Systems and methods for monitoring animal movement

Abstract

A system, apparatus, and / or method are provided for determining the condition of an animal. Movement data of the animal over a predetermined time period can be received. The movement data may include at least one of the animal's acceleration and / or speed, distance traveled, position, and / or stride length. The animal's gait over the predetermined time period can be determined based on the movement data. The duration and / or frequency of the animal's gait can be determined. The animal's activity level over the predetermined time period can be determined based on at least one of the duration or frequency of the animal's gait. The animal's activity level can be displayed via a display device.

Description

[0001] Cross-reference to related applications

[0002] This application claims priority to U.S. Provisional Patent Application Serial No. 63 / 082,241, filed September 23, 2020, the entire contents of which are incorporated herein by reference. Background Technology

[0003] Animals (such as pets) often cannot communicate parameters related to their health, such as their overall health status, activity level, and potential illnesses. While animals can be taken to a veterinarian for examination, such visits are often expensive and inconvenient, and the veterinarian may not have sufficient information to accurately diagnose the animal. Delayed treatment of underlying problems can lead to pain or even death in animals. An animal's movement can help determine one or more conditions, such as its health status, activity level, and potential illnesses.

[0004] Quantifying attributes of animal movement, such as forward movement, can be useful for pet owners and veterinarians in assessing animal health. Animals can be manually observed to determine their movement in one or more directions. However, such manual methods are often cumbersome and do not provide timely diagnoses of an animal's health. Furthermore, manual observation of animals is prone to inaccuracies, incompleteness, and forgetfulness. Therefore, what is needed is a method and / or system for automatically determining animal movement, for example, over a predetermined time period. Such determination can be used to easily and accurately identify one or more conditions in an animal. Summary of the Invention

[0005] A method for determining the condition of an animal is provided. Movement data of the animal over a predetermined time period can be received. The movement data may include at least one of the animal's acceleration, distance traveled, position, and / or steps taken. The animal's gait over the predetermined time period can be determined based on the movement data. The duration and / or frequency of the animal's gait can be determined. The animal's activity level over the predetermined time period can be determined based on at least one of the duration or frequency of the animal's gait. The animal's activity level can be displayed via a display device.

[0006] A system for determining the activity level of an animal is provided. The system includes sensors configured to receive movement data of the animal during a first predetermined time period. The movement data may include at least one of the following: acceleration of the animal during the first predetermined time period, distance traveled by the animal during the first predetermined time period, position of the animal during the first predetermined time period, and / or strides taken by the animal during the first predetermined time period. The system may include one or more processors configured to: determine the gait of the animal during the first predetermined time period based on the movement data of the animal during the first predetermined time period; determine at least one of the duration or frequency of the animal's gait during the first predetermined time period; determine the activity level of the animal during the first predetermined time period based on at least one of the duration or frequency of the animal's gait during the first predetermined time period; and display the activity level of the animal during the first predetermined time period via a display device. Attached Figure Description

[0007] The invention will be more fully understood from the detailed description and accompanying drawings, in which:

[0008] Figure 1 It is a block diagram of a system with multiple modules configured to collect and analyze animal behavior;

[0009] Figure 2 This is a perspective view of the example active ring;

[0010] Figure 3A It is wearing Figure 2 Example of an animal depicting a ring-shaped activity;

[0011] Figure 3B It is wearing Figure 2 The example depicts another animal in the activity ring;

[0012] Figure 4A This is a perspective view of an example waste area with the sensor positioned on it;

[0013] Figure 4B This is a perspective view of an example waste area where the sensor is not located.

[0014] Figure 5A This is a perspective view of an example feeding dish and water bowl with the sensor positioned on them;

[0015] Figure 5B This is a perspective view of an example feeding dish and water bowl where the sensor is not located on the feeding or water bowl;

[0016] Figures 6A to 6D yes Figure 1 Example screenshots of the system in use; and

[0017] Figure 7 This is an example of the system described in this article. Detailed Implementation

[0018] The following description of preferred embodiments is merely exemplary in nature and is in no way intended to limit the invention, its application, or its use.

[0019] The description of illustrative embodiments according to the principles of the invention is intended to be read in conjunction with the accompanying drawings, which are considered an integral part of the entire written description. In the description of embodiments of the invention disclosed herein, any references to direction or orientation are intended only for ease of description and not to limit the scope of the invention in any way. Relative terms such as “lower,” “upper,” “horizontal,” “vertical,” “above,” “below,” “above,” “under,” “top,” and “bottom,” and their derivatives (e.g., “horizontally,” “downward,” “upward,” etc.) should be interpreted as referring to the orientation described at the time or shown in the drawings discussed. These related terms are for ease of description only and do not require the device to be constructed or operated in a particular orientation unless explicitly indicated otherwise. Terms such as “attach,” “fix,” “connect,” “couple,” “interconnect,” and similar terms refer to relationships in which structures are directly or indirectly fixed or attached to each other via intermediate structures, and to movable or rigid attachments or relationships, unless explicitly described otherwise. Furthermore, the features and benefits of the invention are illustrated by reference to exemplary embodiments. Therefore, the present invention is explicitly not limited to such exemplary embodiments showing some possible non-limiting combinations of features, which may exist alone or in other combinations of features; the scope of the invention is defined by the appended claims.

[0020] As used throughout this document, a range is used as a shorthand to describe the individual values ​​within that range and for each value. Any value within a range may be chosen as the endpoint of the range. Furthermore, all references cited herein are incorporated herein by reference in their entirety. In the event of any conflict between definitions in this disclosure and definitions in cited references, this disclosure shall prevail.

[0021] This system, method, and apparatus are designed to provide, for example, monitoring of animals based on their movement. Movement can be forward movement, such as an animal's forward gait. Monitoring of animals can be used to determine an animal's activity level, its condition (e.g., health status), etc. Example animals can include pets (e.g., cats, dogs, rabbits, guinea pigs, birds), farm animals (e.g., horses, cattle, chickens), zoo animals (e.g., lions, bears), wild animals, etc. As described herein, monitoring of an animal's motion can provide (e.g., automatically) indications of the animal's health status (e.g., general indications). Monitoring of animals can provide the detection (e.g., early detection) of health abnormalities in animals (such as illness, disease, injury, lameness, obesity, arthritis, etc.). Detection can be feasible because health abnormalities (e.g., injury) can cause changes in an animal's gait. Example injuries may include strains, sprains, fractures, joint dislocations, etc. For example, injuries may include ruptured craniocarpal ligaments and / or patellar dislocation, which can cause lameness in dogs. Examples of injuries can include common injuries (e.g., a sprained ankle) and / or traumatic injuries (e.g., from a car accident). Health abnormalities may include dementia. For example, an animal experiencing dementia may walk during the night and sleep during the day. Animal health monitoring can provide (e.g., automatically) indications of an animal's activity, such as tracking / assessing an animal's daily activity, checking / assessing whether a boarding pet is exercising, etc.

[0022] Animal health monitoring can provide (e.g., automatically) markers of an animal's training, various life stages / states such as aging or obesity. Animal health monitoring can provide tools for estimating an animal's energy use and / or can be used as a measure of disease states such as joint problems like arthritis, hip dysplasia, lameness, foot injuries, bone disease, weakness and / or dysfunction (e.g., due to age), neurological disorders, etc. Monitoring an animal's movement can bring numerous benefits, especially if the animal's caregiver or veterinarian takes corrective action upon detecting health abnormalities. For example, the system and / or method can be designed for use in an animal's dwelling and can result in the provision of important information to the animal's caregiver and / or veterinarian.

[0023] The system may include one or more devices and / or mechanisms worn by the animal for receiving, identifying, storing, and / or transmitting information about the animal. The mechanism may be worn on one or more of the animal's head, ears, neck, torso, limbs (e.g., arms, legs), tail, mouth (e.g., teeth, dental caps, replacement teeth), eyes (e.g., contact lenses), etc. The mechanism may be placed in one or more implants within the animal's body (such as implants within the animal's abdomen and / or tail base, or neutral sac). The system may include one or more devices coupled to collars, harnesses, bracelets, anklets, belts, earrings, headbands, etc. In other examples, the system may include one or more devices attached to one or more attachment mechanisms (such as coats, boots, decorative clothing (e.g., ribbons), sweaters, hats, etc.). In other examples, one or more of the devices and / or mechanisms may be implanted within the animal's body. For example, one or more of the devices and / or mechanisms may be subcutaneous implants that can be placed under the skin of an animal.

[0024] (For example, an identification device coupled to a device worn by the animal) can identify the animal within the system. The animal can be linked to an animal file. Animal movement can be monitored, tracked, and / or electronically recorded (e.g., automatically monitored, tracked, and / or electronically recorded) at predefined frequencies (e.g., daily, weekly, monthly, yearly). As described herein, animal movement can be used to determine the animal's health status, activity level, etc. Animal movement can be monitored, tracked, and / or recorded without disturbing the animal or disrupting its natural behavior.

[0025] Monitoring of animal movement can be performed by collecting one or more types of data. Data may include motion data, location data, orientation data, spatial data, etc. Data can be collected and / or monitored during one or more activities of the animal, such as walking, trotting, jogging, slow walking, pacing, running, etc. Data can be collected and / or monitored to determine the animal's gait speed. Data may pertain to the animal's movement in one or more directions (such as forward, backward, lateral, vertical, etc.). The collected data can be stored in a repository accessible to animal caregivers, veterinarians, etc. The data can be accessed via portable electronic devices (e.g., applications of portable electronic devices) and / or servers.

[0026] The portable electronic device can be one or more of a variety of devices, including but not limited to smartphones, cellular phones, tablet computers, personal digital assistants (“PDAs”), laptop computers, etc. This data can be analyzed to identify animal behavior and / or habits and to provide data and / or suggestions to the owner based on that data. Data can be collected and / or generated over time for purposes such as statistical processing of animal movement. To understand animal health trends, changes in animal health status, determine animal activity levels, determine the presence of health abnormalities in the animal, etc., the data can be compared with previously collected and / or stored data. Previously collected and / or stored data may be correlated with the animal being monitored, and / or previously collected and / or stored data may be correlated with another animal (e.g., for comparative purposes).

[0027] An animal's health status (such as whether the animal is injured / sick / ill) and / or its activity can be determined based on its movement. An animal's health status can be recorded. To determine an animal's health status, parameters indicating its health status can be monitored and / or recorded. Such parameters may include the number of times the animal walks, runs, paces, gallops, rests, etc., within a certain time period, and the duration of walking, trotting, jogging, walking slowly, pacing, galloping, resting, etc. For example, the time period for an animal to run could be one hour per day, one minute per day, etc.

[0028] Statistical methods can be applied to derive information about an animal's health status based on its movement. For example, a minimum and / or maximum amount of time a healthy animal will run during a given time period (e.g., daily, weekly, monthly, etc.). Mean and median values ​​for these parameters can be defined for healthy and / or unhealthy animals. If an animal performs fewer or more of the defined health parameters (e.g., running) than the amount defined for a healthy animal, the animal can be identified as unhealthy (e.g., sick, injured, ill, etc.). In other examples, if an animal performs fewer or more of the defined health parameters (e.g., running) than the amount defined for a healthy animal, the animal can be identified as not exercising and / or training regularly as required. In other examples, an animal's body fat index (BFI), body condition score (BCS), muscle condition score (MCS), and / or weight can be determined and / or identified to derive the animal's health status.

[0029] Statistical methods can be applied to derive information about an animal's health status based on the movement of a single animal, the movement of more than one animal, the movement of similar animals, the movement of different animals, or combinations thereof. The resulting information can be used to form measures, matrices, and / or indices, such as health measures, health matrices, and / or health indices. One or more characteristics of an animal's movement (such as the uniformity of weight distribution between the animal's legs, the distance between the animal's feet, the difference between the animal's right and left sides, the speed of the animal's right and left sides, and / or the combination of the animal's feet used to form the animal's gait (e.g., two beats, three beats, four beats, etc.)) can be used to form a health measure or health index. A health measure or health index can be a characteristic of the animal's life stage (e.g., young vs. old), the animal's disease condition (e.g., arthritis), etc.

[0030] A subset of an animal's characteristics can be used to determine whether its movement indicates a healthy or unhealthy animal. Such characteristics can include the animal's species, breed, age, sex, geographic location, life stage, size / weight, etc. For example, dogs can be expected to move faster and / or farther than cats. Therefore, the daily running distance required for a cat may not be sufficient for a dog. In another example, the daily running distance required for a dog may not be sufficient for a horse. Specific, identified, received, and / or transmitted parameters can be recorded. Parameters can be recorded continuously, for example, from the moment the system is activated throughout the animal's life. In other examples, parameters can be recorded at predefined time periods (e.g., a day, a week, a month, etc.) and at a predefined frequency (e.g., every workday).

[0031] Figure 1 An example system for monitoring the behavior, health, habits, and / or other characteristics of an animal is shown. System 100 may include sensor 102, measuring device 104, and / or storage device 112.

[0032] Sensor 102 can be configured to detect the animal's position, movement (or stillness), orientation, etc. Sensor 102 can be one or more of the following shape factors: including but not limited to accelerometers, gyroscopes, magnetometers, force transducers, displacement transducers, pressure transducers, force sensors, displacement sensors, pressure sensors, force sensors, photographic / video recording devices, cameras, audio sensors, and combinations thereof. In an example, sensor 102 may include one or more of a thermometer, electrocardiogram (ECG), optical plethysmography (PPG) device, microphone, respiratory plethysmography (RIP) device, photoelectric plethysmography (OEP) device, or transthoracic impedance device. For example, caloric expenditure can be assessed by measuring the heat generated, cardiac / respiratory output, distance traveled, and / or strides. ECG and PPG can provide pulse / heart rate detection. Microphones, RIPs, OEPs, and impedance devices can provide respiratory rate.

[0033] Alternatively or concurrently, sensor 102 may be one or more of the following sensors: optical sensors, optical reflection sensors, LED / photodiode-to-optical sensors, LED / phototransistor-to-optical sensors, laser diode / photodiode-to-optical sensors, laser diode / phototransistor-to-optical sensors, optocouplers, fiber-optic coupled optical sensors, magnetic sensors, ultrasonic sensors, microphones, weight sensors, force sensors, displacement sensors, pressure sensors, various proximity sensors (such as inductive proximity sensors, magnetic proximity sensors, capacitive proximity sensors), and / or combinations thereof. Sensor 102 may include communication circuitry such as Bluetooth (e.g., classic Bluetooth and / or Bluetooth Low Energy), RFID, Wi-Fi, and other wireless technologies. Sensor 102 may communicate with one or more devices; for example, sensor 102 may communicate with a server.

[0034] Measuring device 104 can be configured to measure animal-related characteristics. Measuring device 104 can be a device separate from or identical to sensor 102. Example measuring device 104 can be implemented in one or more of a variety of shape factors, including but not limited to weighing scales, weight transducers, force transducers, displacement transducers, pressure transducers, weight sensors, force sensors, displacement sensors, pressure sensors, real-time clocks, timers, counters, and / or combinations thereof. Measuring device 104 may include communication circuitry such as Bluetooth (e.g., classic Bluetooth and / or Bluetooth Low Energy), RFID, Wi-Fi, medical implantable communication systems (MICS) (e.g., hybrids of these technologies, such as MICS / Bluetooth), and other wireless technologies. Measuring device 104 can communicate with one or more devices; for example, measuring device 104 can communicate with a server.

[0035] Storage device 112 can be configured to store data provided to and / or from system 100. The data may include, for example, motion data and / or position data provided by sensor 102. Example storage device 112 may be a memory device, a data storage device, and combinations thereof, such as memory chips, semiconductor memories, integrated circuits (ICs), non-volatile memory or storage devices (such as flash memory, read-only memory (ROM), erasable read-only memory (EROM), electrically erasable read-only memory (EEROM), erasable programmable read-only memory (EPROM), electrically erasable programmable read-only memory (EEPROM), electrically erasable programmable read-only memory (EEPRO)), volatile memory (such as random access memory (RAM), static random access memory (SRAM), dynamic random access memory (DRAM), single data rate memory (SDR), double data rate memory (DDR), quad data rate memory (QDR), microprocessor registers, microcontroller registers, CPU registers, controller registers), magnetic storage devices (such as magnetic disks, magnetic hard disks, magnetic tapes), optical storage devices (such as optical discs, compact discs (CDs), digital versatile discs (DVDs), Blu-ray discs, magneto-optical discs (MO discs)) and / or combinations thereof. In one embodiment, the storage device includes a semiconductor RAM IC for intermediate recording of the animal's behavior, health, and / or characteristics, followed by data transfer to a flash memory IC for non-volatile recording. Storage device 112 may be an external storage device, such as a USB flash drive, external hard drive, etc.

[0036] System 100 may include processor 110, which is configured to compute and / or process, for example, data provided to system 100. Example processors may be electronic circuits, systems, modules, subsystems, submodules, devices, and combinations thereof, such as central processing units (CPUs), microprocessors, microcontrollers, processing units, control units, tangible media for recording, and / or combinations thereof. Storage device 112 may be configured to store data derived from processor 110. Processor 110 may include communication circuitry such as Bluetooth (e.g., classic Bluetooth and / or Bluetooth Low Energy), RFID, Wi-Fi, and other wireless technologies. Processor 110 may communicate with one or more devices; for example, processor 110 may communicate with a server.

[0037] In the example, sensor 102 and / or storage device 112 can be assembled in various configurations, including in a standalone device. In another example, sensor 102, storage device 112, and processor 110 can be assembled in a standalone device. In other examples, processor 110 and / or storage device 112 can be configured as a remote device, such as a remote server (e.g., a cloud storage device). Although Figure 1 The diagram illustrates the connections between processor 110 and each of sensor 102, measuring device 104, and storage device 112, but the example should not be limited thereto. In this example, one or more of the devices may communicate with one or more of the other devices (including any device or no device). For example, sensor 102 may communicate with both processor 110 and storage device 112, or sensor 102 may not communicate with storage device 112, etc. One or more devices may be added to system 100 and / or removed from system 100. For example, an additional sensor 102 may be added to system 100 and / or storage device 112 may be removed from system 100.

[0038] Data related to animal movement can be processed and / or recorded to determine the animal's activity level and / or health status. For example, the number and duration of an animal's walking, trotting, jogging, slow walking, pacing, running, and / or resting can be used to determine the animal's health status, activity level, etc. The animal's weight, body temperature, date and / or time of events (e.g., walking, trotting), number of events (e.g., walking, trotting, jogging), and / or duration of movement can be used to determine the animal's health status. One or more of the animal's activities can be recorded via video recording, images, and / or audio recording and / or can be processed.

[0039] Figure 2 This is a perspective view of an example device 200 worn by an animal. Although Figure 2Mechanism 200 is shown as a collar, but it should be understood that mechanism 200 can be one or more mechanisms worn by and / or used to restrain an animal. For example, collar mechanism 200 may include collars, harnesses, bracelets, anklets, belts, earrings, headbands, etc. In other examples, devices that can accommodate or couple to electronic devices may include one or more attachment mechanisms, such as coats, boots, decorative clothing (e.g., ribbons), sweaters, hats, etc. Mechanism 200 can be used to restrain animals, store information about animals, and / or transmit information related to animals.

[0040] Mechanism 200 can be linked to a specific animal (e.g., to a specific animal's file). Mechanism 200 may include a circuit system 202, which may include a processor, storage device, wireless communication hardware, one or more sensors (e.g., accelerometers, gyroscopes, magnetometers, etc.), location devices (e.g., proximity beacons, GPS, satellite-based location systems, Bluetooth-based positioning / tracking systems, cellular-based location systems, etc.), temperature sensors, humidity detectors, biostatistical sensors, etc. The location devices (e.g., cellular-based location systems) can be used to triangulate the animal's location. In the example, the location device may measure the distance (e.g., relative distance) to another device (such as a user's mobile device). By determining the relative distance to another device (which may have one or more of an accelerometer, gyroscope, or cellular service), the animal's absolute distance can be determined. The wireless communication hardware may include a transmitter and a receiver. For example, the wireless communication hardware of mechanism 200 may include low-energy communication devices such as Bluetooth Low Energy or RFID. Mechanism 200 may include a Medical Implantable Communication System (MICS), Bluetooth, or a combination of these technologies such as MICS / Bluetooth. Mechanism 200 may include a memory for storing data. Circuitry system 202 may be coupled to a collar, such as collar 204, of mechanism 200.

[0041] An accelerometer located on mechanism 200 can be used to measure the animal's motion. For example, the accelerometer can measure the animal's acceleration, changes in the animal's velocity, and / or changes in the animal's orientation. A gyroscope can be configured to measure changes in the animal's orientation and / or changes in the animal's rotational rate. A magnetometer can be configured to measure the animal's orientation (e.g., absolute orientation) in the NESW plane.

[0042] As described above, mechanism 200 may include location devices, such as proximity beacons, GPS, etc. The location devices can track the animal's location. For example, the location devices can indicate whether the animal is inside a room, outside a room, etc. For example, the location devices can indicate whether the animal is in a park (e.g., a dog park), in an exercise area (such as the exercise area of ​​a kennel in a dog boarding facility), in an area packed in crates, etc. The animal's movement can be correlated with its location. For example, when the animal is outside a room, its acceleration / rate / speed and / or distance traveled may be greater than when it is inside a room. Therefore, it can be expected that the animal will run more when it is outside a room than when it is inside a room. For example, an animal located outside that does not run more than a predefined distance and / or does not run for a predefined time (e.g., based on the animal's size, breed, sex, etc.) may be identified as having an abnormal condition, while an animal located inside that does not run more than a predefined distance and / or does not run for a predefined time (e.g., based on the animal's size, breed, sex, etc.) may not be identified as having an abnormal condition. An animal's movement may be associated with the time of year and / or the outdoor conditions it is in. For example, dogs run less in cold temperatures (e.g., January) or rainy weather than in mild temperatures (e.g., April) or sunny days. Dogs scratch more on days with high pollen counts than on days with low pollen counts.

[0043] An animal's location over a given period (e.g., indoors) can be used to determine if the animal is being provided with the necessary amount of movement. This information can be used to determine whether the animal's caregiver should provide more or less outdoor time and / or exercise routines. Automatic alerts can be sent to the system when the animal spends less time indoors than a predefined amount, or when the animal moves less distance and / or for less time than a predefined amount, thus notifying the caregiver, pet guardian, veterinarian, etc. Based on these alerts, the caregiver can adjust the amount of time the animal spends outdoors and the amount of exercise the animal receives (e.g., the duration and / or distance of exercise). The animal's location and movement can be correlated. For example, the animal's movement while in boarding can be determined. Such information can be useful in determining the level of exercise the animal receives while in boarding.

[0044] Organization 200 can send animal-related data to servers, electronic devices (such as a pet guardian's or caregiver's mobile phone), etc. For example, organization 200 can send motion data (including gait data), orientation data, location data, etc., to servers, electronic devices, etc. The server can perform calculations on the data to, for example, determine whether the amount and / or duration of the animal's movement is expected. The server can determine the animal's signature based on the animal's movement. The animal's signature can be compared with the signatures of abnormal (e.g., sick, obese, etc.) animals and / or normal (e.g., not sick) animals. The server can be configured to transmit data to users and / or one or more other parties (e.g., veterinarians, pet guardians, caregivers, etc.). In the example, the electronic device (e.g., a caregiver's mobile phone) can perform calculations on the data to determine whether the animal's movement is above or below a predefined level expected for the animal. The electronic device can be configured to transmit data to users and / or one or more other parties (e.g., veterinarians, spouses, etc.).

[0045] The apparatus 200 may have biostatistical monitoring sensors. These sensors can be configured to determine and / or calculate the animal's body measurements. For example, a temperature sensor and / or a heart rate sensor can be used to determine the animal's body temperature and / or heart rate. The biostatistical monitoring sensors may be located on a movable collar or positioned on another device located on or around the animal.

[0046] Figure 3A , Figure 3B Example uses of mechanism 300 are shown. Figure 3A As shown, the cat can, for example, wear the mechanism 300 with a movable collar-shaped element. Figure 3B As shown, the dog can wear the mechanism 300. Although Figure 3A , Figure 3B The example shown is a ring, but it should be understood that the ring (e.g., a movable ring) is for illustrative purposes only, and as described herein, mechanism 300 can be any device (e.g., a wearable device) that can be implemented in shape factors other than a ring. For example, mechanism 300 can be a jacket, vest, hat, gloves, contact lens, ring (e.g., earring), or any other device (or combination of devices) that can be worn on the outside (or inside) of an animal. In other examples, as described herein, mechanism 300 can be any device and / or area that the animal may access, such as a waste area, feeding area, play area, etc.

[0047] As described herein, mechanism 300 (e.g., a movable collar) may have one or more sensors 302, such as accelerometers. Sensors 302 may be coupled to mechanism 300, for example, coupled externally to mechanism 300. In other examples, the sensors (e.g., accelerometers) may be integrally formed within mechanism 300. Figure 3A As shown, a position sensor 310 may be included in the system. The position sensor 310 may be located on the animal (e.g., worn by the animal) or positioned on a surface that is not the animal. The position sensor 310 may be a proximity sensor. For example, a proximity sensor may be used to determine whether the animal is near a predefined area (such as a feeding bowl, water bowl, and / or waste area).

[0048] Sensors and other devices can be used to determine animal movement, such as the direction, acceleration, rate (or velocity), and duration of the animal's movement. Animal movement can be determined based on animal motion data, orientation data, location data, etc. Sensors and other devices can be used to determine the location where the animal is moving. The location where the animal is moving can be useful in determining whether the animal is healthy or unhealthy (e.g., whether the animal is running in a play area or hiding in a resting area). The location where the animal is moving can be useful in determining whether the animal is exhibiting desired or undesirable behavior. The location where the animal performs an event can be useful in determining whether the animal is behaving in a desired or undesirable location. For example, when the animal is indoors (such as on its bed), it can be expected that the animal is resting, and / or when the animal is outdoors (such as in a dog park), it can be expected that the animal is moving at a predefined rate (or velocity) and for a predefined duration.

[0049] As described herein, the movable collar can provide animal movement data, orientation data, etc. Furthermore, animal location data can be provided, for example, via proximity sensors. Movement data, orientation data, and / or location data can be provided by devices worn or not worn by the animal. For example, location data can be provided by devices located near the animal (such as proximity sensors that can be located in feeding areas and / or waste areas).

[0050] Figure 4A , Figure 4B Example waste areas are shown that can be used to monitor animal movement to, for example, determine the animal's gait and / or other animal activities (such as defecation, urination, vomiting, etc.). A waste area can be any area where an animal regularly, periodically, or irregularly empties its intestines, bladder, and combinations thereof. Figure 4AAn example waste area 400 (waste area 400) is shown, which includes one or more devices, such as proximity sensors and / or measuring devices. The proximity sensor may be a camera zoom, motion detector, RFID tag, RFID reader, proximity beacon, GPS, passive infrared, microwave, ultrasound, etc. The proximity sensor can be used to track animal movement. For example, the proximity sensor can be used to track the acceleration, rate, speed, duration, frequency, direction, etc., of an animal's movement (e.g., gait) over a predefined time period.

[0051] Animal behavior and / or habits related to gait can be monitored at waste area 400 using sensors, devices (e.g., measuring devices) located at or on the waste area. Animal gait can also be monitored at waste area using sensors, devices (e.g., measuring devices) located on the animal (e.g., a movement collar) as described herein. The litter box 400 can track the distance and / or acceleration / rate / speed of an animal approaching, leaving, or moving towards the litter box. Although waste area 400 is shown as a litter box, it should be understood that waste area can be any shape factor other than a litter box. For example, waste area can be a designated area (e.g., inside or outside a room) where an animal may defecate, urinate, and / or vomit. Designated areas can include backyards, wallpapered areas, toilets, cages (such as birdcages), etc.

[0052] like Figure 4A As shown, waste area 400 may be an area designated for animals (e.g., cats) to urinate and / or defecate. Waste area 400 may have one or more sensors. The one or more sensors may be... Figure 4A and Figure 4B The example sensor 410 is shown. (As shown) Figure 4A As shown, sensor 410 may be located on a portion of a waste area (such as waste area 400). Sensor 410 may not be located on a portion of a waste area. For example, as Figure 4B As shown, sensor 410 may be located on a wall, table, or any other surface that may be within a predefined proximity to the waste area. As described herein, sensor 410 may be a motion sensor (such as an accelerometer, gyroscope, magnetometer, etc.), a proximity sensor, an orientation sensor, a position sensor, and / or one or more other sensors. Waste area 400 may include communication circuitry such as Bluetooth, RFID, Wi-Fi, and other wireless technologies. Waste area 400 may communicate with a moving loop (such as mechanism 300) and / or a server. Waste area 400 may communicate directly with a user's portable electronic device, or such communication may occur indirectly through a server and applications (such as web applications).

[0053] As described herein, the waste area 400 may include a proximity sensor, such as a camera zoom, for tracking the animal's movement over time, such as direction, acceleration, rate, speed, height, and / or resting periods. The waste area 400 may include memory, a controller, and a local user interface / display. As described herein, sensors, devices (e.g., measuring devices) located on the animal (e.g., a movement collar) may also be used, or alternatively, to monitor the animal's movement in the waste area.

[0054] Waste area 400 may have measuring devices, such as measuring device 420. As described herein, measuring device 420 may be one or more weighing scales, weight transducers, force transducers, displacement transducers, pressure transducers, weight sensors, force sensors, displacement sensors, pressure sensors, real-time clocks, timers, counters, and / or combinations thereof. Measuring device 420 may include one or more photoelectric sensors, such as diffuse reflective sensors, light-transmitting sensors, retroreflective sensors, and / or distance-settable sensors. For example, the area may be defined by a light beam. When the light beam is interrupted, it can be determined that an animal has entered or left the area. The measuring device may include a thermometer and / or a microphone that can be used to determine the presence or absence of an animal in the area. For example, urine and / or feces deposited by an animal in an area (e.g., waste area) may alter (e.g., increase) the temperature of the area or the animal's temperature. The microphone may be used to determine the presence of an animal or the animal's activity (such as urination, defecation, or passing urine).

[0055] Measuring device 420 can be used to measure the weight and / or pressure of an animal located at or near a waste area. Measuring device 420 can be used to measure one or more weights, pressures, etc., at or around a waste area. For example, measuring device 420 can be used to measure the weight of an animal in a litter box, pressures induced by the animal (e.g., pressures induced by the animal's paws), etc., including combinations thereof. Measuring device 420 can be used, for example, to measure the pressure of an animal, enabling the measuring device to identify when the animal enters, approaches, passes through, etc., a waste area. Measuring device 420 can be used to measure the pressure of an animal, thereby determining the animal's gait. For example, when the animal's acceleration, rate, and / or speed increase, the animal's legs can exert greater pressure on the ground.

[0056] Figure 5A , Figure 5BAn example feeding and watering area is shown that can be used to monitor animal movement to, for example, determine the animal's gait (e.g., the animal's gait at or near the feeding and watering area). The animal's gait can be monitored at the feeding and / or watering area using sensors, devices (e.g., measuring devices), etc., located at the feeding and / or watering area. For example, feeding bowl 500a and / or water bowl 500b may include communication circuitry systems such as Bluetooth, RFID, Wi-Fi, and other wireless technologies. Feeding bowl 500a and / or water bowl 500b may communicate with a movable collar (such as mechanism 300) and / or a server. Feeding bowl 500a and / or water bowl 500b may communicate directly with a user's portable electronic device, or such communication may occur indirectly via a server and application (such as a web application).

[0057] Feeding bowl 500a and / or water bowl 500b may include proximity sensors, such as camera zoom, for tracking the gait of the animal at or near feeding bowl 500a and / or water bowl 500b over time. Feeding bowl 500a and / or water bowl 500b may include memory, a controller, and a local user interface / display. As described herein, sensors, devices (e.g., measuring devices) located on the animal (e.g., a moving collar) may also or alternatively be used to monitor the animal's gait in the feeding and / or drinking area. Although the feeding and / or drinking area is shown as feeding bowl 500 and water bowl 500b, it should be understood that the feeding bowl and / or water bowl may be... Figure 5A , Figure 5B The feeding bowls and / or water bowls shown have different shape factors. For example, drinking devices can include any device that animals use to eat and / or drink. For example, drinking devices can be water bottles (e.g., used by guinea pigs, rabbits), sponges, raised water pools, etc.

[0058] like Figure 5A As shown, the food dish 500a and / or water bowl 500b can be designated areas for an animal (e.g., a cat) to eat and / or drink. The food dish 500a and / or water bowl 500b can have one or more sensors. For example, the sensors can be located on both the food dish and the water bowl, on the food dish but not the water bowl, or on the water bowl but not the food dish. One or more sensors can be... Figure 5A and Figure 5B The example sensors shown are 510a and 510b. (As shown...) Figure 5A As shown, sensors 510a and 510b may be located on a portion of the eating and / or drinking area, such as on the food plate 500a and / or the drinking bowl 500b. Sensors 510a and 510b may also not be located on a portion of the eating and / or drinking area. For example, as... Figure 5BAs shown, sensors 510a and 510b may be located on a wall, table, or any other surface that may be within a predefined proximity to the eating and / or drinking area. As described herein, sensors 510a and 510b may be one or more motion sensors (such as accelerometers, gyroscopes, magnetometers, etc.), proximity sensors, orientation sensors, position sensors, and / or one or more other sensors.

[0059] The food dish 500a and / or water bowl 500b may have measuring devices, such as measuring devices 520a and 520b. As described herein, measuring devices 520a and 520b may be one or more weighing scales, weight transducers, force transducers, displacement transducers, pressure transducers, weight sensors, force sensors, displacement sensors, pressure sensors, real-time clocks, timers, counters, and / or combinations thereof. In the example, the measuring devices may be used to measure the weight and / or pressure of an animal at or near the feeding and / or drinking area. The measuring devices may be used to measure the weight and / or pressure of food and / or beverage located at or near the feeding and / or drinking area. The measuring devices 520a and 520b may be used to measure one or more weights, pressures, etc., at or near the feeding and / or drinking area.

[0060] As described herein, an animal's gait can be determined based on movement and / or motion data, and orientation data. Motion data may relate to whether and / or how one or more parts of the animal (such as one or more of the animal's legs) move. Orientation data may relate to whether and / or how one or more parts of the animal (such as the animal's head) are pointing upwards or downwards. An animal's gait can be determined based on location data (e.g., if the animal moves from one location to another). An animal's gait can be determined based on a combination of location data, orientation data, and / or motion data. For example, an animal's gait can be determined based on whether it moves with high acceleration / rate / speed while its head is pointing upwards to move from one location in the pet yard to another. An animal's gait can include walking, trotting, jogging, slow walking, pacing, running, etc.

[0061] An animal's motion data can be derived from one or more sensors (such as one or more accelerometers) placed on the animal's collar, legs, torso, etc. For example, an accelerometer placed on the animal's collar can determine (e.g., sense) a dog's movement. Sensor data (e.g., accelerometer data) received from the animal's collar can be associated with data related to one or more of the animal's appendages (e.g., legs, arms, neck). For example, accelerometer data received from the animal's collar can be associated with motion data related to the animal's legs. Motion data related to the animal's legs can be used to determine the animal's gait.

[0062] For example, sensor data can be received from a sensor (e.g., an accelerometer) located on and / or coupled to an article (e.g., a collar) on an animal. The sensor data can be normalized and / or converted to describe the movement of the collar around the animal, such as rotation of the collar around the animal's neck. The sensor data can be normalized by determining the direction of the acceleration (e.g., linear acceleration) components of the acceleration measurement signal and / or adjusting the values ​​of the x, y, and z axes.

[0063] As described herein, accelerometer data obtained from an animal's ring can be used to determine the movement data (e.g., acceleration, speed, direction, position) of one or more of the animal's appendages (e.g., legs). For example, by determining the movement data of an animal's legs, it can be determined whether the animal is walking, trotting, jogging, walking slowly, pacing, running, resting, etc. Furthermore, by determining the time of the animal's appendage movement, it can be determined the duration and / or frequency of the animal's walking, trotting, jogging, walking slowly, pacing, running, resting, and / or having already walked, trotting, jogging, walking slowly, pacing, running, resting, etc. Such information can be used to determine the animal's activity (or inactivity) and / or whether the animal is injured, sick, immobile, healthy, etc. For example, an animal that has run for a predetermined amount of time may be considered a healthy animal. An animal that has rested for a predetermined amount of time may be considered an unhealthy animal, etc.

[0064] Sensor data associated with an animal can be correlated with time periods. Time periods can be correlated with frames. Sliding windows can be used to divide sensor data into frames containing short time periods. For example, frames can be milliseconds (e.g., 50 milliseconds), seconds (e.g., 10 seconds), minutes (e.g., 30 minutes), hours (e.g., 2 hours), days, weeks, etc. Sensor data within a frame can be used to determine the animal's gait within that frame. Sensor data within overlapping frames can be determined. Sensor data within overlapping frames can be used to illustrate the animal's transition from one gait to another.

[0065] The range of features associated with sensor data can be determined (e.g., calculated). For example, the entropy, amplitude, kurtosis, signal energy, standard deviation, etc., of the sensor data can be determined. The distribution of the entropy, amplitude, kurtosis, signal energy, standard deviation, etc., of the sensor data can be analyzed to assess one or more values ​​(e.g., the range of values) expected for each gait category. For example, the standard deviation of an animal's sensor data can be determined. The determined standard deviation can be compared with a predefined standard deviation associated with the animal's gait. Based on the comparison between the determined standard deviation and the predefined standard deviation, the animal's gait can be determined.

[0066] Machine learning techniques can be used, for example, to determine an animal's gait based on sensor data. Sensor data can include training data, test data, and / or validation data. For example, sensor data can be collected to generate a set of training data. Training data can be examples of sensor data used during the learning process. The training data can be used to fit the sensor data to, for example, determine sensor data that can be associated with one or more gaits of the animal.

[0067] Training data can be used to train one or more networks (e.g., neural networks). Properties of the network and / or its layers (e.g., specifications) can determine which parts of the network can be activated based on incoming data (e.g., incoming sensor data). The network can include one or more networks, such as one or more Long Short-Term Memory (LSTM) networks. As known to those skilled in the art, one or more LSTM networks can include artificial recurrent neural network (RNN) architectures. LSTM networks can include feedback connections. LSTM networks can process the localization, movement, and / or orientation of animals. For example, LSTM networks can process and / or provide inertial measurement unit (IMU) data provided by electronic devices (e.g., via accelerometers, gyroscopes, magnetometers, etc.). An LSTM unit can include a cell, input gates, output gates, and / or forget gates. The cell can recall values ​​within time intervals (e.g., arbitrary time intervals), and / or one or more gates can regulate the flow of information entering and leaving the cell.

[0068] The network may include one or more (e.g., two) LSTM layers, dropout layers, dense rectified linear unit (ReLU) activation layers, and / or dense softmax activation layers. The network architecture (e.g., the model) can be determined empirically. Hyperparameters can be optimized using one or more methods (such as via grid search). The network (e.g., the model) may use classification cross-entropy as the loss function and may employ the Adam optimizer. The network may be trained via an iterative process, during which the network is trained on a training set and tested on a test set (e.g., then tested). The network can be tuned according to an optimization algorithm, and the loss can be calculated. This process may be repeated for a set number of iterations, a set time period, and / or until the loss reaches a predetermined threshold.

[0069] Once training is complete, validation data that might not have been previously detected by the system can be provided to the network. Validation data can be used to establish performance metrics. Validation data excludes data that falls outside the expected feature range for one or more gaits in the animal. Ranges can be identified in stages prior to the validation phase (such as the preprocessing phase). Excluding data may result in data that is representative of the gait or falls within the same range (e.g., data only), eliminating most non-significant data.

[0070] To validate the performance of the data, the network can be tested on data collected in one or more contexts (e.g., one or more different contexts). Test data in different contexts can identify the general applicability of the data, such as the general applicability of the classifier. For example, during data collection, the range of one or more (e.g., different) forward movement patterns can be identified. The classifier can be used to infer the gait presented at each time point in the data. Classification performance metrics can be (e.g., then can) calculated by evaluating the relationship between predicted labels and annotations.

[0071] As described herein, one or more data sources can be used to determine an animal's movement (e.g., forward movement, such as gait). For example, one or more motion sensors (such as accelerometers, gyroscopes, magnetometers, etc.), proximity sensors, orientation sensors, position sensors, etc., can be used to determine an animal's movement (e.g., gait). Data sources can be placed on the animal (e.g., on the animal's collar) and / or near the animal (e.g., in a feeding bowl, waste area, resting area, play area). By collecting and / or combining two or more data sources (e.g., data sources with complementary sensing platforms), a framework for evaluating animal movement (e.g., forward movement, such as gait) can be determined. For example, a pressure sensor located on a mat can provide information about the animal's weight distribution as the animal moves forward, backward, and / or laterally. Pressure sensor data, combined with accelerometer data (e.g., accelerometer data recorded simultaneously with pressure sensor data), can identify patterns in the accelerometer data that may represent data from the pressure sensors. Identifying patterns in accelerometer data that can be representative of pressure sensor data can provide insights into movement patterns (e.g., forward movement, such as gait information) that may not be readily available from accelerometer data alone. Such analysis can be used to identify animals suffering from a range of movement-based health challenges, such as hip / elbow dysplasia, osteoarthritis, etc., using only accelerometer data.

[0072] An animal's gait can be determined based on one or more of its movement, position, orientation, etc. Gait indicators may include: when the animal is running, the animal's legs move at a predetermined acceleration and / or rate; when the animal is sprinting or jumping, the animal's height changes by a predetermined height; when the animal is resting, the orientation of the animal (e.g., the animal's legs), etc. An animal's gait can be determined based on the animal's movement associated with these indicators. As another example, the animal's acceleration and / or rate can be determined by one or more sensors (e.g., accelerometers) located on the animal.

[0073] If the accelerometer is located on the animal (e.g., on the animal's collar), the animal's acceleration and / or rate can be correlated with the acceleration and / or rate of movement of the animal's neck. The acceleration and / or rate of movement of the animal's neck can be converted (e.g., transformed) into the acceleration and / or rate of movement of one or more of the animal's appendages (e.g., legs). If the animal's legs move with an acceleration and / or rate smaller than the acceleration and / or rate at which the animal's legs would move when the animal is running (e.g., a non-running sign), it can be determined that the animal is not running. In such an example, it can be determined that the animal is walking, trotting, resting, etc. Alternatively, if the animal's legs move with an acceleration and / or rate larger than the acceleration and / or rate at which the animal's legs would move when the animal is running (e.g., a running sign), it can be determined that the animal is running. In such an example, it can be determined that the animal is walking, trotting, resting, etc.

[0074] Mathematical and / or algorithmic techniques (such as bivariate analysis, multivariate analysis, and trend analysis) can be used to determine trends in animal movement (e.g., running, trotting, resting, etc.). Data collected and processed over time can represent a typical profile of an animal's behavior and habits. Animal behavior and habits can be used to determine an animal's gait. For example, injured or otherwise ill animals may exhibit different movement habits compared to healthy animals. Trend analysis can be used to determine whether the behavior, habits, etc., of a monitored animal are random or whether a trend is developing.

[0075] Data can be captured during the duration of an animal's activity and / or inactivity. Data can be captured by periodically sampling one or more sensors, such as motion sensors (e.g., accelerometers, gyroscopes, etc.), proximity sensors (e.g., camera devices, etc.). Arrays of digital data can be processed to, for example, extract an animal's movement or inactivity (e.g., walking, trotting, resting, etc.). Data can be processed on the fly within the device (e.g., a user device) (e.g., applying methods as data samples are received, rather than storing the entire dataset). Data can be stored in the device (in full length or partially). Data can be processed, for example, in a delayed manner within the device. Data can be processed from outside the device. For example, data can be processed in a server, a portable electronic device, and / or a database where data processing can be performed.

[0076] Notifications may be delivered to users in the following forms: email messages sent to the user's specified email address; text messages sent to the user's specified mobile phone number via SMS (Short Message Service); calendar reminders set by the system in the user's specified calendar; telephone calls to the user's specified mobile or landline phone number; and messages via mobile phone applications using the user's mobile phone.

[0077] It can record the time and / or duration of animal movement (e.g., forward movement, backward movement, lateral movement, swaying from side to side, etc.). It can record the date and / or time of events such as running, walking, jumping, and resting. It can record the time of year and / or outdoor conditions. It can record the animal's orientation and / or location. All records can be stored and / or presented in text or graphic format, for example.

[0078] Animal profiles can be accessed via portable electronic devices. These devices can provide a user interface, for example, through an application downloaded to them. Users can create animal-associated profiles. The application can display the animal's profile and / or facilitate the uploading of animal monitoring information (such as animal movement). Icons or symbols displayed on the application can specify one or more movements of the animal that can be monitored and / or tracked. For example, a five-bar icon can indicate an animal running, a three-bar icon can indicate an animal walking, and a zero-bar icon can indicate an animal sleeping, etc. For ease of reference, such data can be displayed in the form of charts.

[0079] Figures 6A to 6D Example screenshots illustrating the use of a system for determining an animal's movement information (e.g., gait information) are shown. For example, screenshots can be provided on a portable electronic device. The screenshots provide information related to the animal's movement (e.g., type of movement, duration of movement, average acceleration and / or rate (or speed) of movement, direction of movement, times when the animal is most active during movement, times when the animal is least active during movement, etc.). The information shown in the screenshots is for illustrative purposes only and is not intended to be limiting. In the example, other information (such as backward movement, lateral movement, vertical movement, resting periods, etc.) may be provided to the user.

[0080] Figure 6A Example screenshots are shown of data collected and / or provided by one or more sensors, such as proximity sensors located near the animal (e.g., in feeding areas, waste areas, play areas, etc.). Identity 602 shows the identity of the animal in which movement (e.g., gait) is being monitored, determined, and / or displayed. Although identity 602 is in Figure 6A The name of the animal is shown, but identity 602 may display one or more other types of information used to identify the animal, such as the animal's size (e.g., thin, short, long, short), breed, unique code (e.g., number) identifying the animal, pet owner information, etc. Screenshots may be provided on a display, such as on the display of a portable electronic device.

[0081] A time period (such as date 604) can be provided. The time period can define the time frame for which data is monitored and / or provided (e.g., the time frame for monitoring and / or providing data such as gait data of an animal). Use Figure 6A The example shown above provides gait data for a single day (such as July 20, 2020). In other examples, the time period can be any duration, including multiple days, a week, a month, etc. Based on the desired time period, gait information (such as movement type 606) can be provided. Figure 6A As shown, the movement type can be running, although other movement type information can be provided in other examples (such as movement type 606 being walking), such as... Figure 6B As shown.

[0082] Information related to motion type 606 can be provided and / or identified. For example, such as... Figure 6A , Figure 6B As shown, the following information can be provided and / or determined: the duration 608 of movement type 606; the average acceleration and / or rate (or speed) 610 of movement type 606; the most active time when movement type 606 occurs; and / or the least active time when movement type 606 occurs. The number and list of these events are for illustrative purposes only. Different (including more or fewer) categories of data, time periods, animal movement, etc., can be displayed. For example, multiple movement types can be provided, averages and / or comparisons involving different movement types can be provided, conditions related to movement type data can be provided (such as whether the animal is healthy or unhealthy based on the movement type data), and suggestions based on movement type can be provided (such as suggestions to let the animal rest and / or to have the animal examined by a veterinarian), etc.

[0083] like Figure 6C As shown, a screenshot can provide information related to one or more motion types (e.g., motion decomposition 614). The motion decomposition 614 information may include one or more pieces of information related to one or more motion types, such as the name of the motion type during a predetermined time period, the duration of one or more motion types, the acceleration and / or rate (or velocity) of the motion type, etc. For example, as... Figure 6CAs shown in the user screenshot, the animal may have run for 73 minutes, walked for 223 minutes, and / or rested for 730 minutes on July 20, 2020. As described herein, the numbers and lists of these events are for illustrative purposes only. Different categories of data (including more or less) can be displayed. For example, information related to whether the animal's movement and rest (e.g., sleeping) were sufficient or insufficient can be determined. Information on the animal's condition based on movement and / or information on how to remedy the condition can be provided. For example, if the animal runs less than a predetermined amount within a certain time period, instructions can be given to the animal's caregiver to take the animal to a veterinarian.

[0084] like Figure 6D As shown, information related to an animal's movement type can be provided in graphical form. For example, a screenshot can be displayed graphically as information related to the animal's running movement type 606. The information displayed graphically can include the duration of the animal's run within that time period, the animal's acceleration and / or rate (or speed) during that time period, etc. Figure 6D As shown, the graphical information related to motion data can be correlated with the duration of an animal's run over a seven-day period. Although Figure 6D The display shows a seven-day time period and graphical information related to the duration of different movement types; however, the number of events, event lists, etc., are for illustrative purposes only. Different categories of data (including more or less) can be displayed. More or fewer screenshots can be provided, presenting more or less data to the user. Screenshots and / or data can be used to provide animal movement data (e.g., forward movement data, such as gait data), animal marking data (e.g., gait marking data), animal orientation data, animal location data, etc.

[0085] Based on the above, information related to an animal's gait can be provided. For example, it can be expected that healthy animals will have certain gait characteristics (such as running for more than a predetermined amount of time), unhealthy animals will have certain gait characteristics (such as running for less than a predetermined amount of time), and animals with certain conditions will have certain gait characteristics (such as obese or old animals running for less than a predetermined amount of time), etc.

[0086] Figure 7An example method 700 for monitoring animal movement and / or motion data is described. At 702, movement data can be received from a sensor. As described herein, the sensor can be one or more sensors. For example, the sensor can be a sensor (or other device) configured to detect the animal's position, detect the animal's movement (or stillness), detect the animal's orientation, etc. As described herein, the sensor can be one or more of a variety of shape factors. For the purposes of this disclosure, the sensor can include one or more measuring devices. For example, the sensor can be one or more of the following: accelerometer, gyroscope, magnetometer, weighing scale, weight transducer, force transducer, displacement transducer, pressure transducer, weight sensor, force sensor, displacement sensor, pressure sensor, load cell, photographic / video recording device, camera, video camera, contact thermometer, non-contact thermometer, and combinations thereof. The sensor can be one or more of the following: optical sensor, optical reflection sensor, LED / photodiode pair optical sensor, LED / phototransistor pair optical sensor, laser diode / photodiode pair optical sensor, laser diode / phototransistor pair optical sensor, optocoupler, fiber optic coupled optical sensor, magnetic sensor, weight sensor, force sensor, displacement sensor, pressure sensor, various proximity sensors (such as inductive proximity sensors, magnetic proximity sensors, capacitive proximity sensors), and / or combinations thereof. Motion data can be correlated with time periods.

[0087] Motion data can be data on an animal's movement, position, orientation, etc. This data can be provided via one or more sensors or devices. Motion data can be correlated with hours, days, weeks, months, etc. Motion data can be received from one or more other devices, such as measuring devices or one or more other sensors. Motion data can be received at a processor. Motion data can be correlated with the movement of one or more parts of the animal's body. For example, if a sensor is located on a collar around the animal's neck, the sensor can detect movement of the animal's neck. In other examples, the sensor can be located on the animal's legs, ears, teeth, torso, etc. In such examples, the sensor can detect movement in the corresponding area of ​​the animal where the sensor is located. As described herein, animal movement can be determined in one or more locations where the sensor is not located. For example, a sensor coupled to a collar can determine movement of the animal's neck. Movement of the animal's neck can be used to determine movement of one or more other locations of the animal, such as one or more appendages (e.g., legs).

[0088] At point 704, the animal's gait can be determined (e.g., the animal's gait during a first predetermined time period). The animal's gait can include whether and / or how the animal walks, trots, jogs, walks slowly, runs, etc. The animal's gait can include its walking speed. The animal's gait can be determined based on the animal's movement data, orientation data, position data, etc. Movement data can relate to the movement of one or more parts of the animal, such as one or more of the animal's appendages (e.g., legs). Orientation data can relate to one or more parts of the animal, such as whether the animal's head is pointing upwards or downwards. The animal's gait can be determined based on whether the animal moves from one location to another. The animal's gait can be determined based on a combination of position data, orientation data, and / or movement data. For example, the animal's gait can be based on: the animal moving forward with high acceleration and / or rate (or speed) to travel from one location to another while its head is pointing upwards.

[0089] An animal's gait can be assigned to one or more data frames. Each frame can provide the animal's gait over a specific time period (e.g., a short time period). Frames that provide gait information can overlap. For example, one or more frames can provide an overlap of one animal's gait (e.g., running) with another animal's gait (e.g., walking). This overlap can provide the transition between one and another animal's gait. Data associated with the gait information can be determined. For example, entropy, amplitude, kurtosis, signal energy, standard deviation, etc., of data associated with the animal's gait can be determined.

[0090] At point 706, the duration and / or frequency of an animal's gait can be determined. For example, it can be determined how long and / or how many times the animal ran, walked, sprinted, or rested within a given time period. For instance, it can be determined that the animal ran for 90 minutes within a 24-hour period. 90 minutes could include three runs of 30 minutes each. As another example, it can be determined that the animal may have rested for 15 hours within a 24-hour period. These 15 hours could include 10 consecutive hours of sleep at night and two additional 150-minute rest periods.

[0091] At point 708, the animal's activity level within a predetermined time period can be determined. The animal's activity level can be based on its gait during the predetermined time period, such as the frequency and / or duration of its gait. Using the example above, it can be determined that the animal has run for 90 minutes within a 24-hour time period. A running threshold for a healthy animal (e.g., a healthy animal with similar body size, breed, age, weight, sex, and / or medical condition) could be 75 minutes within a 24-hour time period. By comparing the actual animal's gait information with the threshold gait information, it can be determined that the animal's gait information is consistent with that of a healthy animal.

[0092] Using other examples, it can be determined that an animal rested for 15 hours within a 24-hour period. The rest threshold for a healthy animal (e.g., a healthy animal with similar body size, breed, age, weight, sex, and / or medical condition) could be 12 hours within a 24-hour period. By comparing the actual animal's gait information with the threshold gait information, it can be determined that the animal's gait information is consistent with that of an unhealthy animal. Based on the determination of whether the animal exhibits a healthy or unhealthy gait, the animal's caregiver can be notified to seek medical attention for the animal.

[0093] By comparing actual animal gait information with threshold gait information, it can be determined whether the animal is receiving adequate exercise. For example, if an animal does not run the predetermined amount of time within a certain period, it can be determined that the animal is receiving insufficient exercise and / or excessive rest, which may cause health problems for the pet. In some examples, caregivers may personally provide additional exercise for the pet. In other examples, the animal may be boarded, and a pet guardian can advise the pet's boarder that the pet needs additional exercise.

[0094] Health and / or unhealthy threshold information can be updated based on machine learning techniques. For example, a machine learning model can initially be set to indicate that resting more than 10 hours per 24-hour period is unhealthy. Based on training the model using a separate dataset, the thresholds can be changed to indicate that resting 10 to 14 hours represents a healthy animal, and resting more than 14 hours per 24-hour period is unhealthy. Additional datasets can be updated based on veterinary data. For example, additional datasets can be updated in real time based on daily feedback provided by veterinarians when treating pets of various sizes, breeds, weights, ages, sexes, medical conditions, etc.

[0095] At point 708, information related to the animal can be displayed, such as the animal's activity level over a predetermined time period. Activity level can include the animal's gait, gait breakdown (such as gait identity, gait duration, gait frequency, etc.), etc. For example, information indicating that the animal has been running for 90 minutes can be provided. As described herein, information associated with the animal's activity level can be provided. For example, if the animal's activity indicates a healthy condition, such information can be provided. Alternatively, if the animal's activity indicates an unhealthy condition, such information can be provided. If it is determined that the animal is unhealthy, remedial information can be provided. Remedial information can include information that the pet owner can take (such as administering over-the-counter medication) and / or instructions that the animal should be examined by a veterinarian. Information related to the animal's activity level can be displayed on the screen of a portable electronic device such as a mobile phone, tablet, or cell phone.

[0096] While specific examples, including the currently preferred mode of implementation, have been described, those skilled in the art will recognize that various variations and substitutions of the systems and techniques described above are possible. It should be understood that other embodiments can be utilized, and structural and functional modifications can be made, without departing from the scope of the invention. Therefore, the spirit and scope of the invention should be interpreted broadly as set forth in the appended claims.

Claims

1. A method for determining the health status of an animal, comprising: The movement data of an animal during a first predetermined time period is received via a sensor, wherein the movement data includes at least one of the following: the animal's acceleration during the first predetermined time period, the animal's speed during the first predetermined time period, the distance traveled by the animal during the first predetermined time period, the animal's position during the first predetermined time period, or the steps taken by the animal during the first predetermined time period. The gait of the animal during the first predetermined time period is determined by one or more processors based on the animal's movement data during the first predetermined time period, the movement data being based on one or more of the animal's movement, position, and orientation. Determine the duration and frequency of the animal's gait during the first predetermined time period; Determine the first time corresponding to the animal's most active gait exercise during the first predetermined time period; Determine a second time corresponding to the animal's least active gait exercise during the first predetermined time period; Record the time period of the first predetermined time period within one year; Record the outdoor conditions under which the animal practiced its gait during the first predetermined time period; The activity level of the animal during the first predetermined time period is determined based on the duration and frequency of its gait during the first predetermined time period. The activity level of the animal during the first predetermined time period is displayed via a display device; Animal characteristic data is received via one or more processors, the animal characteristic data including at least one of the animal's age, weight, body size, or breed; and The health status of the animal is determined by one or more processors based on the animal's characteristic data and the animal's activity level and gait during the first predetermined time period.

2. The method according to claim 1, wherein, The animal's gait includes at least one of the following: trotting, jogging, crawling, walking slowly, pacing, or running.

3. The method according to claim 2, further comprising: The health status is determined by one or more processors.

4. The method according to any one of the preceding claims, further comprising: The activity level of the animal during a second predetermined time period is determined by one or more processors, the second predetermined time period being longer than the first predetermined time period.

5. The method according to any one of claims 1 to 3, further comprising: The level of exercise of the animal during the first predetermined time period is determined based on the animal's gait during the first predetermined time period.

6. The method according to claim 1, wherein, The animal's health condition includes whether the animal is experiencing at least one of obesity, arthritis, hip dysplasia, or neurological conditions.

7. The method according to any one of claims 1 to 3, wherein, The sensor is coupled to an item worn by the animal.

8. The method according to any one of claims 1 to 3, wherein, The sensor includes at least one of an accelerometer, a gyroscope, a magnetometer, or a Global Positioning System (GPS) device.

9. The method according to any one of claims 1 to 3, wherein, The sensor was implanted into the animal.

10. The method according to claim 1, further comprising: The animal's movement data is input into the neural network; Exclude any data falling outside the expected characteristic range of one or more gaits of the animal; and The animal's characteristic data is updated based on the animal's movement data.

11. A system for determining the activity level of an animal, comprising: A sensor configured to receive movement data of the animal during a first predetermined time period, wherein the movement data includes at least one of the following: acceleration of the animal during the first predetermined time period, speed of the animal during the first predetermined time period, distance traveled by the animal during the first predetermined time period, position of the animal during the first predetermined time period, or strides taken by the animal during the first predetermined time period; and One or more processors, said one or more processors being configured to: The animal's gait during the first predetermined time period is determined based on the animal's movement data during the first predetermined time period; Determine the duration and frequency of the animal's gait during the first predetermined time period; Determine the first time corresponding to the animal's most active gait exercise during the first predetermined time period; Determine a second time corresponding to the animal's least active gait exercise during the first predetermined time period; Record the time period of the first predetermined time period within one year; Record the outdoor conditions under which the animal practiced its gait during the first predetermined time period; The activity level of the animal during the first predetermined time period is determined based on the duration and frequency of its gait during the first predetermined time period. The activity level of the animal during the first predetermined time period is displayed via a display device; and The animal's health status is determined based on its activity level during the first predetermined time period.

12. The system according to claim 11, wherein, The animal's gait includes at least one of the following: walking, trotting, jogging, slow walking, strolling, or running.

13. The system according to claim 11, wherein, The one or more processors are also configured to track activity levels over a second predetermined time period, which is longer than the first predetermined time period.

14. The system according to claim 11, wherein, The one or more processors are further configured to determine the level of exercise of the animal during the first predetermined time period based on the animal's gait during the first predetermined time period.

15. The system according to claim 11, wherein, The one or more processors are further configured to: Receive animal characteristic data, said animal characteristic data including at least one of the following: the animal's age, the animal's weight, the animal's body size, the animal's sex, the animal's breed, the animal's body fat index (BFI), the animal's body condition score (BCS), or the animal's muscle condition score (MCS); and The animal's health status is determined based on the animal's characteristic data and its gait during the first predetermined time period.

16. The system according to claim 15, wherein, The animal's health condition includes whether the animal is experiencing at least one of obesity, arthritis, hip dysplasia, or neurological conditions.

17. The system according to claim 11, wherein, The sensor is coupled to an item worn by the animal.

18. The system according to claim 11, wherein, The sensor includes at least one of an accelerometer, a gyroscope, a magnetometer, or a Global Positioning System (GPS) device.

19. The system according to claim 11, wherein, At least one of the one or more processors is located at the server.

Images