PERSONALIZED WELLNESS SYSTEMS AND METHODS OF USE
A health and wellness system for a non-human subject comprising analyzing genetic data and phenotypic data of the non-human subject with a machine learning algorithm and making a recommendation or recommendation for products or activities for the non-human subject.
1 . A method for modifying a nutritional product recommendation for a non-human animal subject, the method comprising;
(a) retrieving, from a database, a data set associated with an initial nutritional product recommendation to improve ameliorate or prevent a condition in said non-human animal subject, wherein said initial nutritional product recommendation is based, at least in part, on genetic data and phenotype data of said non-human animal subject;
(b) receiving activity data or behavioral data for said non-human animal subject obtained from an activity tracking device of said non-human animal subject;
(c) processing said activity data or behavioral data to determine qualitative or quantitative measures that predict whether said non-human animal subject is likely to have or develop another condition that differs from said condition in (a);
(d) modifying said initial nutritional product recommendation based, at least in part, on said activity data or behavioral data processed in (c), wherein said modifying said initial nutritional product improves, ameliorates, or prevents said another condition.
2 . The method of claim 1 , wherein said initial nutritional product comprises a supplement, a treat, a food, or any combination thereof.
3 . The method of claim 1 , wherein said modifying said initial nutritional product recommendation comprises modifying an amount of said initial nutritional product or an amount of one or more ingredients in said initial nutritional product.
4 . The method of claim 1 , wherein said modifying said initial nutritional product recommendation comprises recommending a new nutritional product.
5 . The method of claim 4 , wherein said new nutritional product comprises a supplement, a treat, a food, or any combination thereof.
6 . The method of claim 1 , wherein said activity tracking device is a collar.
7 . The method of claim 6 , wherein said collar is a Global Positioning System (GPS)-connected collar.
8 . The method of claim 1 , wherein said condition or said another condition is a skin condition, a coat condition, or a skin or coat infection.
9 . The method of claim 1 , wherein said condition or said another condition is an allergic reaction.
10 . The method of claim 9 , wherein said allergic reaction is an allergic itch.
11 . The method of claim 1 , wherein said condition or said another condition is pain, inflammation, or a combination thereof.
12 . The method of claim 1 , wherein said condition or said another condition is osteoarthritis, pain associated with osteoarthritis, or both.
13 . The method of claim 1 , wherein said activity data comprises data related to activity type, data related to an activity level, consumption data, sleep data, or any combination thereof.
14 . The method of claim 13 , wherein said consumption data comprises calories or water consumed by said non-human animal subject.
15 . The method of claim 1 , wherein said behavioral data comprises a repetitive behavior.
16 . The method of claim 15 , wherein said repetitive behavior comprises itching, chewing, scratching, sighing, aggression, neurosis, anxiety, abnormal energy level, or any combination thereof.
17 . The method of claim 1 , wherein said genetic data is not associated with a breed type.
18 . The method of claim 1 , further comprising:
(e) receiving new activity data or new behavioral data of said non-human animal subject obtained from said activity tracking device;
(f) processing said new activity data or said new behavioral data to determine qualitative or quantitative measures that predict whether said non-human animal subject is likely to have or develop said another condition or a third condition that differs from said condition in (a); and
(g) modifying said initial nutritional product recommendation based, at least in part, said new activity data or said new behavioral data processed in (f), wherein said modifying said initial nutritional product improves, ameliorates, or prevents said another condition or said third condition.
19 . The method of claim 1 , wherein said modified nutritional product recommendation is displayed on a graphical user interface of a personal electronic device of a user.
20 . The method of claim 1 , wherein said processing is performed by a machine learning algorithm.