Abstract:
Apparatus comprises at least one processor; and at least one memory including computer program code. The memory and the computer program code are configured to, with the at least one processor, cause the apparatus at least to perform a method of: determining an emotional or physical condition of a user of a device; and changing either: a) a setting of a user interface of the device, or b) information presented through the user interface, dependent on the detected emotional or physical condition.

Description:
FIELD OF THE INVENTION 
       [0001]    This invention relates to user interfaces. Particularly, the invention relates to changing a user interface based on a condition of a user. 
       BACKGROUND TO THE INVENTION 
       [0002]    It is well known to provide portable communication devices, such as mobile telephones, with a user interface that causes graphics and text to be displayed on a display and that allows a user to provide inputs to the device, for the purpose of controlling the device and interacting with software applications. 
       SUMMARY OF THE INVENTION 
       [0003]    A first aspect of the invention provides a method comprising: 
         [0004]    determining an emotional or physical condition of a user of a device; and 
         [0005]    changing either:
       a) a setting of a user interface of the device, or   b) information presented through the user interface,
 
dependent on the detected emotional or physical condition.
       
 
         [0008]    Determining an emotional or physical condition of the user may comprises using semantic inference processing of text generated by the user. The semantic processing may be performed by a server that is configured to receive text generated by the user from a website, blog or social networking service. 
         [0009]    Determining an emotional or physical condition of the user may comprises using physiological data obtained by one or more sensors. 
         [0010]    Changing a setting of the user interface of the device or changing information presented through the user interface may be dependent also on information relating to a location of the user or relating to a level of activity of the user. 
         [0011]    The method may comprise comparing a determined emotional or physical state of a user with an emotional or physical state of the user at an earlier time to determine a change in emotional or physical state, and changing the setting of the user interface or changing information presented through the user interface dependent on the change in emotional or physical state. 
         [0012]    Changing a setting of a user interface may comprise changing information that is provided on a home screen of the device. 
         [0013]    Changing a setting of a user interface may comprise changing one or more items that are provided on a home screen of the device. 
         [0014]    Changing a setting of a user interface may comprise changing a theme or background setting of the device. 
         [0015]    Changing information presented through the user interface may comprise automatically determining plural items of information that are appropriate to the detected emotional or physical condition, and displaying the items. This method may comprise determining a level of appropriateness for each of plural items of information and automatically displaying the ones of the plural items that are determined to have the highest levels of appropriateness. Here, determining a level of appropriateness for each of plural items of information may additionally comprise using contextual information. 
         [0016]    A second aspect of the invention provides an apparatus comprising 
         [0017]    at least one processor; and 
         [0018]    at least one memory including computer program code, 
         [0000]    the at least one memory and the computer program code configured to, with the at least one processor, cause the apparatus at least to perform a method of: 
         [0019]    determining one of a) an emotional condition and b) a physical condition of a user of a device; and 
         [0020]    changing one of:
       a) a setting of a user interface of the device, and   b) information presented through the user interface,
 
dependent on the detected condition of the user.
       
 
         [0023]    A third aspect of the invention provides apparatus comprising: 
         [0024]    means for determining an emotional or physical condition of a user of a device; and 
         [0025]    means for changing either:
       a) a setting of a user interface of the device, or   b) information presented through the user interface,
 
dependent on the detected emotional or physical condition.
       
 
     
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
         [0028]    Embodiments of the present invention will now be described, by way of example only, with reference to the accompanying drawings, in which: 
           [0029]      FIG. 1  is a schematic diagram illustrating a mobile device according to aspects of the invention; 
           [0030]      FIG. 2  is a schematic diagram illustrating a system according to aspects of the invention, the system including the mobile device of  FIG. 1  and a server side; and 
           [0031]      FIG. 3  is a flow chart illustrating operation of the  FIG. 2  server according to aspects of the invention; 
           [0032]      FIG. 4  is a flow chart illustrating operation of the  FIG. 1  mobile device according to aspects of the invention; and 
           [0033]      FIG. 5  is a screen shot provided by a user interface of the  FIG. 1  mobile device according to some aspects of the invention. 
       
    
    
     DETAILED DESCRIPTION OF EMBODIMENTS 
       [0034]    Referring firstly to  FIG. 1 , a mobile device  10  includes a number of components. Each component is commonly connected to a system bus  11 , with the exception of a battery  12 . Connected to the bus  11  are a processor  13 , random access memory (RAM)  14 , read only memory (ROM)  15 , a cellular transmitter and receiver (transceiver)  16  and a keypad or keyboard  17 . The cellular transceiver  16  is operable to communicate with a mobile telephone network by way of an antenna  21   
         [0035]    The keypad or keyboard  17  may be of the type including hardware keys, or it may be a virtual keypad or keyboard, for instance implemented on a touch screen. The keypad or keyboard provides means by which a user can enter text into the device  10 . Also connected to the bus  11  is a microphone  18 . The microphone  18  provides another means by which a user can communicate text into the device  10 . 
         [0036]    The device  10  also includes a front camera  19 . This camera is a relatively low resolution camera that is mounted on a front face of the device  10 . The front camera  19  might be used for video calls, for instance. 
         [0037]    The device  10  also includes a keypad or keyboard pressure sensing arrangement  20 . This may take any suitable form. The function of the keypad or keyboard pressure sensing arrangement  20  is to detect a pressure that is applied by a user on the keypad or keyboard  17  when entering text. The form may depend on the type of the keypad or keyboard  17 . 
         [0038]    The device includes a short range transceiver  22 , which is connected to a short range antenna  23 . The transceiver may take any suitable form, for instance it may be a Bluetooth transceiver, an IRDA transceiver or any other standard or proprietary protocol transceiver. Using the short range transceiver  22 , the mobile device  10  can communicate with an external heart rate monitor  24  and also with an external galvanic skin response (GSR) device  25 . 
         [0039]    Within the ROM  15  are stored a number of computer programs and software modules. These include an operating system  26 , which may for instance be the MeeGo operating system or a version of the Symbian operating system. Also stored in the ROM  15  are one or more messaging applications  27 . These may include an email application, an instant messaging application and/or any other type of messaging application that is capable of accommodating a mixture of text and image(s). Also stored in the ROM  15  are one or more blogging applications  28 . This may include an application for providing microblogs, such as those currently used for instance in the Twitter service. The blogging application or applications  28  may also allow blogging to social networking services, such as Facebook™ and the like. The blogging applications  28  allow the user to provide status updates and other information in such a way that it is available to be viewed by their friends and family, or by the general public, for instance through the Internet. In the following description, one messaging application  27  and one blogging application are described for simplicity of explanation. 
         [0040]    Although not shown in the Figure, the ROM  15  also includes various other software that together allow the device  10  to perform its required functions. 
         [0041]    The device  10  may for instance be a mobile telephone or a smart phone. The device  10  may instead take a different form factor. For instance the device  10  may be a personal digital assistant (PDA), or netbook or similar. The device  10  in the main embodiments is a battery-powered handheld communications device. 
         [0042]    The heart rate monitor  24  is configured to be supported by the user at a location such that it can detect the user&#39;s heartbeats. The GSR device  25  is worn by the user at a location where it is in contact with the user&#39;s skin, and as such is able to measure parameters such as resistance. 
         [0043]    Referring now to  FIG. 2 , the mobile device  10  is shown connected to a server  30 . Forming part of the device  10  and associated with a user  32  are a number of sensors. These include the heart rate monitor  24  and the GSR sensor  25 . They also include a brain interface sensor (EEG)  33  and a muscle movement sensor (sEMG)  34 . Also provided is a gaze tracking sensor  35 , which may form part of goggles or spectacles. Further provided is a motion sensor arrangement  36 . This may include one or more accelerometers, that are operable to detect acceleration of the device, unless detect whether the user is moving or is stationary. The motion sensor arrangement  36  may alternatively or in addition include a positioning receiver, such as a GPS receiver. It will be appreciated that a number of the sensors mentioned here involve components that are external to the mobile device  10 . In  FIG. 2 , they are shown as part of the device  10  since they are connected to the device  10  in some way, typically through a wired link or wirelessly using a short range communication protocol. 
         [0044]    The device  10  is shown as comprising a user interface  37 . This incorporates the keypad or keyboard  17 , but also includes outputs, particularly in the form of information and graphics provided on a display of the device  10 . The user interface is implemented as a computer program, or software, that is configured to operate along with user interface hardware, including the keypad  17  and a display. The user interface software may be separate from the operating system  26 , in which case it interacts closely with the operating system  26  as well as the applications. Alternatively, the user interface software may be integrated with the operating system  26 . 
         [0045]    The user interface  37  includes a home screen, which is an interactive image that is provided on the display of the device  10  at times when no active applications are provided on the display. The home screen is configurable by a user. The home screen may be provided with a time and date component, a weather component and a calendar component. The home screen may also be provided with shortcuts to one or more software applications. The shortcuts may or may not include active data relating to those applications. For instance, in the case of the weather application, the shortcut may be provided in the form of an icon that displays a graphic indicative of the weather forecast for the current location of the device  10 . The home screen may additionally comprise shortcuts to web pages, in the form of bookmarks. The home screen may additionally comprise one or more shortcuts to contacts. For instance, the home screen may comprise an icon indicating a photograph of a family member of the user  32 , whereby selecting the icon results in that family member&#39;s telephone number being dialed, or alternatively a contact for that family member being opened. As will be described below, the home screen of the user interface  37  is modified by the device depending on an emotional condition of the user  32 . 
         [0046]    Through the user interface  37 , the user  32  is able to upload blogs, microblogs and status updates etc. using the blogging application  18  to on-line services such as Twitter™, Facebook™ etc. These messages and blogs etc. then reside at locations on the Internet. The server  30  includes a connection  38  by which it can receive such status updates, blogs etc. from an input interface  39 . The content of these blogs, status updates etc. are received at a semantic inference engine  40 , the operation of which is described in more detail below. 
         [0047]    Inputs from the sensors  24 ,  25  and  32  to  36  are received at a multi-sensor feature computation module  42 , which forms part of the mobile device  10 . 
         [0048]    Outputs from the multi-sensor feature computation module  42  and the semantic inference engine  40  are received at a learning algorithm module  43  of the mobile device. Also received at the learning algorithm module  43  are signals from a performance evaluation module  44 , which forms part of the mobile device  10 . The performance evaluation module  44  is configured to assess performance of interaction between the user  32  and the user interface  37  of the device  10 . 
         [0049]    An output of the learning algorithm module  43  is connected to an adaption algorithm module  45 . The adaption algorithm module  45  exerts some control over the user interface  37 . In particular, the adaption algorithm module  45  alters the interactive image, for instance the home page, provided by the user interface  37  depending on outputs of the learning algorithm module  43 . This is described in more detail below. 
         [0050]    The mobile device  10  and the server  30  together monitor a physical or emotional condition of the user  32  and adapt the user interface  37  with the aim of being more useful to the user in their physical or emotional condition. 
         [0051]      FIG. 3  is a flow diagram that illustrates operation of the server  30 , in particular operation of the semantic inference engine  40 . Operation starts at step S 1  with the receipt of input text from the module  39 . Step S 2  performs emotiveness recognition on the input text. Step S 2  involves an emotive elements database S 3 . An emotive value determination is made at step S 4  using inputs from the emotiveness recognition step S 2  and the emotive elements database S 3 . The emotive elements database S 3  includes a dictionary, a thesaurus and domain specific key phrases. It also includes attributes. All of these elements can be used by the emotive value determination step S 4  to attribute a value to any emotion that is implied in the input text received at step S 1 . The emotiveness recognition step S 2  and the emotive value determination step S 4  involve feature extraction, in particular domain specific key-phrase extraction, parsing and attribute tagging. The features extracted from text will typically be a two dimensional vector [arousal valence]. For instance, arousal values may be in a range (0.0, 1.0) and valence may be in a range (−1.0, 1.0) 
         [0052]    An example input of text is “Are you coming to dinner tonight?”. This phrase is processed by the semantic inference engine  40  by breaking it down into its individual components. The word “you” is known from the emotive elements database S 3  to be an auxiliary pronoun, that is denotes a second person and thus is directed. The word “coming” is known by the emotive elements database S 3  to be a verb gerund. The phrase “dinner tonight” is identified as being a key phrase, that might be a social event. From the “?” the semantic inference engine  40  knows that action is expected, because the character is an interrogative. From the word “tonight”, the semantic inference engine  40  knows that the word is identified as a temporal adverb that identifies an event in the future. In conjunction with the words “you” and “coming”, the semantic inference engine  40  is able to determine that the text relates to an action in the future. With this example, the semantic inference engine  40  at step S 4  determines that there is no emotive content in the text, and allocates an emotive value of zero. A comparison of the emotive value at step S 5  with the value of zero leads to a step S 6  on a negative determination. Here, a parameter at “emotion type” is set to zero, and this information is sent for classification at step S 7 . Following a positive determination from step S 5  (from a different text string), the operation proceeds to step S 8 . Here, the type or types of emotion that are inferred by the text message are extracted. This step involves use of an emotive expression database. An output of step S 8  is sent for classification at step S 7 . Step S 7  involves sending features provided by either of steps S 6  and S 8  to the learning algorithm module  43  of the mobile device  10 . The emotion features sent for classification at step S 7  indicate the presence of no emotion for text such as “are you coming for dinner tonight?”, “I am reading Lost Symbol” and “I am running late”. However, for the text “I am in a pub!!”, the semantic inference engine  40  determines, particularly from the noun “pub” and the choice of punctuation, that the user  32  is in a happy state. The skilled person will appreciate that other emotion conditions that can be inferred from text strings that are blogged or provided as status information by the user  32 . 
         [0053]    Although not shown in  FIG. 3 , the semantic inference engine  40  is configured also to infer a physical condition of the user from the input text at step S 1 . From the text “I am reading Lost Symbol”, the semantic inference engine  40  is able to determine that the user  32  is performing a non-physical activity, in particular reading. From the text “I am running late”, the semantic inference engine  40  is able to determine that the user  32  is not physically running, and is able to determine that the verb gerund “running” instead is modified by the word “late”. From the text “I am in a pub!!”, the semantic inference engine  40  is able to determine that the text indicates a physical location of the user, not a physical condition. 
         [0054]    Referring now to  FIG. 4 , sensor inputs are received at the multi-sensor feature computation component  42 . Physical and emotional conditions extracted from the text by the semantics inference engine  40  are provided to the learning algorithm module  43  along with information from the sensors. As shown at  FIG. 4 , the learning algorithm module  43  includes a mental state classifier, for instance a Bayesian classifier,  46 , and an output  47  to an application programming interface (API). The mental state classifier  46  is connected to a mental state models database  48 . 
         [0055]    The mental state classifier  46  is configured to classify an emotional condition of the user, utilising inputs from the multi-sensor feature computation component  42  and the semantic inference engine  40 . The classifier preferably is derived as a result of training using data collected from real users over a period of time in simulated situations soliciting emotions. In this way, the classification of the emotion condition of the user  32  can be made to be more accurate than might otherwise be possible. 
         [0056]    The results of the classification are sent to the adaptation algorithm module  45  by way of the output  47 . 
         [0057]    The adaptation algorithm module  45  is configured to alter one or more settings of the user interface  37  depending on the emotional condition provided by the classifier  46 . A number of examples will now be described. 
         [0058]    In a first example, a user has posted the text “I am reading Lost Symbol” to a blog, for instance Twitter™ or Facebook™. This is understood by the semantic engine  40 , and provided to the learning algorithm module  43 . The adaptation algorithm module  45  is provided with an emotional condition classification of the user  32  by the learning algorithm module  43 . The adaptation algorithm module  45  is configured to confirm that the user is indeed partaking in a reading activity utilising outputs of the emotion sensors  36 . This can be confirmed by determining that motion, as detected by an accelerometer sensor for instance, is at a low level, consistent with a user reading a book. The emotional response of the user  32  as they read the book results in changes in output of various sensors, including the heart rate monitor  24 , the GSR sensor  25  and the EEG sensor  33 . The adaptation algorithm module  45  adjusts a setting of the user interface  37  to reflect the emotion conditional of the user  32 . In one example, a colour setting of the user interface  37  is adjusted depending on the detected emotional condition. In particular, the dominant background colour of the home page may change from one colour, for instance green, to a colour associated with the emotional condition, for instance red for a state of excitation. If the blog message is provided on the home page of the user interface  37 , or if a shortcut to the blogging application  28  is provided on the home page, the colour of the shortcut or the text itself may be adjusted by the adaptation algorithm module  45 . Alternatively or in addition, a setting relating to a physical aspect of the user interface  37 , for instance a dominant colour of the background or an appearance of the relevant shortcut, may be modulated to change along with the heart rate of the user  32 , as detected by the heart rate monitor  24 . 
         [0059]    In the case of a user posting a blog or status update “I am running late”, the mobile device  10  may detect from a positioning receiver, such as the GPS receiver included in the motion sensing transducer arrangement  36 , that the user is at their home location, or alternatively their office location. Furthermore, from the motion transducer, for instance the accelerometer, the mobile device  10  can determine that the user  32  is not physically running, nor travelling in a vehicle or otherwise. This constitutes a determination of a physical condition of the user. In response to such a determination, and considering the text, the application algorithm module  45  controls the user interface  37  to change a setting of the user interface  37  to give a calendar application a more prominent position on the home screen. Alternatively or in addition, the adaptation algorithm module  45  controls a setting of the user interface  37  to provide on the home screen a timetable of public transport from the current location of the user, and/or a report of traffic conditions on main routes near to the current location of the user. 
         [0060]    In a situation where the user has provided the text “I am in a pub!!”, the adaptation algorithm module  45  monitors both the physical condition and the emotional condition of the user using outputs of the multi-sensor feature computation component  42 . If the adaptation algorithm module  45  detects that after a predetermined period of time, for instance an hour, the user is not in an excited emotional condition and/or is relatively inactive, the adaptation algorithm module  45  controls a setting of the user interface  37  such as to provide on the home screen or in the form of a message a recommendation in the user interface  37  for an alternative leisure activity. The alternative may be an alternative pub, or a film that is showing at a cinema local to the user, or alternatively the locations and potentially other information about some friends or family members of the user  32  whom have been determined to be nearby the user. 
         [0061]    In another embodiment, the device  10  is configured to control the user interface  37  to provide to the user plural possible actions based on the emotional or physical condition of the user, and to change the possible actions presented through the user interface based on text entered by the user or actions selected by the user. An example will now be described with reference to  FIG. 5 . 
         [0062]      FIG. 5  is a screenshot of a display provided by the user interface  37  when the device  10  is executing the messaging application  27 . The screenshot  50  includes at a lowermost part of the display a text entry box  51 . In the text entry box  51 , the user is able to enter text that is to be sent to a remote party, for instance by SMS or by Instant Messaging. Above the text entry box  51  are first to fourth regions  52  to  55 , each of which relates to a possible action that may be performed by the user. 
         [0063]    For instance, after the user has opened or executed the messaging application  17  but before the user commences typing text into the text entry box  51 , the user interface  37  of the device is controlled to provide first to fourth possible actions in the regions  52  to  55  of the display  50 . The possible actions are selected by the learning algorithm  43  on the basis of the mental or physical condition of the user and from context information detected by the sensors  24 ,  25 ,  33  to  36  and/or from other sources such as a clock application and calendar data. Alternatively, the user interface  37  may display possible actions that are set by a manufacturer or service provider or by the user of the device  10 . For instance, the possible actions presented prior to the user beginning to enter text into the text entry box  51  may be the next calendar appointment, which is shown in  FIG. 5  at the region  55 , a shortcut to a map application, a shortcut to contact details of the spouse of the user of the device  10  and a shortcut to a website, for instance the user&#39;s homepage. 
         [0064]    Subsequently, the user commences entering text into the text entry box  51 . In  FIG. 5 , some example text is shown. In this embodiment, the device  10  includes a copy of the semantic inference engine  40  that is shown to be at the server  30  in  FIG. 2 . The device  10  uses the semantic inference engine  40  to determine an emotional or physical condition of the user of the device  10 . The learning algorithm  43  and the adaptation algorithm  45  are configured to use the information so determined to control the user interface  37  to present possible actions at the regions  52  to  55  that are more appropriate to the user&#39;s current situation. For instance, based on the text shown in the text entry box  FIG. 1  or  FIG. 5 , the semantic inference engine  40  may determine that the user&#39;s emotional condition is hungry. Additionally, the semantic inference engine  40  may determine that the user is enquiring about a social meeting, and infer there from that the user is feeling sociable. The learning algorithm  43  and the adaptation algorithm  45  use this information to control the user interface  37  to provide possible actions that are appropriate to the emotional and physical conditions of the user of the device  10 . In  FIG. 5 , it is shown that the user interface  37  has provided details of two local restaurants, at regions  52  and  54  respectively. The user interface  37  also has provided at region  55  the next calendar appointment. This is provided on the basis that it is determined by the learning algorithm  43  and the adaptation algorithm  45  that it may be useful to the user to know their commitments prior to making social arrangements. The user interface  37  also has provided at region  53  a possible action of access to information about local public transport. This is provided on the basis that the device  10  has determined that the information might be useful to the user if they need to travel to make a social appointment. 
         [0065]    The possible actions selected for display by the user interface  37  are selected by the learning algorithm  43  and  45  on the basis of a point scoring system. Points are awarded to a possible action based on some or all of the following factors: a user&#39;s history, for instance of visiting restaurants, the user&#39;s location, the user&#39;s emotional state, as determined by the inference engine  40 , the user&#39;s physical state, as determined by the semantic inference engine  40  and/or the sensors  24 ,  25  and  33  to  36 , and the user&#39;s current preferences, as may be determined for instance by detecting which possible actions are selected by the user for information and/or investigation. The number of points associated with a possible action are adjusted continuously, so as to reflect accurately the current condition of the user. The user interface  37  is configured to display a predetermined number of possible actions that have the highest score at any given time. In  FIG. 5 , the predetermined number of possible actions is four, so the user interface  37  shows the four possible actions that have the highest score at any given time in respective ones of the regions  52  to  55 . It is because of this that the possible actions that are displayed by the user interface  37  changes over time, and because text entered by the user into the text entry box  51  can change the possible actions that are presented for display. 
         [0066]    It will be appreciated that this embodiment involves the semantic inference engine  40  being located in the mobile device  10 . The semantic inference engine  40  may also be located at the server  30 . In this case, the content of the semantic inference engine  40  may be synchronised with or copied to the semantic inference engine located within the mobile device  10 . Synchronisation may occur on any suitable basis and in any suitable way. 
         [0067]    In a further embodiment, the device  10  is configured to control the user interface  37  to provide possible actions for display based on the emotional condition and/or the physical condition of the user as well as context. The context may include one or more of the following: the user&#39;s physical location, weather conditions, the length of time that the user has been at their current location, the time of day, the day of the week, the user&#39;s next commitment (and optionally the location of the commitment), and information concerning where a user has been located previously, with particular emphasis given to recent locations. 
         [0068]    In one example, the device determines that the user is located at Trafalgar Square in London, that it is midday, that the user has been at the location for 8 minutes, that the day of the week is Sunday, and that the prevailing weather conditions are rain. The device determines also from the user&#39;s calendar that the user has a theatre commitment at 7:30 pm that day. The learning algorithm  43  is configured to detect from information provided by the sensors  24 ,  25  and  33  to  36  and/or from text generated by the user in association with the messaging application  27  and/or the blogging application  28  a physical condition and/or an emotional condition of the user. Using this information in conjunction with the context information, the learning algorithm  43  and the adaptation algorithm  45  select a number of possible actions that have the highest likelihood of being relevant to the user. For instance, the user interface  37  may be controlled to provide possible actions including details of a local museum, details of a local lunch venue and a shortcut to an online music store, for instance the Ovi (™) store provided by Nokia Corporation. As with the previous embodiment, the possible actions that are selected for display by the user interface  37  are allocated points using a point scoring system and the possible actions with the highest numbers of points are selected for display at a given time. 
         [0069]    The adaptation algorithm module  45  may be configured or programmed to learn how the user responds to events and situations, and adjusts recommendations provided on the home screen accordingly. 
         [0070]    For example, content and applications in the device  10  may be provided with metadata fields. Values included in these fields may be allocated (for instance by the learning algorithm  43 ) denoting the physical and emotional state of the user before and after an application is used, or content consumed, in the device  10 . For instance, in respect of a comedy TV show content item, a movie, an audio content item such as a music track or album, or a comedy platform game application, metadata fields may be completed as follows: 
         [0000]    
       
         
               
               
               
               
             
           
               
                   
                   
               
               
                   
                 [Mood_Before 
                 Mood_After 
                 Activity] 
               
               
                   
                   
               
             
             
               
                   
                 0.1 Happy 
                 0.7 Happy 
                 0.8 Rest 
               
               
                   
                 0.8 Sad 
                 0.2 Sad 
                 0.1 Run 
               
               
                   
                 0.1 Angry 
                 0.1 Angry 
                 0.1 Car 
               
               
                   
                   
               
             
          
         
       
     
         [0071]    The metadata indicates the probability of the condition being the actual condition of the user, according to the mental state classifier  46 . This data shows how the content item or game transformed the user&#39;s emotional condition prior to consuming the content or playing the game to their emotional condition afterwards. It also shows the user&#39;s physical state whilst completing the activity. 
         [0072]    Instead of an application or a content item, the data may relates to an event such as posting a micro-blog message in IM, Facebook™, Twitter™ etc. 
         [0073]    Using the current physical &amp; mental context information and the set of target tasks, the reinforcement learning algorithm  43  and the adaptation algorithm  45  can formulate the actions that results in best rewards to the user. 
         [0074]    It will be appreciated that steps and operations described above are performed by the processor  13 , using the RAM  14 , under control of instructions that form part of the user interface  37 , or the blogging application  28 , running on the operating system  26 . During execution, some or all of the computer program that constitutes the operating system  26 , the blogging application  28  and the user interface  37  may be stored in the RAM  14 . In the event that only some of this computer program is stored in the RAM  14 , the remainder resides in the ROM  15 . 
         [0075]    Using features of the embodiments, the user  32  can be provided with information through the user interface  37  of the mobile device  10  that is more relevant to their situation than is possible with prior art devices. 
         [0076]    It should be realized that the foregoing embodiments should not be construed as limiting. Other variations and modifications will be apparent to persons skilled in the art upon reading the present application. 
         [0077]    Moreover, the disclosure of the present application should be understood to include any novel features or any novel combination of features either explicitly or implicitly disclosed herein or any generalization thereof and during the prosecution of the present application or of any application derived therefrom, new claims may be formulated to cover any such features and/or combination of such features.