Heater apparatus and methods

Abstract

Apparatus for drying and / or styling hair comprises sensors 25, 32, 33, 34 for sensing and outputting data indicative of how the apparatus is being operated by the user during hair treatment. A heater

Description

Field of the Invention The present invention relates to heating apparatus and methods. The heaters can be used for styling and / or drying hair. Such styling and / or drying of the hair may be performed by a user in respect of their own hair, for example, or by a hair stylist. The invention has particular, but not exclusive, relevance to a styling and / or drying device comprising one or more low thermal mass heaters. Background to the Invention Heated hairstyling tools use heat to increase the temperature of hair to a desired styling temperature. For example, a hair straightener having a heated plate applies heat directly via conduction to heat the hair, which may be either wet or dry, to achieve the desired temperature for styling. The hair may be heated to a temperature that is particularly suitable for styling hair (for example, to or beyond a hair glass transition phase temperature). At lower temperatures, the user may have to make many passes with the hair straightener over the hair to achieve a desired styling effect, whereas at higher temperatures, there is a risk of causing permanent damage to the hair. Similarly, a heated brush or hair dryer can also be used to style hair by heating air which in turn heats the hair to a temperature suitable for styling. The hair is typically styled from wet, for example after the user has washed their hair, although the hair could also be styled from dry. Existing hair styling appliances typically use heaters that provide a certain amount of thermal energy to the hair styling appliance. The amount of thermal energy provided to the hair styling appliance corresponds to one mode of operation so that the hair of most users of the hair styling appliance may be heated to a temperature that is particularly suitable for styling hair. However, there is a need for improvements to such existing hair styling appliances. Users often have an expected result for the styling of their hair. When the styling result does not correspond to the expected result, the discrepancy generates user’s frustration. The user’s frustration leads to user’s behaviours, such as a tighter grip on the hair, which in turn provoke damage to the hair. The present invention aims to address or at least partially ameliorate one or more of the above problems. Summary of the Invention Aspects and embodiments of the invention are set out in the appended claims. These and other aspects of the invention, and aspects and embodiments which are useful in understanding the invention set out in the appended claims, are also described in the disclosure herein. Any feature in one aspect of the disclosure may be applied to other aspects of the disclosure, in any appropriate combination. In particular, method aspects may be applied to device and computer program aspects, and vice versa. Furthermore, features implemented in hardware may generally be implemented in software, and vice versa. Any reference to software and hardware features herein should be construed accordingly. In one aspect the invention provides apparatus for drying and / or styling hair, the apparatus being manipulable by a user to perform a desired treatment on the hair of the user, the apparatus comprising: sensors for sensing and outputting sensor data indicative of operational parameters on how the apparatus is operated by the user during the treatment; a heater for heating hair of a user, the heater comprising a plurality of independently controllable heater electrodes that define a plurality of independently controllable heating zones; and a controller configured to: process the sensor data to predict the desired treatment which the user is trying to achieve; and / or process the sensor data to calculate a frustration score, the frustration score being indicative of a level of frustration of the user while attempting to achieve the desired treatment; individually control the temperature or the power output of the one or more heating zones of the plurality of individually controllable heating zones, based on the predicted desired treatment and / or on the calculated frustration score, to help the user to achieve the desired treatment and / or to avoid the hair being burnt. The apparatus may further comprise a user interface for allowing the user to specify the desired treatment to be performed on their hair. The controller may be configured to predict the desired treatment which the user is trying to achieve based on the desired treatment specified by the user. The apparatus may further comprise communication circuitry such that the apparatus is configured to receive user input information about the desired treatment from an external processing device, and wherein the user input information is input on a user interface which is associated with the user on the external processing device. The controller may be configured to predict the desired treatment which the user is trying to achieve based on the user input information about the desired treatment. The external processing device may be part of a mobile phone or a smart watch and is configured to run an application, remote from the apparatus. The sensors may comprise at least one of one or more motion sensors for sensing and outputting sensor data indicative of how the apparatus is being moved by the user; and / or a grip sensor configured to measure a pressure between arms of the apparatus and / or a pressure in a handle and / or a head of the apparatus, and / or configured to detect an open or closed configuration of arms of the apparatus; and / or a hand sensor configured to measure the placement of the hand of the user during the treatment, and / or a timer configured to measure time elapsed while the user is attempting to achieve the desired treatment. The one or more motion sensors of the apparatus may comprise any one or more of an accelerometer, a gyrometer, a magnetometer, an inclination sensor, the controller being configured to determine amplitudes of movements of the apparatus, including angles, inclinations and rotations. The controller may be configured to process the sensor data from the one or more motion sensors and the grip sensor to predict the desired treatment which the user is trying to achieve. The hand sensor may comprise at least one of resistive and / or capacitive means to measure the placement of the hand of the user on the apparatus. The controller may be configured to process the sensor data from the hand sensor to predict the desired treatment which the user is trying to achieve. The controller may be configured to predict the desired treatment which the user is trying to achieve based on at least one of: time data, such as time of day, day of the week, historical data from previous styling sessions, and / or hair type data. The controller may be configured to process the sensor data from the timer to calculate the frustration score from the measured time elapsed while attempting to achieve the desired treatment. The controller may be configured to calculate the frustration score based on any one or more of: data indicative of the measured pressure between arms of the apparatus and / or pressure in a handle and / or a head of the apparatus; and / or data indicative of speed of the determined movements of the apparatus; and / or data about the desired treatment. The controller may be configured to retain historical user data and use that to form an expected or baseline behaviour from the user. The larger the deviation from the expected behaviour, the higher the frustration score. The controller may further be configured to calculate the frustration score based on data about power output of the apparatus. The controller may be configured to predict the desired treatment and / or to calculate the frustration score based on: a set of deterministic rules. Forthe frustration score, the controller may use sensor data including data indicative of a time elapsed while attempting to achieve the desired treatment and / or data indicative of a pressure between arms of the apparatus and / or a pressure in a handle and / or a head of the apparatus. The controller may be configured to predict the desired treatment and / or to calculate the frustration score based on: data fora trained artificial intelligence algorithm stored in a memory of the apparatus. The artificial intelligence algorithm may comprise a trained convolutional neural network and / or modular neural network and / or random forest and / or K-Nearest Neighbours. The controller may be configured to control a temperature or a power output of the one or more heating zones by: capping an increase in the temperature or the power output of the one or more heating zones of the plurality of controllable heating zones, based on the predicted desired treatment and / or on the calculated frustration score, to avoid the hair to be burnt. The controller may be configured to control a temperature or a power output of the one or more heating zones by: setting a target temperature or power output of the one or more heating zones of the plurality of controllable heating zones which are engaged with the hair, based on the predicted desired treatment and / or on the calculated frustration score, to help the user to achieve the desired treatment. The controller may be configured to: determine whether the calculated frustration score is greater than a threshold value, and if it is, to: output one or more feedback messages for the user to lower the user’s frustration, and / or inhibit the output of feedback messages which are likely to increase the user’s frustration, and / or to control a target temperature or power output of the one or more heating zones of the plurality of controllable heating zones which are engaged with the hair, to help the user to achieve the desired treatment and / or to avoid the hair being burnt. The controller may be configured to control the target temperature or the power output of the one or more heating zones of the plurality of controllable heating zones so as to enable a better drying or styling of the hair which is loaded in the apparatus. The apparatus may be a hair straightener, a hair dryer, a hot paddle brush, a hot round brush, a heater roller, or a hair curler. The heater may comprise a hair contacting surface, for heating the hair contacting the hair contacting surface by conduction. The frustration score is a real number between 0 and 1. For example a score of 0 may be indicative of the user being “very happy” and a score of 1 may be indicative of the user being “very frustrated”. In another aspect the invention provides apparatus for drying and / or styling hair, the apparatus being manipulable by a user to perform a desired treatment on the hair of the user, the apparatus comprising: sensors for sensing and outputting sensor data indicative of operational parameters on how the apparatus is operated by the user during the treatment, the sensor data including data indicative of a time elapsed while attempting to achieve the desired treatment and / or data indicative of a pressure between arms of the apparatus and / or a pressure in a handle and / or a head of the apparatus; a heater for heating hair of a user, the heater comprising a plurality of independently controllable heater electrodes that define a plurality of independently controllable heating zones; and a controller configured to: process the sensor data to calculate a frustration score based on the time elapsed while attempting to achieve the desired treatment and / or the pressure between arms of the apparatus and / or the pressure in a handle and / or a head of the apparatus, the frustration score being indicative of a level of frustration of the user while attempting to achieve the desired treatment; individually control the temperature or the power output of the one or more heating zones of the plurality of individually controllable heating zones, based on the calculated frustration score, to help the user to achieve the desired treatment and to avoid the hair being burnt; and / or output one or more feedback messages for the user to lower the user’s frustration, and / or inhibit the output of feedback messages which are likely to increase the user’s frustration, based on the calculated frustration score. Individually controlling the temperature or the power output of the one or more heating zones of the plurality of individually controllable heating zones may comprise at least one of: capping an increase in the temperature or the power output of the one or more heating zones of the plurality of controllable heating zones, based on the calculated frustration score, to avoid the hair to be burnt; and / or setting a target temperature or power output of the one or more heating zones of the plurality of controllable heating zones which are engaged with the hair, based on the calculated frustration score, to help the user to achieve the desired treatment. The heater may comprise a hair contacting surface, for heating the hair contacting the hair contacting surface by conduction. The controller may be configured to calculate the frustration score based on: a set of deterministic rules; and / or data for a trained artificial intelligence algorithm stored in a memory of the apparatus. The artificial intelligence algorithm may comprise a trained convolutional neural network and / or modular neural network and / or random forest and / or K-Nearest Neighbours. In another aspect the invention provides a method for generating a trained frustration calculator configured to calculate a frustration score, the frustration score being indicative of a level of frustration of a user while attempting to achieve a desired treatment, the method comprising: obtaining a plurality of annotated training streams of data; and training the frustration calculator by applying a machine learning algorithm to the obtained training streams of data, wherein the annotation indicates a level of frustration of the user, associated with each training stream of data, and wherein the plurality of annotated training streams of data comprise a training stream of data corresponding to a time elapsed while attempting to achieve the desired treatment and / or a training stream of data corresponding to a pressure between arms of the apparatus and / or a pressure in a handle and / or a head of the apparatus, for a plurality of levels of frustration. In another aspect the invention provides a method for generating a trained desired treatment predictor configured to predict a desired treatment which a user is trying to achieve, the method comprising: obtaining a plurality of annotated training streams of data; and training the desired treatment predictor by applying a machine learning algorithm to the obtained training streams of data, wherein the annotation indicates a desired treatment which a user is trying to achieve, associated with each training stream of data, and wherein, for a plurality of desired treatments, the plurality of annotated training streams of data comprise: a training stream of data corresponding to motion sensors indicative of amplitudes of movements of the apparatus, and a training stream of data corresponding to a grip sensor indicative of a pressure between arms of the apparatus and / or a pressure in a handle and / or a head of the apparatus and / or indicative of an open or closed configuration between arms of the apparatus. The machine learning algorithm may be trained to minimize a loss between the annotation associated with each training stream of data and a determination by the machine learning algorithm. The machine learning algorithm may comprise a convolutional neural network and / or modular neural network and / or random forest and / or K-Nearest Neighbours. In another aspect the invention provides a method of producing apparatus for drying and / or styling hair, wherein the apparatus comprises a heater for heating hair of a user, the heater comprising a plurality of independently controllable heater electrodes that define a plurality of independently controllable heating zones, a memory and a controller coupled to the memory, the method comprising: obtaining a trained machine learning algorithm; and storing the obtained trained machine learning algorithm in the memory of the apparatus. The storing may comprise transmitting the generated trained machine algorithm to the apparatus via a network, the apparatus receiving and storing the trained machine learning algorithm. The trained machine learning algorithm may be generated, stored and / or transmitted in the form of one or more of: a data representation of the trained machine learning algorithm; executable code for applying the trained machine learning algorithm. The heater may comprise a hair contacting surface, for heating the hair contacting the hair contacting surface by conduction. In another aspect the invention provides apparatus for drying and / or styling hair, the apparatus being manipulable by a user to perform a desired treatment on the hair of the user, the apparatus comprising: sensors for sensing and outputting sensor data indicative of operational parameters on how the apparatus is operated by the user during the treatment, the sensor data including data indicative of a time elapsed while attempting to achieve the desired treatment and / or data indicative of a pressure between arms of the apparatus and / or a pressure in a handle and / or a head of the apparatus; a heater for heating hair of a user, the heater comprising a plurality of independently controllable heater electrodes that define a plurality of independently controllable heating zones; a memory storing a trained frustration calculator, and a controller coupled to the memory and configured to: use the stored trained frustration calculator to calculate a frustration score based on the time elapsed while attempting to achieve the desired treatment and / or the pressure between arms of the apparatus and / or in a handle and / or a head of the apparatus, the frustration score being indicative of a level of frustration of the user while attempting to achieve the desired treatment; individually control the temperature or the power output of the one or more heating zones of the plurality of individually controllable heating zones, based on the calculated frustration score, to help the user to achieve the desired treatment and to avoid the hair being burnt; and / or output one or more feedback messages for the user to lower the user’s frustration, and / or inhibit the output of feedback messages which are likely to increase the user’s frustration, based on the calculated frustration score. The heater may comprise a hair contacting surface, for heating the hair contacting the hair contacting surface by conduction. In another aspect the invention provides a corresponding computer program or a corresponding computer program product comprising instructions. Brief Description of the Drawings Embodiments of the invention will now be described, by way of example only, and with reference to the drawings in which: Figure 1 a shows an overview of an exemplary hair styling device; Figure 1b shows a hair styling device in use; Figure 2 is a block diagram illustrating the main electronic components of the hair styling device shown in Figure 1; Figure 3a is an exploded view of a heater forming part of the hair styling device shown in Figure 1; Figure 3b is an assembled partially transparent view of the heater shown in Figure 3a; Figure 4a schematically illustrates the heating zones on the heating surface of the heater shown in Figure 3; Figure 4b schematically illustrates an alternative arrangement of heating zones; Figure 5 schematically illustrates a further alternative arrangement of heating zones that are of different sizes and shapes; Figure 6a illustrates the way in which the heating zones may be formed on a tubular substrate for use in a curling tong or the like; Figure 6b illustrates the way in which the heating zones may be arranged on a curved substrate which may be used on a heated brush; Figure 7 illustrates a tress of hair that partly overlaps with zones Z2 and Z4 of a heater; Figure 8 shows a flow chart illustrating an example method of operation of the apparatus, according to the disclosure; Figure 9 shows a flow chart illustrating an example method of generating a trained machine learning algorithm, according to the disclosure; Figure 10 shows an example architecture of a frustration calculator according to the disclosure; and Figure 11 shows a flow chart illustrating an example method for producing a hair styling appliance according to the disclosure. Overview of Hair Styling Device Figure 1a illustrates a hand-held (portable) hairstyler 1 (or hair styling appliance in the present disclosure). The hair styler 1 includes a first movable arm 4a and a second movable arm 4b, which are coupled at proximal ends thereof to a shoulder 2. The first arm 4a bears a first heater 6a at its distal end, and the second arm 4b bears a second heater 6b at its distal end. The first and second heaters 6a, 6b oppose one another and are brought together as the first and second arms 4a, 4b are moved from an open configuration to a closed configuration. As shown in Figure 1b, during use, a tress of hair 40 is sandwiched between the two arms 4 so that the user’s hair is in contact with, and therefore heated by, outer heating surfaces of the heaters 6a, 6b. Therefore, as the user pulls the hair styler 1 along the tress of hair 40, the tress of hair 40 is heated by conductive heating to a suitable temperature to facilitate styling. A user interface 11 is provided to allow the user to input information about them to the device and / or for the device to output information to the user. The user interface 11 may have a dial, button or touch display for allowing the user to input information to the device 1. The user interface 11 may be configured for allowing the user to specify e.g., a desired treatment to be performed on their hair. The user interface 11 may have an indicator light, display, sound generator or haptic feedback generator for outputting information to the user. In this embodiment, the user interface 11 also comprises a control button or switch 14 to enable the user to turn the device 1 on or off; and an indicator light 15 to show whether the power is on. A printed circuit board assembly (not shown) may be provided at any suitable location within the housing of the device 1 and carries the control circuitry for controlling the operation of the device 1 and for controlling the interaction with the user via the user interface 11. In this example, electrical power is provided to the device 1 by means of a power supply located at an end of the device, via a power supply cord 3. The power supply may be an AC mains power supply. However, in an alternative embodiment the power supply may comprise one or more DC batteries or cells (which may be rechargeable, e.g., from the mains or a DC supply via a charging lead), thereby enabling the device 1 to be a cordless product. In use, the device 1 is turned on, energising the heaters 6 to cause them to heat up. The user then opens the first and second arms 4a, 4b and, normally starting from the roots of the hair (i.e. near the scalp), a length or tress of hair 40 (which may be clumped) is introduced between the arms 4a, 4b, transversely across the heaters 6a, 6b. The user then closes the arms 4a, 4b so that the length of hair 40 is held between the first and second arms 4a, 4b and then the user pulls the hair through the closed arms (as illustrated in Figure 1b). The outer (hair contacting) surface of the heaters 6 is flat in this embodiment and so the hair styler 1 can be used to straighten the user’s hair. The hair styling device 1 shown in Figure 1 can also be used to curl the hair by turning the device 1 through approximately 180 degrees or more after clamping the hair between the arms 4a, 4b and before moving the device 1 along the tress of hair 40. Hair has a relatively high thermal mass and when in contact with the heating surface of the heater 6 the hair absorbs a significant amount of the heat energy. The heaters 6 must quickly supply the lost heat energy back to the heating surface otherwise the temperature of the heating surface will drop and potentially impact on the quality of the thermal styling. If the temperature of the heaters 6 fall below that required to raise the hair temperature above the glass transition temperature of the hair, the hair will not retain the styled shape. However, if the hair is heated to a temperature that is too high, the hair can undergo significant damage. Furthermore, different hair types require different amounts of heat energy for hair styling (because of different thickness, quality, condition, thermal mass of hair). Typically, fine straight hair requires less heat than thick curly hair for styling. Depending on the type of hair, the glass transition temperature of the hair when dry may be a temperature in the range of approximately 40°C-200°C. When the hair is moist ordamp, the glass transition temperature may be in the range of 0°C to 150°C. As such, the device 1 must be able to control the temperature so that the heating surface of the heaters 6 remains within a particular temperature range. Furthermore, it must maintain the temperature range both when hair is frequently and quickly loaded and unloaded onto the heating surface, and when hair is held on the heating surface for a prolonged period of time. Control Circuitry Figure 2 is a simplified block diagram of control circuitry 15 that controls the operation of the hair styler device 1 shown in Figure 1. As shown, the control circuitry 15 comprises a power supply 21 that, in this embodiment, derives power from a battery power source. A mains power supply input may be provided to charge the battery via an AC to DC converter (not shown), which may be external or internal to the device 1. Alternatively, the power supply 21 may derive power from an AC mains supply input. In this example, power is provided to the heaters 6 for heating the user’s hair. The power supplied to the heaters 6 is controlled by a controller 28 having a microprocessor 29. The power supplied to the heaters 6 is controlled by drive circuitry 23 (which may include one or more power semiconductor switching devices (triacs)) which controls the application of an AC mains voltage, ora DC voltage derived from the AC mains or from a battery, to the heaters 6 in accordance with instructions from the microprocessor 29. The microprocessor 29 is coupled to a memory 30 (which is typically a non-volatile memory) that stores processor control code for implementing one or more control methods that control the heating of the heaters 6 in accordance with a desired operating temperature of the heaters 6 and sensed temperatures of the heaters obtained from temperature measurement circuitry 25. The microprocessor 29 allows for complex control of the heaters 6. For example, the controller 28 may be configured to adjust the power delivered to the heaters by using an on / off triac based upon the output of the temperature measurement circuitry 25. The memory 30 may store a number of transfer functions such as: simple on-off control means or bang-bang control means; proportional-integral-derivative (PID) control means; fuzzy logic; feed back control means; feed forward control means. The controller 28 comprises means to measure the input voltage or alternatively to detect the speed at which the heaters 6 heat up, so as to detect the type of input voltage. A high input voltage would lead to a faster heat up of the heaters 6 and hence a control loop can react appropriately. The input voltage and / or speed of heat up can also be used to detect a failure. The controller 28 may comprise means to detect the use of the hair styling appliance and control the power supply to the heaters accordingly. This feature helps to reduce power consumption and improve safety. For example, the controller 28 may comprise means to reduce the temperature of the heaters when they are not active and then rapidly heat them up when they are about to be used. The controller 28 may allow a heater to power down to a standby temperature if a user momentarily places the hair styling appliance on a table, for example. The controller 28 may then power up the heater to an operating temperature when the hair styling appliance is picked up to be used. If the controller 28 detects that the hair styling appliance has not been used for a longer period of time, then the control means may shut down the hair styling appliance. This enables the hair styling appliance to meet the mandatory requirement of the safety standard that the appliance must turn off after 30 minutes whether it is being used or not. Detection of use may be achieved by detecting the opening and closing of the first movable arm relative to a second arm and / or detecting the opening and closing of the first movable arm relative to a second movable arm of the hair styling appliance, or through the use of one or more motion detection devices to detect the motion of the hair styling appliance or the use of a capacitive touch system. The one or more motion detection devices are shown in Figure 2 and referred to with numerical reference 31. The one or more motion detection devices 31 may comprise any one of an accelerometer, a gyrometer, a magnetometer, an inclination sensor. The controller is configured to determine amplitudes of movements of the apparatus, including angles, inclinations and rotations, based on sensor data from the motion detection devices 31. The hair styler 1 includes a grip sensor 32 to measure an open or closed position between movable arms of the apparatus and / or a pressure between the first movable arm 4a and the second movable arm 4b, e.g., when styling the hair. The hair styler 1 includes a hand sensor 34 configured to measure the placement of the hand of the user during the treatment. The hand sensor 34 comprises at least one of resistive and / or capacitive means to measure the placement of the hand of the user on an outside casework (of the moveable arms 4a and 4b) of the apparatus. The hair styler 1 includes a timer 35 configured to measure time elapsed while attempting to achieve the desired treatment. In Figure 2, the hair styler 1 includes an optional hair diagnostic sensor 33 configured to output data indicative of diagnostic information about the hair being styled or dried. The diagnostic information comprises at least one of: a level of moisture in the hair, a humidity ambient to the hair being styled or dried, a temperature ambient to the hair being styled or dried, a geographic location of the hair being styled or dried. The temperature measurement circuitry 25 may be temperature sensors such as thermistors or they may use circuitry that senses the resistance of heater electrodes that are used to heat the heaters 6, which resistance depends on the temperature of the heater electrode. Figure 2 also shows that the user interface 11 is coupled to the microprocessor 29, for example to provide one or more user controls, input and / or output indications such as a visual indication or an audible alert. Finally, the control circuitry includes communications circuitry 27 to allow the device to communicate with an external processing device, such as a remote sensor, a remote server, or a remote application (e.g., on a mobile telephone or smart watch). The communications circuitry 27 may use, for example, Bluetooth, Wi-Fi and / or 3GPP communication protocols to communicate with the external processing device. A user interface may be associated with the user on the external processing device, such that the user may input user input information. The hair styling appliance described in the present disclosure may further comprise means for providing a polyphonic sound. The means may provide a particular sound brand or jingle when switching on and / or off. The means may provide a sound to indicate particular events, such as reaching a desired operating temperature and / or sleep mode. The hair styling appliance described in the present disclosure may comprise lighting means. The lighting means may provide a pleasing aesthetic appearance as well as indicate temperature or other events. The lighting means may comprise an electroluminescent backlight as it enables wide angle, wide area viewing. Alternatively or additionally, the lighting means may comprise an LED lighting with a suitable lightpipe and / or optical diffuser. Heaters The heaters 6a, 6b are low thermal mass heaters and can therefore heat up and cool down quickly. Figures 3a and 3b show an exemplary embodiment of such heaters 6a, 6b, which comprise a stack of thin layers. Referring in particularto Figure 3a, the heaters 6a, 6b include an upper dielectric (electrically insulating) layer 62, an electrode layer 63 that has a plurality of separate heater electrodes 64, and a lower dielectric layer 66 which electrically insulates the heater electrodes 64 from other components mounted behind the heater 6a, 6b. The three layers 62, 63 and 66 are bonded together either through an adhesive layer (pressure set or thermoset) or through diffusion bonding of the contacting materials (e.g. melting them together) and define a heater 6 that is very thin (the three layers have an overall thickness of between 30pm to 1000pm in the case of low voltage operation (less than about 40 Volts) and 0.8mm to 2.0mm in the case of AC operation) and with very low thermal mass. The upper surface of the layer 62 provides the hair contacting surface of the heater 6, although a non-stick coating may be applied to the upper surface of the layer 62 to facilitate the passage of the user’s hair over the heating surface. The bonded layers 62, 63 and 66 define a flexible heater 6 and rigidity of the heater is provided in the illustrated embodiment by mounting the heater layers 62, 63 and 66 into a rigid support 68 which forms a base. These layers may be mounted onto the rigid support after the layers themselves have been bonded together or they may be bonded one at a time (or multiple at a time) onto the rigid support 68. If a flexible heater is desired, then there is no need for the rigid support 68 or if a support is used, this may be a non-rigid support. In the illustrated embodiment, there are ten heater electrodes 64 that each snake across and back across the width of the heater 6, folding twice such that they each cross the width three times. The ends of each of the heater electrodes 64 are electrically connected through the lower dielectric layer 66 to electrical connections within the rigid support 68, which connect to an electrical connector 70. Drive circuitry 23 that is mounted within one of the arms 4 connects to the heater electrodes 64 via the electrical connector 70 and applies electrical power to the individual heater electrodes 64 to control the heat generated by each heater electrode 64. The electrical connector 70 extends from a surface of the rigid support 68 facing away from the surface layer 62 (shown in Figures 3a and 3b as extending directly away from the upper layer 62, but it could also be provided as extending in a perpendicular direction). Each of the heater electrodes 64 thus creates an individual heating zone 642 on the hair contacting surface of the heater 6, which spans the width (which we shall refer to as the x-direction) of the heater 6 and the heater electrodes 64 are arranged sequentially one after the other along the length (the y-direction) of the heater 6. Figures 4a and 4b show schematic views of different arrangements of such heating zones 642. Figure 4a shows an arrangement corresponding to that of Figures 3a and 3b, in which the heating zones 642-1 to 642-10 are arranged along the y-direction only. Figure 4b shows an alternative arrangement, in which heating zones 642-1 to 642-16 are arranged in both the x- and y-directions. Such an arrangement of heating zones 642 can be provided by arranging two sets of heater electrodes 64 like those shown in Figure 3a side by side in the width, x-direction. The heaters 6 may be separated in this way into any number of heating zones 642 and may comprise any number of heating zones along the x- and y-directions. In particular, whilst Figure 4b shows two zones along the x-direction, a greater number of zones in the x-direction could also be provided. The heating zones 642 of the heaters 6a, 6b can be operated (heated) independently, which can help to reduce hot / cold spots when using very low thermal mass heaters 6 such as those shown in Figure 3. The heating zones illustrated in Figure 4 are all the same size. Of course, different sized heating zones 642 may be provided, as illustrated in Figure 5, which shows a heater 6 having seven different sized heating zones (labelled Z1 to Z7). The way in which the heater electrodes 64 would be arranged to define these different sized zones would be understood by the skilled reader and will not be described in detail here. The heating zones 642 described above form part of a heater having a flat hair contacting surface. The heater is not limited to flat hair contacting surfaces and can be configured for use a tubular form (as illustrated in Figure 6a) for example for use in a hair curler device or in a curved form (as illustrated in Figure 6b) for example for use in a heated hair brush. The heater surface may have a corrugated or ribbed shape to provide a hair crimping device. The temperature of each heating zone 642 is independently controllable. Each heating zone 642 can be set to a target temperature. The target temperature of each heating zone 642 may be different. A separate temperature sensor may be provided for sensing the temperature of each heating zone 642 which is fed back to the microprocessor 29 to allow the microprocessor 29 to control the delivery of power to the heater electrode 64 of the corresponding heating zone 642. Alternatively, if the heater electrodes 64 are formed of a material having a Positive Temperature Coefficient (PTC) ora Negative Temperature Coefficient (NTC) (such that its resistance varies with its temperature), then the temperature of each heating zone 642 can be determined by determining the resistance of the corresponding heater electrode 64. The microcontroller 28 controls the heating in order to reduce the difference between the actual temperature of the heating zone 642 and the target temperature for that heating zone 642. Heating Zone Sizing When the user loads a tress of hair 40 onto the heaters 6, some parts of the heater will be loaded with hair whilst other parts will not be loaded with hair. Upon loading with hair, and using the already described temperature measurement circuitry 25, more power is supplied to the heater 6 to ensure that all regions on the hair contacting surface can be retained within and / or recovered back to the desired operating temperature limits. Figure 7 shows a tress of hair 40 overlying heating zones Z2, Z3 and Z4, with heating zone Z3 being fully loaded with hair whilst heating zones Z2 and Z4 being only partially loaded with hair. The Figure 7 extent of the heating zones gives the microcontroller 28 an indication of the size of the tress of hair 40 introduced between the arms of the styling appliance. In the present disclosure, the size of the tress of hair can refer to a volume of hair, a number of hair fibres, a surface area of hair, or any combinations of the previous, such as a hair density. The size of the tress of hair 40 gives an indication of the amount of hair introduced between the arms of the styling appliance. Additionally or alternatively, the styler may comprise sensing means to determine the amount of hair introduced in the styling apparatus. The sensing means may include capacitive sensing means to detect the amount of hair between the heaters. Operation based on different input streams of data Figure 8 shows a flow chart illustrating an example method 100 of operation of the apparatus, according to the disclosure. In the method 100, the apparatus is manipulable by a user to perform a desired treatment on the hair of the user. In the method 100 of Figure 8, at S1, sensors already described in the present disclosure sense and output sensor data indicative of operational parameters on how the apparatus is operated by the user during the treatment. At S2, the microcontroller 28 processes the sensor data to predict the desired treatment which the user is trying to achieve and / or processes the sensor data to calculate a frustration score, the frustration score being indicative of a level of frustration of the user while attempting to achieve the desired treatment. At S3, the microcontroller 28 individually controls the temperature or the power output of the one or more heating zones of the plurality of individually controllable heating zones, based on the predicted desired treatment and / or on the calculated frustration score, to help the user to achieve the desired treatment and to avoid the hair being burnt. In the present disclosure, the desired “treatment” or “style” refers to a general, high-level type of hair styling, such as at least one of: curling, straightening, crimping or brushing. In a first example of the method 100 of Figure 8, at S1, the one or more motion sensors 31 sense and output sensor data and the grip sensor 32 senses and outputs sensor data. When the appliance is used for styling, the user performs specific movements and / or the user holds the appliance at certain angles, with the appliance having its moveable arms 4a and 4b in a closed position, depending on the style they are trying to achieve. Different styles require different movements, movement speeds, and angles, with the appliance having its moveable arms 4a and 4b in a closed position. In the first example, the microcontroller 28 uses the sensor data from the motion sensors 31 and the grip sensor 32 to predict the attempted style (i.e., is the user trying to curl, straighten, crimp, etc.). At S2, the controller 28 processes the sensor data from the sensors 31 and the sensor 32 to predict the desired treatment which the user is trying to achieve. Additionally, optionally, in some further examples of the method 100 of Figure 8, at S1, the hand sensor 34 also senses and outputs sensor data. When the appliance is used for styling, the user places their hand at specific points depending on the style they are trying to achieve. Different styles require different hand placement. The controller, at S2, further processes the sensor data from the hand sensor 34 to predict the desired treatment which the user is trying to achieve, giving a better indication of the style being attempted. Additionally, optionally, in some further examples of the method 100 of Figure 8, at S2, the controller is further configured to predict the desired treatment which the user is trying to achieve based on time data, such as time of day (e.g., the user curls their hair in the morning and straightens their hair in the evening), day of the week (e.g., the user curls their hair on Saturdays), historical data from previous styling sessions. Additionally, optionally, in some further examples of the method 100 of Figure 8, at S2, the controller is further configured to predict the desired treatment which the user is trying to achieve based on hair type data (this can be input by the user on the user interface 11). In some examples, as already stated, the user interface 11 allows the user to specify the desired treatment to be performed on their hair. In such examples, at S2, the controller 28 is further configured to predict the desired treatment which the user is trying to achieve based on the desired treatment specified by the user. Additionally or alternatively, as already stated, the styler may be configured to receive user input information, such as information about the desired treatment, from the external processing device, and the controller may further be configured to predict the desired treatment which the user is trying to achieve based on such received user input information about the desired treatment. In all of the cases disclosed above, after the style is predicted at S2, the controller 28 controls at S3 the heater (e.g., a heater plate, as explained in greater detail below, or the individually controllable heating zones already described) to help the user to promote their hair health (such as by avoiding the hair being burnt) and / or to help the user to more accurately achieve the desired style. In some examples, the controller is configured to control a temperature or a power output of the one or more heating zones by capping an increase in the temperature or the power output of the one or more heating zones of the plurality of controllable heating zones, based on the predicted desired treatment score, to avoid the hair to be burnt. Additionally or alternatively, the controller is configured to control a temperature or a power output of the one or more heating zones by setting a target temperature or power output of the one or more heating zones of the plurality of controllable heating zones which are engaged with the hair, based on the predicted desired treatment, to help the user to achieve the desired treatment. The controller is for instance configured to control the target temperature or the power output of the one or more heating zones of the plurality of controllable heating zones so as to enable a better drying or styling of the hair which is loaded in the apparatus. For example, the controller 28 may determine at S2 that the styler moves slower and then may determine that the desired treatment is “curling”. At S3, the controller 23 may lower the amount of heat injected into the hair, while curling, to help preserve hair health and / or achieve a shinier, longer lasting styler. Additionally or alternatively to the first example described above, in a second example of the method 100 of Figure 8, at S1, the timer 35 measures and outputs data about the time elapsed while the user is attempting to achieve the desired treatment, such as the curling, straightening, crimping or brushing of the hair. At S2, the controller 28 processes the sensor data from the timer 35 to calculate the frustration score from the measured time elapsed while attempting to achieve the desired treatment, as the time spent by the user while trying to style their hair is indicative of how frustrated the user may be. For example, the longer the time, the more frustrated the user. As a non-limiting example, the frustration score may be a real number, e.g., between 0 and 1, wherein a score of 0 is indicative of the user being “very happy” and a score of 1 is indicative of the user being “very frustrated” (or vice versa). Additionally, optionally, in some further examples of the method 100 of Figure 8, atS1, the grip sensor 32 senses and outputs data indicative of the measured pressure between movable arms of the apparatus. At S2, the controller is further configured to process the data from the grip sensor 32 and to calculate the frustration score based on the processed data from the grip sensor. The pressure applied to the moveable arms 4a and 4b may be indicative of the frustration of the user while trying to style their hair. For example, the tighter the grip on the hair, the more frustrated the user. As explained below, other behaviours may be indicative of frustration. Additionally, optionally, in some further examples of the method 100 of Figure 8, at S1, the motion sensors 31 sense and output data indicative of speed of the determined movements of the apparatus. At S2, the controller 28 is further configured to process the data from the motion sensors 31 and to calculate the frustration score based on the processed data from the motion sensors 31. For example, rapid movements on the hair are indicative of frustration. Behaviours showing frustration and associated with the speed may include rapid rotations, rapid passes on one tress of hair, rapid shaking of the styler, the styler is still and / or stationary during a prolonged duration (i.e., total absence of speed in that latter case). Additionally, optionally, in some further examples of the method 100 of Figure 8, at S2, the controller is further configured to calculate the frustration score based on data about power output of the apparatus. For example, the greater the power output, the greater the frustration. As already stated, the controller 28 comprises means to measure the power demand. In a preferred example, the microcontroller 28 determines a power demand of the apparatus, based on a temperature of the plurality of independently controllable heating zones or based on the power output needed to maintain each heating zone of the plurality of heating zones at a target temperature. Other optional inputs can include data about the desired treatment, as the greater the divergence from the expected style, the greater the frustration. In all of the cases disclosed above, after the frustration score is calculated at S2, the controller 28 controls at S3 the heater (e.g., a heater plate, as explained in greater detail below, or the individually controllable heating zones already described) to help the user to promote their hair health (such as by avoiding the hair being burnt) and / or to help the user to more accurately achieve the desired style. In some examples, the controller is configured to control a temperature or a power output of the one or more heating zones by capping an increase in the temperature or the power output of the one or more heating zones of the plurality of controllable heating zones, based on the calculated frustration score, to avoid the hair to be burnt, as a frustrated user is more likely to bum their hair. Additionally or alternatively, the controller is configured to control a temperature or a power output of the one or more heating zones by setting a target temperature or power output of the one or more heating zones of the plurality of controllable heating zones which are engaged with the hair, based on the calculated frustration score, to help the user to achieve the desired treatment, as a frustrated user is less likely to perform a desired styling. The controller is for instance configured to control the target temperature or the power output of the one or more heating zones of the plurality of controllable heating zones so as to enable a better drying or styling of the hair which is loaded in the apparatus. The step S2 of method 100 may further comprise a step where the controller 28 determines whether the calculated frustration score is greater than a threshold value. The threshold value may correspond to a critical frustration, for example 0.5 if the score is between 0 and 1. If it is determined at S2 that the calculated frustration score is greater than a threshold value, then the controller is configured to control the apparatus so that in S3, the apparatus: outputs one or more feedback messages for the user to lower the user’s frustration, and / or inhibits the output of feedback messages which are likely to increase the user’s frustration. The feedback messages are output on the user interface 11 already described. The feedback messages may comprise visual messages and / or audible messages. The one or more feedback messages to lower the user’s frustration may comprise instructions to help the user to achieve the desired treatment (such as “slow down” or “rotate style r” as non-limiting examples) and / or written message of encouragement and / or a calming music, as non-limiting examples). Inhibiting the output of feedback messages which are likely to increase the user’s frustration may comprise inhibiting the output of messages irrelevant to and / or out-of-synchrony with the treatment (such as “are you happy with your treatment?” when the frustration score is greater than the threshold value, for instant), as non-limiting examples. Alternatively or additionally, if it is determined at S2 that the calculated frustration score is greater than a threshold value, then the controller may be configured to control a target temperature or power output of the one or more heating zones of the plurality of controllable heating zones which are engaged with the hair, to help the user to achieve the desired treatment and / or to avoid the hair being burnt, as already described. In another example embodiment, the sensors of the apparatus are for sensing and outputting sensor data indicative of operational parameters on how the apparatus is operated by the user during the treatment. In this embodiment, the sensor data includes data indicative of a time elapsed while attempting to achieve the desired treatment and / or data indicative of a pressure between movable arms of the apparatus. In this embodiment, the controller is configured to process the sensor data to calculate a frustration score based on the time elapsed while attempting to achieve the desired treatment and / or the pressure between movable arms of the apparatus. In this embodiment, the controller is configured to individually control the temperature or the power output of the one ormore heating zones of the plurality of individually controllable heating zones, based on the calculated frustration score, to help the user to achieve the desired treatment and to avoid the hair being burnt. Alternatively or additionally, in this embodiment, the controller is configured to output one or more feedback messages for the user to lower the user’s frustration, and / or inhibit the output of feedback messages which are likely to increase the user’s frustration, based on the calculated frustration score, as already described. In the examples described above, the controller is configured to predict the desired treatment and / or to calculate the frustration score based on a set of deterministic rules. As described above, for the prediction of the desired treatment, the set of deterministic rules may be mainly based on data from the one or more motion sensors 31 and the grip sensor 32, optionally based on data from the hand sensor, time data and / or hair type data. As described above, for the calculation of the frustration score, the set of deterministic rules may be mainly based on data from the timer 35 and / or the grip sensor 32, as a longer time spent styling is likely to frustrate the user and / or a tighter grip on the hair is indicative of frustration. A combination of the data may be beneficial in the calculation, as a slow increase of the grip is not necessarily indicative of frustration, whereas a rapid increase in the grip is more likely an indication of the frustration of the user. Optionally the set of deterministic rules, as already explained, may be based on data from the motion sensors 31, about power output or the desired style. Alternatively or additionally, the controller is configured to predict the desired treatment and / or to calculate the frustration score based data for a trained artificial intelligence algorithm stored in a memory of the apparatus. As described in more detail below, the artificial intelligence algorithm may comprise a trained convolutional neural network and / or modular neural network and / or random forest and / or K-Nearest Neighbours. Generating the trained machine learning algorithm Figure 9 shows a flow chart illustrating an example method 200 according to the disclosure. The method 200 is for generating a trained machine learning algorithm. In one example, the trained algorithm is a trained frustration calculator configured to calculate a frustration score, the frustration score being indicative of a level of frustration of a user while attempting to achieve a desired treatment. In another example, the trained algorithm is a trained desired treatment predictor configured to predict a desired treatment which a user is trying to achieve. In Figure 9, the method 200 comprises: obtaining, at S21, a plurality of annotated training streams of data; and training, at S22, the algorithm by applying the algorithm to the obtained training streams of data. The learning process is typically computationally intensive and may involve large volumes of training data. As explained in more detail below, the machine learning step S22 involves inferring the frustration score or the desired treatment, based on the training data, and encoding the determined frustration score or the desired treatment in the form of the trained algorithm. The training data are annotated. In other words, during the training and in the streams of data, the state of frustration of the user or the desired treatment are known. As such, in the method 200 of Figure 9, in the one example, the annotation indicates a level of frustration of the user, associated with each training stream of data. In the other example, the annotation indicates a desired treatment which a user is trying to achieve, associated with each training stream of data. A domain specialist may manually annotate the streams of data with ground truth annotation corresponding to the level of frustration or the desired treatment, during the training. In the method 200 of Figure 9, in the one example, for a plurality of different levels of frustration, the plurality of annotated training streams of data comprise: a training stream of data corresponding to a time elapsed while attempting to achieve the desired treatment and / or a training stream of data corresponding to a pressure between movable arms of the apparatus. For example, the machine learning algorithm may learn that a longer time spent styling frustrates the user and / or a tighter grip on the hair is indicative of frustration. A combination of the data may be beneficial in the calculation, as the machine learning can learn that a slow increase of the grip is not necessarily indicative of frustration, whereas a rapid increase in the grip is more likely an indication of the frustration of the user. In the method 200 of Figure 9, in the other example, for a plurality of desired treatments (such as such as at least one of curling, straightening, crimping or brushing), the plurality of annotated training streams of data comprise: a training stream of data corresponding to motion sensors indicative of amplitudes of movements of the apparatus, and a training stream of data corresponding to a grip sensor indicative of an open or closed position between movable arms of the apparatus. For example, the machine learning algorithm may learn that, for each treatment, the user performs specific movements and / or the user holds the appliance at certain angles, with the appliance having its moveable arms 4a and 4b in a closed position, depending on the style they are trying to achieve. Training at S22 the machine learning algorithm comprises training the machine learning algorithm to minimise a loss between the annotation associated with each training stream of data and a prediction (of a level of frustration of the user or a desired treatment) by the machine learning algorithm. The loss may be a similarity metric of Lp-norm, p being an integer greater or equal to 1, such as an average absolute deviation or a least mean square distance from the prediction (of the level of frustration of the user or the desired treatment) as determined by the machine learning algorithm during the training to the known annotation (the known level of frustration or the known desired treatment). Other ways of calculating the loss are envisaged. Referring back to Figure 9, the trained algorithm is built by its application to the training data. Any suitable machine learning algorithm may be used. For example, approaches based on a convolutional neural network and / or modular neural network and / or random forest and / or K-Nearest Neighbours may be used. As explained above, the trained frustration calculator is primarily trained to calculate the frustration score based on data corresponding to the time elapsed while attempting to achieve the desired treatment and / or data corresponding to the pressure between the movable arms of the apparatus. However, additional, optional training streams of data may be fed to the frustration calculator during training, such as: a training stream of data indicative of speed of the determined movements of the apparatus; and / or a stream of data indicative of the desired treatment. Figure 10 shows a non-limiting example architecture of a frustration calculator according to the disclosure. The frustration calculator of Figure 10 is generated based on the training data obtained atS21. In Figure 10, the training streams of data comprise: a training stream of data corresponding to a time elapsed while attempting to achieve the desired treatment (stream “Time Styling”), a training stream of data corresponding to a pressure between movable arms of the apparatus (stream “Grip Pressure’}, a training stream of data indicative of speed of the determined movements of the apparatus (stream “User Speed”), a stream of data indicative of the desired treatment (stream “Predicted Style”). The stream “Predicted Style” may correspond to an actual prediction by the treatment predictor already described and / or correspond to an input by the user on the user interface, as the machine learning algorithm learns that when the styling result does not correspond to the expected result, the discrepancy generates user’s frustration. In the non-limiting example of Figure 10, the example frustration calculator comprises one or more layers: an appliance input layer 101, such that the input layer 101 e R4, each dimension of the appliance input layer 101 corresponding to a training stream of data; a hidden layer 102, such that the hidden layer 102 g R3; and an output layer 103 such that the output layer 104 g R1, the dimension of the output layer 103 corresponding to the calculated frustration score. Other configurations with other layers may also be envisaged, and other architectures are also envisaged for the machine learning algorithm. For example, deeper architectures may be envisaged and / or an architecture of the same shape as the architecture described above that would generate an output layer 103 with sizes different from those already discussed may be envisaged. For example, as explained above, the trained desired treatment predictor is primarily trained to predict the treatment based on data corresponding to amplitudes of movements of the apparatus and data corresponding to an open or closed position between movable arms of the apparatus. However, additional, optional training streams of data may be fed to the desired treatment predictor during training, such as: a training streams of data from the hand sensor, time data and / or hair type data. It should be understood that an appliance may have both a trained frustration calculator and a trained treatment predictor. Computer system and hairstyling appliance A computer system (not shown in the Figures) may execute the deep learning algorithm to generate the trained algorithm to be stored on the memory 30 of the hair styling appliance. The computer system may communicate and interact with multiple such hair styling appliances. The computer system may conventionally comprise a memory, a processor and a communications interface. The computer system may be configured to communicate with one or more hairstyling appliances, via the communications interface and a link (e.g. Wi-Fi connectivity, but other types of connectivity may be envisaged). The memory of the computer system is configured to store data, for example for use by the processor. In some examples the data stored on the memory may comprise the training data and / or the deep learning algorithm. In some examples, the training data may correspond to actual observed data streams on the hair styling appliance, or the training data may be generated, for example in a laboratory. The training may be performed at the computer system separate, optionally remote, from hair styling appliance. However, if sufficient processing power is available locally then the deep learning could be performed (at least partly) by the microprocessor 29 of the hairstyling appliance. The trained algorithm is arranged to produce the calculation of the frustration score and / or the prediction of the treatment more easily, after it is stored in the memory 30 of the hair styling appliance, even though the process 200 for generating the trained algorithm from the training data may be computationally intensive. After it is configured, the hair styling appliance may provide calculation of a frustration score and / or prediction of a desired treatment, by applying the learned algorithm during use of the hair styling appliance, using the same input data streams as during the training. Hairstyling appliance manufacture As illustrated in Figure 11, a method 300 of producing a hair styling appliance configured to calculate a frustration score and / or predict a desired treatment comprises: obtaining, at S31, a trained algorithm generated by the method 200 according to any aspects of the disclosure; and storing, at S32, the obtained classifier in the memory 30 of the hair styling appliance. The trained algorithm may be generated and stored using any suitable representation, for example as a data description comprising data elements specifying calculation and / or prediction conditions and their outputs. Such a data description could be encoded e.g. using XML or using a bespoke binary representation. The data description is then interpreted by the microprocessor 29 running on the appliance when applying the trained algorithm. Alternatively, the deep learning algorithm may generate the calculator and / or the predictor directly as executable code (e.g. machine code, virtual machine byte code or interpretable script). This may be in the form of a code routine that the appliance can invoke to apply the calculator and / or the predictor. The appliance may be connected temporarily to the computer system to transfer the generated calculator and / or predictor (e.g. as a data file or executable code) or transfer may occur using a storage medium (e.g. memory card). In a preferred approach, the calculator and / or the predictor is transferred to the appliance from the computer system over the communications link (this could include transmission over the Internet from a central location of the computer system to a local network where the appliance is located using the communications circuitry 27, e.g., via a mobile phone connected to the appliance via the Bluetooth, Wi-Fi and / or 3GPP communication protocols). Thanks to the communications circuitry 27, the calculator and / or the predictor could be installed as part of a firmware update of device software, or independently. Installation of the calculator and / or the predictor may be performed once (e.g. at time of manufacture or installation) or repeatedly (e.g. as a regular update). The latter approach can allow the calculator and / or the predictor performance of the calculator and / or the predictor to be improved overtime, as new training data become available. Modifications and alternatives Detailed embodiments and some possible alternatives have been described above. As those skilled in the art will appreciate, a number of modifications and further alternatives can be made to the above embodiments whilst still benefiting from the inventions embodied therein. It will therefore be understood that the invention is not limited to the described embodiments and encompasses modifications apparent to those skilled in the art lying within the scope of the claims appended hereto. The invention has been described above by way of implementation in a hair styling device for straightening hair (‘hair straighteners’) which employ flat hair styling heaters 6. However, it could alternatively be implemented in any form of hair styling device, such as (but not limited to) crimpers, curlers or heated brushes. The heaters 6 may define a heating surface that is flat, curved, ridged or in the shape of a barrel. The hair styling device may have two arms, for example like the device illustrated in Figure 1, or it may be a single armed device. For example, the device may be a device with a first arm and a second moveable arm arranged to be moveable relative to the first arm between an open configuration and a closed configuration. Such a device may comprise first and second heaters opposing one another at the distal ends of the two arms, as previously described, that are brought together as the second moveable arm is moved towards the first arm from an open configuration to a closed configuration. During use, a tress of hair is sandwiched between the two arms so that the user’s hair is in contact with, and therefore heated by, outer heating surfaces of the heaters.. Pressure between the two arms may be indicative of the user’s frustration as described above. In some arrangements, pressure sensors in a handle and / or a head of the device may be used to determine a frustration score, for example by sensing how tightly the user is gripping the handle and / or how tightly the user is wrapping the hair around the head. For example, another embodiment would be to place a pressure sensor in the handle of a single armed device, such as a curling wand; the user will grip the device harder as they become more frustrated. Another example is to place a pressure sensor in the head of a single armed device, such as a curling wand; the user wraps their hair around the head of the device and pulls it taut. The tighter the wrap, the more frustration the user is feeling. The heaters described above may also be used in hair dryers or in combination devices that use conductive heating and air to dry and style the user’s hair (such as those described in the applicant’s earlier PCT application WO 2021 / 019239). In embodiments where air is used, the heaters 6 may be perforated so that air passes through the heater and is warmed by the heater as the air passes through. In the above embodiments, Metal Oxide Semiconductor Field Effect Transistor (MOSFET) switches were used to control powering and sensing of the heater electrodes. As those skilled in the art will appreciate, other switches could be used instead. For example, Field Effect Transistors (FETs) could be used, such as Gallium Nitride FETs or bipolar junction transistors (BJTs). In the above embodiments, a DC power source was used to provide electrical power for heating the heater electrodes 64. This DC power source will typically be one or more batteries, although DC supplies that derive their power from a mains power AC signal may be used. Thicker or more dielectric layers are typically used between the heater electrodes 64 and the hair contacting surface of the hair styler when AC power is used to heat the heaters. In the above-described examples the hair styling device 1 may comprise a single heater 6, or may alternatively comprise two or more heaters 6. The heater may not comprise a plurality of independently controllable heater electrodes that define a plurality of independently controllable heating zones of the hair contacting surface, but the heater may have a single heating zone or one or more heating zones which are not independently controllable. Throughout the description and claims of this specification, the words “comprise” and “contain” and variations of the words, for example “comprising” and “containing”, means “including but not limited to”, and is not intended to (and does not) exclude other components, integers or steps. The expressions “to dry hair”, “drying hair” or “decrease a moisture level of hair” and the like, as used in the present disclosure, can refer both to the removal of “unbound” water that exists on the outside of hair when wet, or the removal of “bound” water, which exists inside individual hairs, and which can be interacted with when heat styling hair. The “bound” water need not necessarily be removed when drying hair, although removal of some bound water may occur during a drying or styling process. Various other modifications will be apparent to those skilled in the art and will not be described in further detail here.

Claims

1. Apparatus for drying and / or styling hair, the apparatus being manipulable by a user to perform a desired treatment on the hair of the user, the apparatus comprising: sensors for sensing and outputting sensor data indicative of operational parameters on how the apparatus is operated by the user during the treatment;a heater for heating hair of a user, the heater comprising a plurality of independently controllable heater electrodes that define a plurality of independently controllable heating zones; anda controller configured to:process the sensor data to predict the desired treatment which the user is trying to achieve; and / orprocess the sensor data to calculate a frustration score, the frustration score being indicative of a level of frustration of the user while attempting to achieve the desired treatment;individually control the temperature or the power output of the one or more heating zones of the plurality of individually controllable heating zones, based on the predicted desired treatment and / or on the calculated frustration score, to help the user to achieve the desired treatment and / or to avoid the hair being burnt.

2. The apparatus of claim 1, further comprising:a user interface for allowing the user to specify the desired treatment to be performed on their hair,the controller being further configured to predict the desired treatment which the user is trying to achieve based on the desired treatment specified by the user.

3. The apparatus of claim 1 or claim 2, wherein the apparatus further comprises communication circuitry such that the apparatus is configured to receive user input information about the desired treatment from an external processing device, andwherein the user input information is input on a user interface which is associated with the user on the external processing device,the controller being further configured to predict the desired treatment which the user is trying to achieve based on the user input information about the desired treatment.

4. The apparatus of claim 3, wherein the external processing device is part of a mobile phone or a smart watch and is configured to run an application, remote from the apparatus.

5. The apparatus of any of claims 1 to 4, wherein the sensors comprise at least one of: one or more motion sensors for sensing and outputting sensor data indicative of how the apparatus is being moved by the user; and / ora grip sensor configured to measure a pressure between arms of the apparatus and / or a pressure in a handle and / or a head of the apparatus, and / or configured to detect an open or closed configuration of arms of the apparatus; and / ora hand sensor configured to measure the placement of the hand of the user during the treatment, and / ora timer configured to measure time elapsed while the user is attempting to achieve the desired treatment.

6. The apparatus of claim 5, wherein the one or more motion sensors of the apparatus comprise any one or more of an accelerometer, a gyrometer, a magnetometer, an inclination sensor, the controller being configured to determine amplitudes of movements of the apparatus, including angles, inclinations and rotations, andwherein the controller is configured to process the sensor data from the one or more motion sensors and the grip sensor to predict the desired treatment which the user is trying to achieve.

7. The apparatus of claim 5 or claim 6, wherein the hand sensor comprises at least one of resistive and / or capacitive means to measure the placement of the hand of the user on the apparatus, andwherein the controller is further configured to process the sensor data from the hand sensor to predict the desired treatment which the user is trying to achieve.

8. The apparatus of any of the previous claims, wherein the controller is further configured to predict the desired treatment which the user is trying to achieve based on at least one of:time data, such as time of day, day of the week, historical data from previous styling sessions, and / orhair type data.

9. The apparatus of any of claims 5 to 8, wherein the controller is configured to process the sensor data from the timer to calculate the frustration score from the measured time elapsed while attempting to achieve the desired treatment.

10. The apparatus of claim 9, wherein the controller is further configured to calculate the frustration score based on any one or more of:data indicative of the measured pressure between arms of the apparatus and / or pressure in a handle and / or a head of the apparatus; and / ordata indicative of speed of the determined movements of the apparatus; and / or data about the desired treatment.

11. The apparatus of any of the previous claims, wherein the controller is further configured to calculate the frustration score based on data about power output of the apparatus, and / orwherein the controller is further configured to retain historical user data and to use the retained historical data to form an expected or baseline behaviour from the user, the controller being configured to calculate the frustration score based on a deviation from the expected or baseline behaviour.

12. The apparatus of any of claims 1 to 11, wherein the controller is configured to predict the desired treatment and / or to calculate the frustration score based on:a set of deterministic rules, optionally, for the frustration score, using sensor data including data indicative of a time elapsed while attempting to achieve the desired treatment and / or data indicative of a pressure between arms of the apparatus and / or a pressure in a handle and / or a head of the apparatus; and / ordata for a trained artificial intelligence algorithm stored in a memory of the apparatus, optionally wherein the artificial intelligence algorithm comprises a trained convolutional neural network and / or modular neural network and / or random forest and / or K-Nearest Neighbours.

13. The apparatus of any of claims 1 to 12, wherein the controller is configured to control a temperature or a power output of the one or more heating zones by:capping an increase in the temperature or the power output of the one or more heating zones of the plurality of controllable heating zones, based on the predicted desired treatment and / or on the calculated frustration score, to avoid the hair to be burnt.

14. The apparatus according to any of claims 1 to 13, wherein the controller is configured to control a temperature or a power output of the one or more heating zones by:setting a target temperature or power output of the one or more heating zones of the plurality of controllable heating zones which are engaged with the hair, based on the predicted desired treatment and / or on the calculated frustration score, to help the user to achieve the desired treatment.

15. The apparatus according to any preceding claim, wherein the controller is configured to:determine whether the calculated frustration score is greater than a threshold value, and if it is, to:output one or more feedback messages for the user to lower the user’s frustration, and / orinhibit the output of feedback messages which are likely to increase the user’s frustration, and / orcontrol a target temperature or power output of the one or more heating zones of the plurality of controllable heating zones which are engaged with the hair, to help the user to achieve the desired treatment and / or to avoid the hair being burnt.

16. The apparatus according to claim 14 or claim 15, wherein the controller is configured to control the target temperature or the power output of the one or more heating zones of the plurality of controllable heating zones so as to enable a better drying or styling of the hair which is loaded in the apparatus.

17. The apparatus according to any preceding claim, wherein the apparatus is a hair straightener, a hair dryer, a hot paddle brush, a hot round brush, a heater roller, or a hair curler, optionally wherein the heater comprises a hair contacting surface, for heating the hair contacting the hair contacting surface by conduction; orwherein the frustration score is a real number between 0 and 1, optionally wherein a score of 0 is indicative of the user being “very happy” and a score of 1 is indicative of the user being “very frustrated”.

18. Apparatus for drying and / or styling hair, the apparatus being manipulable by a user to perform a desired treatment on the hair of the user, the apparatus comprising:sensors for sensing and outputting sensor data indicative of operational parameters on how the apparatus is operated by the user during the treatment, the sensor data including data indicative of a time elapsed while attempting to achieve the desired treatment and / or data indicative of a pressure between arms of the apparatus and / or a pressure in a handle and / or a head of the apparatus;a heater for heating hair of a user, the heater comprising a plurality of independently controllable heater electrodes that define a plurality of independently controllable heating zones; anda controller configured to:process the sensor data to calculate a frustration score based on the time elapsed while attempting to achieve the desired treatment and / or the pressure between arms of the apparatus and / or the pressure in a handle and / or a head of the apparatus, the frustration score being indicative of a level of frustration of the user while attempting to achieve the desired treatment;individually control the temperature or the power output of the one or more heating zones of the plurality of individually controllable heating zones, based on the calculated frustration score, to help the user to achieve the desired treatment and to avoid the hair being burnt; and / oroutput one or more feedback messages for the user to lower the user’s frustration, and / or inhibit the output of feedback messages which are likely to increase the user’s frustration, based on the calculated frustration score.

19. The apparatus of claim 18, wherein individually controlling the temperature or the power output of the one or more heating zones of the plurality of individually controllable heating zones comprises at least one of:capping an increase in the temperature or the power output of the one or more heating zones of the plurality of controllable heating zones, based on the calculated frustration score, to avoid the hair to be burnt; and / orsetting a target temperature or power output of the one or more heating zones of the plurality of controllable heating zones which are engaged with the hair, based on the calculated frustration score, to help the user to achieve the desired treatment, and / or wherein the heater comprises a hair contacting surface, for heating the hair contacting the hair contacting surface by conduction.

20. The apparatus of claim 18 or claim 19, wherein the controller is configured to calculate the frustration score based on:a set of deterministic rules; and / ordata for a trained artificial intelligence algorithm stored in a memory of the apparatus, optionally wherein the artificial intelligence algorithm comprises a trained convolutional neural network and / or modular neural network and / or random forest and / or K-Nearest Neighbours.

21. A method for generating a trained frustration calculator configured to calculate a frustration score, the frustration score being indicative of a level of frustration of a user while attempting to achieve a desired treatment, the method comprising:obtaining a plurality of annotated training streams of data; andtraining the frustration calculator by applying a machine learning algorithm to the obtained training streams of data,wherein the annotation indicates a level of frustration of the user, associated with each training stream of data, andwherein the plurality of annotated training streams of data comprise a training stream of data corresponding to a time elapsed while attempting to achieve the desired treatment and / or a training stream of data corresponding to a pressure between arms of the apparatus and / or a pressure in a handle and / or a head of the apparatus, for a plurality of levels of frustration.

22. A method for generating a trained desired treatment predictor configured to predict a desired treatment which a user is trying to achieve, the method comprising:obtaining a plurality of annotated training streams of data; andtraining the desired treatment predictor by applying a machine learning algorithm to the obtained training streams of data,wherein the annotation indicates a desired treatment which a user is trying to achieve, associated with each training stream of data, andwherein, for a plurality of desired treatments, the plurality of annotated training streams of data comprise:a training stream of data corresponding to motion sensors indicative of amplitudes of movements of the apparatus, anda training stream of data corresponding to a grip sensor indicative of a pressure between arms of the apparatus and / or a pressure in a handle and / or a head of the apparatus and / or indicative of an open or closed configuration between arms of the apparatus.

23. The method according to claim 21 or claim 22, wherein the machine learning algorithm is trained to minimize a loss between the annotation associated with each training stream of data and a determination by the machine learning algorithm.

24. The method of any of claims 21 to 23, wherein the machine learning algorithm comprises a convolutional neural network and / or modular neural network and / or random forest and / or K-Nearest Neighbours.

25. A method of producing apparatus for drying and / or styling hair, wherein the apparatus comprises a heater for heating hair of a user, the heater comprising a plurality of independently controllable heater electrodes that define a plurality of independently controllable heating zones, a memory and a controller coupled to the memory, the method comprising:obtaining a trained machine learning algorithm generated by the method according to any one of claims 21 to 24; andstoring the obtained trained machine learning algorithm in the memory of the apparatus.

26. The method of claim 25, wherein the storing comprises transmitting the generated trained machine algorithm to the apparatus via a network, the apparatus receiving and storing the trained machine learning algorithm.

27. The method of claim 26, wherein the trained machine learning algorithm is generated, stored and / or transmitted in the form of one or more of: a data representation of the trained machine learning algorithm; executable code for applying the trained machine learning algorithm, and / orwherein heater comprise a hair contacting surface, for heating the hair contacting the hair contacting surface by conduction.

28. Apparatus for drying and / or styling hair, the apparatus being manipulable by a user to perform a desired treatment on the hair of the user, the apparatus comprising:sensors for sensing and outputting sensor data indicative of operational parameters on how the apparatus is operated by the user during the treatment, the sensor data including data indicative of a time elapsed while attempting to achieve the desired treatment and / or data indicative of a pressure between arms of the apparatus and / or a pressure in a handle and / or a head of the apparatus;a heater for heating hair of a user, the heater comprising a plurality of independently controllable heater electrodes that define a plurality of independently controllable heating zones;a memory storing a trained frustration calculator obtained by the method of claim 21, anda controller coupled to the memory and configured to:use the stored trained frustration calculator to calculate a frustration score based on the time elapsed while attempting to achieve the desired treatment and / or the pressure between arms of the apparatus and / or in a handle and / or a head of the apparatus, the frustration score being indicative of a level of frustration of the user while attempting to achieve the desired treatment;individually control the temperature or the power output of the one or more heating zones of the plurality of individually controllable heating zones,based on the calculated frustration score, to help the user to achieve the desired treatment and to avoid the hair being burnt; and / oroutput one or more feedback messages for the user to lower the user’s frustration, and / or inhibit the output of feedback messages which are likely to 5 increase the user’s frustration, based on the calculated frustration score.

29. The apparatus of claim 28, wherein the heater comprises a hair contacting surface, for heating the hair contacting the hair contacting surface by conduction.10 30. A computer program or a computer program product comprising instructionswhich, when executed by a processor, enable the processor to perform the method according to any one of claims 21 to 27.

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