Abstract: A personal care device including at least one sensor (28) configured to obtain sensor data including information about a user; a controller (30) having a feature extraction module (230) and a classifier (240), the feature extraction module configured to extract one or more features from the obtained sensor data, the classifier configured to determine a status of a user based on the extracted one or more features; and a personal care device (10) configured to provide a personal care function and receive one or more control signals to adjust the personal care function based on a determined status of at least a portion of the user's body.

Abstract: A system (10) and method for selecting a mouthpiece (25) for a user. The method includes receiving a signal with a personal care system (10) to initiate oral arch measurements using a personal care device (12). Data is collected from a position sensor (16) related to a location of a probe (14) of the personal care device as the probe is moved about an oral arch of the user. A controller (18) of the personal care system determines a dimension of the oral arch from the data. The controller selects a mouthpiece for the user based on the dimension of the oral arch. Information identifying the mouthpiece is transmitted to the user or other intended recipient.

Abstract: A method (100) for analyzing medication dosage for a patient (210), comprising: (i) receiving (120) a signal indicative of an activity behavior of the patient over a first time period, wherein the signal is collected by a sensor of a wearable device (220) worn by the patient; (ii) receiving (130) information about medication intake by the patient during the first time period, wherein the information comprises both medication dosage and medication intake times during the first time period; (iii) analyzing (140) the received signal and received medication intake information to determine an effectiveness of the medication on the patient, wherein the effectiveness can indicate an overdosage or underdosage of the medication during the first time period, and wherein analyzing the received signal and received medication intake information comprises generating a medication status score, the medication status score configured to minimize patient-controlled variability in the activity behavior of the patient.

Abstract: The invention discloses an oral care device (100) comprising a head portion (102) having a protuberance (104) for engaging an interproximal region within an oral cavity. The oral care device (100) also comprises at least one sensor (108) for acquiring motion data for the oral care device, and a processor (110). The processor is configured to determine when the protuberance of the head portion engages an interproximal region in the oral cavity; and determine, based on motion data acquired by the at least one sensor as the protuberance moves between interproximal regions, a position of the head portion of the oral care device in the oral cavity. An oral care system and a method of determining a position of an oral care device in an oral cavity are also disclosed.

Abstract: A method (300) for identifying a characteristic of a user of a personal care device (10) comprising a sensor (28), a controller (30), and a database (34), comprising the steps of: training (320) the device with training data, comprising the steps of: (i) obtaining (322) sensor data for at least one personal care session for each of at least two different users; (ii) extracting (324), via an extraction module, a plurality of features from each of the personal care sessions; and (iii) training (328), using the extracted features, a classifier to identify a characteristic of each of the at least two different users of the device; obtaining (330) sensor data for at least part of a new personal care session; extracting (340) a plurality of features from the sensor data for the new personal care session; and identifying (360), using the trained classifier, a characteristic of the user of the device.

Abstract: A computer-implemented method of identifying a subject's body part on which a hand-held device is used to perform a personal care operation. The hand-held device comprises a head portion for contacting the subject's skin one or more sensors for measuring a parameter and generating measurement signals as the hand-held device is used on the subject's skin. The sensor(s) comprise(s) at least one of a skin contact sensor, skin tone sensor, and/or proximity sensor. The method includes obtaining a measurement signal from each sensor; analyzing the obtained measurement signal using a trained machine learning model (MLM) to identify the subject's body part that the hand-held device is used on. The trained MLM analyzes a plurality of measurements in a time window on each of the obtained measurement signals to identify the body part. An indication of the identified body part is then outputted.

Abstract: According to an aspect, there is provided an apparatus for use with a treatment device. The treatment device is configured to apply a light pulse to skin of a subject to perform a treatment operation to hairs on the skin. The apparatus comprises a processing unit configured to receive one or more images of a first area of the skin from an imaging unit, wherein the imaging unit is arranged to obtain images of the skin of the subject; process the one or more images to determine whether the hairs on the first area of the skin have been treated with a light pulse based on a degree of at least one of carbonization and curling of the hairs on the first area of the skin as shown in the one or more images; and output a first signal indicating whether the hairs on the first area of skin have been treated with a light pulse.

Abstract: Proposed are concepts for distinguishing between fall events and non-fall-events for different sub-groups within a monitored group (i.e., monitored population) of subjects. It is proposed that an entire/group population of monitored subjects may be portioned into sub-groups, each sub-group consisting of a plurality of members (i.e., subjects) having a certain property value or characteristic unique to that group. A respective decision value may be determine for each sub-group, wherein the decision value for a sub-group takes account of a previously obtained false fall detection rate for that sub-group.

Abstract: There is provided a controller for use with an oral care device; wherein the controller is configured to estimate the location of the oral care device relative to an interdental space in a mouth using predetermined data and current use data, the current use data relating to at least one of: actions of the user during use of the oral care device, operations of the oral care device; and generate a control signal based on the outcome of the estimation. There is also provided an oral care system and a kit of parts, and a computer implemented method for an oral care device.

Abstract: Proposed are concepts for distinguishing between fall events and non-fall-events for different sub-groups of subjects within a monitored group (i.e. monitored population) of subjects. It is proposed that an entire group/population of monitored subjects may be partitioned into sub-groups, each sub-group consisting of a plurality of members (i.e. subjects) having a certain property value or characteristic unique to that group. A respective decision value may be determined for each sub-group, wherein the decision value for a sub-group takes account of a previously obtained false fall detection rate for that sub-group.

Abstract: A risk prediction system for predicting a risk of a negative event occurring for a monitored subject. The system comprises an input interface configured to obtain case data containing a history of events for the monitored subject and a predictive model based on deep learning networks. The predictive model comprises embedding layers for embedding the case data to generate embedded data, one or more sequence learning layers configured to learn patterns from sequences of the embedded data and generate sequenced data for each layer and one or more output layers each configured to map the sequenced data of each layer to a risk prediction for a negative event occurring.

Abstract: A method for classifying movement of a user during a period of low activity, such as sleep, is provided. The method includes providing a wearable device having a motion sensor; obtaining sensor data from the motion sensor in a buffer having raw sensor data points within a time period; determining whether at least part of the raw sensor data points in the first buffer meets a predefined condition based on a stationarity of motion in the raw sensor data; deriving a low-temporal resolution representation of the raw sensor data points in the first buffer when the at least part of the plurality of raw sensor data points in the first buffer meets the predefined condition based on stationarity; adapting the low-temporal resolution representation based on an estimated effect of a phenomenon on the low-temporal resolution representation; and classifying movement of the user based on the adapted low-temporal resolution representation.

Abstract: A method (400) for determining a user's compliance with a guided cleaning session during use of an oral cleaning device (10) includes the steps of: (i) providing (410) an oral cleaning device including a sensor (28), a guidance generator (46), and a controller (30); (ii) providing (420), by the guidance generator, a guided cleaning session to the user; (iii) generating (430), at a first location during the guided cleaning session, sensor data from the sensor indicating a position or motion of the oral cleaning device; (iv) comparing (440) the generated sensor data to expected sensor data for the first location; and (v) generating (450), based on the comparison, an estimate of the user's compliance with the guided cleaning session.

Abstract: A method (300) for identifying a characteristic of a user of a personal care device (10) comprising a sensor (28), a controller (30), and a database (34), comprising the steps of: training (320) the device with training data, comprising the steps of: (i) obtaining (322) sensor data for at least one personal care session for each of at least two different users; (ii) extracting (324), via an extraction module, a plurality of features from each of the personal care sessions; and (iii) training (328), using the extracted features, a classifier to identify a characteristic of each of the at least two different users of the device; obtaining (330) sensor data for at least part of a new personal care session; extracting (340) a plurality of features from the sensor data for the new personal care session; and identifying (360), using the trained classifier, a characteristic of the user of the device.

Abstract: Proposed are concepts for distinguishing between fall events and non-fall-events for different sub-groups of subjects within a monitored group (i.e. monitored population) of subjects. It is proposed that an entire group/population of monitored subjects may be partitioned into sub-groups, each sub-group consisting of a plurality of members (i.e. subjects) having a certain property value or characteristic unique to that group. A respective decision value may be determined for each sub-group, wherein the decision value for a sub-group takes account of a previously obtained false fall detection rate for that sub-group.

Abstract: A personal care device including at least one sensor (28) configured to obtain sensor data including information about a user; a controller (30) having a feature extraction module (230) and a classifier (240), the feature extraction module configured to extract one or more features from the obtained sensor data, the classifier configured to determine a status of a user based on the extracted one or more features; and a personal care device (10) configured to provide a personal care function and receive one or more control signals to adjust the personal care function based on a determined status of at least a portion of the user's body.

Abstract: A method for monitoring the position of an oral care device in the mouth of a user, the method comprising emitting energy towards the user's face, receiving reflected energy from the user's face corresponding to the emitted energy, and determining the position of an oral care device in the mouth of the user using the received reflected energy and facial characteristics information of the user which relates to one or more facial features of the user.

Abstract: A system (10) and method for selecting a mouthpiece (25) for a user. The method includes receiving a signal with a personal care system (10) to initiate oral arch measurements using a personal care device (12). Data is collected from a position sensor (16) related to a location of a probe (14) of the personal care device as the probe is moved about an oral arch of the user. A controller (18) of the personal care system determines a dimension of the oral arch from the data. The controller selects a mouthpiece for the user based on the dimension of the oral arch. Information identifying the mouthpiece is transmitted to the user or other intended recipient.

Abstract: The invention discloses an oral care device (100) comprising a head portion (102) having a protuberance (104) for engaging an interproximal region within an oral cavity. The oral care device (100) also comprises at least one sensor (108) for acquiring motion data for the oral care device, and a processor (110). The processor is configured to determine when the protuberance of the head portion engages an interproximal region in the oral cavity; and determine, based on motion data acquired by the at least one sensor as the protuberance moves between interproximal regions, a position of the head portion of the oral care device in the oral cavity. An oral care system and a method of determining a position of an oral care device in an oral cavity are also disclosed.

Abstract: A method (600) for estimating a location of an oral care cleaning device (10), including the steps of: (i) providing (610) an oral cleaning device comprising a sensor (28), a guidance generator (46), a feedback component (48), and a controller (30); (ii) providing (620) a guided cleaning session to the user comprising a plurality of time intervals separated by a cue to switch from a first location within the mouth to a second location; (iii) generating (630) sensor data from the sensor; (iv) estimating (640), based on the generated sensor data, the location of the oral care device during the plurality of time intervals; (v) generating (650) a model to predict the user's cleaning behavior; and (vi) determining (660) the location of the oral care device based on the estimated location of the oral care device and the model of the user's cleaning behavior.