Pain monitoring

Abstract

A method for tracking a patient's recovery condition after treatment or treatment. The method is based on capturing sensor data during a personal care procedure of a user and using these data to infer user pain information. For example, pain may be inferred from a biosensor or from a pattern in a force / motion sensor integrated in a personal care device. The pain data may be converted to a value of a metric for each personal care link, and from the trend of the metric over time, patient recovery progression may be inferred. Reports may be generated based on the trended metrics and derived to clinical practitioners, etc.

Description

Technical Field

[0001] The present invention relates to a method and system for monitoring pain, such as after a treatment or therapy. Background Art

[0002] After a dental procedure (e.g., extraction, periodontal pocket cleaning, scaling, root canal therapy, oral surgery), dentists have little or no way to monitor the patient's healing process. Patients may assume that any pain that occurs after the procedure is normal and therefore do not alert the dentist, which may be a sign of a problem. As a result, problems may be ignored, leading to medical complications or worse outcomes. This is harmful to both the patient and the dentist, and damages the dentist-patient relationship.

[0003] In a survey conducted by the applicant, 45 dental professionals were interviewed and the most prominent issue was the lack of information about the patient's recovery progress after treatment.

[0004] The same problem applies to monitoring a patient’s condition after a dental visit where the patient reports pain but does not receive treatment. The dentist may ask the patient to monitor the condition and contact again if the pain gets worse or does not subside. The patient may forget to track the progression of the pain, may adapt to the pain and begin to ignore it, and therefore not schedule follow-up appointments with the dentist. This can cause an initially minor problem to become worse, with adverse effects on the patient’s dental health.

[0005] Similar issues exist outside of the oral health field, for example with skin health conditions in the field of dermatology. Dermatologists provide skin treatments but are unable to track the subsequent progress of the condition. Another example is in the field of muscle and joint pain, where it is difficult to monitor improvement without regular physical examinations.

[0006] Therefore, a method that facilitates easier and more objective monitoring of a patient's condition after treatment or diagnosis would be valuable. Summary of the invention

[0007] The invention is defined by the claims.

[0008] According to an example of one aspect of the present invention, a method for determining a patient's condition (e.g., recovery condition) after treatment or diagnosis is provided. The method includes: obtaining data indicating user pain as a function of time during each personal care session in a series of personal care sessions performed by the user using a personal care device, the personal care session being after treatment or diagnosis, and wherein the data indicating user pain is determined based on sensor data from at least one sensor; determining a metric for each session based on the data indicating user pain; calculating a post-treatment or diagnosis condition based on a trend of the metric in a series of personal care sessions after treatment or diagnosis, and generating a data report indicating the calculated post-treatment or diagnosis condition for export.

[0009] It is suggested to monitor the patient's post-treatment or post-treatment condition by capturing sensor data during the patient's regular home personal care routine (e.g., an oral cleaning routine when they brush their teeth or a trimming routine when they shave). The captured sensor data indirectly indicates pain, and then a metric for each session is calculated using these data, and the value of the metric can then be tracked over time to monitor the patient's condition. The concept is based on the recognition that the systematic use of personal care devices is something that users routinely do at fixed and reliable time points, and its normal use usually requires a series of systematic physical stimuli to be applied to anatomical structures or different areas of anatomical structures. Therefore, this provides an effective method to measure pain information associated with relevant anatomical structures and use data captured from sensors associated with personal care devices. Therefore, personal care sessions performed at home provide a convenient opportunity to obtain sensor data that can provide an indication of pain levels, which can provide an indication of recovery status, or an indication of the progress of pathology or wound improvement. For example, when a user cleans their teeth, they naturally apply a series of systematic pressure stimuli around the mouth, thereby stimulating a pain response in the problematic area of ​​the teeth, and sensor data measurements can be used to detect this. Likewise, when shaving, stimulation is applied to different areas of the skin.

[0010] One application area is the oral care field. In some embodiments, the personal care device is an oral care device, the aforementioned personal care action is a cleaning action, and the personal care link is an oral cleaning link. In this case, the diagnosis and treatment can be a dental diagnosis and treatment and / or the treatment can be a dental treatment. In other embodiments, the personal care device can be a skin care device, such as a phototherapy device, the personal care action is a skin care action, and the personal care link is a skin care link. In other embodiments, the personal care device is a trimming device (such as a razor), the personal care action is a trimming action (such as shaving), and the personal care link is a trimming link (such as shaving). In other embodiments, the personal care device is a muscle / joint care device (such as a massage device). In each case, the personal care device is a device for applying to an area of ​​the user's body to perform a care function, thereby causing physical stimulation of one or more areas of the body by such application during the care link. Therefore, the normal use of the device essentially requires systematic physical detection of one or more areas of the body, which can trigger a pain response, and the pain response can be measured by monitoring the pattern in the sensor data.

[0011] Thus, a personal care session may generally include personal care functions performed by or using a personal care device that involve interaction (eg, physical interaction) with a user.

[0012] In some embodiments, a personal care device may be a device for application to an area of ​​a user's body to perform a care function, whereby physical stimulation of one or more areas of the body is induced by such application during a care session.

[0013] A personal care device may be a device where normal use of the device for personal care functions during a personal care session includes or requires or affects or results in physical probing of one or more areas of the body.

[0014] With respect to the metric calculated for each personal care session, the metric may, in some embodiments, include an overall pain experience metric for each session. It may include an average of one or more sensor readings in the personal care session, where the one or more sensor readings themselves indirectly indicate user pain. For example, the metric may be an average of one or more sensor measurements that provide an indicator for pain, such as applied pressure.

[0015] The provided method may include the step of measuring or recording sensor data during each of a plurality of personal care sessions. The method may, for example, include detecting the start of a personal care session, starting recording sensor data in response thereto, detecting the end of a personal care session, and ending recording sensor data in response thereto.

[0016] There are different options for the sensor data based on which data indicative of pain for the user is determined.

[0017] In some embodiments, the sensor data includes data from a biosensor. For example, the biosensor may be a skin conductance sensor, such as a galvanic skin response (GSR) sensor. Such sensor data is known to reflect arousal associated with pain, and thus may be used to obtain user pain information. Other example biosensors include a heart rate sensor, a PPG sensor, a muscle tension sensor, or a camera for sensing facial expressions.

[0018] In some embodiments, the biosensor may be integrated into the personal care device, for example in the handle of the device. In other examples, the biosensor may be provided as a separate sensor unit.

[0019] In addition to or as an alternative to the use of biosensors, in some embodiments, the sensor data includes data from one or more force and / or motion sensors integrated in the personal care device indicating personal care actions performed by the user using the device during one or more personal care sessions, or data from one or more operation signal sensors integrated in the personal care device, the one or more operation signal sensors being adapted to output an operation signal indicating an operating parameter of the device, the operating parameter being related to the physical interaction of the device with the body surface. An example of an operation parameter is an electrical drive signal associated with an actuator that actuates a portion of the personal care device designed to contact the body surface during use, such as a transmission mechanism that drives the body contacting portion of an electric toothbrush or shaver to vibrate, or a motor mechanism that drives the body contacting portion of a massage device. The electrical characteristics of the drive signal may vary with the applied pressure because the applied pressure applies greater physical resistance. Another example of an operation parameter is a jet stream from an oral irrigator or electric flosser.

[0020] Information indicative of user pain during one or more personal care sessions may be determined based on analysis of patterns in sensor data, and optionally based on reference sensor pattern information associated with user pain or user comfort. This approach will be explained in more detail later.

[0021] In some embodiments, measuring trends in a series of personal care sessions after a treatment or diagnosis and treatment may include receiving or obtaining an indication of the time and / or date that the treatment or diagnosis and treatment occurred. The metrics derived from each personal care session may be time and / or date stamped. The trend of the metric may include plotting the metric value as a function of time after the time and / or date point of the treatment or diagnosis and treatment.

[0022] In some embodiments, calculating the patient condition includes determining a duration of time that a metric remains above a predetermined threshold level following a treatment or session based on a trend of the metric over a series of personal care sessions.

[0023] In some embodiments, the method further includes comparing the duration that the post-treatment or procedure metric remains above a predetermined threshold level to a predefined expected recovery time period and determining whether the time period exceeds the expected recovery period.

[0024] In some embodiments, the threshold level is determined based on a pre-treatment or pre-diagnosis metric level measured using sensor data from at least one sensor acquired prior to the treatment or diagnosis.

[0025] In some embodiments, determining the post-treatment or post-procedure condition comprises comparing the rate of change of the metric in a series of steps after the treatment or procedure with a threshold rate of change. In other words, it can be checked whether the pain is reduced at an expected rate.

[0026] In some embodiments, the method includes performing a response action based on the patient's condition. The response action may include, for example, automatically scheduling an appointment with a practitioner (eg, a dentist), or sending an alert message to the practitioner.

[0027] In some embodiments, the responsive action includes transmitting the data report to a practitioner computing device via a communication channel.

[0028] In some embodiments, a data report is transmitted only when a post-treatment or post-diagnosis condition is determined to be outside a normal range, and optionally, where the normal range is determined based on the time that has elapsed since the treatment or diagnosis event (i.e., the expected recovery condition depends on how long ago the treatment or diagnosis occurred).

[0029] In some embodiments, the personal care device is one of: an oral care device; a skin care device, such as a light therapy device; a trimming device, such as a shaver; or a muscle / joint care device, such as a massage device.

[0030] In some embodiments, the personal care device is an oral care device, the personal care session is an oral cleaning session, and the personal care action is a cleaning action.The treatment may be a dental treatment and / or the consultation may be a dental consultation.

[0031] Another aspect of the present invention is a computer program product comprising computer executable code, which is configured to, when executed on a processor, cause the processor to perform a method according to any embodiment described in this specification or according to any claim of this application. When the processor is operatively coupled to at least one sensor (for providing sensor data, from which data indicating pain in the user is derived), the code can cause the processor to perform this method.

[0032] Another aspect of the present invention is a processing device, comprising: an input / output; and one or more processors. The one or more processors are configured to: obtain information indicating user pain as a function of time during each personal care session in a series of personal care sessions performed by the user using a personal care device, the personal care session being after a treatment or a diagnosis, and wherein the data indicating user pain is determined based on sensor data from at least one sensor; determine a metric for each session based on the data indicating user pain; calculate a post-treatment or post-diagnosis patient condition based on a trend of the metric in a series of personal care sessions after the treatment or diagnosis event, and generate a data report indicating the calculated post-treatment or post-diagnosis condition for export.

[0033] In some embodiments, the sensor data may include data from a biosensor. In some embodiments, the biosensor is a skin conductance sensor, such as a galvanic skin response (GSR) sensor.

[0034] In some embodiments, the sensor data may include data from one or more force and / or motion sensors integrated into the personal care device that indicates personal care actions performed by a user using the device during one or more personal care sessions.

[0035] Additionally or alternatively, in some embodiments, the sensor data may include data from one or more operating signal sensors integrated into the personal care device, wherein the one or more operating signal sensors are suitable for outputting operating signals indicative of operating parameters of the device, the operating parameters being related to physical interaction of the device with a body surface.

[0036] In some embodiments, information indicative of user pain during one or more personal care sessions is determined based on analysis of patterns in sensor data, and optionally based on reference sensor pattern information associated with user pain or user comfort.

[0037] In some embodiments, calculating a post-treatment or post-procedure condition may include determining a duration that a post-treatment or post-procedure metric remains above a predetermined threshold level based on a trend of the metric over a series of personal care sessions.

[0038] In some embodiments, the processing device is further configured to compare the duration that the post-treatment or diagnostic metric remains above a predetermined threshold level to a predefined expected recovery time period and determine whether the time period exceeds the expected recovery period.

[0039] In some embodiments, the threshold level may be determined based on a pre-treatment or pre-diagnosis metric level measured using sensor data from at least one sensor acquired prior to the treatment or diagnosis.

[0040] In some embodiments, determining a post-treatment or post-procedure condition comprises comparing a rate of change of the metric over a series of sessions following the treatment or procedure to a threshold rate of change.

[0041] In some embodiments, the processing device is further configured to perform a responsive action based on the patient condition.

[0042] In some embodiments, the responsive action includes transmitting the data report to a practitioner computing device via a communication channel.

[0043] In some embodiments, a data report is transmitted only if a post-treatment or post-procedure condition is determined to be outside a normal range, and optionally, where the normal range is determined based on the time that has elapsed since the treatment or procedure.

[0044] Another aspect of the present invention is a system.

[0045] The system may include a processing device, such as a processing device according to any embodiment described herein, such as described above,

[0046] The system may include a personal care device.

[0047] The system may include at least one sensor. The at least one sensor may be used to provide sensor data from which data indicative of pain in the user is derived.

[0048] The processing device may be arranged to receive sensor data generated by at least one sensor as input at the input / output.

[0049] In some embodiments, the personal care device can include at least one sensor, although this is not required.

[0050] In some embodiments, the personal care device is an oral care device, the personal care session is an oral cleaning session, and the personal care action is a cleaning action.

[0051] In some embodiments, a personal care session includes performing, via a personal care device, a personal care function involving interaction with a user.

[0052] In some embodiments, the personal care device may include one or more functional components for use in performing personal care functions during each personal care session. The one or more functional components may physically interact with the user's body during the personal care session, such as by touching the user's body or by transmitting, such as electromagnetic transmission, acoustic transmission, and / or fluid transmission, directed to the body.

[0053] In some embodiments, a personal care device is a device for application to an area of ​​a user's body to perform a care function, whereby physical stimulation of one or more areas of the body is caused by such application during a care session.

[0054] In some embodiments, the personal care device is one of: an oral care device; a skin care device, such as a light therapy device; a trimming device, such as a shaver; or a muscle / joint care device, such as a massage device.

[0055] In some embodiments, at least one sensor may include one or more force and / or motion sensors configured to generate sensor data indicative of personal care actions performed by a user using the device during one or more personal care sessions. One or more force and / or motion sensors may be included in the personal care device, for example, integrated in the personal care device.

[0056] In some embodiments, the at least one sensor may include one or more operating signal sensors integrated into the personal care device, which are adapted to output an operating signal indicative of an operating parameter of the device, the operating parameter being related to a physical interaction of the device with a body surface.

[0057] In some embodiments, at least one sensor may include a biosensor configured to generate sensor data indicative of a biological parameter of a user during one or more personal care sessions. This may be included in the personal care device, for example integrated into the personal care device, or may be separate from the personal care device.

[0058] In some embodiments, the processing device is integrated into the personal care device.

[0059] In some embodiments, the processing device is comprised by a computing device external to the personal care device that is communicatively coupled to the personal care device or communicatively coupled to a data repository that is communicatively coupled to the personal care device.

[0060] In some embodiments, the processing device is a cloud-based processing device.

[0061] These and other aspects of the invention will be apparent from and elucidated with reference to the embodiment(s) described hereinafter. BRIEF DESCRIPTION OF THE DRAWINGS

[0062] For a better understanding of the invention, and to more clearly show how the same may be put into practice, reference will now be made, by way of example only, to the accompanying drawings, in which:

[0063] Figure 1 The steps of an example method according to one or more embodiments are outlined;

[0064] Figure 2 illustrates components of example processing devices and systems according to one or more embodiments;

[0065] Figure 3-Figure 4 illustrates trends of example metrics across multiple personal care sessions before and after a treatment or session, and illustrates comparative example scenarios of improved recovery and non-improved recovery;

[0066] Figure 5 illustrates trends of example metrics across multiple personal care sessions before and after treatment or therapy, and illustrates how the time period required for the metric to return to pre-treatment levels is compared to a reference time period to infer recovery; and

[0067] Figure 6-Figure 8 Illustrated is a method for inferring user pain during a personal care session by analyzing patterns in force and / or motion sensor data obtained from sensors integrated in a personal care device. DETAILED DESCRIPTION

[0068] The present invention will be described with reference to the accompanying drawings.

[0069] It should be understood that although the detailed description and specific examples indicate exemplary embodiments of the apparatus, system and method, these descriptions and specific examples are for illustrative purposes only and are not intended to limit the scope of the invention. These and other features, aspects and advantages of the apparatus, system and method of the present invention will be better understood from the following description, the appended claims and the accompanying drawings. It should be understood that these figures are merely schematic and are not drawn to scale. It should also be understood that the same reference numerals are used throughout the figures to indicate the same or similar parts.

[0070] The present invention provides a method for tracking the status of a patient after a treatment or therapy (e.g., recovery or progress). It is based on capturing sensor data during a user's personal care session and using this data to infer user pain information. For example, pain can be inferred from a biosensor or from patterns in a force / motion sensor integrated into a personal care device. The pain data can be converted into a metric for each personal care session, and by trending the metric over time, the patient's recovery or progress can be inferred. Reports can be generated based on the trended metrics and exported to practitioners, etc.

[0071] The concept is based on the following principles: systematic use of a personal care device is something that the user does routinely at fixed and reliable time points, and its normal use usually requires a series of systematic physical stimulations to the anatomical structure or different areas of the anatomical structure. Therefore, this provides an effective way to measure pain information associated with the relevant anatomical structure and use the data captured from the sensors associated with the personal care device.

[0072] For example, one area of ​​application is use with oral care devices, such as for oral cleaning. Since teeth cleaning is something people usually do twice a day, the monitoring method can be integrated into the user's daily routine very easily and efficiently, making compliance very high.

[0073] An advantage of embodiments of the present invention is that it enables clinical practitioners (e.g., dentists, dermatologists, etc.) to stay informed of the progress of a patient's condition, even when the patient is at home. This brings several advantages. It improves the patient experience by allowing the doctor to monitor their healing. The user experience is improved by allowing the doctor to understand how the patient's condition is progressing (or regressing). Clinical efficiency is also improved by optimizing the doctor's time: for example, scheduling a follow-up appointment can be postponed until pain data indicates that there may be a problem that needs to be checked. Another benefit is improved health outcomes. For example, monitoring of healing after treatment increases the chances of successful treatment.

[0074] Figure 1 The steps of an example computer-implemented method 10 according to one or more embodiments are summarized in block diagram form. The steps will be described in summary form and then further explained in the form of an example embodiment.

[0075] A method is a method used to determine the post-treatment status of a patient following a treatment or diagnosis.

[0076] The method 10 includes obtaining 12 data indicating pain of a user as a function of time during each personal care session in a series of personal care sessions performed by a user using a personal care device. The personal care session may be a session following a treatment or a therapy session. The data indicating pain of the user is determined based on sensor data from at least one sensor.

[0077] The method further comprises determining 14 a metric for each session based on the data indicative of pain for the user.

[0078] The method also includes calculating 16 a post-treatment or post-treatment condition based on trends in the metric over a series of personal care sessions following the treatment or treatment.

[0079] The method further comprises generating 18 a data report indicative of the calculated patient condition for export.

[0080] The method may also include transmitting the report to a remote computer, such as a computer accessible to a practitioner, such as a dentist in oral care, via a communication channel. For example, the report may be uploaded to a server, such as a cloud-based server or other server accessible to the practitioner. In this way, the practitioner may be informed of the patient's recovery status.

[0081] As indicated above, the method may also be implemented in hardware form, for example in the form of a processing unit configured to perform the method according to any example or embodiment described in this document or according to any claim of this application.

[0082] To further aid understanding, Figure 2 A schematic representation of an example processing unit 32 is presented, which is configured to perform a method according to one or more embodiments of the present invention. The processing unit is shown in the context of a system 30 that includes the processing unit. The processing unit itself represents one aspect of the present invention. The system 30 is another aspect of the present invention. The system provided does not necessarily include all of the hardware components illustrated; it may include only a subset thereof.

[0083] The processing unit comprises one or more processors 36 configured to perform the method according to the method outlined above or according to any embodiment described in this document or any claim of this application. In the illustrated example, the processing unit also comprises an input / output 34 or a communication interface. Figure 2In the illustrated example, the system 30 also includes one or more sensors 46 for providing sensor data 48. Although not shown, in some embodiments, the system may also include a personal care device. In some embodiments, the one or more sensors 46 may be included in the personal care device, for example, integrated in the personal care device. In some embodiments, the one or more sensors 46 may be separate from the personal care device.

[0084] In some embodiments, the one or more sensors 46 include one or more force or motion sensors configured to generate sensor data indicating a personal care action performed by a user using the device during one or more personal care sessions. The one or more force or motion sensors may be included in the personal care device. In some embodiments, the system 30 may include a personal care device that includes one or more force or motion sensors.

[0085] In some embodiments, the one or more sensors 46 include one or more operating signal sensors integrated into the personal care device, the one or more operating signal sensors being adapted to output an operating signal indicative of an operating parameter of the device, the operating parameter being related to the physical interaction of the device with the body surface. An example of an operating parameter is an electrical drive signal associated with an actuator that actuates a portion of the personal care device, such as a transmission mechanism that drives an electric toothbrush or shaver to vibrate, or a motor mechanism that drives a massage device. The electrical characteristics of the drive signal can vary as a function of the applied pressure, because the applied pressure applies greater physical resistance to the actuator mechanism. Another example of an operating parameter is a jet stream from an oral rinsing device or an electric flossing device.

[0086] In some embodiments, one or more sensors 46 include a biosensor configured to generate sensor data indicating a biological parameter of a user during one or more personal care sessions. In some examples, this can be integrated into a personal care device or can be separate from any personal care device. In some embodiments, system 30 can include a personal care device that includes a biosensor.

[0087] In some embodiments, processing device 32 is integrated into the personal care device. In other embodiments, processing device 32 may be included by a computing device external to the personal care device that is communicatively coupled to the personal care device or that is communicatively coupled to a data repository that the personal care device is communicatively coupled to. In other embodiments, processing device 32 may be a cloud-based processing device.

[0088] In order to illustrate and illustrate the concept of the present invention, an example will be presented below with reference to an oral care device, for which the above-mentioned personal care action is a cleaning action, and the personal care link is an oral cleaning link. However, it should be recognized that the principles outlined are easily applied to other types of personal care devices, such as, for example, skin care devices (e.g., phototherapy devices), trimming devices (e.g., shavers) or muscle / joint care devices (e.g., massage devices). For any personal care device, the device is generally designed to be applied to a certain area of ​​the user's body for a care function, thereby causing physical stimulation of one or more areas of the body by such application during the care link. Therefore, the normal use of the device essentially requires systematic physical detection of one or more areas of the body, which can induce a pain response and can be measured by sensor data. Therefore, it can be seen that the principles of the general inventive concepts outlined above and described below can be used for any personal care device. Therefore, the reference to the oral care device in the following embodiments can be replaced by a reference to any other personal care device without causing substantial changes to the principles of the present invention. Similarly, the reference to the cleaning action can be replaced by a reference to the personal care action, and the reference to the cleaning link can be replaced by a reference to the personal care link.

[0089] If the personal care device is an oral care device, then in some embodiments, the oral care device may be an electric toothbrush.A toothbrush may have a brush head with an array of cleaning elements, such as bristles, thereon.

[0090] As mentioned previously, the present invention can also be embodied in software form. Therefore, another aspect of the present invention is a computer program product, which includes code means (e.g., machine readable code, such as computer program code), which, when running on a processor, is configured to cause the processor to perform a method according to any example or embodiment of the present invention described in this document or according to any claim of this patent application.

[0091] Figure 3 and Figure 4 The concepts according to one or more embodiments of the invention are illustrated by simple examples.

[0092] Each chart shows the trend of the metric calculated for each personal care session in a series of personal care sessions spanning a period of 25 days, wherein the metric is a metric calculated based on the data indicating the user's pain obtained during each personal care session. For example, the metric can represent the average pain experienced during each personal care session. In other examples, it can represent the maximum pain level experienced during each session. In other examples, it can represent the average value of at least one sensor signal (e.g., the pressure applied to the body surface by at least a portion of the device) obtained during the session, wherein the sensor signal is regarded as an indicator of the pain experienced. For example, it is well known that the applied pressure can be expected to be inversely correlated with the pain level because when the user feels pain, they press less. For example, if the personal care device is an oral care device, such as an electric toothbrush device, the applied pressure can correspond to the applied pressure of the brush head cleaning element (e.g., bristles) on the tooth / oral surface. Similarly, if the personal care device is a trimming device, such as a razor, the sensor signal can indicate the applied pressure of the razor trimming area on the user's skin during use. This pressure sensor data provides information indicating the shaving action of the user during one or more shaving sessions. Similar principles apply to other types of personal care devices.

[0093] Different options for obtaining data indicative of a user's pain are described in more detail later. In all cases, some sensor data is acquired during the course of each personal care session and then used to infer information about the user's pain experience during the personal care session. Because users naturally probe or physically stimulate body surfaces (e.g., teeth) in a systematic manner during personal care sessions, personal care sessions provide a convenient and efficient regularly occurring period in which pain data can be acquired. The pain data is indicative of the healing status of the relevant anatomical structure, such as the mouth in the case of an oral case.

[0094] exist Figure 3 In , a metric is calculated for a period of four days prior to treatment. The value of the metric is plotted on a graph. On day 5, the user / patient undergoes treatment, such as dental surgery, e.g., root canal surgery, tooth extraction, or filling. Thereafter, the value of the metric drops significantly. This indicates an increase in pain levels, resulting in a commensurate change in the metric. For example, the metric represents the inferred health of the mouth. The metric value remains low for a period of about six days. Thereafter, the metric value quickly returns to approximately the value before treatment and remains at this level for at least another 15 days.

[0095] According to this trend of the metric, the recovery status after treatment can be calculated. In some examples, an overall recovery status after treatment can be determined, based on the fact that the metric value regresses to its pre-treatment level, which indicates that the recovery status after treatment is good. In some examples, the recovery status after treatment can be calculated at different time points after treatment. In some examples, the recovery status after treatment can be calculated in part based on the time since treatment and based on the expected level of the metric (i.e., the proportion of the patient's pre-treatment level at this time point after treatment). For example, the second day after surgery, the pain level is usually expected to be higher than before surgery, and therefore the metric is expected to be significantly lower than the pre-operative value. Therefore, the recovery status calculated at this time may indicate that the recovery status is normal, despite the fact that the metric value is significantly reduced. In contrast, at a time after treatment, such as 10 days, the pain is expected to return to the pre-treatment level or better, and so is the metric value. Therefore, the time in the trended metric where the metric value remains at a lower level after treatment for longer than a predefined threshold time period may indicate that the recovery status is not good.

[0096] In fact, the latter case Figure 4 This example has the same 4-day monitoring period before treatment, followed by treatment. Figure 3 As in the scenario with , the metric value drops significantly, indicating an increase in pain levels. However, in Figure 4 In a scenario where the metric value remains low for a longer period of time, the post-treatment recovery status after, for example, 10 days may indicate poor recovery in such a scenario.

[0097] In some examples, the post-treatment recovery status can take one of a series of discrete classifications, such as slow recovery, normal recovery, and fast recovery. The post-treatment recovery status can be calculated as a numerical value according to a defined numerical scale.

[0098] Prior to the scheduled treatment, there may be a calibration monitoring period of, for example, 3-7 days, during which user pain data in each personal care session is obtained and a metric for each personal care session is calculated on this basis. As will be explained later, in a simple example, the pain data is obtained by measuring the pressure applied by the personal care device during each personal care session, and where the applied pressure is considered to be inversely correlated with pain. In the case of an oral care device, the applied pressure can be the brushing pressure. Then, for each personal care session, the overall pain level can be taken as the average pressure. In a simple example, the average pressure value for a given personal care session can be used as a metric for that personal care session.

[0099] While examples have been presented above of the recovery condition being a post-treatment recovery condition, in other examples it may be a recovery condition following a non-treatment event, such as a visit with a dentist or other physician where no treatment is performed. For example, a user attends an appointment for pain-related complaints, and the physician advises the patient to simply wait and monitor the condition to see if it improves on its own.

[0100] Optionally, information indicating the location on or within the anatomical structure where the treatment was performed may be obtained, for example based on user input by a clinician or user. For example, in the case of oral care, this may be information indicating the location within the mouth where the treatment was performed. In some examples, a position sensing component may be part of a system operable to track the location of an operative portion of a personal care device (e.g., a brush head of an electric toothbrush) as a function of time on or within the anatomical structure to which the device is applied, so that the pain data obtained may be correlated with the location on or within the anatomical structure (e.g., a location within the mouth in the case of oral care). Optionally, if the body location to which the treatment corresponds is known (e.g., a location within the mouth), the pain data may be processed to extract only the pain information associated with that location, and the metric calculated and trended as a metric corresponding only to that location.

[0101] After treatment, pain data is monitored during the personal care session as before, and metrics are calculated as before. As described above, optionally, this can be restricted to the specific location where the treatment was performed.

[0102] The measure is trended. Any (sudden) change from the pre-treatment pattern of the measure value is indicative of pain. If this change remains consistent, the pain is still present and the patient has not recovered. Optionally, the duration of the pain (and optionally the spread and intensity of the pain) can be extracted and - depending on the procedure - the doctor is made aware, for example, to either call the patient for an appointment (if the pain persists longer than normal) or to continue monitoring (progress is normal). As soon as the patient returns to the pre-treatment measure value, this means that the pain has disappeared. The doctor can even cancel a scheduled appointment if it is judged that the patient has fully recovered and therefore no follow-up is needed.

[0103] Thus, it can be appreciated from the above examples that determining a post-treatment or post-therapy recovery status can be based on: determining a baseline value for a metric based on a metric value corresponding to a personal care session occurring prior to the treatment or therapy; and trending the metric value over time in the personal care session after the treatment or therapy, and comparing the metric value after the treatment or therapy to the baseline value. In some embodiments, the recovery status at a given point in time can include comparing the metric value at the given point in time to the baseline value, and then comparing any deviation to an expected deviation or a threshold deviation, and wherein the expected deviation or the threshold deviation can be a function of time after the treatment or therapy.

[0104] In another embodiment, rather than setting a baseline based on pre-treatment metric values, a baseline may be set based on values ​​for an area of ​​relevant anatomy (eg, an unaffected portion of the mouth, such as the opposite side of the mouth from that receiving treatment).

[0105] Figure 5 Another example of trend values ​​of a metric before and after treatment or diagnosis is illustrated. In this example, the time it takes for the metric value to return to the pre-treatment or pre-treatment level is used as a simple indicator of recovery status. For example, calculating the post-treatment recovery status may include: determining the duration that the metric remains above a predetermined threshold level after treatment or diagnosis based on the trend of the metric in a series of personal care sessions. The method may also include comparing the duration that the post-treatment metric value remains above the predetermined threshold level with a predefined expected recovery time period, and determining whether the time period exceeds the expected recovery period. For example, the metric may be a pain metric. For example, the threshold metric value may be determined based on a pre-treatment metric value, which is measured using sensor data from at least one sensor acquired before treatment.

[0106] According to this example, the idea is to categorize the patient's cure rate, for example, for triage (eg, to allow for early call back for follow-up care) and / or for risk stratification for in-office reprocessing.

[0107] refer to Figure 5 , which illustrates the tracking of post-treatment recovery rate in order to assess the post-treatment recovery status. Figure 5 Two scenarios are illustrated in FIG. 1 , labeled Scenario A and Scenario B. Scenario A represents a rapid recovery rate, while Scenario B represents a slower recovery rate. Each illustrated scenario shows a trend over time of the calculated values ​​of a pain-derived metric during a personal care session. As previously discussed, the metric is monitored over a period of time before and after treatment. The timing of treatment is represented by Figure 5The average metric value before treatment can be set as the baseline metric level. After treatment, the pain derived metric value decreases compared to the pre-treatment level. Thereafter, the metric value is monitored over time.

[0108] Based on this trend, the length of time it takes for the metric to return to a baseline level or a percentage of the baseline can be determined. The specific percentage can be defined based on the specific pathology or specific treatment suffered by the patient. The time it takes for the metric to return to the pre-treatment level can then be compared to a threshold or reference healing time. The threshold or reference healing time can be set based on the specific treatment or pathology. Based on whether the time it takes for the metric to rise to the baseline or a defined percentage of the baseline is greater than a reference expected recovery time period, the recovery condition can be classified as, for example, fast, normal, or slow healing.

[0109] For example, in the oral care area, following a treatment in the form of scaling and root planing, the patient may experience mild discomfort around the teeth for a few days. The patient may notice sensitivity to cold and heat (and sometimes sweets) that lasts for up to 6 weeks. Following deep periodontal pocket cleaning or the placement of a dental implant, the gums may take 5-7 days to heal. Following an implant procedure, the jawbone and gums may take 3-6 months to fully heal before a denture can be placed over the implant. Therefore, the expected normal recovery time may vary depending on the dental treatment.

[0110] exist Figure 5 In the example of , the reference expected recovery time period is labeled "Δt_ref". In scenario A, the time period it takes for the metric value to return to the pre-treatment baseline is labeled Δt1, and in scenario B, the time period it takes for the metric value to return to the pre-treatment baseline is labeled Δt2. In this example, Δt1 is less than Δt_ref, and therefore, for the patient in scenario A, the recovery condition is classified as "quick recovery". On the other hand, Δt2 is greater than Δt_ref, and therefore, for the patient in scenario B, the recovery condition is classified as "slow recovery".

[0111] Depending on the classification, different response actions may be triggered. For example, if the recovery status is "slow," an appointment with the dentist may be automatically scheduled, or the clinician may be alerted with an automatically generated alert message.

[0112] Additionally or alternatively, one option is to explicitly calculate the rate of change of the metric at one or more time points. The rate of change can be compared to a threshold rate of change representing an expected recovery rate for a given treatment. The expected recovery rate at a given time point can also be a function of the time since the treatment occurred. The threshold can be stored in, for example, a lookup table.

[0113] Thus, in some embodiments, determining a post-treatment recovery condition comprises comparing a rate of change of the metric over at least a subset of a series of personal care sessions post-treatment to a threshold rate of change.

[0114] As noted above, according to any embodiment, the method may also include performing a response action based on the determined recovery status. This may include automatically scheduling an appointment or automatically sending an alert message to a clinician (eg, a dentist).

[0115] Furthermore, as noted above, the method includes generating a data report indicative of the recovery status. According to one or more embodiments, the responsive action may include transmitting the data report to a practitioner computing device via a communication channel.

[0116] In some embodiments, data reports are transmitted only if it is determined that the post-treatment recovery condition is outside a normal range, and optionally, the normal range is determined based on the time that has passed since the treatment event. In other words, if the recovery condition is not normal, an alert is issued to the practitioner.

[0117] A portion of the method involves obtaining data indicative of user pain as a function of time during each of a series of personal care sessions performed by the user using a personal care device, wherein the data indicative of user pain is determined based on sensor data from at least one sensor. Different methods of obtaining data indicative of user pain from different types of sensors will now be discussed.

[0118] According to at least one set of embodiments, it is proposed to use physiological or biological sensor measurements. For example, skin conductance sensors (such as galvanic skin response (GSR) sensors) are known to provide outputs related to pain-related arousal. Therefore, in some embodiments, the signal level of the skin conductance sensor as a function of time can be used as a pain signal as a function of time.

[0119] Another bioparameter measurement known to be associated with pain is heart rate variability. See, for example, the following paper: Forte, G., Troisi, G., Pazzaglia, M., Pascalis, VD, & Casagrande, M. (2022). Heart Rate Variability and Pain: A Systematic Review. Brain Sciences, 12(2), 153.

[0120] Heart rate variability may be derived from a heart rate sensor signal, such as a PPG sensor signal.

[0121] Another bio-parameter measurement known to be associated with pain is respiration or breathing rate. Therefore, a breathing rate sensor may be used in some examples. For example, the breathing rate may be derived from a PPG sensor signal.

[0122] Another bio-parameter measurement known to be correlated with pain is facial expression. Facial expression data can be obtained by processing camera image data.

[0123] One or more biosensors may be integrated into the personal care device itself. For example, a skin conductance sensor may be integrated into a handle portion of a personal care device, such as a handle portion of an oral care device, such as a handle portion of an electric toothbrush. Likewise, additionally or alternatively, a PPG sensor may be integrated into a handle portion of a personal care device, such as a shaver or electric toothbrush. Alternatively, a separate biosensing unit or units may be provided. Alternatively, one or more biosensors may be integrated into a wearable unit, such as a wristband or patch. In some embodiments, the processing device may also be integrated into the same wearable unit.

[0124] According to another group of one or more embodiments, in addition to or instead of using biosensor data to derive data indicating user pain as a function of time, data from a force and / or motion sensor integrated in a personal care device can also be used to infer pain information. In this case, the sensor data includes data from one or more sensors integrated in the personal care device indicating the personal care actions performed by the user using the device during one or more personal care sessions. These may include one or more force and / or motion sensors. In addition or alternatively, data from one or more operation signal sensors integrated in the personal care device can be used, and the one or more sensors are suitable for outputting an operation signal indicating an operating parameter of the device, which is related to the physical interaction between the device and the body surface. An example of an operating parameter is an electrical drive signal associated with an actuator that actuates a part of the personal care device, such as a transmission mechanism that drives an electric toothbrush or shaver to vibrate, or a motor mechanism that drives a massage device. The electrical characteristics of the drive signal can vary as a function of the applied pressure because the applied pressure applies greater physical resistance to the actuator. Another example of an operating parameter is a jet of an oral rinsing device or an electric flossing device.

[0125] Information indicative of pain for the user during each of the one or more personal care sessions may be determined based on analysis of patterns in the sensor data.

[0126] In some embodiments, the personal care device can be an oral care device. In some embodiments, the oral care device can be an electric toothbrush. The toothbrush can have a brush head with an array of cleaning elements, such as bristles, on the brush head.

[0127] The integrated force and / or motion sensor may include a pressure sensor for sensing the pressure applied to a surface by a portion of the personal care device during use, for example, the pressure applied to the teeth by the cleaning elements of the brush head during operation. In the case of a toothbrush device, such a pressure sensor may be integrated into the brush head itself, but is more commonly integrated into the handle portion of the toothbrush to which the brush head is attached. The brush head may be removably attached to the handle portion for ease of replacement. For example, the pressure applied to the teeth may be sensed via a cantilever pressure sensing method.

[0128] The integrated force and / or motion sensor may include a motion sensor for sensing motion of the oral care device.The motion sensor may include or take the form of an inertial measurement unit (IMU), which typically includes one or more accelerometers, such as a three-axis accelerometer arrangement.

[0129] There are different methods to perform pattern analysis in sensor data in order to determine information indicative of pain for a user.

[0130] According to one method, the obtained sensor data includes a pressure sensor waveform indicating the pressure applied by a portion of the personal care device to the body surface during use, wherein the data indicating the user's pain is determined based on the pressure signal. For example, if the personal care device is an oral care device in the form of an electric toothbrush device, the pressure sensor waveform can indicate the pressure applied by the brush head cleaning elements (e.g., bristles) to the teeth / oral surface. Such pressure sensor data provides information indicating the cleaning action performed by the user using the device during one or more oral cleaning sessions, because it is related to the force with which the user presses the cleaning elements onto the oral / tooth surface during the cleaning session. Similarly, if the personal care device is a trimming device, such as a shaver, the pressure sensor waveform can indicate the pressure applied by the trimming area of ​​the shaver to the user's skin during use. Such pressure sensor data provides information indicating the shaving action of the user during one or more shaving sessions. Similar principles apply to other types of personal care devices, various examples of which have been discussed above.

[0131] Applied pressure sensor data can be used to infer data indicative of user pain during a personal care session, as it is well known that applied pressure will be inversely correlated with the level of pain experienced (e.g., as pain increases, brushing pressure will decrease). Therefore, analysis of pressure patterns over the course of a single personal care cycle (e.g., a cleaning cycle) or multiple cycles can provide information about the user's pain experience. For example, in the simplest embodiment, observation of pressure during an entire personal care cycle (e.g., a brushing cycle) will show a pattern in which differences in applied pressure as a function of time or location (e.g., compared to baseline measurements) will provide an indication of pain: that is, if an unexpected drop in applied pressure is seen in a pattern in which a fairly constant pressure is typically observed, this may be an indication that there is an abnormality in a low-pressure area that causes pain. Even more simply, a standard threshold pressure can be set, and any drop in applied pressure below that threshold in a portion of the sampled signal is considered to be an indication of pain experience at the location of the anatomical structure to which that portion of the signal corresponds (e.g., the mouth).

[0132] With respect to this set of embodiments, as a general approach, it can be said that information indicative of user pain during each of one or more personal care sessions can be determined further based on reference sensor pattern information associated with user pain or user comfort. The reference sensor pattern information can include a reference pattern of baseline brushing pressure as a function of time (or position) during a personal care cycle, the reference pattern being personalized for the user, and wherein pain in a personal care session is detected by comparing the reference baseline pattern with a pattern measured in a new personal care session. More simply, the reference sensor pattern information can include one or more characteristic pattern features in a sensor signal waveform, each characteristic pattern feature indicating a user pain response at a given moment during a personal care session, or user comfort during a given cycle of a personal care session. In particular, for a pressure sensor signal, a relevant characteristic pattern feature would be a trough or negative spike in the pressure sensor waveform, indicating a drop in pressure applied during a sub-interval of a given personal care session. For example, a trough in the signal where the pressure is below a predefined threshold baseline pressure may indicate a pain event where the pressure remains below the threshold within a sub-interval of a personal care session. The threshold may be set based on a reference baseline pressure (eg, a baseline pressure taken prior to treatment or during a period or at an anatomical location associated with low or zero pain).

[0133] Figure 6 One example of an oral care device for performing a cleaning function is illustrated. Figure 6An example brushing pressure signal as a function of time is illustrated. A trough in the signal is indicated by an arrow 62. During the time subinterval spanned by this trough, the applied pressure is below a defined threshold 64, and therefore a pain event is determined to have occurred during the time subinterval spanned by the trough. A trough 62 having a depth below the threshold 64 represents a characteristic pattern feature, the detection of which indicates that pain is being experienced during the time period spanned by the trough.

[0134] Optionally, in some embodiments, the pressure signal as a function of time or position in the mouth can be converted into a signal indicative of user pain as a function of time or position during each of one or more cleaning sessions. In a simple example, the pressure signal can be used directly as an indicator of pain, as it is expected to be inversely correlated with the pain experienced.

[0135] As mentioned above, by adding location information, the brushing pressure signal will be made more specific. The combination of the position sensor and the pressure sensor allows each pain event to be associated with an oral location. This allows the dentist or user to know if the pressure drop coincides with the location of a specific dental problem (such as a post-treatment wound), so that the signal can be attributed to the pain level with greater certainty.

[0136] Thus, in some embodiments, wherein the obtained sensor data may include position sensor data, and wherein the method includes determining information indicative of user pain as a function of position in the mouth. Determining a measure indicative of user pain as a function of position in the mouth may be based on associating each trough detected in the pressure signal with a corresponding position in the mouth using the position sensor data. The method may further include generating a pain map indicative of user pain as a function of position in the mouth, and optionally transmitting the generated pain map to the user interface for display on the user interface.

[0137] Furthermore, it is worth noting that the utility of position sensors to correlate pain events with locations in the mouth is not limited to embodiments using pressure sensors. Regardless of which specific force and / or motion sensor data is used to infer pain information, the additional use of position sensors allows characteristic pattern features associated with pain detected in the force / motion sensor signals to be correlated with locations in the mouth. As suggested above, the generation of pain maps is also more broadly compatible with any other embodiments described in this document.

[0138] According to another approach (which can be combined with or used in place of the pressure sensor approach already described), one or more motion sensing components can be used to sense the movement of the personal care device. In this case, the sensor signal can show a sudden (impulsive) movement of the personal care device when acute pain is felt. The movement may be, for example, perpendicular to (e.g., away from) an anatomical surface (e.g., a tooth surface), but sudden movement in any direction is possible after pain is felt. Here, it can be inferred that the level of pain increases with the increase in motion impulses.

[0139] Thus, according to this method, the sensor data may include a motion sensor signal, and wherein the information indicative of pain to the user is determined based on detecting an inflection point in the motion, the inflection point being indicative of a user's response to locally experienced pain.

[0140] Therefore, this method is also based on detecting one or more characteristic pattern features in the sensor signal waveform, which are indicative of the user's pain response at a given moment during the personal care session, or the user's comfort during a given period of the personal care session. In this method, the characteristic waveform pattern features are inflection points or spikes or pulses in the signal.

[0141] The motion sensor may include an inertial sensor, such as an accelerometer.

[0142] Figure 7 An example motion sensor signal as a function of time during a single personal care session is illustrated. In this case, the motion sensor is sensitive to at least a direction perpendicular to (e.g., away from) an anatomical surface of interest (e.g., a tooth surface) during use of the personal care device (e.g., a tooth surface). Figure 7 74). An upward inflection point or spike or fluctuation in the signal is indicated at arrow 72. The amplitude or height of the inflection point or spike or fluctuation in the signal exceeds a threshold motion level 74, which in this example may correspond to motion speed or acceleration. If an inflection point in the signal exceeds a predefined threshold 74, it may be classified as corresponding to a pain event.

[0143] According to another approach (which may be used in combination with or in place of any other approach in this document), a motion sensor may be used that is operable to detect movement in one or more directions, for example, during use of the personal care device. The pattern in the signal represents the brushing action of the user, which manifests as an alternating pattern in the signal waveform. Figure 8 An example is shown. In this example, Figure 8The motion in the plane direction (y direction) with respect to the tooth surface is shown schematically in the figure of However, the brushing motion can be sensed by a motion sensor that senses motion in any direction, for example, only a three-axis accelerometer that is operable to sense motion in any direction is required.

[0144] At locations where pain is experienced, the amplitude of the brushing motion is expected to be reduced compared to areas where pain is not felt. Thus, herein, the sensor data comprises a motion sensor signal, and wherein the information indicative of user pain is determined based on detecting alternating motion cycles in the motion sensor signal, the alternating motion cycles being indicative of the user's brushing action, and wherein the amplitude or duration of the alternating motion cycles is used to infer the patient's comfort level.

[0145] In particular, pain may be detected by detecting a characteristic waveform feature in the form of an alternating signal portion having an amplitude below a threshold 74. In some examples, the threshold may be set to a defined proportion of the average amplitude of the signal over the entire individual session, such as half the average amplitude. Sub-portions of the signal whose amplitude of the detected alternating motion signal is below the defined threshold may be classified as corresponding to a pain event. Likewise, further, the use of a position sensor may allow these sub-portions of the signal to be associated with specific locations of the anatomical structure, such as in the mouth, such as specific tooth locations.

[0146] For example, the acquired sensor data may include position sensor data, and wherein the method includes determining information indicative of user pain as a function of position on / in an anatomical structure (e.g., in the mouth). The user pain as a function of position may be determined based on associating each signal cycle of the detected lower amplitude alternating motion with a corresponding position on / in an anatomical structure (e.g., in the mouth) using the position sensor data.

[0147] In addition to or in lieu of the amplitude of the brushing motion, the brushing frequency may also be used to detect areas of higher pain. Specifically, in areas of higher pain, slow and careful movement or brushing (at that location) may be expected. Thus, in some embodiments, determining information indicative of user pain includes determining the frequency of an alternating motion signal along a direction parallel to an application surface (e.g., a tooth surface), identifying portions of the continuous motion signal having a frequency below a threshold frequency, and classifying those portions as corresponding to pain events. Again, here, adding a position sensor would improve specificity.

[0148] In addition to the amplitude and frequency of the brushing motion, or in place of the amplitude and frequency of the brushing motion, the duration of time spent applying the device to a specific area, such as the duration spent cleaning a specific tooth or tooth area, can also be used to infer the pain level experienced in the area. Here, the analysis of the sensor signal may include first identifying a plurality of different signal portions corresponding to the time period spent cleaning different areas (such as different tooth areas, such as different teeth) in the force and / or motion sensor signal. In some cases, this can be done by associating different signal portions with the output of the motion sensor. In other cases, this can be done by identifying the pattern segments separated by interruptions or pauses in the signal when the user moves to the next signal. For example, for a pressure signal, a pause may have a recognizable signature or fingerprint, such as a signal period with a duration lower than a threshold duration, and wherein, for example, the pressure or motion amplitude is lower than a certain threshold. Once different signal segments are identified, the length of time of each signal segment can be determined, and from which the time spent by the user in each area (such as cleaning each tooth) can be determined. Alternatively, the dwell time on each tooth can be determined from an external source (such as a brushing behavior monitoring module integrated in a native software application of a personal care device). A short time may indicate higher pain. A short time in combination with the presence of one of the characteristic signal waveform features discussed during the signal segment, such as alternating motion of lower amplitude, a spike in out-of-plane motion, or a drop in pressure, may also be used to indicate pain.

[0149] Although the above examples are described with reference to example signals corresponding to in-plane motion, in practice the detected alternating motion may be in any direction.

[0150] The above-described embodiments of the present invention employ processing means. The processing means may generally include a single processor or multiple processors. It may be located in a single containing device, structure or unit, or may be distributed between multiple different devices, structures or units. Therefore, the processing means adapted or configured to perform a specific step or task may correspond to the step or task performed by one or more of the multiple processing components individually or in combination. Those skilled in the art will understand how to implement such distributed processing means. The processing means includes a communication module or input / output for receiving data and outputting data to other components.

[0151] The one or more processors of the processing device can be implemented in a variety of ways using software and / or hardware to perform the various functions required. The processor usually adopts one or more microprocessors, which can be programmed using software (e.g., microcode) to perform the required functions. The processor can be implemented as a combination of dedicated hardware to perform certain functions, and one or more programmed microprocessors and associated circuits to perform other functions.

[0152] Examples of circuits that may be employed in various embodiments of the present disclosure include, but are not limited to, conventional microprocessors, application specific integrated circuits (ASICs), and field programmable gate arrays (FPGAs).

[0153] In various implementations, the processor may be associated with one or more storage media, such as volatile and non-volatile computer memory, such as RAM, PROM, EPROM, and EEPROM. The storage media may be encoded with one or more programs that perform desired functions when executed on one or more processors and / or controllers. The various storage media may be fixed within the processor or controller, or may be removable so that one or more programs stored thereon may be loaded into the processor.

[0154] Variations to the disclosed embodiments may be understood and implemented by those skilled in the art in practicing the claimed invention by studying the 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.

[0155] A single processor or other unit may fulfill the functions of several items recited in the claims.

[0156] The mere 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.

[0157] The computer program may be stored / distributed on a suitable medium, such as optical storage media or solid-state media supplied with or as part of other hardware, but may also be distributed in other forms, such as via the Internet or other wired or wireless telecommunications systems.

[0158] If the term "suitable for" is used in the claims or the specification, it should be noted that the term "suitable for" is intended to be equivalent to the term "configured to".

[0159] Any reference signs in the claims should not be construed as limiting the scope.

Claims

1. A method (10) for determining the condition of a patient after a treatment or diagnosis, comprising: obtaining data indicative of user pain as a function of time during each of a series of personal care sessions performed by the user using a personal care device, the personal care session following the treatment or session, and wherein the data indicative of user pain is determined based on sensor data from at least one sensor; Determining (14) a metric for each session based on the data indicating pain to the user; calculating (16) a post-treatment or post-treatment condition based on a trend of the metric in the series of personal care sessions following the treatment or treatment, and A data report indicating the calculated post-treatment or post-diagnosis condition is generated (18) for export. 2 . The method of claim 1 , wherein the at least one sensor is a sensor integrated in the personal care device.

3. The method of claim 1 or 2, wherein the sensor data comprises data from a biosensor.

4. The method of claim 3, wherein the biosensor is a skin conductance sensor, such as a galvanic skin response (GSR) sensor.

5. A method according to any one of claims 1-4, wherein the sensor data includes data from one or more force and / or motion sensors integrated in the personal care device, indicating personal care actions performed by the user using the device during one or more personal care sessions, or data from one or more operation signal sensors integrated in the personal care device, wherein the one or more operation signal sensors are suitable for outputting operation signals indicating operation parameters of the device, wherein the operation parameters are related to the physical interaction of the device with the body surface.

6. A method according to claim 5, wherein information indicative of user pain during each of the one or more personal care sessions is determined based on an analysis of patterns in the sensor data, and optionally based on reference sensor pattern information associated with user pain or user comfort.

7. The method according to any one of claims 1 to 6, wherein the calculating the post-treatment or post-diagnosis condition comprises: Based on the trend of the metric over the series of personal care sessions, a duration of time that the metric remains above a predetermined threshold level after the treatment or session is determined.

8. The method of claim 7, wherein the method further comprises comparing the duration that the metric remains above a predetermined threshold level after treatment or therapy with a predefined expected recovery time period, and determining whether the time period exceeds the expected recovery period.

9. A method according to claim 7 or 8, wherein the threshold level is determined based on a pre-treatment or pre-diagnosis measurement level, and the pre-treatment or pre-diagnosis measurement level is measured using sensor data acquired from at least one sensor before the treatment or diagnosis.

10. The method according to any one of claims 1-9, wherein the determining of the post-treatment or post-diagnosis condition comprises comparing the rate of change of the metric in the series of links after treatment or diagnosis with a threshold rate of change.

11. The method of any one of claims 1-10, further comprising performing a responsive action based on the patient condition.

12. The method of claim 11, wherein the responsive action comprises transmitting the data report to a practitioner computing device via a communication channel.

13. A method according to claim 12, wherein the data report is transmitted only if it is determined that the post-treatment or post-diagnosis condition is outside a normal range, and optionally, wherein the normal range is determined based on the time that has passed since the treatment or diagnosis.

14. The method of any one of claims 1-13, wherein the personal care device is an oral care device, the personal care session is an oral cleaning session, and the personal care action is a cleaning action.

15. A method according to any preceding claim, wherein the personal care session comprises performing, by the personal care device, a personal care function involving interaction with the user.

16. A method according to any of the preceding claims, wherein the personal care device is a device for application to an area of ​​the user's body to perform a care function, whereby physical stimulation of one or more areas of the body is caused by such application during the personal care session.

17. The method of any one of the preceding claims, wherein the personal care device is one of: Oral care devices; Skin care devices, such as light therapy devices; a trimming device, such as a razor; or Muscle / joint care devices, such as massage devices.

18. A computer program product comprising computer executable code, the computer executable code being configured to, when executed on a processor, cause the processor to perform the method according to any one of claims 1-17.

19. A processing device (32), comprising: Input / Output (34); as well as One or more processors (36), the one or more processors configured to: obtaining information indicative of user pain as a function of time during each of a series of personal care sessions performed by the user using a personal care device, the personal care session following a treatment or session, and wherein the data indicative of user pain is determined based on sensor data from at least one sensor; determining a metric for each session based on the data indicating pain of the user; calculating a post-treatment or post-treatment condition based on a trend of the metric in the series of personal care sessions following the treatment or treatment, and A data report indicating the calculated patient condition is generated for export.

20. The apparatus of claim 19, wherein the sensor data comprises data from a biosensor.

21. The device of claim 20, wherein the biosensor is a skin conductance sensor, such as a galvanic skin response (GSR) sensor.

22. A device according to any one of claims 19-21, wherein the sensor data includes data from one or more force and / or motion sensors integrated in the personal care device, indicating personal care actions performed by the user using the device during one or more personal care sessions, or data from one or more operation signal sensors integrated in the personal care device, wherein the one or more operation signal sensors are suitable for outputting operation signals indicating operation parameters of the device, wherein the operation parameters are related to the physical interaction of the device with the body surface.

23. An apparatus according to claim 22, wherein the information indicative of user pain during each of the one or more personal care sessions is determined based on an analysis of patterns in the sensor data and, optionally, based on reference sensor pattern information associated with user pain or user comfort.

24. The apparatus according to any one of claims 19-23, wherein said calculating said post-treatment or post-diagnosis condition comprises: Based on the trend of the metric over the series of personal care sessions, a duration of time that the metric remains above a predetermined threshold level after the treatment or session is determined.

25. An apparatus according to claim 24, wherein the one or more processors are further configured to compare the duration that the metric remains above a predetermined threshold level after treatment or diagnosis with a predefined expected recovery time period, and determine whether the time period exceeds the expected recovery period.

26. An apparatus according to claim 24 or 25, wherein the threshold level is determined based on a pre-treatment or pre-diagnosis metric level, and the pre-treatment or pre-diagnosis metric level is measured using sensor data acquired from at least one sensor before the treatment or diagnosis.

27. An apparatus according to any one of claims 19-26, wherein determining the post-treatment or post-diagnosis condition includes comparing the rate of change of the metric in the series of links after treatment or diagnosis with a threshold rate of change.

28. The apparatus of any one of claims 19-27, wherein the one or more processors are further configured to perform a responsive action based on the patient condition.

29. The device of claim 28, wherein the responsive action comprises transmitting the data report to a practitioner computing device via a communication channel.

30. An apparatus according to claim 29, wherein the data report is transmitted only if the post-treatment or post-diagnosis condition is determined to be outside a normal range, and optionally, wherein the normal range is determined based on the time that has passed since the treatment or diagnosis.

31. A system (30), comprising: The processing device (32) according to any one of claims 19-30; Personal care devices; as well as at least one sensor (46); Wherein the processing means is arranged to receive sensor data generated by the at least one sensor as input at the input / output.

32. The system according to claim 31, Wherein the personal care device comprises the at least one sensor.

33. The system of claim 31 or 32, wherein the personal care device is an oral care device, the personal care session is an oral cleaning session, and the personal care action is a cleaning action.

34. The system of any one of claims 31-33, wherein the personal care session comprises performing, via the personal care device, a personal care function involving interaction with the user.

35. A system according to any one of claims 31-34, wherein the personal care device is a device for application to an area of ​​the user's body to perform a care function, whereby physical stimulation of one or more areas of the body is caused by such application during the personal care session.

36. The system of any one of claims 31-35, wherein the personal care device is one of: an oral care device; a skin care device, such as a light therapy device; a trimming device, such as a shaver; or a muscle / joint care device, such as a massage device.

37. A system according to any one of claims 31 to 36, Wherein the at least one sensor comprises: one or more force and / or motion sensors configured to generate sensor data indicative of personal care actions performed by the user using the device during one or more personal care sessions, or one or more operation signal sensors integrated in the personal care device, the one or more operation signal sensors being adapted to output an operation signal indicative of an operation parameter of the device, the operation parameter being related to a physical interaction of the device with a body surface; or A biosensor is configured to generate sensor data indicative of a biological parameter of the user during one or more personal care sessions.

38. The system of any one of claims 31-37, wherein: The processing device is integrated in the personal care device; or The processing device is comprised by a computing device external to the personal care device, the computing device being communicatively coupled to the personal care device or being communicatively coupled to a data repository, the personal care device being communicatively coupled to the data repository; or The processing device is a cloud-based processing device.

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