Abstract: A system and method for operating a household cleaning appliance, including: providing a household cleaning appliance including, a powered and electronically controlled cleaning implement, and at least one physical sensor taken from a group consisting of: an orientation sensor, an acceleration sensor, an inertial sensor, a global positioning sensor, a pressure sensor, a load sensor, audio sensor, humidity sensor, and a temperature sensor; providing a camera associated with the household cleaning appliance; deriving an augmented classification using one or more classifiers classifying the physical sensor data and the image data; and modifying operation of the cleaning implement based upon the augmented classification.

Abstract: A system and method for operating a personal grooming/household appliance, including: providing a personal grooming appliance including at least one motion sensor taken from a group consisting of: an orientation sensor, an acceleration sensor, and an inertial sensor; providing a camera associated with the personal grooming appliance; classifying data received from the motion sensor and from the camera using at least one trained machine learning classifier to generate an augmented classification; and providing user feedback information based upon the augmented classification, wherein the augmented classification pertains to a combination of a first state pertaining to a position of the grooming appliance with respect to a user's body part and also pertains to a second state that is different than the first state.

Abstract: Included are embodiments for remotely determining a battery characteristic. Some embodiments include searching for a first wireless signal that identifies the energy storage device and, in response to receiving the first wireless signal, determining a current charge level of the energy storage device. Some embodiments include receiving a second wireless signal from the energy storage device, determining from the second wireless signal, whether the current charge level of the energy storage device reaches a predetermined threshold, and in response to determining that the current charge level of the energy storage device reaches the predetermined threshold, facilitating replacement of the battery.

Abstract: Included are embodiments for remotely determining a battery characteristic. Some embodiments include searching for a first wireless signal that identifies the energy storage device and, in response to receiving the first wireless signal, determining a current charge level of the energy storage device. Some embodiments include receiving a second wireless signal from the energy storage device, determining from the second wireless signal, whether the current charge level of the energy storage device reaches a predetermined threshold, and in response to determining that the current charge level of the energy storage device reaches the predetermined threshold, facilitating replacement of the battery.

Abstract: A personal appliance. The personal appliance includes a handle having an implement connecting structure. An implement is connected to the implement connecting structure. An implement displacement sensor is positioned in the handle. The implement displacement sensor measures a displacement of the implement relative to a fixed position of the handle. A power source, an acceleration sensor and an angular velocity sensor are positioned in the handle.

Abstract: 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.

Abstract: A grooming device including a handle and a grooming implement connected to the handle. The handle includes a first portion having a housing, a proximal end and a distal end. A displacement sensor is positioned within the housing. A power source is positioned within the housing with the power source providing power to the displacement sensor. A neck portion is pivotably connected to the proximal end of the first portion about a handle pivot axis. The neck portion includes a proximal end, a distal end and a location element. As the neck portion pivots about the handle pivot axis relative to the first portion the displacement sensor detects displacement of the location element.

Abstract: A personal appliance. The personal appliance includes a handle having an implement connecting structure. An implement is connected to the implement connecting structure. An implement displacement sensor is positioned in the handle. The implement displacement sensor measures a displacement of the implement relative to a fixed position of the handle. A power source, an acceleration sensor and an angular velocity sensor are positioned in the handle.

Abstract: Included are embodiments for remotely determining a battery characteristic. Some embodiments include searching for a first wireless signal that identifies the energy storage device and, in response to receiving the first wireless signal, determining a current charge level of the energy storage device.

Abstract: A device and method for applying a material to a surface to repair, restore or refurbish at least a portion of the surface. The device has a sensor and one or more applicator nozzles. The device further includes a reservoir for containing a material to be deposited, and a CPU. The method includes providing information from the sensor about the surface to the CPU, which uses the information to identify where the material is to be deposited and/or how much to deposit.

Abstract: Disclosed are hair analysis systems and methods comprising: (a) a step to capture an image at least of the top of the head of a user at an image capture unit and to send the image from the image capture unit to a hair analysis unit; (b) a step to analyze the user's hair coverage and/or scalp coverage condition at hair analysis unit, based on the image from the image capture unit by using a deep neural network that predicts user's hair coverage and/or scalp coverage relative to a gender population and is trained on class labels acquired by crowd sourcing, and to provide an analysis result to a display unit; and (c) a step to display at a display unit the analysis result to the user. The present invention provides the system and the method with an improved sensitivity.

Abstract: Disclosed are hair analysis systems and methods comprising: (a) a step to capture an image of a user at an image capture unit and to send the image from the image capture unit to a hair analysis unit; (b) a step to analyze the user's hair condition at hair analysis unit, based on the image from the image capture unit by using a deep neural network, and to provide an analysis result to a display unit; and (c) a step to display at a display unit the analysis result to the user. The present invention provides the system and the method with an improved sensitivity.

Abstract: Included are embodiments for remotely determining a battery characteristic. Some embodiments include searching for a first wireless signal that identifies the energy storage device and, in response to receiving the first wireless signal, determining a current charge level of the energy storage device. Some embodiments include receiving a second wireless signal from the energy storage device, determining from the second wireless signal, whether the current charge level of the energy storage device reaches a predetermined threshold, and in response to determining that the current charge level of the energy storage device reaches the predetermined threshold, sending, by the computing device, an alert indicating the current charge level.

Abstract: A system for classifying the usage of a handheld consumer device having a sensor and an analyzer. The sensor determines usage data at successive time instants and provides a temporally successive sequence of usage data during a usage session. The analyzer classifies the usage of the device with respect to at least one set usage classes and assembles a temporally successive sequence of input tuples of usage data relating to a predetermined time period of the usage session, each of the input tuples having at least one element representing the usage data at the respective time instant and for inputting the sequence of input tuples into at least one artificial neural network arranged to output at least one output tuple comprising a number of elements in accordance with the number of usage classes, each element of the output tuple representing a prediction value that the usage of the consumer device at the given time instant relates to a respective usage class.

Abstract: An apparatus for performing a localization of a movable treatment device having at least one inertial sensor and configured to treat the target surface. The apparatus has a motion pattern classification device configured to discriminate between two or more motion classes contained in a set of motion classes, and an interface for providing, from the inertial sensor to the motion pattern classification device, inertial sensor data representing a movement of the movable treatment device. The motion pattern classification device has a neural network configured to receive and classify inertial sensor data with respect to the motion classes associated with one or more different zones relating to the target surface so that the classification of inertial sensor data indicates an estimation of the location of the movable treatment device with respect to the one or more zones of the target surface.

Abstract: An apparatus for classifying the motion of a movable treatment device having at least one inertial sensor, a motion pattern classification device configured to discriminate between two or more motion classes contained in a set of motion classes of the movable treatment device, and an interface for providing inertial sensor data from the inertial sensor to the motion pattern classification device. The inertial sensor data represents a movement of the movable treatment device, wherein the motion pattern classification device comprises at least one neural network configured to receive and classify the inertial sensor data with respect to the motion classes contained, each associated with at least one class member selected based on the motion of the movable treatment device.

Abstract: A method and an apparatus for performing a localization of a movable treatment device having an inertial sensor and configured to treat a target surface. A motion pattern recognition device discriminates between two or more motion patterns contained in a set of motion patterns. An interface provides at least one inertial sensor data from the inertial sensor to the motion pattern recognition device. At least one inertial sensor data represents a movement of the movable treatment device. A neural network is configured to receive the at least one inertial sensor data and to map the at least one inertial sensor data to at least one motion pattern contained in the set of motion patterns associated with one or more different zones of the target surface so that the mapping of the at least one inertial sensor data with the at least one motion pattern indicates an estimation of the location of the device with respect to at least one zone of the target surface.

Abstract: 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 communication device positioned in the handle and a power source positioned in the handle. The power source powers the at least one motion sensor and the communication device. User profile data is collected from the user. Shave event data associated with the user during a shave is collected from the at least one motion sensor. The shave event data and user profile data is processed to generate user feedback information. The user feedback information is communicated to the user.

Abstract: A shaving appliance includes: a handle and a shaving head connected to the handle; a plurality of sensors provided in the shaving head and/or handle; a sensor circuit connected via a data connection to receive sensor signals from the plurality of sensors and to generate shave stroke direction information from the sensor signals; and a notification circuit determining relative shave stroke direction information for a user from the shave stroke direction information and from hair growth direction information electronically stored with respect to the user.

Abstract: 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 communication device associated with the handle and a power source associated with the handle. The power source powers the at least one motion sensor and the communication device. User profile data is collected from the user. Shave event data associated with the user during a shave is collected from the at least one motion sensor. The shave event data and user profile data are processed to generate user feedback information. The user feedback information is communicated to the user.