The Gillette Company

Susan Clare Robinson

Leigh Knight

Ian Anthony Good

Balasundram Periasamy Amavasai

Robert Thomas Hinkle

Faiz Feisal Sherman

Matthew Lloyd Barker

Paul Leslie Warrick

Kevin David Cowley

Tina Susannah Clarelli

Taoran Dong

Sean Patrick Wheeler

Matthew Stephen Bauer

Kate Budds

Werner Friedrich Johann Bonifer

Alexander James Hinchliffe Friend

Venugopal Vasudevan

Michael Thomas Roller

Joshua Thomas Kissel

Shirley Namubiru

Nigel Weston

Nicola Dawn Dixon

Angela Louise Richardson

Weiyan Yang

Claus Hittmeyer

Amanda Washington

Christopher Francis Rawlings

Áine Rhian Wilcox

Amanda Michelle Washington

Digital imaging systems and methods are described for analyzing pixel data of an image of a shaving stroke for determining pressure being applied to a user's skin. A plurality of training images of a plurality of individuals are aggregated, each of the training images comprising pixel data of a respective individual when shaving with a shaving razor. A pressure model, trained with the pixel data, is operable to determine pressure being applied to the respective individual's skin. An image of a user when shaving with the shaving razor is received and analyzed, by the pressure model, to determine a user-specific pressure being applied to the user's skin by the shaving razor when a user shaving stroke is taken. A user-specific electronic recommendation to address at least one feature identifiable within the pixel data is generated and rendered, on a display screen of a user computing device.

Digital imaging systems and methods of analyzing pixel data of an image of a shaving stroke for determining pressure being applied to a user's skin

Artificial intelligence based systems and methods are described for analyzing pixel data of an image of a user's body for determining a hair density value of the user's hair. An example method includes aggregating a plurality of training images of a plurality of users' bodies, and training a hair density model operable to output a hair density value. The example method may further include receiving an image of a user comprising pixel data of a portion of the user's body or body area, and analyzing, by the hair density model, the image to determine a user-specific hair density value of the user's hair. The example method may further include generating a product recommendation, wherein the product is designed to address a feature identifiable within the pixel data of the user's body or body area.

Digital imaging systems and methods of analyzing pixel data of an image of a user's body for determining a hair density value of a user's hair

Artificial intelligence based systems and methods are described for analyzing pixel data of an image of a user's body for determining a hair growth direction value of the user's hair. An example method includes aggregating a plurality of training images of a plurality of users' bodies, and training a hair growth direction model operable to output a hair growth direction value. The example method may further include receiving an image of a user comprising pixel data of a portion of the user's body or body area, and analyzing, by the hair growth direction model, the image to determine a user-specific hair growth direction value of the user's hair. The example method may further include generating a product recommendation, wherein the product is designed to address a feature identifiable within the pixel data of the user's body or body area.

Digital imaging systems and methods of analyzing pixel data of an image of a user's body for determining a hair growth direction value of the user's hair

A digital imaging method of analyzing pixel data of an image of a user's body for determining a user-specific hair removal efficiency value after removing hair is disclosed. The digital imaging method includes: aggregating training images of respective individuals' bodies after removing hair; training, using the pixel data of the training images, a hair removal efficiency model to determine hair removal efficiency values associated with a degree of hair removal efficiencies ranging from a least efficient to a most efficient; receiving an image of a user's body after removing hair; analyzing by the user image using the hair removal efficiency model to determine a user-specific hair removal efficiency value; generating a user-specific electronic recommendation designed to address a feature identifiable within the pixel data of the user's body based on the user-specific hair removal efficiency value; and rendering the recommendation on a display screen of a user computing device.

Digital imaging systems and methods of analyzing pixel data of an image of a user's body after removing hair for determining a user-specific hair removal efficiency value

Digital imaging systems and methods are described for determining a user-specific skin irritation value of a user's skin after removing hair. An example method may be performed by one or more processors and may include aggregating training images comprising pixel data of skin of individuals after removing hair. A skin irritation model may be trained using the training images to output skin irritation values associated with a degree of skin irritation from least to most irritation. The method may include receiving an image of a user including pixel data of the user's skin after hair is removed from the skin, analyzing the image using the skin irritation model to determine a user-specific skin irritation value, generating a user-specific recommendation designed to address a feature identifiable within the pixel data of the user's skin, and rendering the recommendation on a display screen of a user computing device.

Digital imaging systems and methods of analyzing pixel data of an image of a user's body for determining a user-specific skin irritation value of the user's skin after removing hair

Sensor-based shaving systems and methods of analyzing a user's shave event are described for determining a unique threshold value of the user. A grooming device comprises a handle having a connecting structure connected to a hair cutting implement. A shave event sensor associated with the grooming device measures a user behavior, which includes collecting a first dataset comprising shave data defining a shave event. The first dataset is transmitted via a communication device and is analyzed to determine baseline behavior data of the user, and a unique threshold value of the user is determined from the baseline behavior data. One or more subsequent datasets, each comprising shave data of one or more corresponding shave events, is compared to the unique threshold value to determine comparison data. An indication is provided, based on the comparison data, to indicate a deviation from the threshold value and to influence the user behavior.

Sensor-based shaving systems and methods of analyzing a user's shave event for determining a unique threshold value of the user

A digital imaging method of analyzing pixel data of an image of a user's body for determining a user-specific trapped hair value before removing hair is disclosed. The digital imaging method includes: aggregating training images of respective individuals' bodies before removing hair; training, using the pixel data of the training images, a trapped hair model to determine trapped hair values associated with a trapped hair scale ranging from least trapped hair to most trapped hair; receiving an image of a user's body before removing hair; analyzing the user image using the trapped hair model to determine a user-specific trapped hair value; generating a user-specific electronic recommendation designed to address a feature identifiable within the pixel data of the user's body based on the user-specific trapped hair value; and rendering the recommendation on a display screen of a user computing device.

Digital imaging systems and methods of analyzing pixel data of an image of a user's body before removing hair for determining a user-specific trapped hair value

Digital imaging systems and methods are described for determining a user-specific skin redness value of a user's skin after removing hair. An example method may be performed by one or more processors and may include aggregating training images comprising pixel data of skin of individuals after removing hair. A skin redness model may be trained using the training images to output skin redness values associated with a degree of skin redness from least to most red. The method may include receiving an image of a user including pixel data of the user's skin after hair is removed from the skin, analyzing the image using the skin redness model to determine a user-specific skin redness value, generating a user-specific recommendation designed to address a feature identifiable within the pixel data of the user's skin, and rendering the recommendation on a display screen of a user computing device.

Digital imaging systems and methods of analyzing pixel data of an image of a user's body for determining a user-specific skin redness value of the user's skin after removing hair

A method for generating user feedback information from a shave event associated with a user. A shaving razor is provided to user. The shaving razor includes a handle, a hair cutting implement connected to the handle, at least one motion sensor in the handle, a hair cutting implement displacement sensor associated with the handle, a communication device associated with the handle and a power source associated with the handle. The power source powers the at least one motion sensor, the hair cutting implement displacement sensor and the communication device. Shave event data associated with the user during a shave is collected from the at least one motion sensor and the hair cutting implement displacement sensor. The shave event data is processed to generate user feedback information.

Method for generating user feedback information from a shave event

A method for generating user feedback information from a shave event associated with a user. A shaving razor is provided to user. The shaving razor includes a handle, a hair cutting implement connected to the handle, at least one motion sensor in the handle, a hair cutting implement displacement sensor positioned in the handle, a communication device positioned in the handle and a power source positioned in the handle. The power source powers the at least one motion sensor, the hair cutting implement displacement sensor and the communication device. Shave event data associated with the user during a shave is collected from the at least one motion sensor and the hair cutting implement displacement sensor. The shave event data is processed to generate user feedback information.

A networked shaving appliance system includes: (a) a shaving appliance including a handle and a shaving head cartridge connected to the handle and motion, orientation, and/or pressure sensors associated with the handle and/or shaving head cartridge; (b) a sensor circuit connected to receive sensor signals and generate shave event information from the sensor signals; (c) a network circuit wirelessly connected with a computer network and communicating at least the shave event information to the computer network; and (d) a computerized tool operating, at least in part, on a computerized user device connected to the computer network. The computerized tool is configured to receive shave event data associated with a user of the computerized device from the computer network, receive user profile data from the user via a graphical user interface provided by the computerized tool, process the shave event data with the user profile data to generate user feedback information, and communicate the user feedback information to the user via the graphical user interface provided by the computerized tool.

Networked shaving appliance system

Included is a method for providing a customized product recommendation to a user. Information is collected from a user regarding issues experienced by the user after cutting and/or removing hair selected from the group consisting of discomfort, dry skin, missed hairs, hair not cut close enough, nicks, cuts, trapped hairs, ingrown hairs, razor bumps, blemishes, acne, razor burn, irritation, redness, pseudofolliculitis barbae, and itching. The information collected from the user is analyzed. A product for the user is selected from at least two available products based upon the information collected from the user. The selected product is recommended to the user.

Method for providing a customized product recommendation

Included is a method for providing a customized product recommendation to a user. Information is collected from a user regarding a type of shaving stroke the user takes when shaving. The information collected from the user is analyzed. A product for the user is selected from at least two available products based upon the information collected from the user. The selected product is recommended to the user.

Growing community of inventors

Windsor, United Kingdom

Susan Clare Robinson