Determining location of personal care device

Abstract

According to one aspect, there is provided a computer-implemented method (100) for determining a position of a personal care device relative to a body part of a subject, the method comprising receiving (102) an indication of an expected treatment area of the body part to be treated using the personal care device; determining (104) a size (208) of the expected processing area based on the received indication; receiving (106), from a first sensor associated with the personal care device, first sensor data associated with a position of the personal care device relative to the body part acquired during execution of the treatment procedure using the personal care device; predicting (108) a sequence of positions of the personal care device relative to the body part based on the first sensor data received from the first sensor; and modifying (110) the sequence of predicted positions based on the determined size of the expected processing area.

Description

Technical Field

[0001] The present invention relates to the positioning of personal care devices, and more particularly, to determining the position of a personal care device relative to a body part of an object. Background Art

[0002] Personal care devices are used by people to perform personal care activities, such as hair care activities (e.g., shaving or trimming), skin treatment activities (e.g., skin brushing), and oral care activities (e.g., toothbrushing).

[0003] Determining the position of a personal care device while a user performs a personal care activity can be beneficial, such as being able to evaluate the completion of the personal care activity. However, some systems that can determine the position of a personal care device may require a series of complex sensors. In some systems, a camera may be required to accurately determine the position of the personal care device, but this may lead to privacy issues, especially when using personal care devices in a bathroom environment.

[0004] In systems that do not use a camera, the movement of the personal care device can be detected, but it may be difficult to determine which body part is being treated, and whether the entire body part or just a part of the body part is being treated.

[0005] US2020 / 0201272A1 discloses a processing device that is capable of moving relative to a target surface, which is divided into one or more regions. The processing device includes means configured to perform the positioning of the processing device relative to the target surface. The movement of the processing device is detected by an inertial sensor. The means includes a motion pattern recognition device, in particular a neural network, which is configured to map the motion data of the inertial sensor to at least one of a plurality of motion patterns in a set of motion patterns. Each motion pattern is respectively associated with one or more different regions of the target surface. Thus, the mapping of the motion data of the inertial sensor to at least one motion pattern indicates the position estimate of the processing device relative to one or more regions of the target surface.

[0006] US2022 / 0347871A1 discloses a method for determining the position of a personal care device relative to an object's skin surface. The method involves receiving data representing the measured curvature of the skin surface within a region of the object's skin surface in contact with the personal care device. The method also involves determining an indication of the position of a first region of the object's skin surface by comparing the measured curvature with curvature information of a plurality of regions of the object's skin surface contained in a database.

[0007] Therefore, there is a need for a system that can determine the position of a personal care device relative to a body part to be treated. Summary of the Invention

[0008] It has been recognized that it is necessary to determine the position of a personal care device relative to a body part being treated to overcome the above problems. The inventors of the present disclosure have recognized that data obtained from sensors associated with the personal care device (such as an inertial measurement unit or IMU) can provide an indication of the overall movement of the personal care device during a personal care activity, and that the movement can be modified (such as scaled) based on knowledge of the body part (and more specifically, the body part region) being treated during the personal care activity.

[0009] According to a first specific aspect, there is provided a computer-implemented method for determining the position of a personal care device relative to a body part of an object, the method comprising receiving an indication of an expected treatment area of the body part to be treated by the personal care device; determining the dimensions of the expected treatment area based on the received indication; receiving first sensor data associated with the position of the personal care device relative to the body part, obtained during a treatment session using the personal care device, from a first sensor associated with the personal care device; predicting a sequence of positions of the personal care device relative to the body part based on the first sensor data received from the first sensor; and modifying the predicted position sequence based on the determined dimensions of the expected treatment area.

[0010] In this way, a single sensor associated with the personal care device can be used to obtain data indicative of the device's movement, and the movement can be modified based on knowledge of the use location where the measurements are obtained. Thus, multiple sensors are not required and positioning can be achieved without using a camera. In addition, if the personal care device is also capable of measuring data indicative of the quality of execution of the personal care activity (such as treatment speed, applied pressure, etc.), then this data can also be associated with specific regions of the body part being treated, enabling a more meaningful assessment of the quality of treatment at different regions of the body part.

[0011] In some embodiments, modifying the predicted position sequence may include rescaling the predicted position sequence based on the determined dimensions of the expected treatment area.

[0012] Modifying the predicted position sequence may include modifying the predicted position sequence in response to determining that the predicted position sequence includes one or more positions outside the expected treatment area such that the modified position sequence lies within the expected treatment area.

[0013] In some embodiments, the method may further include projecting the modified position sequence onto a diagram of the expected treatment area.

[0014] In some embodiments, the method may further include receiving, from a second sensor associated with the personal care device, second sensor data related to a processing parameter associated with the personal care device during a processing session. The method may further include generating, based on the first sensor data received from the first sensor and the second sensor data received from the second sensor, feedback related to the processing session for delivery to a receiving device.

[0015] The method may further include providing the generated feedback on a graphical representation of the body part for presentation to the user.

[0016] In some embodiments, an indication of an expected processing area of a body part may include an indication of a to-be-processed area or a non-processed area on a segmented graphical representation of the body part presented to the user.

[0017] An indication of an expected processing area of a body part may include an image of an expected processing style or pattern on the body part. The step of determining the size of the expected processing area may include determining the size according to the expected processing style or pattern.

[0018] The method may further include: applying a weight to each predicted position in the predicted position sequence based on the distance of each predicted position in the predicted position sequence to the expected processing area. The step of modifying the predicted position sequence may also be based on the applied weights.

[0019] According to a second specific aspect, there is provided a personal care device including a first sensor configured to measure first sensor data associated with the position of the personal care device relative to a body part to be treated. The personal care device further includes a processor configured to: receive an indication of an expected processing area of the body part to be treated using the personal care device; determine the size of the expected processing area based on the received indication; receive the first sensor data during a processing session of using the personal care device from the first sensor; predict a sequence of positions of the personal care device relative to the body part based on the first sensor data received from the first sensor; and modify the predicted position sequence based on the determined size of the expected processing area.

[0020] In some embodiments, the first sensor of the personal care device may include a sensor selected from the group consisting of an inertial measurement unit (IMU), an accelerometer, a displacement sensor, and a proximity sensor.

[0021] The personal care device may further include a second sensor configured to measure a processing parameter associated with the personal care device. The processor may be configured to: receive the second sensor data during the processing session from the second sensor; and

[0022] Generate feedback related to a processing session for delivery to a receiving device based on first sensor data received from a first sensor and second sensor data received from a second sensor.

[0023] In some embodiments, a processor of a personal care device may be configured to modify a predicted position sequence by rescaling the predicted position sequence such that the modified position sequence lies within an expected processing region.

[0024] According to a third specific aspect, there is provided a system for determining a position of a personal care device relative to a body part of an object, the system including the personal care device; a first sensor associated with the personal care device, the first sensor being configured to generate first sensor data associated with a position of the personal care device relative to the body part; a processor configured to: receive an indication of an expected processing region of the body part to be processed by the personal care device; determine dimensions of the expected processing region based on the received indication; receive first sensor data generated by the first sensor during a processing session of using the personal care device; predict a sequence of positions of the personal care device relative to the body part based on the first sensor data received from the first sensor; and modify the predicted position sequence based on the determined dimensions of the expected processing region.

[0025] According to a fourth specific aspect, there is provided a computer program product including a non-transitory computer-readable medium containing computer-readable code configured to, when executed on a suitable computer or processor, cause the computer or processor to perform the method steps disclosed herein.

[0026] With reference to the embodiments described below, these and other aspects will become apparent and be elucidated. BRIEF DESCRIPTION OF THE DRAWINGS

[0027] Exemplary embodiments will now be described with reference to the following drawings by way of example only. In the drawings:

[0028] Figure 1 is a flowchart of an example of a method for determining a position of a personal care device relative to a body part of an object;

[0029] Figure 2 is a flowchart of another example of a method for determining a position of a personal care device relative to a body part of an object;

[0030] Figure 3 is an illustration of an example of a user interface;

[0031] Figure 4 is a flowchart of another example of a method for determining a position of a personal care device relative to a body part of an object;

[0032] Figure 5 A schematic diagram of an example of a personal care device;

[0033] Figure 6 A schematic diagram of an example of a system for determining the position of a personal care device relative to a body part of an object; and

[0034] Figure 7 A schematic diagram of an example of a processor in communication with a machine-readable medium. DETAILED DESCRIPTION

[0035] According to various embodiments disclosed herein, a mechanism is provided by which data indicating how a personal care device moves during a personal care activity can be used to accurately determine the position of the personal care device relative to a body part.

[0036] As used herein, the term "personal care device" is intended to denote any device or instrument that can be used to perform a personal care activity. Personal care devices can include, for example, hair cutting devices such as hair trimmers or shaving devices, skin treatment devices such as facial cleansing brushes, skin rejuvenation devices or intense pulsed light (IPL) devices, oral care devices such as electric toothbrushes or air floss devices, and the like. As used herein, the term "body part" is intended to denote any part of the human body that can be treated with a personal care device. For example, a shaving device (i.e., a personal care device) can be used to perform a shaving activity (i.e., a personal care activity) on an object's head (i.e., a body part). In another example, an intense pulsed light (IPL) device (i.e., a personal care device) can be used to perform a hair removal activity (i.e., a personal care activity) on an object's leg (i.e., a body part).

[0037] According to a first aspect, the present invention provides a method. Referring to the accompanying drawings, the method according to the embodiments is described with reference to Figures 1 to 3 as follows. Figure 1It is a flowchart of an example of a method 100 for determining the position of a personal care device relative to a body part of an object. The object can be, for example, a user of the personal care device. The method 100 can include a computer-implemented method and can use one or more processors or processing means to execute the method steps. The method 100 includes, in step 102, receiving an indication of an expected processing area of the body part to be processed by the personal care device. In step 104, the method 100 includes determining the size of the expected processing area based on the received indication. The method includes, in step 106, receiving first sensor data associated with the position of the personal care device relative to the body part, obtained during the execution of a processing session using the personal care device, from a first sensor associated with the personal care device. In step 108, the method includes predicting a sequence of positions of the personal care device relative to the body part based on the first sensor data received from the first sensor. In step 110, the method includes modifying the predicted position sequence based on the determined size of the expected processing area.

[0038] Refer to Figure 2 The steps of the method 100 are described in more detail with reference to an example in which a processor 202 is used to execute each step. Although a single processor 202 is shown in this example, it should be understood that multiple processors can also be used and different steps can be executed by different processing resources, which can be located in the same location or different locations. Figure 2 The example of

[0039] The processor 202 receives (step 102) an indication of an expected processing area of the body part to be processed by the personal care device. In some embodiments, the indication of the expected processing area can be received through user input (e.g., from the user). Such user input 204 can be provided via a user interface, such as a user interface associated with a computing device such as a desktop computer, a tablet computer, a smart phone, a wearable device, and an interactive mirror. An interactive mirror, sometimes also referred to as a smart mirror, is a unit that can display information to the user in addition to serving as a mirror for displaying the user's image. Information such as text, images, and videos can be displayed on the display part of the interactive mirror, which can be located, for example, on the mirror surface (or part of the mirror surface) panel or behind the mirror surface (or part of the mirror surface). In this way, the display screen or a part of it can be seen through a part of the mirror, enabling the user to view their own image and the information presented on the display screen simultaneously.

[0040] For example, a user may provide text input by typing text that describes an intended treatment area (e.g., the chin), or by selecting the intended treatment area from a list of possible treatment areas. In other examples, a user may provide an indication by selecting the intended treatment area from an illustration (e.g., an image) of a body part presented to the user. For example, an indication of an intended treatment area with respect to a body part may include an indication of a treatment area or a non-treatment area on a segmented illustration of the body part presented to the user. The segmented illustration may be presented to the user on a display screen of a computing device (e.g., the user's smart phone), and the user may indicate one or more intended treatment areas by selecting the relevant segments or regions in the illustration. An indication of the intended treatment area may be provided based on one or more areas that the user indicates are not to be treated. For example, if the user indicates that a particular area is not desired to be treated, it may be understood that all areas that are not selected are desired to be treated. In an example where the user is performing a shaving activity, the user may indicate areas on the object's face where hair is desired to be retained, and the processor 202 may determine that other areas are desired to be shaved.

[0041] In some embodiments, an indication of an intended treatment area with respect to a body part may include an image of an intended treatment style or pattern on the body part. For example, a user may select a treatment style (e.g., a facial hairstyle) that they want to achieve from a plurality of options. In other examples, the user may upload an image of an intended treatment style or pattern, such as an image of a person whose body part has been treated according to the intended treatment style or pattern. For example, the user may upload an image of a person with a facial hairstyle that they want to replicate.

[0042] In other examples, an indication of an intended treatment area of a body part to be treated by a personal care device may be received in other ways, such as from the personal care device itself. For example, depending on the settings of the personal care device, or the nature or type of an accessory (e.g., a cutting element or a treatment element) attached to the personal care device, it may be determined which area of the body part is to be treated.

[0043] Figure 3 is an illustration of an example of the user interface 300, on which an illustration 302 of a body part 304 of an object is displayed. The illustration 302 may be a live illustration of the object (e.g., a live video captured by a camera, or an image of the object in an interactive mirror), a still image of the object, an avatar representing the object, or a general illustration of the body part. In Figure 3 example, a general segmented illustration 302 of the object's head is shown. The user interface 300 also includes selectable icons 306, each corresponding to a body part region. The user may select one or more icons 306 to indicate the intended treatment area.

[0044] In another example, the user can provide an indication by freehand drawing a contour around the area to be processed. Alternatively, an image of the desired result of the personal care activity (e.g., a photo of an object with desired facial hair) can be provided, for example, by uploading an image (e.g., a photo), and the processor 202 can utilize a detection algorithm (e.g., a hair detection algorithm) to determine which areas of the body part are intended to be processed.

[0045] Referring again to Figure 2 , based on the indication received in step 102, the processor 202 determines (step 104) the dimensions 208 of the area to be processed. For example, the dimensions can be three-dimensional measurements such as width (W), height (H), and depth (D). Thus, in an example where the personal care activity is a shaving activity, the dimensions 208 of the shaving area can correspond to the dimensions when the area is mapped to a three-dimensional version (e.g., a model) of the body part to be shaved (e.g., the head or face of the object). In some embodiments, in the case of providing an image of the area to be processed, the dimensions 208 can be determined by mapping the image (e.g., a two-dimensional image) onto a general three-dimensional model of the body part (e.g., the head) and determining the dimensions based on the mapping. If multiple images of the area to be processed are provided, a more accurate determination can be made. The multiple images can be used to estimate the shape of the body part instead of using a general body part model, and the multiple images can then be mapped to the model to derive the dimensions. Another option is to estimate the three-dimensional body part shape from a single image, or estimate the body part depth, and map the image to the body part model and derive the dimensions. In an example where the indication regarding the area to be processed of the body part includes an image of the desired processing style or pattern of the body part, determining the dimensions 208 of the area to be processed can include determining the dimensions according to the desired processing style or pattern. In other words, the processor 202 can calculate the dimensions of the area to be processed based on the image of the desired processing style or pattern provided by the user.

[0046] Steps 102 and 104 can be performed before the personal care activity begins. For example, the user can provide an indication regarding the area to be processed before starting the personal care activity. In some examples, previously provided indications can be stored (e.g., stored in a memory) and used by the processor 202 in subsequent steps of the method 100.

[0047] During a personal care activity (e.g., a treatment session performed using a personal care device), a sensor associated with the personal care device (i.e., the first sensor 206) is configured to acquire data (i.e., first sensor data). The first sensor data acquired by the first sensor can indicate how the personal care device moves during the treatment session. For example, the first sensor can include an inertial measurement unit (IMU), an accelerometer, a displacement sensor (such as an optical displacement sensor, a motion or movement sensor, or a proximity sensor). The IMU can include one or more accelerometers, gyroscopes, and / or magnetometers. In some examples, the personal care device can include multiple sensors, such as two or more of the sensors discussed above, and this can improve the acquired data.

[0048] The processor 202 receives (step 106) the first sensor data associated with the position of the personal care device relative to the body part during a treatment session performed using the personal care device from the first sensor 206. For example, the received first sensor data can include a series of data points, each data point indicating the position of the personal care device relative to a reference point (e.g., the starting point of the personal care device). Thus, as the personal care device moves during the treatment session, its position is recorded at a defined sampling rate, and thus a sequence of positions (e.g., a movement path) is recorded throughout the treatment session. The nature of the data acquired by the first sensor 206 depends on the type of sensor used. For example, the IMU can measure the orientation and acceleration of the personal care device as it moves, and based on this data, the position of the personal care device relative to its starting position can be determined using known techniques.

[0049] Based on the first sensor data received from the first sensor in step 106, the processor 202 predicts (step 108) a sequence of positions 210 of the personal care device relative to the body part. When the first sensor data is acquired, the first sensor 206 does not know which body part or which region of the body part is being treated. Thus, based on the first sensor data, the processor 202 is able to predict the sequence of positions of the personal care device relative to its starting position, but this prediction does not take into account which body part is being treated, and whether the entire body part or only a part of the body part is being treated. Thus, it is not possible to determine when the personal care device moves between different regions (e.g., different segments) of the body part. For example, during a shaving activity, it is not possible to determine when the shaving device moves from the subject's cheek to the subject's chin.

[0050] Accordingly, the processor 202 modifies (step 110) the sequence of predicted positions 210 based on the determined size 208 of the expected processing area. Modifying the sequence of predicted positions can involve mapping the sequence of predicted positions onto a three-dimensional model of the body part that has already been processed. For example, the sequence of predicted positions from a shaving activity can be mapped onto a three-dimensional model of a person's head. In some embodiments, the three-dimensional model can be a generic model having the shape, size, and dimensions of an average person's head. Such a generic body part can be given any dimensions: W = 1 (e.g., 0 to 1), H = 1 (e.g., 0 to 1), and D = 1 (e.g., 0 to 1). Accordingly, the sequence of predicted positions is scaled to fit within a cube of any size 1×1×1.

[0051] In some embodiments, the total area covered by the sequence of predicted positions can be scaled (e.g., multiplied by a factor) based on the size of the expected processing area. For example, the sequence of predicted positions can be scaled to between 0 and 1 for each of the three dimensions x, y, and z, and the scaling applied can correspond to the body part being processed (e.g., the head of an object). If it is determined in step 104 that the area of the expected processing area is smaller than the entire body part, a scaling factor can be applied to reduce the area covered by the position sequence to match the size of the expected processing area. Accordingly, modifying the sequence of predicted positions can include rescaling the sequence of predicted positions based on the determined size of the expected processing area.

[0052] Example 1: Shaving an area of the head. By definition, the sequence of predicted positions is contained within a cube from 0 to 1 (e.g., 1×1×1). In this example, the proportion of the processing area of the body part relative to the cube is H×W×D = 5×5×2 (different from the proportion of the entire head relative to the cube, e.g., the proportion of the entire head is H×W×D = 30×20×15), and the origin (0, 0, 0) is set to 15×7.5×10 instead of 0×0×0 in the case of the entire head. By multiplying the sequence of predicted positions by the proportion of the body part being processed (i.e., 5×5×2 in this example), the sequence of predicted positions is rescaled to its actual size (e.g., in cm) within the cube from 0 to 1, resulting in a prediction at the cm level. By adding the origin, the scaled prediction is moved to its actual position relative to the body part model. Then, those scaled and moved predictions are projected onto the body part being processed.

[0053] Example 2: Shaving an area of the head. In an alternative example, it may also be considered to predict the ratio of the position sequence (i.e., the area of the position sequence). In such examples, the actual size of the prediction can be determined as, for example, 0.8×0.7×0.4 (instead of 1×1×1 in Example 1 above). Then, the ratio of the treatment area of the body part relative to the cube can be determined (e.g., 5×5×2), and the origin can be set (e.g., 15×7.5×10). Multiply the area of the predicted position sequence by 5 / 0.8×5 / 0.7×2 / 0.4 to rescale the predicted position sequence to match the size of the treated body part area, such that the predicted position sequence finally extends over the entire size of the treated body part. By adding the origin 15×7.5×10, the scaled prediction is moved to the actual position of the model relative to the body part. Then, the scaled and shifted prediction can be projected onto the treated body part.

[0054] Although in some embodiments, a body part of a general or standard size may be used to scale the predicted position sequence, in other embodiments, the area covered by the predicted position sequence (e.g., the area covered by the bounding box around the predicted position sequence) may be estimated or predicted, and scaling may be based on the size of the expected treatment area.

[0055] During a personal care activity, the user may, for example, due to a mistake or in order to be able to see the expected treatment area, move the personal care device out of the expected treatment area. In some embodiments, if it is determined that the personal care device has moved out of the expected treatment area, any predicted positions outside the expected treatment area may be ignored. In some embodiments, in response to determining that the predicted position sequence includes one or more positions outside the expected treatment area, the predicted position sequence may be modified such that the modified position sequence lies within the expected treatment area. In other words, if, after analyzing the movement path of the personal care device, it is determined that any of the sequence positions fall outside the expected treatment area, the area covered by the predicted position sequence may be scaled such that all positions in the predicted position sequence fall within the expected treatment area.

[0056] One result of performing method 100 is to modify the predicted position sequence to fit the expected treatment area indicated by the user. Thus, any motion data can be measured during a personal care activity, and this can be modified to apply to the expected treatment area of the body part indicated by the user.

[0057] Figure 4It is a flowchart of another example of a method 400 for determining the position of a personal care device relative to a body part of an object. At step 402, method 400 may further include projecting a modified position sequence onto a diagram of an expected treatment area. For example, the movement path of the personal care device during the treatment session can be projected onto a diagram of the expected treatment area of the body part (such as an image, photo, video, avatar, etc.). Projecting the modified position sequence onto the diagram of the expected treatment area can be achieved using known projection techniques, including, for example, calculating the minimum Euclidean distance (such as relative to the body part diagram / model). In other examples, as will be understood by those skilled in the art, a mesh model of the expected treatment area of the body part uses, for example, "point-to-plane distance" techniques. By projecting the modified position sequence onto the diagram of the expected treatment area of the body part, the sensor data obtained using the first sensor and / or the second sensor can be attributed to specific regions within the expected treatment area (such as the left cheek, right cheek, chin, etc.). Method 400 may include a computer-implemented method, which may include the steps of method 100 described above.

[0058] At step 404, method 400 may further include receiving, from a second sensor associated with the personal care device, second sensor data related to the treatment parameters associated with the personal care device during the treatment session. The second sensor may include, for example, a pressure sensor or a force sensor configured to measure the pressure applied by the personal care device to the body part (such as applied to the user's skin); a timer configured to measure the time taken to perform the personal care activity; a sensor configured to measure motion data indicating the way the personal care device moves during the personal care activity; and so on. In some embodiments, the second sensor data may be received from the first sensor 206. In some cases, multiple second sensors may be provided, and the second sensor data may be received from two or more sensors.

[0059] Method 400 further includes, at step 406, generating feedback related to the processing operation based on first sensor data received from a first sensor and second sensor data received from a second sensor for delivery to a receiving device. The first sensor data and the second sensor data can provide an indication of the degree of movement of the personal care device over an intended treatment area during the processing operation, an indication of the manner in which the personal care device moves during the processing operation, an indication of the pressure or force applied by the personal care device to a user body part, an indication of the speed of movement of the personal care device during the processing operation, and so on. Based on the received first sensor data and second sensor data, an assessment of the effectiveness of the user's performance of the personal care activity during the processing operation can be made, and feedback can be provided to the user based on one or more parameters related to the data measured using the first sensor and the second sensor. For example, the feedback can include an indication that the user moves the personal care device faster when treating one side of the body part than when treating the other side of the body part. In another example, the feedback can include an indication that the pressure applied to the body part during the processing operation exceeds a normal value and may cause skin irritation. In another example, the feedback can include an indication that the personal care device moves linearly (e.g., generally in a straight line) during the processing operation, although a circular motion of the personal care device is recommended.

[0060] In some embodiments, the feedback can include a suggestion that enables the user to change one or more aspects of their personal care device usage to improve the effectiveness of use in future processing operations. In other words, the feedback can be considered actionable feedback.

[0061] The receiving device to which the feedback is delivered can include the personal care device itself, or some other device having the functionality to enable the feedback to be delivered to a recipient (e.g., a user or subject). For example, the feedback can be delivered to the user's smart phone (e.g., via an application), a tablet computer, or an interactive mirror. The feedback can be provided in the form of a text message displayed on a screen, such as "Pressed too hard during this session! Try using less force next time". In other examples, the feedback can be provided in the form of one or more lights with different glowing colors to indicate the quality of the processing operation.

[0062] In some embodiments, the feedback may be provided in the form of a chart or illustration. For example, method 400 may further include, at step 408, providing the generated feedback on an illustration of the body part for presentation to the user. The illustration of the body part may include a real - life likeness of the body part (e.g., a photo or image of the object's body part), an image of the body part (e.g., in an interactive mirror), an avatar, or a general illustration of the body part. In an example where the personal care activity is a shaving activity, an illustration of the object's face may be displayed, and different colors (e.g., red - yellow, and green) may be used to indicate the performance of the personal care activity in different regions of the expected treatment area of the body part based on the first data and the second data (e.g., motion, pressure applied, and / or time spent). For example, a green area may indicate that, according to the data received from the first sensor and the second sensor, the performance of the personal care activity in that area is very good, a yellow area may indicate that the performance of the personal care activity in that area is relatively good, but there may still be some beneficial improvements for the user, and a red area may indicate that the performance of the personal care activity in that area is not very good and improvements should be made.

[0063] In some embodiments, method 400 may further include, at step 410, applying weights to each prediction position in the sequence of prediction positions based on the distance of each prediction position in the sequence of prediction positions to the expected treatment area. For example, a weighted - distance function may be used to apply the weights. In some embodiments, prediction positions within the expected treatment area may be applied smaller weights, and prediction positions outside the expected treatment area may be applied larger weights. The weight of a prediction position may increase as the distance outside the expected treatment area increases, and a minimum weight may be applied to any prediction position that falls within the expected treatment area.

[0064] In an example where weights have been applied to the prediction positions, the sequence of prediction positions may also be modified based on the applied weights. By applying the minimum - weighted - distance technique, prediction positions that are very far outside the expected treatment area (and thus have large weights) may be ignored or disregarded, and positions that are determined to be only slightly outside the expected treatment area (and thus have small weights) may be considered. In this way, situations where the personal care device is accidentally moved a long distance outside the expected treatment area during the processing session, while no actual treatment is being performed on that part, can be ignored.

[0065] In other embodiments, the weights can be applied in different ways. Once the predicted position sequence has been scaled, it can be projected onto a three-dimensional model of the entire body part (i.e., including both treated and untreated regions). To determine the end point of the projection relative to the model of the body part, the point with the minimum weighted distance from the prediction to the three-dimensional model of the body part is considered. Points within the treated region of the body part are set to a low weight value (e.g., 1). Points in the untreated region of the body part are set to a high weight value (e.g., depending on the distance to the treated region of the body part). When projecting the predicted position sequence, the distance to each point in the three-dimensional model is calculated and multiplied by the weight, and the prediction with the minimum weighted distance is selected as the winner. As a result, predictions far outside the treated region are still projected outside the treated region, while the remaining predictions are projected inside the treated region. When providing feedback to the user, feedback related to points outside the untreated region can be omitted.

[0066] Another example of considering the application of weights is shown below.

[0067] Example 3: Shaving an area of the head. First, determine the size of the entire predicted position sequence excluding outliers (e.g., 0.8×0.7×0.4 instead of 1×1×1 used in Example 1 above). Then determine the ratio of the treated region of the body part relative to the cube, e.g., 5×5×2, and set the origin to 15×7.5×10. The predicted position sequence is rescaled by multiplying the prediction by 5 / 0.8×5 / 0.7×2 / 0.4 so that the entire predicted position sequence matches the size of the treated region of the body part, such that the entire predicted position sequence ultimately fully extends over the entire size of the treated body part. The scaled prediction is moved to the actual position relative to the body part model by adding the origin 15×7.5×10. Then, the scaled and shifted prediction can be projected onto the treated body part. In some embodiments, outliers can be projected outside (i.e., external to) the treated body part if a better fit can be provided.

[0068] According to another aspect, the present invention provides a personal care device. Figure 5FIG. is a schematic diagram of an example of a personal care device 500 that can be used to perform the method steps disclosed herein. The personal care device 500 includes a first sensor 206 and a processor 502. The first sensor 206 is configured to measure first sensor data associated with the position of the personal care device relative to the body part to be treated. As described above, the first sensor 206 may include an inertial measurement unit (IMU), an accelerometer, a displacement sensor, a proximity sensor, or other similar components capable of determining motion data associated with the personal care device during the treatment session. The processor 502 may include or be similar to the above-described processor 202 and is configured to perform the steps of the methods 100, 400 disclosed herein. Specifically, the processor 502 is configured to receive an indication of an expected treatment area of the body part to be treated using the personal care device; based on the received indication, determine the size of the expected treatment area; during the treatment session using the personal care device, receive first sensor data from the first sensor; based on the first sensor data received from the first sensor, predict a sequence of positions of the personal care device relative to the body part; and modify the predicted position sequence based on the determined size of the expected treatment area.

[0069] In some embodiments, the personal care device 500 may further include a second sensor 504 configured to measure treatment parameters associated with the personal care device. The second sensor 504 may include, for example, a pressure sensor, a timer, a motion sensor, an IMU, etc. The processor 502 may be configured to receive second sensor data during the treatment session from the second sensor 504; and generate feedback related to the treatment session for delivery to a receiving device based on the first sensor data received from the first sensor 206 and the second sensor data received from the second sensor 504.

[0070] In some embodiments, the processor 502 may be configured to modify the predicted position sequence by rescaling the predicted position sequence such that the modified position sequence lies within the expected treatment area. In other words, the path formed by the predicted position sequence of the personal care device during the treatment session may be scaled according to the size of the expected treatment area.

[0071] According to another aspect, the present invention provides a system. In the above example, the personal care device 500 includes the first sensor 206, the processor 502, and (if present) the second sensor 504. In these examples, the processing steps may be performed within the personal care device 500 itself. In other embodiments, the processing steps (e.g., the steps of the methods 100, 400 disclosed herein) may be performed by a processor located remote from the personal care device 500, such as the processor of a smart phone or a computing device in communication with the personal care device.

[0072] Figure 6 It is a schematic diagram of an example of a system 600 for determining the position of a personal care device relative to a body part of an object. The system 600 includes a processor 602, a personal care device 604, and a first sensor 606. The first sensor 606 is associated with the personal care device 604 and is configured to generate first sensor data associated with the position of the personal care device relative to the body part. The processor 602 can communicate with the personal care device 604 and / or the first sensor 606, and is configured to receive an indication of an expected processing area of the body part to be processed by the personal care device; based on the received indication, determine the size of the expected processing area; receive, from the first sensor, the first sensor data generated by the first sensor during the processing session of using the personal care device; predict a sequence of positions of the personal care device relative to the body part based on the first sensor data received from the first sensor; and modify the predicted position sequence based on the determined size of the expected processing area. In some embodiments, the personal care device 604 may further include a sensor (not shown) that has the functions of the second sensor 504 discussed above.

[0073] According to another aspect, the present invention provides a computer program product. Figure 7 It is a schematic diagram of an example of a processor communicating with a machine-readable medium 704. According to various embodiments, a computer program product includes a non-transitory computer-readable medium 704 that contains computer-readable code configured to cause a computer or processor 702 to perform the steps of the methods 100, 400 disclosed herein when executed on a suitable computer or processor.

[0074] The processors 202, 602, 702 may include one or more processors, processing units, multi-core processors, or modules configured or programmed to control the components of the personal care devices 500, 604 in the manner described herein. In a particular implementation, the processors 202, 602, 702 may include multiple software and / or hardware modules, each module being separately configured to perform or for performing each or multiple steps of the methods described herein.

[0075] As used herein, the term "module" is intended to include hardware components, such as a processor or a component of a processor configured to perform a specific function, or include software components, such as a dataset of instructions that have a specific function when executed by a processor.

[0076] It should be understood that the embodiments of the present invention are equally applicable to computer programs, especially computer programs on or in a carrier suitable for putting the present invention into practice. The program can be in the form of source code, object code, intermediate source code, and object code such as partially compiled form, or any other form suitable for use in the implementation of the method according to the embodiments of the present invention. It should also be understood that such programs can have many different architectural designs. For example, the program code implementing the functions of the method or system according to the present invention can be divided into one or more subroutines. Various different distributions of functions among these subroutines will be obvious to those skilled in the art. The subroutines can be stored together in an executable file to form a self - contained program. Such an executable file can include computer - executable instructions, such as processor instructions and / or interpreter instructions (such as Java interpreter instructions). Alternatively, one or more or all of the subroutines can be stored in at least one external library file and linked to the main program statically or dynamically, for example, during runtime. The main program contains at least one call to at least one subroutine. The subroutines can also include function calls to each other. One embodiment related to a computer program product includes computer - executable instructions corresponding to each processing stage of at least one method described herein. These instructions can be divided into subroutines and / or stored in one or more files that can be statically or dynamically linked. Another embodiment related to a computer program product includes computer - executable instructions corresponding to each device of at least one system and / or product described herein. These instructions can be divided into subroutines and / or stored in one or more files that can be statically or dynamically linked.

[0077] The carrier of a computer program can be any entity or device capable of carrying the program. For example, the carrier can include a data memory, such as ROM, for example, CDROM or semiconductor ROM, or a magnetic recording medium, such as a hard disk. In addition, the carrier can be a transmissible carrier, such as an electrical signal or an optical signal, which can be transmitted via a cable or an optical fiber or radio or other means. When the program is contained in such a signal, the carrier can be constituted by such a cable or other device or apparatus. Alternatively, the carrier can be an integrated circuit in which the program is embedded, and the integrated circuit is suitable for executing the relevant method or for use in the execution of the relevant method.

[0078] In practicing the principles and techniques described herein, variations of the disclosed embodiments can be understood and effected by those skilled in the art in light of the accompanying drawings, the disclosure, and the appended claims. In the claims, the word "comprising" does not exclude other elements or steps, and the indefinite article "a" or "an" does not exclude a plurality. A single processor or other unit may fulfill the functions of several items recited in the claims. The fact that certain measures are recited in mutually different dependent claims does not indicate that a combination of these measures cannot be used to advantage. A computer program may be stored or distributed on a suitable medium, such as an optical storage medium or a solid state medium supplied together with hardware or as part of other hardware, but it may also be distributed in other forms, such as via the Internet or other wired or wireless telecommunication systems. Any reference signs in the claims should not be construed as limiting their scope.

Claims

1. A computer-implemented method (100) for determining the position of a personal care device relative to a body part of an object, the method comprising: Receiving (102) an indication of an expected treatment area of the body part to be treated by the personal care device; Receiving (106) from a first sensor associated with the personal care device first sensor data associated with the position of the personal care device relative to the body part acquired during a treatment session using the personal care device; And Predicting (108) a sequence of positions of the personal care device relative to the body part based on the first sensor data received from the first sensor; Characterized in that the method further comprises: Determining (104) the size (208) of the expected treatment area based on the received indication; and Modifying (110) the predicted position sequence based on the determined size of the expected treatment area.

2. The computer-implemented method (100) according to claim 1, wherein modifying the predicted position sequence comprises: Rescaling the predicted position sequence based on the determined size (208) of the expected treatment area.

3. The computer-implemented method (100) according to claim 1 or 2, wherein modifying the predicted position sequence comprises: Modifying the predicted position sequence in response to determining that the predicted position sequence includes one or more positions outside the expected treatment area such that the modified position sequence lies within the expected treatment area.

4. The computer-implemented method (100, 400) according to any one of the preceding claims, further comprising: Projecting (402) the modified position sequence onto a diagram of the expected treatment area.

5. The computer-implemented method (100, 400) according to any one of the preceding claims, further comprising: During a treatment session, receiving (404) from a second sensor associated with the personal care device second sensor data related to treatment parameters associated with the personal care device; Generating (406) feedback related to the treatment session based on the first sensor data received from the first sensor and the second sensor data received from the second sensor for delivery to a receiving device.

6. The computer-implemented method (100, 400) according to claim 5, further comprising: Providing (408) the generated feedback on a diagram of the body part for presentation to a user.

7. The computer-implemented method (100, 400) according to any one of the preceding claims, wherein, The indication of the expected treatment area of the body part comprises an indication of a treatment area or a non-treatment area on a segmented diagram of the body part shown to the user.

8. The computer-implemented method (100, 400) according to any one of the preceding claims, wherein the indication of the expected treatment area of the body part comprises an image of an expected treatment style or pattern on the body part; and wherein determining the size (208) of the expected treatment area comprises determining the size according to the expected treatment style or pattern.

9. The computer-implemented method (100, 400) according to any one of the preceding claims, further comprising: Applying (410) a weight to each predicted position in the predicted position sequence based on the distance from each predicted position in the predicted position sequence to the expected processing area; Wherein the predicted position sequence is further modified based on the applied weights.

10. A personal care device (500), comprising: A first sensor (206) configured to measure first sensor data associated with the position of the personal care device relative to a body part to be treated; A processor (502) configured to: Receive an indication of an expected processing area of the body part to be treated using the personal care device; Receive the first sensor data from the first sensor during a processing session of using the personal care device; and Predict a sequence of positions of the personal care device relative to the body part based on the first sensor data received from the first sensor; Characterized in that the processor (502) is further configured to: Determine the size (208) of the expected processing area based on the received indication; and Modify the predicted position sequence based on the determined size of the expected processing area.

11. The personal care device (500) according to claim 10, wherein, The first sensor (206) includes a sensor selected from the group consisting of: an inertial measurement unit (IMU), an accelerometer, a displacement sensor, and a proximity sensor.

12. The personal care device (500) according to claim 10 or 11, further comprising: A second sensor (504) configured to measure a processing parameter associated with the personal care device; Wherein the processor (502) is configured to: Receive second sensor data from the second sensor during the processing session; and Generate feedback related to the processing session based on the first sensor data received from the first sensor and the second sensor data received from the second sensor for delivery to a receiving device.

13. The personal care device (500) according to any one of claims 10 to 12, wherein the processor (502) is configured to: Modify the predicted position sequence by rescaling the predicted position sequence such that the modified position sequence lies within the expected processing area.

14. A system (600) for determining the position of a personal care device relative to a body part of an object, the system comprising: A personal care device (604); A first sensor (606) associated with the personal care device, the first sensor being configured to generate first sensor data associated with the position of the personal care device relative to the body part; A processor (602) configured to: Receive an indication of an expected processing area of the body part to be treated using the personal care device; Receive the first sensor data generated by the first sensor from the first sensor during a processing session of using the personal care device; and Predict a sequence of positions of the personal care device relative to the body part based on the first sensor data received from the first sensor; It is characterized in that The processor (602) is further configured to: Determine the size (208) of the expected treatment area based on the received indication; and Modify the predicted position sequence based on the determined size of the expected treatment area.

15. A computer program product comprising a non-transitory computer-readable medium (704), the computer-readable medium containing computer-readable code configured to cause the computer or processor to perform the method according to any one of claims 1 to 9 when executed on a suitable computer or processor (702).

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