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Patent US10546658


Issued 2020-01-28

Systems And Methods For Formulating Personalized Skincare Products

Systems and methods for formulating a personalized skincare product for a user. Data inputs reflecting dermal information of the user (e.g., hydration level measurements, oil level measurements, and a photograph of the user's skin reflecting a set of skin concerns) are collected by a computing device and used to determine a set of normalized scores. A skin health data set is generated based on the normalized scores and stored in memory. A skin health metric is determined based on the skin health data set and is stored in memory. The computing device determines, using a machine learning framework, one or more first skincare product formulations based on the user skin health data set. The formulation(s) can be used to manufacture one or more customized skincare products for the user and can be iteratively refined over time, e.g., by collecting additional data from the user over time.



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3 Independent Claims

  • 1. A computerized method of formulating a skin care product for a user using a machine-learning algorithm implemented on a computing device, the method comprising: receiving, by the computing device, data inputs including one or more hydration level measurements of the user's skin taken using a corneocyte test, one or more oil level measurements of the user's skin taken using a sebum test, and a photograph of the user's skin taken using a camera reflecting a set of skin concerns; determining, by the computing device, based on the one or more hydration level measurements, a normalized hydration index score using a first computer vision engine trained on a data set of corneocyte test results; determining, by the computing device, based on the one or more oil level measurements, a normalized oil index score using a second computer vision engine trained on a data set of sebum test results; determining, by the computing device, based on an adjusted photograph of the user's skin, a set of normalized severity scores corresponding to a set of skin concerns of the user using a third computer vision engine trained on an anomaly detection model or a convolutional neural network, wherein the adjusted photograph of the user's skin includes one or more illumination adjustments of the photograph and is determined using the anomaly detection model or the convolutional neural network applied to the photograph by the third computer vision engine; generating, by the computing device, a first skin health data set including the normalized hydration index score, the normalized oil index score, and the set of normalized severity scores; storing, by the computing device, the first skin health data set in first memory in electronic communication with the computing device; determining, by the computing device, based on the first skin health data set, a first skin health metric; storing, by the computing device, the first skin health metric in second memory in electronic communication with the computing device; determining, by the computing device, using a machine learning framework operating on the computing device, one or more first skin care product formulations based on the first skin health metric and the first skin health data set; storing, by the computing device, the one or more first skin care product formulations in third memory in electronic communication with the computing device; and providing, by the computing device, the one or more first skin care product formulations to the user in the form of a recommendation.

  • 16. A computing system for formulating a skincare product for a user using a machine-learning algorithm implemented on a computing device, the system comprising: the computing device, configured to: receive data inputs including one or more hydration level measurements of the user's skin taken using a corneocyte test, one or more oil level measurements of the user's skin taken using a sebum test, and a photograph of the user's skin taken using a camera reflecting a set of skin concerns; determine, based on the one or more hydration level measurements, a normalized hydration index score using a first computer vision engine trained on a data set of corneocyte test results; determine, based on the one or more oil level measurements, a normalized oil index score using a second computer vision engine trained on a data set of sebum test results; determine, based on an adjusted photograph of the user's skin, a set of normalized severity scores corresponding to a set of skin concerns of the user using a third computer vision engine trained on an anomaly detection model or a convolutional neural network, wherein the adjusted photograph of the user's skin includes one or more illumination adjustments of the photograph and is determined using the anomaly detection model or the convolutional neural network applied to the photograph by the third computer vision engine; generate a first skin health data set including the normalized hydration index score, the normalized oil index score, and the set of normalized severity scores; store the first skin health data set in first memory in electronic communication with the computing device; determine, based on the first skin health data set, a first skin health metric; store the first skin health metric in second memory in electronic communication with the computing device; determine, using a machine learning framework operating on the computing device, one or more first skin care product formulations based on the first skin health metric and the first skin health data set; store, the one or more first skin care product formulations in third memory in electronic communication with the computing device; and provide the one or more first skin care product formulations to the user in the form of a recommendation.

  • 19. A computerized method of formulating first and second skin care products for a user using a machine-learning algorithm implemented on a computing device, the method comprising: receiving, by the computing device, first data inputs reflecting dermal information of the user, the first data inputs including one or more hydration level measurements of the user's skin taken using a corneocyte test, one or more oil level measurements of the user's skin taken using a sebum test, and a photograph of the user's skin taken using a camera reflecting a set of skin concerns; determining, by the computing device, based on the one or more hydration level measurements, a normalized hydration index score using a first computer vision engine trained on a data set of corneocyte test results; determining, by the computing device, based on the one or more oil level measurements, a normalized oil index score using a second computer vision engine trained on a data set of sebum test results; determining, by the computing device, based on an adjusted photograph of the user's skin, a set of normalized severity scores corresponding to a set of skin concerns of the user using a third computer vision engine trained on an anomaly detection model or a convolutional neural network, wherein the adjusted photograph of the user's skin includes one or more illumination adjustments of the photograph and is determined using the anomaly detection model or the convolutional neural network applied to the photograph by the third computer vision engine; generating, by the computing device, based on the first data inputs, a first skin health data set for the user, the first skin health data set including one or more normalized scores reflecting the first data inputs; storing, by the computing device, the first skin health data set in first storage in electronic communication with the computing device; determining, by the computing device, a first skincare product formulation based on the first skin health data set; storing, by the computing device, the first skincare product formulation in second storage in electronic communication with the computing device; providing, by the computing device, the first skin care product formulation to the user in the form of a first recommendation; receiving, by the computing device, second data inputs-reflecting changes in the first data inputs after use of a first skincare product based on the first skincare product formulation; generating, by the computing device, based on the first data inputs and second data inputs, a second skin health data set for the user; storing, by the computing device, the second skin health data set in third storage in electronic communication with the computing device; determining, by the computing device, a second skincare product formulation based on the second skin health data set; storing, by the computing device, the second skincare product formulation in fourth storage in electronic communication with the computing device providing, by the computing device, the second skin care product formulation to the user in the form of a second recommendation.