL HUSBANDRY; AVICULTURE; APICULTURE; PISCICULTURE; FISHING; REARING OR BREEDING ANIMALS, NOT OTHERWISE PROVIDED FOR; NEW BREEDS OF ANIMALS
- A01K1/00—Housing animals; Equipment therefor
-
- G—PHYSICS
- G09—EDUCATION; CRYPTOGRAPHY; DISPLAY; ADVERTISING; SEALS
- G09B—EDUCATIONAL OR DEMONSTRATION APPLIANCES; APPLIANCES FOR TEACHING, OR COMMUNICATING WITH, THE BLIND, DEAF OR MUTE; MODELS; PLANETARIA; GLOBES; MAPS; DIAGRAMS
- G09B19/00—Teaching not covered by other main groups of this subclass
-
- G—PHYSICS
- G09—EDUCATION; CRYPTOGRAPHY; DISPLAY; ADVERTISING; SEALS
- G09B—EDUCATIONAL OR DEMONSTRATION APPLIANCES; APPLIANCES FOR TEACHING, OR COMMUNICATING WITH, THE BLIND, DEAF OR MUTE; MODELS; PLANETARIA; GLOBES; MAPS; DIAGRAMS
- G09B19/00—Teaching not covered by other main groups of this subclass
- G09B19/0092—Nutrition
-
- G—PHYSICS
- G09—EDUCATION; CRYPTOGRAPHY; DISPLAY; ADVERTISING; SEALS
- G09B—EDUCATIONAL OR DEMONSTRATION APPLIANCES; APPLIANCES FOR TEACHING, OR COMMUNICATING WITH, THE BLIND, DEAF OR MUTE; MODELS; PLANETARIA; GLOBES; MAPS; DIAGRAMS
- G09B5/00—Electrically-operated educational appliances
- G09B5/02—Electrically-operated educational appliances with visual presentation of the material to be studied, e.g. using film strip
-
- G—PHYSICS
- G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
- G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
- G16H20/00—ICT specially adapted for therapies or health-improving plans, e.g. for handling prescriptions, for steering therapy or for monitoring patient compliance
- G16H20/60—ICT specially adapted for therapies or health-improving plans, e.g. for handling prescriptions, for steering therapy or for monitoring patient compliance relating to nutrition control, e.g. diets
-
- G—PHYSICS
- G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
- G16Z—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS, NOT OTHERWISE PROVIDED FOR
- G16Z99/00—Subject matter not provided for in other main groups of this subclass
Abstract
The present disclosure is directed to systems and methods for preparing nutrition, health, and/or wellness recommendations for an animal. The systems and methods involve collecting data from the animal, analyzing the data, and providing the nutrition, health, and/or wellness recommendation based upon the analyzed data. n the analyzed data.
Description
SYSTEMS AND METHODS FOR PROVIDING ANIMAL HEALTH, NUTRITION,
AND/OR WELLNESS RECOMMENDATIONS
CROSS-REFERENCE TO RELATED APPLICATIONS
This application claims priority to U.S. Provisional Patent
Application No. 62/021,763, the contents of which are incorporated herein by
reference in their entireties.
FIELD OF THE DISCLOSURE
The present disclosure generally relates to systems and
methods for the provision of recommendations on improved nutrition, health,
and/or wellness protocols using animal health, behavior, and/or environmental
information.
BACKGROUND
Various approaches for animal health and behavior monitoring
are known in the art. However, most approaches do not provide adequate
interpretation of the data derived from such monitored data, nor is the
interpretation communicated to the appropriate individuals in the form of insights
about, and recommendations for, the animal.
SUMMARY OF THE DISCLOSURE
Among the various aspects of the present disclosure is the
provision of methods of preparing a nutrition, health, and/or wellness
recommendation for an animal. The recommendation (which may be, for
example, in the form of a diet, exercise, medication/supplement, treatment
protocol, and/or changes in animal owner and/or animal behavior), is prepared
based upon data collected from the animal.
Briefly, therefore, the present disclosure is directed to a method
of preparing a nutrition, health, and/or wellness recommendation for an
animal. The method comprises collecting the data from the animal, analyzing
the data, and providing the nutrition, health, and/or wellness recommendation
based upon the analyzed data. Preferably, the collected data is one or more of a
health, diet, behavior, or environmental parameter of the animal.
The present disclosure is also directed to systems and methods
(including computer-implemented systems and methods) of preparing a nutrition,
health, and/or wellness recommendation for an animal as substantially described
herein.
Other objects and features will be in part apparent and in part
pointed out hereafter.
BRIEF DESCRIPTION OF THE DRAWINGS
These and other features, aspects and advantages of the
disclosure will become more fully apparent from the following detailed
description, appended claims, and accompanying drawings, wherein the
drawings illustrate features in accordance with exemplary aspects of the
disclosure, and wherein:
illustrates a flowchart depicting exemplary embodiments
used in preparing nutrition, health, and/or wellness recommendations for an
animal in accordance with the present disclosure.
illustrates exemplary animal sensing and/or monitoring
devices for use in the systems and methods described herein.
illustrates a diagram of a mobile system comprising a
mobile module for permitting a user to communicate remotely with the animal
sensing and/or monitoring devices.
illustrates a computer suitable for implementing an
embodiment of the monitoring system.
illustrates a representative block diagram of the
elements of the computer of
illustrates a sample schematic of a mobile device at
which the mobile module can be implemented.
illustrates an exemplary user profile display of the mobile
module.
illustrates an exemplary animal profile display of the
mobile module.
FIGS. 9A-9G illustrate an animal settings display of the mobile
module.
illustrates an exemplary device profile display of the
mobile module.
illustrates an exemplary help/support display of the
mobile module.
FIGS. 12A-12C illustrate exemplary dashboard displays of the
mobile module.
FIGS. 13A-13E illustrate exemplary data stream displays of the
mobile module.
FIGS. 14A-14B illustrate exemplary notification displays of the
mobile module.
FIGS. 15-23 illustrate data collected using exemplary systems
and methods disclosed herein.
For simplicity and clarity of illustration, the drawing figures
illustrate the general manner of construction, and descriptions and details of
well-known features and techniques may be omitted to avoid unnecessarily
obscuring the present disclosure. Additionally, elements in the drawing figures
are not necessarily drawn to scale. For example, the dimensions of some of the
elements in the figures may be exaggerated relative to other elements to help
improve understanding of embodiments of the present disclosure. The same
reference numerals in different figures denote the same elements.
The present disclosure has been described herein with
reference to various exemplary embodiments. However, those skilled in the art
will recognize that changes in modifications can be made to the exemplary
embodiments without departing from the scope of the present disclosure. As
used herein, the terms “comprises,” “comprising,” “includes,” “including” and/or
any other variation thereof, are intended to cover a non-exclusive inclusion, such
that a system, process, method, article, and/or apparatus that comprises a list of
elements does not include only those elements but can include other elements
not expressly listed and/or inherent to such system, process, method, article,
and/or apparatus. Further, no element described herein is required for the
practice of the disclosure unless expressly described, e.g., as “essential” and/or
“critical.”
It must also be noted that, as used in this specification and the
appended claims, the singular forms “a,” “an” and “the” include plural referents
unless the content clearly dictates otherwise.
Unless defined otherwise, all technical and scientific terms used
herein have the same meaning as commonly understood by one of ordinary skill
in the art to which the disclosure pertains. Although a number of methods and
materials similar or equivalent to those described herein can be used in the
practice of the present disclosure, certain preferred materials and methods are
described herein.
The terms “first,” “second,” “third,” “fourth,” and the like in the
description and in the claims, if any, are used for distinguishing between similar
elements and not necessarily for describing a particular hierarchical, sequential,
or chronological order. It is to be understood that the terms so used are
interchangeable under appropriate circumstances such that the embodiments
described herein are, for example, capable of operation in sequences other than
those illustrated or otherwise described herein. Furthermore, the terms
“comprise,” “include,” and “have,” and any variations thereof, are intended to
cover a non-exclusive inclusion, such that a process, method, system, article,
device, or apparatus that comprises a list of elements is not necessarily limited
to those elements, but may include other elements not expressly listed or
inherent to such process, method, system, article, device, or apparatus.
The terms “left,” “right,” “front,” “back,” “top,” “bottom,” “over,”
“under,” and the like in the description and in the claims, if any, are used for
descriptive purposes and not necessarily for describing permanent relative
positions. It is to be understood that the terms so used are interchangeable
under appropriate circumstances such that the embodiments described herein
are, for example, capable of operation in other orientations than those illustrated
or otherwise described herein.
The terms “couple,” “coupled,” “couples.” “coupling,” and the
like should be broadly understood and refer to connecting two or more elements
or signals, electrically, mechanically, or otherwise. Two or more electrical
elements may be electrically coupled, but not mechanically or otherwise coupled;
two or more mechanical elements may be mechanically coupled, but not
electrically or otherwise coupled; two or more electrical elements may be
mechanically coupled, but not electrically or otherwise coupled. Coupling
(whether mechanical, electrical, or otherwise) may be for any length of time, e.g.,
permanent or semi-permanent or only for an instant.
“Electrical coupling” and the like should be broadly understood
and include coupling involving any electrical signal, whether a power signal, a
data signal, and/or other types or combinations of electrical signals. “Mechanical
coupling” and the like should be broadly understood and include mechanical
coupling of all types. The absence of the word “removably,” “removable,” and
the like near the word “coupled,” and the like does not mean that the coupling,
etc. in question is or is not removable.
DETAILED DESCRIPTION
In general, the systems and methods described herein involve
the collection, analysis, and/or use of animal data to provide recommendations
to the appropriate individuals (e.g., the owner/caretaker of the animal, veterinary
personnel, etc.) on improving the overall nutrition, health, and wellness of the
animal. As described herein, this data and its analysis can provide meaningful
outcomes, insights, and advice about the animal that enable the individual to
take recommended steps to improve the well-being of the animal. Through a
variety of data collection techniques, discussed in detail below, various data
regarding the animal can be generated and advice and recommendations can be
communicated to the individual (or a group of individuals) to enhance the
nutrition, health, and wellness profile of the animal.
A general framework of the systems and methods described
herein is illustrated in As shown, various animal data 2 is combined with
expert analytics 4 to provide the nutrition, health, and/or wellness
recommendations for the animal. Such data and recommendations can be
stored 8 as described herein. Further, personalized user experiences and
information presentation 10 are provided, e.g., by way of mobile modules in a
mobile device, described below. This may also facilitate communication and
information sharing 12 with health professionals. These various components are
described in detail herein.
The data being acquired can be categorized into a range of
data types. For instance, and as discussed in further detail below, the data can
be provided by an individual (e.g., owner, caretaker, or veterinary personnel)
based upon observation or personal knowledge, or may be derived from sensor
or measurement technology placed on or around the animal or at locations the
animal frequents (e.g., collar/leash, feeding/water stations, litter box, etc.); that
is, the animal’s environment. All data that is collected becomes resident in a
common data structure (whether specific for the particular animal or across a
broader spectrum of breeds or types of animal).
The data is analyzed using various algorithms, formulas, and
calculations which, in essence, codify fundamental expert knowledge and
applied science and research regarding health, nutrition, and wellness
characteristics of animals, as well as predictive analytics, to create a system that
is capable of continuously screening the new data and comparing it to historically
derived data. In this way, important and meaningful outcomes, insights, and
predictions can be identified and communicated to the relevant individuals.
It will be understood that various mathematical and algorithmic
techniques, such as bivariate, multivariate and trend analysis, may be used in
the analysis of the collected data. The combination of raw data collected over
time and processed (derived) data accumulated over time for each animal can
be used to develop a profile of nutrition, health, and/or wellness of the animal.
Other examples may involve the use of various mathematical and algorithmic
techniques, such as calculation of a covariance matrix and further application of
Kalman filter for tracking the mean and covariance of an evolving process and
atypical deviations from baselines. Other particular examples include causal
conditional-type algorithms (e.g., if X then Y, where X is a cause of Y) and
conditional probability-type algorithms (e.g., the probability of an event A that
another event B has occurred). Further trend analysis can be used to assess
whether an atypical variation is random or whether a trend is developing.
As noted, the algorithms are capable of continuously analyzing
and assessing the data to produce predictive outcomes or results of the data
analysis. The outcomes of these algorithmic and predictive analytics-based
calculations may then be further screened and analyzed through expert
knowledge and applied science to provide the nutrition, health, and/or wellness
recommendations. It will be understood that some outcomes, and therefore
recommendations, will be identified as being of higher importance than others.
For example, outcomes, insights, and recommendations can range from
irrelevant (and perhaps even unworthy of recommendation) to highly significant
or critical (and perhaps worthy of an alert due to a high perceived risk to the
animal). Many outcomes, insights, and recommendations will fall between these
two extremes to provide meaningful advice to improve animal nutrition, health,
and/or wellness. As will be discussed in further detail below, this may include
recommended dietary changes based on a perceived health risk, suggested
exercise plans based on perceived behavioral issues, and the like.
Outcomes and insights, and therefore recommendations,
having little or no relevance may or may not be communicated to the appropriate
individual. Those generating relevance, on the other hand, will be queued within
the system for communication to the appropriate individual when/if appropriate.
It will be understood that the individual may have the ability within the system to
set threshold boundaries for the type and level of insights that they deem
relevant or not. Outcomes, insights, and recommendations viewed as highly
relevant or alert-worthy can be prioritized for immediate notification to the
appropriate individual(s). It is also envisioned that multiple individuals could be
notified of high relevance outcomes and recommendations (e.g., the animal
owner/caretaker and the animal’s veterinarian). Communications to the
individual(s) may be made via software web-based or applications, e-mail, text,
phone, or any other forms of electronic communication. For less than highly or
materially relevant outcomes and recommendations, the individual(s) may
receive a report from the system on a daily, weekly monthly, or yearly basis, or
other relevant time frame.
Engagement of the individuals with and to the system can also
be via web-based or software applications, e-mail, text, phone, and other
relevant forms of electronic communication. This may also include interactive
websites and social or peer-to-peer media applications and protocols. In this
way, the individual can have the ability to tailor the user experience and
preferences to fit their and the animal’s needs. As discussed in further detail
below, general categories of, feedback and/or recommendations include any
number of nutrition, health, and wellness aspects of the animal. This may
include, for example, general health characteristics and levels of risk; behavior
aspects such as meaningful patterns and training/modification advice, including
recommended changes in animal owner and/or animal behavior; activity aspects
including meaningful patterns and modification advice; nutritional aspects
including what and how to feed the animal and other general and specific advice
and product recommendations for the animal; alerts and other notifications of
any high-risk and/or critical outcomes and recommendations; and packaging of
data and reports for use in conjunction with veterinary visits.
The systems and methods can also be configured to
communicate with the appropriate individual, for example, by an alert or other
message. The message or alert can correspond, for example, to a particular
event or sequence of events observed by the collected data, or to the breach of
a threshold(s) (either by reaching, exceeding, or falling below a threshold
value(s) or condition(s)), whether predetermined or set by the user, for either
collected or analyzed data. A message or alert can then be sent when the
threshold data has been met. Communications of or about the message or alert
may be sent to the individual(s) via software web-based or applications, e-mail,
text, phone, or any other forms of electronic communication, and typically those
with instant or relatively prompt access by the individual(s) such as phone, text,
or e-mail.
It will be understood that any animal (and its owner) can be the
intended beneficiary of the systems and methods described herein. Thus, the
animal may be a companion animal such as dogs and cats, a farm animal such
as cows, horses, swine, as well as birds and exotic animal such as zoo animals.
In one particular embodiment, the animal is a dog or a cat. In another particular
embodiment, the animal is a dog, a cat, or a multiple or combination thereof.
ANIMAL DATA
As discussed above, the outcomes and recommendations for
improving or enhancing the nutrition, health, and or wellness of the animal are
determined using various data 2 collected from the animal (. This can
involve any one or more characteristics, or parameters, exhibited or possessed
by the animal, or otherwise present in connection with the animal (such as
environmental factors), In a particular embodiment, the foregoing analysis is
performed on one or more of a health, diet, behavior, and environmental
parameter of the animal.
Representative health parameters of the animal may include,
for example, age; sex; gender; species or breed; body weight; body mass index
(BMI); body composition; body condition score; body temperature; gait force;
reproductive aspects (e.g., estrus, spay/neuter status, etc.); skin and coat
condition; UV exposure; cardiovascular system (e.g., heart rate); respiratory
system (e.g., respiration rate); gastrointestinal and kidney functions (e.g., fecal
composition, urine chemistry, etc.); vision, cognitive health; combinations
thereof; and the like.
Representative diet parameters of the animal may include, for
example, food and water consumption including amounts and time of day;
nutritional composition or profile of the food consumed; vitamin, supplement,
and/or medication consumption; combinations thereof; and the like.
Representative behavior parameters of the animal may include,
for example, activity profiles (e.g., calories burned, steps or distance traveled,
intensity levels, changes in elevation, and time of day information); elimination
activity including frequency, amount, and time of day information; vocalization
(e.g., barking, meowing, and other sounds that can indicate animal dispositions);
combinations thereof; and the like.
Representative environmental parameters of the animal may
include, for example, weather information (e.g., air temperature, humidity, heat
index, precipitation, etc.); location coordinates of animal; location coordinates of
food/water/waste container/sleeping or resting locations/etc.; presence or
absence of owner/caretaker at the location; presence or absence of
children/elderly at the location; combinations thereof; and the like.
Taken as a whole, therefore, exemplary animal data may
include, for example, any observable measure of the health or physical state of
an animal determined by various means, and may be quantitative or qualitative,
such as a weight of an animal, a weight of a waste deposited by an animal in a
waste container, a body temperature of an animal, the weight of a platform
before the presence of the animal is detected, the combined weight of the
platform and the animal after the presence of the animal was detected, the
weight of a platform after the departure of the animal was detected, the weight of
the food consumed by the animal, the weight of the water consumed by the
animal, the date when presence of the animal is detected, the time when
presence of the animal is detected, the time when departure of the animal is
detected, the duration of time between detection of the presence of the animal
and the departure of the animal, a tip of the nose temperature of an animal, an
ear temperature of an animal, an anal temperature of an animal, a height of an
animal, a video or a picture or plurality thereof of an animal, a video or a picture
or plurality thereof of animal body parts such as a face, an eye, eyes, parts of a
skin, a paws, a video or a picture or plurality thereof of a waste container, a
video or a picture or plurality thereof of a waste left by an animal, a video or a
picture or plurality thereof of a substance in a waste container, a voice recording
for the duration of animal's presence inside a waste container, a result of
chemical, biological or biochemical analysis, the daily frequency with which
presence of the animal is detected, the cumulative daily weight of the animal's
waste, the cumulative daily weight of the food consumed by the animal, the
cumulative daily weight of the water consumed by the animal, the average daily
weight of the animal, the maximum and the minimum daily weight of the animal,
the cumulative daily duration of time between each detection of the presence of
the animal and the departure of the animal, the average, maximum and minimum
rates of food and water consumption, expressed in weight of food and water
consumed per unit of time, the cumulative daily number of times the presence of
the animal is detected, the amount of time since the last time presence of the
animal is detected, or the average daily time interval between instances where
presence of animal is detected, and combinations and variations thereof.
In some embodiments, data on single or multiple parameters
may be collected and analyzed. Thus, in one embodiment, the data collection
and analysis may be performed on one of a health parameter, a diet parameter,
a behavior parameter, or an environmental parameter. In another embodiment,
the data collection and analysis maybe performed on two or more of a health
parameter, a diet parameter, a behavior parameter and an environmental
parameter Data collection and analysis of combinations of parameters may
therefore also be performed.
For example, the data collection and analysis may be
performed on health and diet parameters; heath and behavior parameters;
health and environmental parameters; diet and behavior parameters; diet and
environment parameters; behavior and environment parameters; health, diet,
and behavior parameters; health, diet, and environmental parameters; health,
behavior, and environment parameters; diet, behavior, and environmental
parameters; and health, diet, behavior, and environmental parameters.
It will be understood that, for a multi-animal home or dwelling, it
will in many respects be advantageous to have the ability to uniquely identify
each animal and the parameters of the same that are collect and analyzed. In
this way, the systems and methods have the ability to uniquely identify individual
animals using the same system so that the data analysis is unique to each
animal regardless of identity or even species (e.g., the possibility of having a
single system in a home that captures data for both dogs and cats). For
example, where multiple animals use a single waste container, each animal
could be identified or distinguished based upon trends or observations (such as
by weight, typical time of day of use, typical length of stay in the container,
typical amount of waste deposited, etc.). By way of another example, where
multiple animals use a single food and/or water container, each animal could be
identified or distinguished based upon trends or observations (such as by weight,
typical time of day of feeding/watering, typical length of stay at the food/water
container, typical amount of food/water consumed, etc.). By way of further
example, multiple measurement devices (e.g., including sensors) can be
employed to accommodate multiple animals, such as distinct food/water
containers, sleeping/resting locations, etc. In this way, the various systems and
methods described herein can support any combination of single or multiple
animals and single or multiple measurement/sensor devices.
Analysis of one or more of the foregoing parameters using
collected data can thereafter be used to provide predictive outcomes and
recommendations on nutrition, health, and/or wellness of the animal.
By way of example, and not by way of limitation, collected and
analyzed data regarding animal heart rate can be indicative or otherwise
informative of the animal’s stress level; the animal’s maximum/minimum heart
rate; the animal’s eating habits or food palatability; any pain experienced by the
animal; the animal’s excitement level; number of calories burned; comparative
analysis of heart rate and activity level; aerobic capacity; joint/ mobility issues;
sleep/dream tracking; presence or absence of arrhythmia; post-surgery, post-
illness or post-exercise return to baseline or normal; incident based anxiety (e.g.,
presence of the mailman or garbage truck); visitor/stranger acceptance;
combinations thereof; and the like. These collected data and analysis may, in
turn, lead to outcomes and recommendations regarding one or more of changes
in environment; initiating, limiting, or increasing exercise protocols;
administration or cessation of vitamins, supplements, or medication; initiating or
modifying training protocols; nutritional/feeding changes; veterinary visits;
combinations thereof; and the like.
By way of another example, and not by way of limitation,
collected and analyzed data regarding food consumption of the animal (including
amount and time-of-day patterns), can be indicative or otherwise informative of
the animal’s enjoyment or liking of the food; whether one animal is eating
another animal’s food (i.e., in a multi-animal house or dwelling); normal or
irregular food ingestion rates (e.g., too fast or too slow); illnesses or
gastrointestinal issues; seasonality issues (e.g., changes in patterns based on
changes in temperature); nutrient deficiencies based on amount of food
consumed; over/under feeding issues; hyper/hypophagia; combinations thereof;
and the like. These collected data and analysis may, in turn, lead to outcomes
and recommendations regarding one or more of changes in environment;
initiating, limiting, or increasing exercise protocols; administration or cessation of
vitamins, supplements, or medication; initiating or modifying training protocols;
nutritional/feeding changes; veterinary visits; combinations thereof; and the like.
By way of another example, and not by way of limitation,
collected and analyzed data regarding active minutes per day of the animal and
the timing thereof can be indicative or otherwise informative of the animal’s
Circadian rhythms; aging; general health and fitness; metabolic disease; illness
or malaise; anxious times or periods during the day; dementia or cognitive
issues; joint or mobility issues; changes in life stage (puppy/adult/senior);
effectiveness of recovery from illness/injury/surgery; effectiveness of diet and
nutrition; multiple animal household relationships; combinations thereof; and the
like. These collected data and analysis may, in turn, lead to outcomes and
recommendations regarding one or more of changes in environment; initiating,
limiting, or increasing exercise protocols; administration or cessation of vitamins,
supplements, or medication; initiating or modifying training protocols;
nutritional/feeding changes; veterinary visits; combinations thereof; and the like.
By way of another example, and not by way of limitation,
collected and analyzed data regarding number of steps taken per day by the
animal can be indicative or otherwise informative of the time of day when calorie
burn is elevated or decreased; the social ability of the animal; the total motion of
the animal; anxiety level of the animal (e.g., pacing while the owner/caretaker is
away); speed and changes in speed over time that can indicate stiffness or
joint/mobility issues; dementia and cognitive health; illness or injury in limbs;
incident based anxiety (e.g., presence of the mailman or garbage truck);
Circadian rhythms; waking/sleeping schedules; post-surgery, post-illness, or
post-exercise return to baseline or normal; rate of aging or relative age of animal,
basal metabolism; need for more physical activity; need for increased or
decreased activity or exercise; combinations thereof; and the like. These
collected data and analysis may, in turn, lead to outcomes and
recommendations regarding one or more of changes in environment; initiating,
limiting, or increasing exercise protocols; administration or cessation of vitamins,
supplements, or medication; initiating or modifying training protocols;
nutritional/feeding changes; veterinary visits; combinations thereof; and the like.
By way of another example, and not by way of limitation,
collected and analyzed data regarding the number of calories burned per day by
the animal can be indicative or otherwise informative of the animal’s metabolism;
the calories required by the animal and the amount of food/treats to provide;
particular type of food/treats to give the animal (e.g., performance or weight
management); feed/treating times of day; activity when owner/caretaker is away;
joint/mobility issues; energy expenditure; dementia or cognitive issues; increased
water needs; combinations thereof; and the like. These collected data and
analysis may, in turn, lead to outcomes and recommendations regarding one or
more of changes in environment; initiating, limiting, or increasing exercise
protocols; administration or cessation of vitamins, supplements, or medication;
initiating or modifying training protocols; nutritional/feeding changes; veterinary
visits; combinations thereof; and the like.
By way of another example, and not by way of limitation,
collected and analyzed data regarding the body weight of the animal can be
indicative or otherwise informative of changes over time (e.g., over/under weight,
over/under feeding; protein levels; by-breed comparisons; onset of illness;
gastrointestinal issues; diseases, conditions, or other health issues (e.g., thyroid
problems, tumors, etc.); energy balance; need to change foods based on life
stage (e.g., when weight plateaus in puppies, begins declining in older dogs,
etc.); effectiveness of weight loss/gain programs or diets; daily caloric needs;
resting metabolism; water/food intake; combinations thereof; and the like. These
collected data and analysis may, in turn, lead to outcomes and
recommendations regarding one or more of changes in environment; initiating,
limiting, or increasing exercise protocols; administration or cessation of vitamins,
supplements, or medication; initiating or modifying training protocols;
nutritional/feeding changes; veterinary visits; combinations thereof; and the like.
By way of another example, and not by way of limitation,
collected and analyzed data regarding water consumption of the animal can be
indicative or otherwise informative of animal hydration levels/status (e.g., as
compared to body weight to determine if hydration levels are adequate);
dehydration/salt content; diabetes or the onset thereof; the animal’s meeting of
hydration requirements; fluctuations in water consumption; the water’s use as a
media for delivery of supplements or medication; elimination behaviors; anxiety,
stress, or boredom; risks of renal crystals; when water source/container needs
replenished; seasonality; risks of renal failure; drinking frequency and changes
over time; time-of-day patterns; cleanliness of water source/container; food
consumption and type; potential consumption of inappropriate food/items;
combinations thereof; and the like. These collected data and analysis may, in
turn, lead to outcomes and recommendations regarding one or more of changes
in environment; initiating, limiting, or increasing exercise protocols;
administration or cessation of vitamins, supplements, or medication; initiating or
modifying training protocols; nutritional/feeding changes; veterinary visits;
combinations thereof; and the like.
In addition, collected data and analysis on certain parameters
can be indicative of a number of particular issues for the animal. For example,
one or more changes in animal activity; changes in rest periods/intensity;
changes in food/water consumption; changes in steps taken; changes in weight;
irregular elimination behavior; body temperature; results of blood, urine, and/or
stress tests; and combinations thereof, may be indicative or otherwise
informative of certain cancers in the animal. By way of another example,
changes in food/water consumption; changes in weight; seasonality; abnormal
scratching; hair loss; changes in appearance; and combinations thereof, may be
indicative or otherwise informative of allergies in the animal (whether food
allergies, environmental allergies, or bacterial/viral allergies). By way of another
example, changes in activity; number of steps (e.g., pacing); heart rate;
increased water intake and decreased food intake; vocalization (e.g., whining);
and combinations thereof, may be indicative or otherwise informative of anxiety,
stress, or boredom in the animal. By way of another example, the age; breed;
reproductive aspects (e.g., estrus, spay/neuter status, etc.); rest patterns; activity
patterns including number of steps and calories burned; changes in caloric
intake; changes in feeding patterns; and combinations thereof, may be indicative
of the life stage (or a change thereof) of the animal. By way of another example,
increases in water intake; increases or decreases in body weight; the age and
breed of the animal; urine color; decreases in activity; food type; and
combinations thereof, may be indicative of diabetes in the animal. These
collected data and analysis may, in turn, lead to outcomes and
recommendations regarding one or more of changes in environment; initiating,
limiting, or increasing exercise protocols; administration or cessation of vitamins,
supplements, or medication; initiating or modifying training protocols;
nutritional/feeding changes; veterinary visits; combinations thereof; and the like.
Differing combinations of collected data and analysis on certain
parameters can also be indicative of multiple issues for the animal. By way of
example, the combination of heart rate and body weight data, may be indicative
or otherwise be informative of hypertension; anorexia; hyperfusia; fitness;
exertion; anxiety, stress, or boredom of the animal. By way of another example,
the combination of heart rate, body weight, and body composition data may be
indicative or otherwise informative of aging; obesity; training deficiencies; fitness
issues; metabolic needs; and nutritional needs of the animal. By way of another
example, the combination of heart rate, body weight, and vocalization data can
be indicative or otherwise informative of anxiety, stress, or boredom, or physical
or emotional distress of the animal. By way of another example, the combination
of weight, body temperature, heart rate, and respiration data can be indicative or
otherwise informative of the overall health and well-being of the animal. By way
of another example, increased water intake of the animal can be indicative or
otherwise informative of anxiety, stress, or boredom; urinary tract issues;
increased calcium levels; liver disease; hyperthyroidism; and acute and chronic
renal issues of the animal. By way of another example, the number of calories
burned per day; resting minutes per day; steps taken per day; and location of the
animal can be indicative or otherwise informative of weight and diet issues;
metabolic issues; activity patterns; pre-disease status; baseline and adjusted
fitness and activity levels; multi-animal household issues of the animal; dementia
and cognitive issues; and the general well-being of the animal. By way of
another example, food intake, water intake, body weight and activity levels can
be indicative or otherwise informative of body mass indications; elimination
behavior; palatability of food; food/water container issues; weight gain/loss (e.g.,
due to Addison’s disease, hypothyroidism); early disease state or onset;
advanced disease states; stress patterns; renal issues; arthritis; joint/mobility
issues; training deficiencies; aging; and life stage changes of the animal. By way
of another example, food intake, water intake, number of steps taken, body
weight. and heart rate can be indicative or otherwise informative of energy
balance (e.g., by breed and/or by life stage); baseline and adjusted
happiness/contentment/satisfaction levels; changes in energy levels; disease
status; food suitability and palatability; and anxiety, stress, or boredom of the
animal. By way of another example, food intake, water intake, activity level.
body weight, age, heart rate, and body temperature can be indicative or
otherwise informative of nutrition/malnutrition issues; cancers; renal issues;
hyperthyroidism; and infectious diseases of the animal. By way of another
example, body weight, age, breed, activity levels, glucose levels, and water
intake can be indicative or otherwise informative of diabetes or onset thereof,
and musculoskeletal diseases such as hip dysplasia and osteoarthritis. These
collected data and analysis may, in turn, lead to outcomes and
recommendations regarding one or more of changes in environment; initiating,
limiting, or increasing exercise protocols; administration or cessation of vitamins,
supplements, or medication; initiating or modifying training protocols;
nutritional/feeding changes; veterinary visits; combinations thereof; and the like.
Still further examples of relevant data and analysis include one
or more of the following: the combination of heart rate and respiration rate of the
animal; urine chemistry as an indicator of physiological changes within the
animal over time; body condition scoring, e.g., whereby animal owners rate the
body condition of the animal (including, for example, providing photographs of
the animal when creating animal profiles in the mobile modules discussed
below); nutritional composition/profile of the animal’s food (including, for
example, providing photographs of the bar codes or other information on the
food they feed their animals, such that databases can be accessed to provide
the label declaration nutrition analysis on such products) which can provide
insights into the animal’s consumed nutrition levels (e.g., for comparing different
manufacturer’s products, batch analysis, etc. to determine true caloric intake and
nutrition composition levels in the animal); UV exposure and related diseases;
elevation (e.g., going up/down steps, climbing hills, etc.) and normal rate of
standing/sitting/laying changes over time as a predictor of early onset of joint
health problems; animal body temperature versus ambient temperature around
the animal. Still other examples of data include linking to weather sites,
correlating behavior of individual and multiple pets to earthquake monitoring
data, using facial recognition as a way to identify which animal is using a device
(who is eating/drinking, using the scale, using the litter box, etc.), GPS or other
location-monitoring technologies to pinpoint location of the animal (e.g., in/out of
house, etc.).
EXPERT ANALYTICS
In addition to the animal data 2, the systems and methods
disclosed herein utilize expert analytics 4 to provide more accurate and/or
meaningful recommendations regarding animal health and/or wellness. The
techniques of the present disclosure thus provide the capability to extract
informative data from the raw data, which is then collected and analyzed by
relevant human expert analysis. As depicted in for example, among the
various experts are veterinarians, physiologists, geneticists, trainers,
behaviorists, nutritionists, and data scientists.
Expert review in real-time or over an extended period of time is
used to determine the optimum therapeutic/nutritional index or recommendation
for that particular animal or animal class. For example, if a threshold level or
baseline of the collected data discussed above is breached, appropriate action
can be recommended by the expert and taken by the animal owner or other
individual. An appropriate action could be alerting the owner/individual, stopping
or starting certain medication or the like. As will be understood, the appropriate
action or recommendation for an animal would be decided based on the
collected data and the expert’s experience and judgment for that particular
animal or class of animals. In will also be understood that the expert analysis
can occur as a one-time exercise using the data set derived from the animal,
and/or as an ongoing exercise using clinical studies and/or existing clinical
information, for instance.
Thus, the expert has the ability to draw upon his or her own
experience, and also has access to additional information, e.g., historical
information within the system memory, historical information about the particular
animal from one or more accessible databases, and information about a plurality
of animals from still other databases. The expert(s) may have a variety of
control-sharing relationships with the systems and methods described herein
from complete control to provide insight or recommendations, or a sharing
arrangement in which, for example, multiple experts are able to provide insight
and recommendations in order to influence treatment or actions taken by the
user/animal owner. Further, the experts are able in some embodiments to
prepare and send analytics-generated messages (e.g., pet health and wellness
information) and system information messages within the system (e.g., via the
mobile module discussed in detail below).
ANIMAL DATA COLLECTION
The aforementioned animal health, behavior, and/or
environmental data can be collected or derived and analyzed using a number of
techniques and/or sensing/monitoring devices.
The data may be derived from qualitative observations by
animal owners/caretakers or periodic veterinary examinations. This may include
observed and recorded changes in weight, activity, food and/or water
consumption, elimination frequency and consistency, and the like, as compared
to prior observations and recordation of the same. Additionally, or alternatively,
the data can be collected on an automated basis, either continuously or and
periodic intervals, using one or more sensors associated with, for example, the
animal itself or locations frequented by the animal (e.g., food/water containers,
waste containers, frequent sleeping/resting locations, etc.) and measuring
devices.
For example, data can be continuously captured during the
entire duration of the animal’s activity inside a waste container, during food or
water consumption, sleep or rest until the animal moves away effectively
disengaging measurement. Data can also be captured by periodically sampling
a sensor or sensors, such as weight, pressure or force sensor or sensors (such
as strain gauges, load cells, piezo sensors, etc.) and converting a contiguous
(analog) electrical signal into a digital data.
Thus, a variety of sensors and measuring devices may be
utilized in the data collection step. Exemplary sensors include, but are not
limited to, accelerometers (single axis or multi-axis), gyroscopes, weighing
scales, weight transducers, force transducers, displacement transducers,
orientation sensors (e.g., compasses), pressure transducers, weight sensors,
force sensors, pedometers, displacement sensors, pressure sensors, load cells,
photographic cameras, video cameras, camcorders, RF location beacons,
contact thermometers, non-contact thermometers, such as infrared
thermometers, laser thermometers, infrared pyrometers, laser pyrometers, litters
or litter additives that change their properties, such as color, odor, outgassing,
fluorescence, luminescence, when come in contact with animal waste, either
urine or excrements. Other sensors may also be used to determine an animal’s
presence or absence at a particular location or height, such as optical sensors,
optical reflecting sensors, LED/photodiode pair optical sensors,
LED/phototransistor pair optical sensors, laser diode/photodiode pair optical
sensors, laser diode/phototransistor pair optical sensors, optocouplers, optical
fiber coupled optical sensors, magnetic sensors, weight sensors, force sensors,
displacement sensors, pressure sensors (relative/differential or absolute),
various proximity sensors, such as inductive proximity sensors, magnetic
proximity sensors, capacitive proximity sensors, global positioning system (GPS)
devices, a global navigation satellite system (GNSS) devices, and/or a
combination thereof. In general, all types of sensors and sensing techniques,
whether now known or later developed, that are capable of generating data
which is representative of motion and/or presence of an animal are intended to
fall within the scope of the present disclosure.
Particular sensor and measuring devices and methods and
systems for using the same in the collection of physiological and behavioral
animal data, and the storage and transmittal of the same, are described in U.S.
Pub. Nos. 2011/0315084; 2012/0299731; 2013/0073254; and 2013/0192526
(each of which are hereby incorporated by reference in their entirety).
For example, U.S. Pub. No. 2011/0315084 provides a cat litter
box including monitoring system that detects a cat’s behavior relative to the cat
litter box. The litter box includes an identification system, such as a radio-
frequency identification (RFID) system, in order to track individual cat activity.
As part of the monitoring, data with important health implications, such as
average trips to the litter box per a set period of time can be stored and
transmitted. User alerts may be sent if there is a significant change in behavior,
such as no visits to the litter box in a set period of time (e.g., 24 hours). The
monitoring system may also include a weight sensor, such that the litter box
store and transmit historical weight information on the cat(s) that use it. User
alerts can be sent if a weight change violates a range. The weight sensor can
also be used for the identification of individual cats and/or for the determination
of the type and quantity of waste left by a cat in the litter box. Health data can be
generated as an alert to potential underlying health problems, such as kidney
disease or diabetes, historical weight information as an early indicator of an
underlying disease, or lack of litter box activity which could indicate isolation from
the litter box (e.g., locked in a separate area of a home, sick and/or injured, etc.).
By way of another example, U.S. Pub. No. 2012/0299731
provides a waste container or perch (e.g., for avian animals) comprising a scale
and other sensors to measure and/or determine characteristics of the animal
while it is disposed in the container or on the perch. Feeding and water stations
comprising scales and other sensors for measuring and/or determining
characteristics of the animal are also disclosed.
By way of another example, U.S. Pub. No. 2013/0073254
provides portable monitoring devices capable of monitoring, calculating,
determining and/or detecting energy and/or calorie “burn” due to physical
activity. The portable monitoring device is affixed to the user during operation,
and the housing of the device is of a physical size and shape that facilitates
coupling to the user via a mechanism (for example, a clip, strap and/or tie) that
facilitates coupling or affixing the device to the user and allows the user to
perform normal or typical user activities without hindering the user from
performing such activities.
By way of another example, U.S. Pub. No. 2013/0192526
provides a rover unit (i.e., a pet collar, harness, or clothing) carried by the animal
capable of detecting and transmitting physiological conditions and actions of the
animal.
Certain exemplary embodiments of sensing/measuring devices
60 are depicted in For instance, the device 60 may comprise an on-
animal monitor 60a, which may be coupled to the collar, leash, or other
accessory of the animal. On-animal devices of this type may be configured to
measure, among other things, animal surroundings, animal activity, body
temperature, ambient temperature, elevation/altitude changes, UV exposure,
and the like. Another type of device 60 comprises a nutrition/hydration station
60b, which may include one or more food and water receptacles. Devices of this
type may be configured to monitor, among other things, food and water mass
consumption, feeding/drinking event duration, eating behavior patterns, and the
like. Another type of device 60 comprises a weight monitor 60c. Devices of this
type can be placed under the animal’s kennel or sleeping/resting location, for
example, to provide real-time weight tracking. Another type of device 60
comprises a litter box activity monitor 60d, which may be positioned on or near
the animal’s waste container. Devices of this type can be configured to monitor,
among other things, activity frequency and duration of use of the waste
container. Combinations of devices 60a, 60b, 60c, and/or 60d may be used to
provide more complete packages of animal data 2. As will be understood, these
exemplary devices can therefore be equipped one or more of the various
sensors discussed above.
ANALYTICAL TECHNIQUES AND SYSTEMS
With respect to data analysis, this may include the many types
of software development methodologies and tools/program languages that exist,
such as cloud-based data architectures, “Big Data” analytics systems and
methods (e.g., via Amazon’s Elastic MapReduce (EMR) and/or Google’s I/O),
and HTML based applications (e.g., HTML5). These methodologies, tools, and
programs may be executed alone or, more preferably, in conjunction with one or
more of (1) inventor’s and applicant’s expert knowledge in animal nutrition,
health, and wellness; (2) expert knowledge of other individuals and groups in
practice and academia; (3) expert knowledge of data scientists and research and
development individuals and groups to create additional, or alternative,
predictive analytics algorithms based on the treatment of the data collected on
individual animals (i.e., data scientists associated with the applicant, as well as,
other third party groups and partners); and (4) emerging machine-learning
technologies that are capable of automating data analysis using high-speed
processors to identify significant trend and insights within the data set.
As those skilled in the art will appreciate, the various system
computing components discussed herein can include one and/or more of the
following: a host server and/or other computing systems including a processor
for processing digital data; storage or memory coupled to said processor for
storing digital data; an input digitizer coupled to the processor for inputting digital
data; an application program stored in said memory and accessible by said
processor for directing processing of digital data by said processor; a display
device coupled to the processor and memory for displaying information derived
from digital data processed by said processor; and a plurality of databases. The
computing systems can include an operating system (e.g., OS/360, MVS,
Windows NT, 95/98/2000/XP/Vista, OS2, UNIX, Unix-like, TPF, Linux, Solaris,
MacOS, Mac OS X, AIX, Google Chrome OS, Plan 9, Android, iOS, Blackberry,
Windows Phone, etc., and the like) as well as various conventional support
software and drivers typically associated with computers and mobile/smart
phone devices.
As noted above, systems for use in connection with the
methods described herein can include storage devices for storing the collected
and/or analyzed data. Such storage devices may include, for example, memory
devices, data storage devices and a combination thereof such as memory chips,
semiconductor memories, Integrated Circuits (IC's), non-volatile memories or
storage device such as flash memories, Read Only Memories (ROMs), Erasable
Read Only Memories (EROMs), Electrically Erasable Read Only Memories
(EEROMs), Erasable Programmable Read Only Memories (EPROMs),
Electrically Erasable Programmable Read Only Memories (EEPROMs), an
Electrically Erasable Programmable Read Only Memory (EEPRO), volatile
memories such as Random Access Memories (RAMs), Static Random Access
Memories (SRAMs), Dynamic Random Access Memories (DRAMs), Single Data
Rate memories (SDRs), Dual Data Rata memories (DDRs), Quad Data Rate
memories (QDR's), microprocessor registers, microcontroller registers, CPU
registers, controller registers, magnetic storage devices such as magnetic disks,
magnetic hard disks, magnetic tapes, optical memory devices such as optical
disks, compact disks (CDs), Digital Versatile Disks (DVDs), Blu-ray Disks,
Magneto Optical Disks (MO Disks), USB flash memory or other external memory
devices (e.g., portable hard drives), and/or a combination thereof.
Systems may also include a processor configured to analyze
collected data. Exemplary processors include, for example, electronic circuits,
systems, modules, subsystems, sub modules, devices and combinations thereof,
such as Central Processing Units (CPUs), microprocessors, microcontrollers,
processing units, control units, tangible media for recording and/or a
combinations thereof. It will be understood that the sensors and measuring
devices, storage devices, and processors may be assembled as a single unit, or
as multiple, standalone devices capable of communication with one another.
It will also be appreciated that the present disclosure can be
embodied as a method, a system (e.g., a data processing system), a device for
data processing, a computer program product, and/or a communications device.
Accordingly, the present disclosure can take the form of an entirely software
embodiment, an entirely hardware embodiment, and/or an embodiment
combining aspects of both software and hardware. Furthermore, the present
disclosure can take the form of a computer program product on a computer-
readable storage medium having computer-readable program code means
embodied in the storage medium. Any suitable computer-readable storage
medium can be utilized, including hard disks, CD-ROM, optical storage devices,
magnetic storage devices, and/or the like.
MOBILE MONITORING SYSTEMS
Turning again to the drawings, illustrates a diagram of
mobile animal monitoring system 1000, comprising mobile module 2000 for
permitting user 3000 to receive information regarding an animal 40 in its
environment 20. As shown, the animal environment includes one or more
sensor/measuring devices 60 as described herein. In the present embodiment,
mobile module 2000 is implemented via mobile device 4000, which is associated
with user 3000 and can be, for instance a portable or handheld electronic device
such as a cellular phone, a smartphone, a personal digital assistant (PDA),
and/or a tablet device. For instance mobile device 400 can be an electrical
device manufactured by Research in Motion Limited (e.g., a Blackberry®
device), Palm, Inc. (e.g., a Palm® device), Apple Computer, Inc. (e.g., an iPod®
MP3 player, an iPod Touch® device, an iPad® device, and/or an iPhone®
device), and/or Samsung Electronics Co. Ltd. (e.g., a Galaxy® device). In other
examples, mobile device 400 can be a portable computer (e.g., a laptop or
similar device such as those manufactured by the aforementioned, or other,
companies).
Mobile device 4000 can be configured to establish a wireless
connection 6100 with Internet 6000. Similarly, the animal data collection
device(s) 60 can be configured to communicate via Internet 6000 through
connection 6200, which may be wired or wireless. Thus, mobile device 400 and
data collection device 60 can communicate via Internet 6000. In some
examples, a portion of connection 6100 and/or of connection 6200 can be
carried out via a network configured for a wireless and/or cellular standard such
as WiFi (IEEE 802.11a/b/g/n), WiPAN (IEEE 802.15, Bluetooth®), W-CDMA
(Wideband Code Division Multiple Access), HSPA (High Speed Packet Access),
EDGE (Enhanced Data Rate for GSM Evolution), WiMAX (Worldwide
Interoperability for Microwave Access), LTE (Long Term Evolution), etc.
illustrates a computer 7000 suitable for implementing an
embodiment of mobile monitoring system 1000. Computer 7000 includes a
chassis 7020 containing one or more circuit boards (not shown), a USB
(universal serial bus) port 7120, a Compact Disc Read-Only Memory (CD-ROM)
and/or Digital Video Disc (DVD) drive 7160, and a hard drive 7140. A
representative block diagram of the elements included on the circuit boards
inside chassis 7020 is shown in A central processing unit (CPU) 8100 is
coupled to a system bus 8140 in In various embodiments, the
architecture of CPU 8100 can be compliant with any of a variety of commercially
distributed architecture families.
System bus 8120 also is coupled to memory 8080 that includes
both read only memory (ROM) and random access memory (RAM). Non-volatile
portions of memory 8080 or the ROM can be encoded with a boot code
sequence suitable for restoring computer 7000 ( to a functional state after
a system reset. In addition, memory 8080 can include microcode such as a
Basic Input-Output System (BIOS). In the depicted embodiment of
various I/O devices such as a disk controller 8040, a graphics adapter 8180, a
video controller 8020, a keyboard adapter 8200, a mouse adapter 8060, a
network adapter 8140, and other I/O devices 8160 can be coupled to system bus
8120. Keyboard adapter 8200 and mouse adapter 8060 are coupled in the
present example to keyboard 7040 and mouse 7100, respectively, of computer
7000. While graphics adapter 8180 and video controller 8020 are indicated as
distinct units in video controller 8020 can be integrated into graphics
adapter 818, or vice versa in other embodiments. Video controller 8020 is
suitable for refreshing monitor 7090 to display images on a screen 7080 of
computer 7000. Disk controller 8040 can control hard drive 7140, USB port
7120, and/or CD-ROM or DVD drive 7160. In other embodiments, distinct units
can be used to control each of these devices separately.
Network adapters 8200 can be coupled to one or more
antennas. In some embodiments, network adapter 8200 can be configured for
WiFi communication (IEEE 802.11), and/or may be part of a WNIC (wireless
network interface controller) card (not shown) plugged or coupled to an
expansion port (not shown) in computer 7000. Such WNIC card can be a
wireless network card built into internal computer 7000 in some examples. A
wireless network adapter can be built into internal client computer 7000 by
having wireless Ethernet capabilities integrated into the motherboard chipset, or
implemented via a dedicated wireless Ethernet chip, connected through the PCI
(peripheral component interconnector) or a PCI express bus. In the same or
other embodiments, network adapters 8200 can be configured for
communication via other wireless protocols, such as via WPAN, W-CDMA,
HSPA, EDGE, WiMAX, LTE, or others. In other embodiments, network adapter
820 can be a wired network adapter.
Although other components of computer 7000 are not shown,
such components and their interconnection are well known to those of ordinary
skill in the art. Accordingly, further details concerning the construction and
composition of computer 7000 and the circuit boards inside chassis 7020 need
not be discussed herein.
When computer 700 is in operation, program instructions stored
on hard drive 714, on memory 808, on a USB drive in USB port 712, and/or on a
CD-ROM or DVD in CD-ROM and/or DVD drive 916, can be executed by CPU
1010 (. Such program instructions may correspond to an operating
system (OS) such as an Apple OS, a Microsoft Windows OS, a Linux OS, and/or
a UNIX OS, among others. A portion of such program instructions can be
suitable for implementing or carrying out the systems and methods described
herein.
In the present example of one or more
sensing/measurement devices 60 are coupled to computer 7000. Alternatively,
the devices 60 may be coupled to the Internet 6000 (not shown) and the mobile
module 2000, in which case the computer 7000 is not necessary. Mobile module
2000 can be configured to communicate with computer 7000 (or device(s) 60) to
permit user 3000 to access information collected by the device 60.
illustrates a sample schematic of mobile device 4000.
Mobile device 4000 comprises processor module 4020 and memory module
4040 coupled together to run mobile device 4000. Memory module 4040 can
comprise an operating system which can be accessed therefrom for execution
by processor module 4020 to operate different functions of mobile device 4000.
In some examples, the operating system can comprise an operating system like
an iOS® OS from Apple Computer Inc., an Android® OS from Google, Inc.,
and/or a Windows Phone OS, from Microsoft, Inc., among others. Mobile device
4000 also comprises display module 4060 coupled to processor module 4020
and configured to present one or more user interfaces for the operation of mobile
device 4000. Processor module 4020 is also coupled to communications
module 4080, which can be configured to establish connection 6100 ( via
one or more of the wireless standards described above.
Mobile module 2000 is also shown in as implemented in
mobile device 4000, and can be coupled to or accessed by processor module
4020 and/or display module 4060. Although shown separate from memory
module 4040 in mobile module 2000 can be coupled to and/or stored at
memory module 4040 in some embodiments. For instance, mobile module 2000
can comprise a mobile application (mobile app) which may be downloaded via
Internet 6000 from a website or an online application store, and/or which may be
stored at mobile device 4000.
As shown in mobile module 2000 can be configured to
provide user 3000 with access to animal sensing/monitoring devices 60 in the
animal environment 20 via Internet 6000 through connection 6100 between
mobile device 4000 and Internet 6000 and through connection 6200 between
Internet 6000 and animal environment 20. Mobile module 2000 can thus allow
user 3000 to engage in remote monitoring of the animal 40. Such monitoring
can comprise, for example, the review of animal activity and behavior, including
food/water consumption, periods of resting and/or activity, and elimination
schedules and routines, among others.
As seen in mobile module 2000 can comprise several
sub-modules, such as settings module 2020, dashboard module 2040, analytics
module 2060, and notifications module 2080. An optional login module (not
shown) may also be included. If present, the login module can be configured to
receive authentication information from a user, like user 3000 ( or an
animal health professional, to confirm the user’s identity prior to providing access
to the sub-modules. As is conventional, the authentication information can
comprise a username and/or a password or personal identification number (PIN)
in some examples.
Settings module 2020 comprises the various user accounts or
profiles, animal profiles, mobile device profiles, and help/support functions. The
user has the ability to create and edit these profiles to include their personal and
animal information. illustrates an exemplary embodiment of a display
9002 comprising user settings including name 90021, communication
information (e.g., e-mail) 90022, and a photo 90023 of the user.
illustrates and exemplary embodiment of a display 9004 comprising user settings
including one or more animal profiles 90041 being monitored by device(s) 60.
These profiles 90041 are created by providing various details 90061 about the
animal, as illustrated in displays 9006a-9006g of FIGS. 9A-9G.
Also in settings module 2020 is the ability to add device profiles
for the various sensing/measuring devices 60, as shown in exemplary display
9008 (). This may include, for example, collar 90081, feeding station
90082, litter box 90083, and/or scale 90084 embodiments such as those
discussed above. The settings module may also include help and/or support
functionality 90101, as shown in display 9010 ().
Turning now to the dashboard module 2040, this module
comprises analytics-generated messages (e.g., pet health and wellness
information) and system information messages (e.g., device power, connectivity,
etc.). FIGS. 12A-12C illustrate exemplary embodiments of displays 9012a-
9012c. Here, activity information regarding the animal, as detected by the
various devices 60, are conveyed to the user via the mobile device 4000. As
shown, the activity information may include eating/drinking activity 90121, litter
box/elimination activity 90122, and/or physical activity/resting details 90123.
Next, the analytics module 2060 comprises individual data
stream details by data type and animal, as collected by device(s) 60. FIGS.
13A-13E illustrate exemplary embodiments of displays 9014a-9014e showing
such data stream details as activity 90141, rest 90142, food consumption 90143,
water consumption 90144, and weight 90145 for a selected animal 90146.
These details may be provided and displayed in variety of ways, including, for
example, the depicted graphs charting day, time, amount, etc., or by way of
other charts/graphs and/or illustrations. The user can have the ability to tailor
the displays to his or her liking, e.g., via the settings module. The analytics
module may also be configured to generate and present reports 20610, 20620
including the data stream details, which can, in turn, be printed, saved, and/or
shared as part of an animal “journal” or “log” discussed below.
Turning now to the notifications module 2080, this module
comprises additional analytics and system information messages. For example,
A illustrates and exemplary embodiment of a display 9016a showing
details 90161 regarding if/when a selected animal 90162 has interacted with one
or more of the sensing/measurement devices 60. Notifications module 2080
may also include “journal”- or “log”-type functionality, in which captured
behaviors or activities (such as eating or drinking, as illustrated in exemplary
display 9016b (B) are logged or recorded in the module. Here, such
relevant or potentially relevant information, including user tagged messages
90163, can be collected and saved for sharing, e.g., with the veterinarian or
health care provider of the selected animal 90162. In addition, and similar to the
analytics module 2060, the notifications module may also be configured to
generate and present reports 20810, 20820 including analytics and system
information details, which, in turn, can be printed, saved, and/or shared as part
of the animal’s “journal” or “log.”
In some instances, the exemplary modules described above
may be implemented as machine-accessible instructions utilizing any of many
different programming codes stored on any combination of machine-accessible
media embodied in a mobile application (e.g., an app) and/or an online
application for various wired and/or wireless mobile communication devices such
as handheld computers, smartphones, portable media players, tablet computers,
etc. In addition or alternatively, the machine-accessible instructions may be
embodied in a volatile or non-volatile memory or other mass storage device
(e.g., a USB drive, a CD, or a DVD). For example, the machine-accessible
instructions may be embodied in a machine-accessible medium such as a
programmable gate array, an application specific integrated circuit (ASIC), an
erasable programmable read only memory (EPROM), a read only memory
(ROM), a random access memory (RAM), a flash memory, a magnetic media, an
optical media, and/or any other suitable type of medium. The systems,
apparatus, methods, and articles of manufacture described herein are not limited
in this regard.
It should be understood that various changes and modifications
to the presently preferred embodiments described herein will be apparent to
those skilled in the art. Such changes and modifications can be made without
departing from the spirit and scope of the present invention and without
diminishing its intended advantages. It is therefore intended that such changes
and modifications be covered by the appended claims.
All elements claimed in any particular claim are essential to the
embodiment claimed in that particular claim. Consequently, replacement of one
or more claimed elements constitutes reconstruction and not repair. Additionally,
benefits, other advantages, and solutions to problems have been described with
regard to specific embodiments. The benefits, advantages, solutions to
problems, and any element or elements that may cause any benefit, advantage,
or solution to occur or become more pronounced, however, are not to be
construed as critical, required, or essential features or elements of any or all of
the claims, unless such benefits, advantages, solutions, or elements are
expressly stated in such claims.
Moreover, embodiments and limitations disclosed herein are
not dedicated to the public under the doctrine of dedication if the embodiments
and/or limitations: (1) are not expressly claimed in the claims; and (2) are or are
potentially equivalents of express elements and/or limitations in the claims under
the doctrine of equivalents.
Having described the invention in detail, it will be apparent that
modifications and variations are possible without departing the scope of the
invention defined in the appended claims. Furthermore, it should be appreciated
that all examples in the present disclosure are provided as non-limiting
examples.
EXAMPLES
The following non-limiting examples are provided to further
illustrate the present invention. It should be appreciated by those of skill in the
art that the techniques disclosed in the examples that follow represent
approaches the inventors have found function well in the practice of the
invention, and thus can be considered to constitute examples of modes for its
practice. However, those of skill in the art should, in light of the present
disclosure, appreciate that many changes can be made in the specific
embodiments that are disclosed and still obtain a like or similar result without
departing from the spirit and scope of the invention.
EXAMPLE 1 - UNEXPECTED DOG WEIGHT LOSS IDENTIFICATION
This example describes how multiple types of data acquired on
a single pet, longitudinally, were be leveraged to identify significant and/or
unexpected changes in pet health and wellness based on the assessment of
each data types trends over time when compared to one another.
Methods
Several devices were used in a typical animal-owning home
environment to acquire specific data about a standard poodle named Frasier.
Each device leveraged technologies to acquire and transmit data from the
animal across a home wireless network to the “cloud” where it was stored and
analyzed. Once analyzed, the data was then made available to the animal
owner to view through a secure web-site (User Interface, “UI”) on a computer or
smart device with internet access. The devices utilized rechargeable batteries
and/or connectivity to standard household electrical outlets to ensure data was
acquired on the animal continuously over an extended period of time.
The type of data acquired determined how that data was
presented in the UI. For example, dog weight in the UI represents the average
of all daily weights acquired by the scale each day. Food and water
consumption shown in the UI represents the total net weight (in ounces) of each
consumed in a day. Activity levels were defined as distance travelled in a day
based on accelerometer data acquired through a dog collar device.
Materials
In this case, three separate devices were used to acquire
specific data about Frasier; 1) a collar-mounted device including an
accelerometer used to track activity levels, 2) a device that tracks food and water
consumption from Frasier’s food and water bowls using standard load cells and
3) a 2’X3’ scale device that tracks Frasier’s weight using load cells.
While it is normal for animals to receive food and water outside
of their food and water bowls, it was assumed that most animal owners tend to
be relatively consistent in their feeding and hydration patterns for animals
outside of their normal food and water bowls, which makes that behavior
constant over time. Also, in this case, the scale used was placed in front of the
food and water bowls, which ensured Frasier’s weight was recorded each time
he ate/drank from the these bowls. Frasier’s weight could also be captured by
placing the scale anywhere in the home where he would be motionless for some
period of time on a regular bases (such as under a dog bed, dog crate, etc.).
Once each of the devices was positioned in the home and
connected to the home wireless network, Frasier’s profile was created in the UI
and power was maintained with each of the devices, whereby the data that was
acquired from each device flowed through the technical architecture to the UI
where the data could be viewed by the pet owner at any time. Views of the data
could be manipulated through the UI to enable data views across multiple time
horizons (daily, weekly, monthly, yearly, all data, etc.).
Results
When observing Frasier’s data over a 4 week period (FIGS. 15-
18), it was clear that 3 of the 4 data stream trends being tracked remained
relatively stable during this period. It was also observed that his weight reduced
significantly during this period (from a high of 80.3 lbs to a low of 78.8 lbs ()). This represented a 1.9% decrease in total body weight during this period
which can be significant especially given the consistent negative trend in weight
that was observed during this time period. To put this in perspective, this rate of
decrease extrapolated over a single year would represent almost a loss of nearly
one-fourth the total body weight which, intuitively, represents an unhealthy
weight loss.
It could be possible for this level of weight loss to be attributed
to other factors such as increased activity levels and/or changes in food and
water consumption levels. In this case, the ability to observe other types of data
on Frasier during the same time further highlights the potential for concern over
his weight loss. In this case, it was observed that food and water consumption
trends remain relatively constant, as does Frasier’s level of activity (all within
normal ranges of variability). As a result of these other data types, one would
not expect to see such a significant decrease in total body weight during this
period.
This example highlights how the ability to acquire and view a
animal’s data over an extended period of time can identify insights into potential
health and wellness concerns that might not be obvious to the pet owner. If
Frasier’s weight had been the only data tracked, it could have been possible to
overlook the significance of the weight change by not seeing actual food/water
consumption and activity data. The ability to see multiple, relevant data types on
a single animal, longitudinally, provided surprising insight into our ability to
analyze and assess changes in the data that might indicate changes in relative
trends that can identify the potential of increased levels of risk to the pets health
and wellness.
In Frasier’s case, a trip to the veterinarian at the end of this test
period resulted in a series of tests that concluded that Frasier was in a relatively
advanced stage of cancer of the lymph nodes. While this data led to a diagnosis
that afforded him the opportunity to receive treatment for his cancer, he lived
only about 7 months following this diagnosis. Had this data been tracked on
Frasier much earlier, relative changes in the data could have been identified
earlier that would have led to an earlier cancer diagnosis and, subsequently, a
better outcome; more time and/or options for treatment and/or increased
opportunity for a resolution to the disease or to extending his lifespan.
EXAMPLES 2A AND 2B - CAT ELIMINATION BEHAVIOR TRACKING
The following two examples detail how data acquisition
leveraging sensor technologies can be used with cats to gain early insights into
changes in elimination behavior patterns, that aren’t visible to cat owners, but
which can enable insights into increased risks associated with the early onset
symptoms of common diseases that impact the length and quality of life of cats
such as diabetes, leukemia, kidney disease, etc. While the types of data
acquired in each of the following cases is identical, the methods of data
acquisition were different, illustrating how different sensing technologies can be
used to capture relevant data.
Example 2A – Weight Sensing
Methods
This example describes a case where a prototype weight-
sensing device was placed under a cat litter box in a typical cat-owning home
environment to acquire specific data about a cat. The device used
motion/movement detection technology to acquire data from the cat’s
engagement of the litter box and stored that data on the device, which was
subsequently connected to a laptop/pc for data export and analysis using a
standard data analysis tool. FIGS. 19-23 are illustrations of the data acquired for
a single cat using a single litter box in a typical home environment.
The type of data acquired in this case was the presence (or
absence) of weight in a litter box beyond the normal weight of the box plus the
litter in the box. The presence of additional weight indicated cat activity in the
litter box. When the cat was not present in the litter box, no change in weight
was detected. However, as soon as the cat put weight on/in the litter box an
engagement event was initiated. The end of an event is identified by time-stamp
once the weight of the cat is no longer measured by the device. Knowing the
start/stop time of each event enables the calculation of event frequency, event
duration and litter box use-patterns in the case of multiple litter boxes existing in
a single home (in this case, only one litter box was used for data collection
purposes but extending the analysis of data to include multiple litter boxes and
even multiple cats is an intuitive extension of this case that can be realized
leveraging the same technologies as described in this case).
Materials
For simplicity, in this case only one device was used to acquire
specific data about a single house cat in a normal home environment. The
device consisted of a metal platform upon which the litter box was placed. On
one end, the platform was slightly elevated by an adjustable spring that enabled
one end of the platform with litter box and litter to be raised or lowered slightly.
Underneath the platform was a small base that included a “contact” post
attached to a standard USB data-writer. When properly adjusted the platform
was elevated 1/8” to ½” above the contact post with only the litter-filled litter box
on the platform. When properly adjusted, the cat entering the litter box
compressed the spring due to the cats weight being added to the system making
contact with contact post. This contact closed a circuit that triggered a data point
and date/time stamp to be written to the data-writer device signifying the start of
an event. As the cat moved in the litter box, a properly tensioned spring would
cause the contact between the platform and contact post to be broken and re-
established, writing a series of data points over time to the data-writer that
confirm event activity is continuing in the litter box. When the cat left the litter
box, the spring tension broken the connection between the platform and
connection post which then stayed broken indicating the end of the litter box
engagement event.
This test can be easily extended, utilizing the same device and
technologies, to include multiple litter boxes and multiple cats in a single home.
This would expand the data analysis to include tracking the individual litter box
engagement patterns of each cat as a measure of normal behaviors and
changes to normal behaviors which can be significant. In the case of multiple
cats in a home, the system must be able to discern which cat is responsible for
each litter box engagement event, which can be accomplished in a variety of
ways including RFID or Bluetooth Low Energy (BLE) tags on the cat collar or
through development of algorithms capable of identifying cats uniquely based on
“signature” patterns in the data acquired.
At any point in time, the data files in the data-writer could be
connected to a laptop/pc via USB connection and the files imported into MS
Excel or other data analysis tools to manually track event frequency, duration
and time of day patterns and their changes over time.
Results
The data described FIGS. 19-23 was collected on a single cat
using a single litter box over multiple days. While no software-based algorithms
or analytics were designed into the prototype system that acquired this data,
observation and manual analysis of the data clearly illustrate the ability to identify
litter box engagement patterns such as event frequency, duration and time-of-
day patterns and the level of variability that exists within and across these
measures.
The data in describes activity in the litter box over
seven days. When each litter box engagement day’s data is plotted on a
24 hour time scale, normal use patterns of both frequency and duration become
evident, as well as, variability in patterns which could signify negative trends in
health including the possibility of early disease symptom onset. Among the
interesting features of this data set is how it can be used to illustrate changes in
cat elimination behavior patterns as a result of non-normal external stimuli on the
cat. For example, on July 4th, the litter box engagement pattern of the cat
seems normal during the day but is unusually low in the evening when compared
to other nights. This happened to be an evening when fireworks were being set
off at the next house in celebration of the 4th of July holiday, causing the cat to
stay hidden. Another example illustrated by this data is seen on July 9th. On
this day, the frequency of elimination, while low, falls within the normal range of
variability but the total duration of activity for this day was significantly less than
any other day during this test period (6 minutes of total activity this day
compared to 12-25 minutes of activity every other day). This day was unique for
the cat as its home owner hosted a large dinner party for 30-40 guests that
afternoon/evening and there was therefore an unusual amount of activity in the
home throughout the day in before/during/after that brought many visitors into
the home throughout the day who were unfamiliar to the cat. As a result, the
cat’s litter box engagement pattern was impacted by significantly reducing the
amount of time spent in the litter box during each event in order to avoid/hide
from the unusual activity in the home that day. The following day (July 10th), the
cat spent a significantly greater time in the litter box than normal.
FIGS. 17-18 illustrate the opportunity to leverage this data to
identify additional metrics that may be of value in assessing cat elimination
behavior patterns and changes to patterns that may be of significance. In this
case, the data can be shown to also identify patterns of normal litter box usage
in terms of time of day patterns and cumulative duration patterns during certain
times of day. In addition to event frequency and duration, it is likely that changes
to time of day usage patterns in the litter box can be used to identify periods of
stress or changes in health and wellness from the cats normal baseline. In the
case of a multiple litter box home, it is also likely that changes in box choice
patterns over time can be used to identify significant changes in behavior which
may indicate significant changes in cat behavior. In the case of a multiple cat
and/or multiple litter box home, it is also likely that changes in cat behavior
patterns relative to one another can be compared to gain new insights into
individual cat behavior patterns of interest, as well as, to gain understanding into
normal interactions between cats in a home and changes to those patterns that
may be of importance.
Example 2A – Motion/Movement Sensing
This example describes how data acquisition leveraging sensor
technologies can be used with cats to gain early insights into changes in
elimination behavior patterns that are not visible to cat owners, but which can
enable insights into increased risks associated with the early onset symptoms of
common diseases that impact the length and quality of life of cats such as
diabetes, leukemia, kidney disease, etc.
Methods
This example describes a case where a motion/movement
detection device was placed on a cat litter box in a typical cat-owning home
environment to acquire specific data about a cat. The device used
motion/movement detection technology to acquire and transmit data from the
litter box and across a home wireless network to the “cloud” where it was stored
and analyzed. Once analyzed, the data was them made available to the cat
owner to view through a secure web-site (User Interface, “UI”) on any computer
or smart device with internet access. The device used rechargeable batteries
and/or connectivity to standard household electrical outlets to ensure data was
acquired on this animal continuously over an extended period of time.
The type of data acquired in this case was motion (or lack of
motion) in a litter box, which was in turn used as an indicator of cat activity in the
litter box. When the cat was not present in the litter box, no motion was
detected. However, as soon as the cat touched the litter box the sensor
recognizes motion which indicates the start of a litter box engagement event by
the cat. During the event, there may be short periods of time when motion
is/isn’t detected, but the event termination can be clearly seen when motion data
ceases to be acquired for an extended period of time. The start and stop of each
litter box engagement event is time-stamped by the system which enables the
calculation of event frequency, event duration and litter box use-patterns in the
case of multiple litter boxes existing in a single home (in this case, only one litter
box was used for data collection purposes but extending the analysis of data to
include multiple litter boxes and even multiple cats is an intuitive extension of this
case that can be realized using the same technologies as described in this
case).
Materials
For simplicity, in this case only one (1) device was used to
acquire specific data about a single house cat in a normal home environment.
The device used included a standard accelerometer sensor and other
componentry that enabled the ability to acquire, store and transmit relevant data.
The components were housed in a plastic case measuring approximately 2”
deep x 3” height x 6” depth and attached to any standard litter box using a heavy
duty double stick Velcro ® tape. The device was connected to normal household
electrical power but was also designed so that it could also be powered by re-
chargeable battery.
This test can be easily extended, leveraging the same
technologies, to include multiple litter boxes and multiple cats in a single home.
This would expand the data analysis to include tracking the individual litter box
engagement patterns of each cat as a measure of normal behaviors and
changes to normal behaviors which can be significant. In the case of multiple
cats in a home, the system must be able to discern which cat is responsible for
each litter box engagement event which can be accomplished in a variety of
ways such as RFID or Bluetooth Low Energy (BLE) tags on the cat collar or
through development of algorithms capable of identifying cats uniquely based on
“signature” patterns in the data acquired.
Once the device was set-up in the home and connected to the
home wireless network, the cat’s profile was created in the UI, power was
provided to the device, and the data that was acquired flowed through the
technical architecture to the UI where the data could be viewed by the cat owner
at any time. Views of the data could be manipulated through the UI to enable
data views across multiple time horizons (daily, weekly, monthly, yearly, all data,
etc.).
Results
The data was collected on a single cat using a single litter box
over a two month period (FIGS. 22 and 23). illustrates the ability to
identify a daily event frequency, as well as to identify the min/max/average time
spent in the litter box per event for that day. illustrates the ability to track
each event uniquely during a given day. While no software-based algorithms or
analytics were designed into the prototype system that acquired this data,
observation and manual analysis of the data clearly illustrate the ability to identify
litter box engagement patterns such as event frequency, duration and time-of-
day patterns and the level of variability that exists within and across these
measures. Leveraging existing technologies, the capability exists to automate
the analysis of this data to develop “normal” baseline behavior patterns and
identify changes to these patterns that could indicate increased risk of a negative
health trend that might indicate the early onset of a medical condition, disease or
health-risk. These patterns could be identified using statistical/mathematical
models and/or heuristics or common rules accepted or known in veterinary
and/or animal wellness practices.
Claims (7)
1. A method of preparing a nutrition, health, and/or wellness recommendation for a non-human animal, the method comprising: collecting data on one or more of a health, diet, behavior, and environmental parameter of the animal; analyzing the data; and providing the nutrition, health, and/or wellness recommendation based upon the analyzed data, the method characterized in that the data is collected by a sensor on the animal and a sensor at a location frequented by the animal.
2. The method of claim 1 wherein the recommendation is one or more of a changes in environment; initiating, limiting, or increasing an exercise protocol; administration or cessation of vitamins, supplements, or medication; initiating or modifying a training protocol; a nutritional/feeding change; a veterinary visit; and a combination thereof.
3. The method of any one of claims 1-2 wherein the one or more health, diet, behavior, and environmental parameters comprise a health parameter of the animal selected from one or more of the animal’s age; sex; gender; species or breed; body weight; body mass index (BMI); body composition; body temperature; gait force; reproductive aspects; skin and coat condition; cardiovascular system; gastrointestinal and kidney functions; vision, cognitive health; and combinations thereof.
4. The method of any one of claims 1-3 wherein the diet parameter of the animal is selected from one more of the animal’s food and water consumption and amount and time of day thereof; nutritional profile of the food consumed: vitamin, supplement, and/or medication consumption; and combinations thereof.
5. The method of any one of claims 1-4 wherein the one or more health, diet, behavior, and environmental parameters comprise a behavior parameter of the animal selected from one or more of an activity profile comprising one or more of calories burned, steps or distance traveled, intensity levels, changes in elevation, and time of day information: elimination activity, which includes one or more of frequency, amount, and time of day information; vocalization; and combinations thereof.
6. The method of any one of claims 1-5 wherein the one or more health, diet, behavior, and environmental parameters comprise an environmental parameter of the animal selected from one or more of weather information, which includes one or more of air temperature, humidity, heat index, and precipitation; location coordinates of animal; location coordinates of food/water/waste container/sleeping or resting locations; presence or absence of owner/caretaker at the location; presence or absence of children/elderly at the location; and combinations thereof.
7. A non-transitory computer-readable medium comprising code representing instructions to cause a processor to perform a process, the code comprising code to prepare a nutrition, health, and/or wellness recommendation for an animal by performing the method comprising: collecting data on one or more health, diet, behavior, and environmental parameters of the animal; analyzing the data; and providing the nutrition, health, and/or wellness recommendation based upon the analyzed data, the method characterized in that the data is collected by a sensor on the animal and a sensor at a location frequented by the animal.
Applications Claiming Priority (3)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
US201462021763P | 2014-07-08 | 2014-07-08 | |
US62/021,763 | 2014-07-08 | ||
PCT/IB2015/055145 WO2016005911A1 (en) | 2014-07-08 | 2015-07-07 | Systems and methods for providing animal health, nutrition, and/or wellness recommendations |
Publications (2)
Publication Number | Publication Date |
---|---|
NZ726936A NZ726936A (en) | 2021-10-29 |
NZ726936B2 true NZ726936B2 (en) | 2022-02-01 |
Family
ID=
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