CN-122028832-A - Personal care device characteristic prediction

CN122028832ACN 122028832 ACN122028832 ACN 122028832ACN-122028832-A

Abstract

Solutions, concepts, designs, methods and systems are presented regarding predicting characteristics of a personal care device that vibrates due to an actuator in use. Specifically, the actuator is controlled such that the amplitude and/or duty cycle of the vibration of the actuator causes a varying vibration of the personal care apparatus. As the vibration of the personal care device changes, a dataset describing the operating parameters of the personal care device is obtained. The data set may include features describing characteristics of the personal care device (e.g., condition, type or assembled status of replaceable components of the personal care device, user or user type of the personal care device, etc.). Thus, the dataset is processed to determine the predictive characteristics.

Inventors

VAN DEN DUNGEN WILHELMUS ANDREAS MARINUS ARNOLDUS

Assignees

皇家飞利浦有限公司

Dates

Publication Date: 20260512
Application Date: 20241010
Priority Date: 20231020

Claims (15)

1. A method for predicting characteristics of a personal care device, the personal care device comprising an actuator that vibrates the personal care device when in use, the method comprising: Controlling (110) the actuator by varying an amplitude and/or a duty cycle of vibration of the actuator to cause varying vibration of the personal care apparatus; In response to controlling the actuator, obtaining (120) a data set describing an operating parameter of the personal care apparatus during vibration of the personal care apparatus, and At least a portion of the data set is processed to determine (130) a predicted characteristic of the personal care device.
2. The method of claim 1, wherein controlling (110) the actuator further comprises controlling the actuator to vibrate in an operating frequency regime while varying an amplitude and/or a duty cycle of the vibration.
3. The method of claim 2, wherein the operating frequency is based on a personal care operating mode frequency.
4. The method of any of the preceding claims, wherein the characteristic of the personal care device comprises a predicted condition of a replaceable component of the personal care device, a predicted type of a replaceable component of the personal care device, a predicted assembled state of a replaceable component of the personal care device, a predicted user of the personal care device, and/or a predicted user type of the personal care device.
5. The method of any of the preceding claims, wherein the dataset comprises accelerometer data describing acceleration on at least one axis of the personal care device.
6. The method of claim 5, wherein the accelerometer data describes 3-axis acceleration, and wherein the method further comprises: Calculating norm vector data describing an absolute vector length of the acceleration based on the accelerometer data, and The accelerometer data and the norm vector data for each of the 3 axes are serialized into a single data segment.
7. The method of any of the preceding claims, wherein the data set includes sound data describing sound produced by the personal care device.
8. A method according to any one of the preceding claims, wherein the dataset comprises current data describing motor current of the actuator.
9. The method according to any of the preceding claims, wherein the dataset describing the operating parameter is obtained (120) in response to the personal care device being in a static state or in response to the personal care device being in an operational use state.
10. The method of any of the preceding claims, wherein the obtained data set comprises values describing the operating parameters of the personal care device, the values spanning up to 1 second, and wherein the obtained data set comprises values describing the operating parameters of the personal care device, the operating parameters being sampled at a rate of at least 800Hz, and optionally the operating parameters being sampled at a rate of at least 1.6 kHz.
11. The method of any of the preceding claims, wherein processing the data set comprises: At least a portion of the dataset is processed with a characteristic classification machine learning algorithm to determine (130) the predicted characteristic of the personal care device.
12. The method of claim 11, further comprising: Generating a spectrogram image based on at least a portion of the dataset, and The spectrogram image is processed with the characteristic classification machine learning algorithm to determine (130) the predicted characteristic of the personal care device.
13. The method of claim 12, wherein the feature classification machine learning algorithm is a spectrogram image classifier, and optionally wherein the feature classification machine learning algorithm is a CNN classifier or FCNN classifier.
14. A computer program comprising computer program code means adapted to implement the method of any one of claims 1 to 13 when said computer program is run on a computer.
15. A personal care apparatus, comprising: an actuator (210) configured to vibrate the personal care apparatus in use; A controller (220) configured to control the actuator by varying an amplitude and/or a duty cycle of vibration of the actuator to cause varying vibration of the personal care apparatus; A sensor (230) configured to obtain a data set describing an operating parameter of the personal care apparatus during vibration of the personal care apparatus in response to controlling the actuator, and A processor (240) configured to process at least a portion of the data set to determine a predicted characteristic of the personal care device.

Description

Personal care device characteristic prediction Technical Field The present invention relates to predicting characteristics of personal care devices. Background Determining certain characteristics of a personal care device (e.g., toothbrush, electric shaver, skin scrubber, etc.) may be important to improve the efficacy, safety, and user experience of the personal care device. For example, understanding the condition, type, or assembled state of replaceable components of a personal care device (e.g., brush head, shaving head, etc.) may enable proper adjustment of motor settings. Furthermore, determining the user or user type of the personal care device may also be used to appropriately adjust the motor settings to take into account the habits of the user. Such characteristic information may also be used to provide feedback to a user of the personal care device. For example, if it is determined that one of the replaceable components is improperly assembled or damaged, it may be indicated to the user so that they may take corrective action. Furthermore, if a user is identified, the information collected by the personal care device may be stored for future reference by the appropriate user. Accordingly, there is a need for an apparatus for automatically predicting characteristics of a personal care device. Disclosure of Invention According to an example in accordance with one aspect of the present invention, a method for predicting a characteristic of a personal care device is provided. The personal care apparatus comprises an actuator which vibrates the personal care apparatus in use. The method comprises the following steps: controlling the actuator by varying the amplitude and/or duty cycle of the vibration of the actuator to cause a varying vibration of the personal care apparatus; in response to controlling the actuator, obtaining a data set describing an operating parameter of the personal care apparatus during vibration of the personal care apparatus, and At least a portion of the data set is processed to determine a predicted characteristic of the personal care device. A method for predicting a characteristic of a personal care device vibrating due to an actuator in use is presented. Specifically, the actuator is controlled such that the amplitude and/or duty cycle of the vibration of the actuator causes a varying vibration of the personal care apparatus. As the vibration of the personal care device changes, a dataset describing the operating parameters of the personal care device is obtained. Thus, the data set includes features describing characteristics of the personal care device (e.g., the condition, type or assembled state of the replaceable components of the personal care device, the user or user type of the personal care device, etc.). The data set is then processed to predict characteristics of the personal care device. The personal care apparatus comprises an actuator which vibrates the personal care apparatus in use. The actuator may be a component of the personal care device configured to affect a personal care function (e.g., a motor that drives movement of the brush head of the toothbrush), or may simply be a component configured to perform a different function but incidentally cause vibration of the personal care device. That is, the actuator may be any component that, in use, affects mechanical movement, thereby causing the personal care apparatus to vibrate. Furthermore, the data set is obtained in response to vibrations of the personal care device. In other words, the data set is obtained/acquired/generated when the personal care device vibrates due to the controlled movement of the actuator. Thus, features indicative of the vibrational response of the personal care device may be present in the data set. The dataset of the personal care device describes operating parameters during vibration of the personal care device. That is, the data set contains values indicative of the system vibration response of the personal care device, which are measured, for example, in terms of acceleration (in one or more dimensions), motor current, sound/noise, when the device is in an operational mode (i.e., when the actuator is moving and thus causing vibration of the personal care device). The vibrational response contained in the dataset reflects characteristics of the personal care device, as changes in certain characteristics of the personal care device will result in changes in the vibrational response of the personal care device (to movement of the actuator). In contrast to vibration sweeps caused by an actuator operating in a mode or range outside of typical operating conditions, the present invention changes the amplitude and/or duty cycle of vibration of the actuator (i.e., performs an amplitude sweep). By obtaining the data set during the amplitude sweep, additional unique vibration response-related features can be present in the data set, which can be detected/identified for predicting the char