PATENT DOCUMENT

Publication Number: US-8836502-B2
Application Number: US-581707-A
Country: US
Kind Code: B2

Title: Personal media device input and output control based on associated conditions

Abstract:
Systems and methods are provided for a media device that controls input and output characteristics based on one or more associated conditions.

Claims:
What is claimed is: 
     
       1. media device comprising:
 a sensor for generating a sensor signal based on at least one current environmental condition associated with the media device, 
 a temporal source for generating a temporal signal associated with the media device, wherein the temporal signal includes at least one of a current time and a current date, 
 a data store for storing a plurality of known condition vectors in a condition vector database, wherein each known condition vector identifies an environmental condition and a temporal condition, and wherein at least one of the known condition vectors identifies a temporal condition that includes at least one of a time data field and a date data field, and 
 a processor for controlling an incoming call alert of the media device by assigning a first weight to the sensor signal and a second weight to the temporal signal, combining the weighted sensor and temporal signals to form a received condition vector, comparing the received condition vector with the stored plurality of known condition vectors, selecting a closest matching condition vector from the plurality of known condition vectors based on the received condition vector, and determining the incoming call alert of the media device based on the closest matching condition vector. 
 
     
     
       2. The device of  claim 1 , wherein the processor is to continuously compare the received condition vector with the plurality of known condition vectors prior to receiving an incoming call to determine the incoming call alert of the media device. 
     
     
       3. The device of  claim 1 , wherein the processor is to use a pattern recognition algorithm when comparing the received condition vector with the plurality of known condition vectors. 
     
     
       4. The device of  claim 1 , wherein the processor is to use a vector matching algorithm when comparing the received condition vector with the plurality of known condition vectors. 
     
     
       5. The device of  claim 1 , wherein the processor is to select the closest matching condition vector by applying a decision model, wherein the decision model includes at least one of a linear regression model, a non-linear regression model, a logistic regression model, a Bayesian network model, a Markov model, a fuzzy model, and a propensity score. 
     
     
       6. The device of  claim 1 , wherein the incoming call alert includes at least one of a vibration pattern, an audio pattern, a video display image, a light pattern, and a text output. 
     
     
       7. The device of  claim 1 , wherein the time data field of the temporal condition specifies a time range associated with normal work hours. 
     
     
       8. The device of  claim 1 , wherein the date data field of the temporal condition specifies a range of days in the week. 
     
     
       9. The device of  claim 1 , wherein at least one of the plurality of known condition vectors identifies an event condition. 
     
     
       10. The device of  claim 9 , wherein the event condition results from a user affecting at least one of a position, orientation, and movement of the media device. 
     
     
       11. The device of  claim 1 , wherein the sensor includes at least one of an accelerometer, a gyroscope, a light sensor, a temperature sensor, a pressure sensor, an infrared (IR) sensor, a proximity sensor, a capacitive proximity sensor, an acoustic sensor, an acoustic frequency sensor, a sonic or sonar sensor, a radar sensor, an image sensor, a video sensor, a global positional system (GPS) detector, a RF detector, a RF or acoustic Doppler detector, a RF triangulation detector, a video sensor, a battery charging sensor, and a peripheral device detector. 
     
     
       12. The device of  claim 11 , wherein the acoustic sensor includes a microphone. 
     
     
       13. A method for interfacing with a media device comprising:
 storing a plurality of known condition vectors in a condition vector database, wherein each known condition vector identifies an environmental condition and a temporal condition, and wherein at least one of the known condition vectors identifies a temporal condition that includes at least one of a time of the day and a day of the week, 
 generating a sensor signal from a sensor based on at least one current environmental condition associated with the media device, 
 generating a temporal signal associated with the media device, wherein the temporal signal includes at least one of a current time and a current date, 
 assigning a first weight to the sensor signal and a second weight to the temporal signal, 
 combining the weighted sensor and temporal signals to form a received condition vector, 
 comparing the received condition vector with the stored plurality of known condition vectors, 
 selecting a closest matching condition vector from the plurality of known condition vectors based on the received condition vector, and 
 determining an incoming call alert of the media device based on the closest matching condition vector. 
 
     
     
       14. The method of  claim 13 , wherein comparing the received condition vector with the stored plurality of known condition vectors is repeated continuously prior to receiving an incoming call to determine the incoming call alert of the media device. 
     
     
       15. The method of  claim 13 , wherein comparing includes employing a pattern recognition algorithm. 
     
     
       16. The method of  claim 13 , wherein comparing includes employing a vector matching algorithm. 
     
     
       17. The method of  claim 13 ,wherein selecting the closest matching condition vector includes applying a decision model, wherein the decision model includes at least one of a linear regression model, a non-linear regression model, a logistic regression model, a Bayesian network model, a Markov model, a fuzzy model, and a propensity score. 
     
     
       18. The method of  claim 13 , wherein the incoming call alert includes at least one of a vibration pattern, an audio pattern, a video display image, a light pattern, and a text output. 
     
     
       19. The method of  claim 13 , wherein at least one of the plurality of known condition vectors identifies an event condition. 
     
     
       20. The method of  claim 19 , wherein the event condition results from a user affecting at least one of a position, orientation, and movement of the media device.

Description:
BACKGROUND 
     This invention relates to personal media devices and, more particularly, to controlling input and output characteristics of personal media devices based on associated conditions. 
     The proliferation of compact portable personal media devices (e.g., portable MP3 players, portable video players, and media capable cellular telephones) has enabled users to conveniently carry and interact with such compact portable media devices during virtually any type of activity. The interaction may include accessing multimedia such as video and audio (e.g., voice and music) and sending or receiving communications via the media device. The types of activities could be personal, social, work-related, or recreational. The activities could occur under various environmental conditions, at various times or dates, in various social settings, or in various personal settings. 
     One problem with existing portable media devices such as cellular telephones is that, in order to alert a user of an incoming communication, the media device typically outputs an alert that is not always appropriate for certain environmental conditions, social situations, or personal situations. For instance, a ringer volume of sufficient intensity for a quiet office environment may not have sufficient intensity for a crowded and noisy stadium. In another instance, a cellular telephone could interrupt a business meeting with a ringing alert because the user did not previously turn off the telephone or its ring setting. Accordingly, there is a need for providing a media device capable of sensing various associated conditions of its surrounding environment and adjusting characteristics of its alert feature based on such associated conditions. 
     Another problem with existing portable media devices is that once an alert for an incoming call is initiated, typical media devices are unable to adapt or adjust their alert characteristics in response to a subsequent change in associated conditions. Accordingly, there is a need for providing a media device capable of sensing various changes in associated conditions, e.g., surrounding environmental conditions, after an alert is initiated and adjusting or adapting a characteristic of the alert in response to such changes or events. 
     Another problem with existing portable media devices is that alert settings typically remain constant regardless of the time of day or day of the week. For example, the alert volume may be set at an acceptably high intensity during the day while the same intensity is too high during the night or early morning when the user may be sleeping. Accordingly, there is a need for providing a media device capable of sensing temporal conditions and adjusting a characteristic of an alert based on such temporal conditions. 
     A further problem with current portable media devices is that these devices are not capable of automatically or intelligently setting their alert characteristics. For instance, cellular telephone users must continuously change the alert settings of their telephones depending on their surroundings. Accordingly, there is a need for providing a media device that is capable of intelligently, automatically, and unobtrusively adjusting alert characteristics or other output/input (I/O) characteristics based on surrounding or associated conditions. 
     A yet further problem with existing portable media devices is that the reception or delivery of information by the media device may be adversely affected by surrounding environmental conditions. For instance, surrounding ambient noise may affect a user&#39;s ability to hear or understand the output from a speaker of the media device where the speaker volume is set at an intensity that is too low for current conditions. In another instance, the display light intensity may be set to enable viewing in outdoor daylight settings, but be too high for certain low light conditions such as in a movie theatre. Accordingly, there is a need for providing a media device capable of adjusting an input or output characteristic in response to associated conditions such as surrounding environmental conditions. 
     SUMMARY 
     The invention, in various embodiments, addresses deficiencies in the prior art by providing systems, methods and devices that enable a personal media device user to control one or more input or output characteristics, such as alert characteristics, of a personal media device in response to associated conditions of the personal media device. Associated conditions may include, without limitation, surrounding environmental conditions, temporal conditions, and/or subsequent event conditions such as user-initiated, user-responsive, and/or other event conditions. 
     In various aspects, the invention employs one or more environmental sensors in a media device. An environmental sensor may include, without limitation, an accelerometer, a gyroscope, a light sensor, temperature sensor, pressure sensor, an infrared (IR) sensor, proximity sensor, capacitive proximity sensor, acoustic sensor, acoustic frequency sensor, sonic or sonar sensor, radar sensor, image sensor, video sensor, global positional system (GPS) detector, RF detector, RF or acoustic doppler detector, RF triangulation detector, battery charging sensor, peripheral device detector, an event counter, and/or other like environment sensor. An event counter may count the number of times that an event has occurred, has not occurred, or should have occurred. For example, if a user fails to answer a call after several alert instances using a particular vibration pattern, a media device may change the alert to a different vibration pattern to illicit a user&#39;s attention. The media device may also include one or more temporal sensors. The temporal sensor may include, without limitation, a clock, differential clock, counter, differential counter, calendar, and/or like temporal sensor. The media device may further support user-initiated or user response inputs via a user interface or changes in the media device&#39;s position, orientation, or movement (POM). Environmental sensors that sense position, orientation, and movement may also be referred to as POM sensors. The acoustic sensor may include a microphone capable of measuring RMS signal levels associated with received sounds and/or supporting a more complicated spectral analysis of received sounds. 
     In one aspect, a media device includes a sensor that generates a sensor signal based on at least one environmental condition associated with the media device. The media device also includes a temporal source that generates a temporal signal associated with the media device. The media device further includes a processor that controls one or more input or output characteristics of the media device based at least in part on the sensor signal and the temporal signal. 
     In one configuration, the media device control includes comparing the sensor signal and temporal signal with the one or more condition vectors or condition rule sets to determine the one or more input or output characteristics of the media device. The comparing process may include employing a pattern recognition algorithm or a vector matching algorithm. In another configuration, the output characteristics include alert characteristics. The alert characteristics may include at least one of a vibration pattern, an audio pattern, a video display image, a light pattern, and a text output. An audio pattern may include, without limitation, a ringtone, song, audio file, or like audio emission. 
     In certain configurations, the media device includes a data store that stores one or more condition vectors or condition rule sets. A condition vector or rule set may include at least one of an environmental condition and a temporal condition. In another configuration, a condition vector also includes an event condition. An event condition may result from a user affecting at least one of the position, orientation, and movement of the media device. 
     In another aspect, a media device includes a plurality of sensors for generating a plurality of sensor signals respectively. Each sensor signal may be based on an associated condition of the media device. The media device may also include a processor that receives the sensor signals and applies a decision model to the received sensor signals to control one or more input or output characteristics of the media device. 
     The decision model may include at least one of a linear regression model, a non-linear regression model, a logistic regression model, a Bayesian network model, a Markov model, a fuzzy model, and a propensity score to select one or more input or output characteristics. The decision model may assign a weight to each of the sensor signals respectively. 
     In a further aspect, a media device includes an environmental sensor that senses a change in an environmental condition associated with the media device and generates a sensor signal related to the change in the environmental condition. The media device may also include an alert controller that initiates a first alert pattern, but then changes the first alert pattern to a second alert pattern in response to the sensor signal from the environmental sensor. 
     Various advantages and applications of controlling the input or output characteristics of a media device based on associated conditions in accordance with principles of the present invention are discussed in more detail below. 
    
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
       The above and other features of the present invention, its nature and various advantages will become more apparent upon consideration of the following detailed description, taken in conjunction with the accompanying drawings, in which like reference characters refer to like parts throughout, and in which: 
         FIG. 1A  is a perspective view of a media device with an exposed frame assembly according to an illustrative embodiment of the invention; 
         FIG. 1B  is another perspective view of a media device according to an illustrative embodiment of the invention; 
         FIG. 2  shows the media device of  FIGS. 1A and 1B  with tethered headphones and, alternatively, a wireless earpiece according to an illustrative embodiment of the invention; 
         FIG. 3  shows a simplified functional block diagram of a media device according to an illustrative embodiment of the invention; 
         FIG. 4  shows a transverse sectional view of a media device including an vibration source and POM sensor according to an illustrative embodiment of the invention; 
         FIG. 5  is a perspective transparent view of an three-dimensional accelerometer within a media device according to an illustrative embodiment of the invention; 
         FIG. 6  shows a perspective transparent view of a plurality of environmental sensors within or attached to a media device according to an illustrative embodiment of the invention; 
         FIG. 7  is a diagram of a computer processing environment  700  including various applications or routines running within a media device according to an illustrative embodiment of the invention; 
         FIG. 8  is a diagram of a condition vector including various associated conditions according to an illustrative embodiment of the invention; 
         FIG. 9  is a diagram of a database including one or more lists associating condition vectors with input or output interface configurations and/or characteristics of one or more applications within a media device according to an illustrative embodiment of the invention; 
         FIGS. 10A-C  include a flow diagram of an exemplary process for determining an alert pattern for a telephone application of a media device based on associated conditions of the media device according to an illustrative embodiment of the invention; and 
         FIG. 11  is a flow diagram of a process for inputting and identifying movement patterns based on one or more pattern recognition algorithms according to an illustrative embodiment of the invention. 
     
    
    
     DETAILED DESCRIPTION OF THE DISCLOSURE 
       FIG. 1A  is a perspective view of a media device  100  according to an illustrative embodiment of the invention. The media device  100  includes a housing  102 , a first housing portion  104 , a second housing portion  106 , a display  108 , a keypad  110 , a speaker housing aperture  112 , a microphone housing aperture  114 , a headphone jack  116 , and frame sidewall  122 . Although not shown, in certain embodiments, the frame sidewall  122  is the exposed portion of a frame residing within or adjacent to the housing  102  that provides structural support for the media device  100  and various internal components. The housing  102  also includes various gaps  118  that may include openings, separations, vents, or other pathways between elements of the housing  102  that enable the passage of air or sound through the housing  102 . 
     In one embodiment, the housing  102  includes a first housing portion  104  and a second housing portion  106  that are fastened together to encase various components of the media device  100 . In certain embodiments, the housing  102  also includes an exposed frame  120  that provides structural support for the media device  100 . The housing  102  and its housing portions  104  and  106  may include polymer-based materials that are formed by, for example, injection molding to define the form factor of the media device  100 . In one embodiment, the housing  102  surrounds and/or supports internal components such as, for example, one or more circuit boards having integrated circuit components, internal radio frequency (RF) circuitry, an internal antenna, a speaker, a microphone, a hard drive, a processor, and other components. Further details regarding certain internal components are discussed later with respect to  FIG. 3 . The housing  102  provides for mounting of a display  108 , keypad  110 , external jack  116 , data connectors, or other external interface elements. The housing  102  may include one or more housing apertures  112  to facilitate delivery of sound, including voice and music, to a user from a speaker within the housing  102 . The housing  102  may include one or more housing apertures  114  to facilitate the reception of sounds, such as voice, for an internal microphone from a media device user. 
     In certain embodiments, the housing  102  includes one or more gaps  118  associated with the housing  102 . These gaps  118  may result from the manufacturing and/or assembly process for the media device  100 . For example, in certain circumstances, the mechanical attachment of the first housing portion  104  with the second housing portion  106  or the sidewall  122  results in a crease  120  or joint between the portions  104  and  106 . In certain media devices  100 , the crease  120  is not air tight, resulting in gaps  118  along the crease. Other gaps may be formed during assembly between, for example, one or more keys of the keypad  110  and the housing  102  or the display  108  and the housing  102 , resulting in additional gaps  118 . In other embodiments, the housing  102  may include additional portions that are integrated to form the housing  102  for the media device  100 . 
     The media device  100  may include a wireless communications device such as a cellular telephone, satellite telephone, cordless telephone, personal digital assistant (PDA), pager, portable computer, or any other device capable of wireless communications. In fact,  FIG. 1  shows an exemplary cellular telephone version of a broad category of media device  100 . 
     The media device  100  may also be integrated within the packaging of other devices or structures such as a vehicle, video game system, appliance, clothing, helmet, glasses, wearable apparel, stereo system, entertainment system, or other portable devices. In certain embodiments, device  100  may be docked or connected to a wireless enabling accessory system (e.g., a wi-fi docking system) that provides the media device  100  with short-range communicating functionality. Alternative types of media devices  100  may include, for example, a media player such as an iPod® or Apple® iphone available by Apple Inc., of Cupertino, Calif., pocket-sized personal computers such as an iPAQ® Pocket PC available by Hewlett Packard Inc., of Palo Alto, Calif. and any other device capable of communicating wirelessly (with or without the aid of a wireless enabling accessory system). 
     In certain embodiments, the media device  100  may synchronize with, for example, a remote computing system or server to receive media (using either wireless or wireline communications paths). Wireless syncing enables the media device  100  to transmit and receive media and data without requiring a wired connection. Media may include, without limitation, sound or audio files, music, video, multi-media, and digital data, in streaming and/or discrete (e.g., files and packets) formats. 
     During synchronization, a host system may provide media to a client system or software application embedded within the media device  100 . In certain embodiments, media and/or data is “downloaded” to the media device  100 , In other embodiments, the media device  100  is capable of uploading media to a remote host or other client system. Further details regarding the capabilities of certain embodiments of the media device  100  are provided in U.S. patent application Ser. No. 10/423,490, filed on Apr. 25, 2003; U.S. application Ser. No. 11/770,641, filed Jun. 28, 2007; and U.S. application Ser. No. 11/834,604, filed Aug. 6, 2007, entitled “Synching Data” the entire contents of each of which are incorporated herein by reference. 
       FIG. 1B  is another perspective view of a media device  100  according to an illustrative embodiment of the invention. In this embodiment, as opposed to the embodiment of  FIG. 1A , the media device&#39;s frame and/or the frame&#39;s sidewalls are not exposed to an external surface of the device. However, in certain embodiments, the frame is connected internally with at least a portion of one of the first housing portion  104  or the second housing portion  106 . 
       FIG. 2  shows the media device  100  of  FIG. 1  with tethered headphones  200  and, alternatively, a wireless earpiece  206  according to an illustrative embodiment of the invention. The tethered headphones  200  include a cable  212  that connects to the media device  100  via external jack  116 . In one embodiment, the cable provides for transport of an audio signal from the media device  100  to the headphones  200 . In another embodiment, the headphones  200  includes a left housing  202  and a right housing  204 , corresponding to the left and right ears of a user, respectively. Each housing  202  and  204  may include a speaker and/or an acoustic assembly as described later with respect to  FIG. 4 . The headphones  200  may optionally include a microphone to facilitate sending sounds from the user to the media device  100 . As an alternative to the headphones  200 , a user may utilize the wireless earpiece  206  which includes a housing  208 . In one embodiment, the earpiece  206  employs wireless channel  210  to receive audio signals from the device  100  or transmit audio signals to the device  100 . The housing  208  may include a speaker, microphone, and/or acoustic assembly as described later with respect to  FIG. 4 . 
       FIG. 3  shows a simplified functional block diagram of the media device  100  according to an illustrative embodiment of the invention. The media device or player  300  may include a processor  302 , storage device  304 , user interface  308 , display  310 , CODEC  312 , bus  318 , memory  320 , communications circuitry  322 , a speaker or transducer  324 , a microphone  326 , a vibration source driver  328 , an environmental sensor  330 , and/or a temporal sensor or source  332 . Processor  302  may control the operation of many functions and other circuitry included in media player  300 . Processor  302  may drive display  310  and may receive user inputs from the user interface  308 . The temporal sensor or source  332  may include a clock within the processor  302 , an oscillator, dedicated clock circuit and/or IC, a software based clock or timer application. The temporal source  332  may be synchronized with a remote timing source such as a network clock, remote server clock, timing standard source. 
     Storage device  304  may store media (e.g., music and video files), software (e.g., for implanting functions on device  300 , preference information (e.g., media playback preferences), lifestyle information (e.g., food preferences), exercise information (e.g., information obtained by exercise monitoring equipment), transaction information (e.g., information such as credit card information), wireless connection information (e.g., information that may enable media device to establish wireless communication with another device), subscription information (e.g., information that keeps tracks of podcasts or television shows or other media a user subscribes to), and any other suitable data. Storage device  304  may include one more storage mediums, including for example, a hard-drive, permanent memory such as ROM, semi-permanent memory such as RAM, or cache. 
     Memory  320  may include one or more different types of memory which may be used for performing device functions. For example, memory  320  may include cache, ROM, and/or RAM. Bus  318  may provide a data transfer path for transferring data to, from, or between at least storage device  304 , memory  320 , and processor  302 . Coder/decoder (CODEC)  112  may be included to convert digital audio signals into an analog signals for driving the speaker  324  to produce sound including voice, music, and other like audio. The CODEC  112  may also convert audio inputs from the microphone  326  into digital audio signals. The CODEC  112  may include a video CODEC for processing digital and/or analog video signals. 
     User interface  308  may allow a user to interact with the media device  300 . For example, the user input device  308  can take a variety of forms, such as a button, keypad, dial, a click wheel, or a touch screen. Communications circuitry  322  may include circuitry for wireless communication (e.g., short-range and/or long range communication). For example, the wireless communication circuitry may be wi-fi enabling circuitry that permits wireless communication according to one of the 802.11 standards. Other wireless network protocols standards could also be used, either in alternative to the identified protocols or in addition to the identified protocol. Other network standards may include Bluetooth, the Global System for Mobile Communications (GSM), and code division multiple access (CDMA) based wireless protocols. Communications circuitry  322  may also include circuitry that enables device  300  to be electrically coupled to another device (e.g., a computer or an accessory device) and communicate with that other device. 
     In one embodiment, the media device  300  may be a portable computing device dedicated to processing media such as audio and video. For example, media device  300  may be a media player (e.g., MP3 player), a game player, a remote controller, a portable communication device, a remote ordering interface, an audio tour player, or other suitable personal device. The media device  300  may be battery-operated and highly portable so as to allow a user to listen to music, play games or video, record video or take pictures, communicate with others, and/or control other devices. In addition, the media device  300  may be sized such that it fits relatively easily into a pocket or hand of the user. By being handheld, the media device  300  (or media device  100  shown in  FIG. 1 ) is relatively small and easily handled and utilized by its user and thus may be taken practically anywhere the user travels. 
     As discussed previously, the relatively small form factor of the media devices  300  enables a user to easily manipulate the devices position, orientation, and movement. Accordingly, embodiments of the invention provide for improved techniques of sensing such changes in position, orientation, and movement to enable a user to interface with or control the media device  300  by affecting such changes. Further, the media device  300  may include a vibration source  328 , under the control processor  302 , for example, to facilitate sending motion, vibration, and/or movement information to a user related to an operation of the media device. 
       FIG. 4  shows a transverse sectional view of a media device  400  including a vibration source  414  and/or environmental sensor  416  according to an illustrative embodiment of the invention. The media device  400  comprises an upper housing  402 . The main structural frame  404  is secured to the housing  402  which may be fabricated from a die-castable material using a die-casting process. The frame  404  includes a surrounding sidewall  406  and a web or backplane  408 . The web  408  extends between the sidewall  406  and forms a printed circuit board compartment between the housing  402  and web  408 . The printed circuit board compartment includes a printed circuit board  410  and associated electrical components  412 . The web  408  supports or houses a battery  420  which, in turn, forms the back of the cellular telephone  400 . 
     The media device  400  may employ a unitized frame member  404  which is composed of a single die-castable material, typically magnesium or zinc, where the sidewall  406  and the web  408  are constructed of the same or different material via a die-cast fabrication technique. In one embodiment, the media device  400  includes at least one vibration source  414 . In another embodiment, the media device  400  includes at least one environmental sensor  416 . The certain embodiments, one or both of the at least one vibration source  414  and environmental sensor  416  are in communication with the web  408 , the circuit board  410 , and/or a portion of a sidewall  406 . 
     In the embodiment shown in  FIG. 4 , the environmental sensor  416  and vibration source  414  are in communication with the web  408  and/or frame  404 . In certain embodiments, at least one of the environmental sensor  416  and vibration source  414  are mounted to and/or in communication with one or more of the web  408 , the frame  404 , the circuit board  410 , the housing  402 , and any other component or element of the media device  400 . 
     In one embodiment, a portion of the printed circuit board  410 , the memory  320 , storage  304 , processor  302 , a battery, and a driver circuit  328  or  418 , operate to form a vibration generating circuit for the vibration source  414 . In certain embodiments, the vibration source  414  includes a generating motor. In other embodiments, the vibration source  414  includes a solenoid or other elements that generate a vibration, vibration pattern, and/or vibration sequence in response to an application running on the processor  302 . 
     By way of example, one of the vibration generating motors, “FM16, FM23, FM25 or FM29” or “CM-5”, manufactured by the Tokyo Parts Industries Corporation, LTD of Tokyo, Japan, may be utilized as a vibration source  414 . By further example, the “FM” motor employs an eccentric member that is attached to a rotating shaft incorporated in a cylindrical case. The eccentric member is rotated according to a rotation of the rotation shaft, and thereby, a vibration is generated from the vibration source  414  that is coupled to at least one of the web  408 , the frame  404 , the circuit board  410 , the housing  402 , and any other component or element of the media device  400 . By another example, the “CM” motor employs a armature coil that is mounted in an eccentric manner. By rotating the armature, a vibration is generated. Further, if the vibration source  414  employs a solenoid, a core within the solenoid is reciprocally moved and, thereby, a vibration is generated. 
     Regardless of the physical element employed, the vibration source  414  may be driven by the driver circuit  328  and/or  418  in response to the processor  302 . The consumption of electric power by the vibration source  414  may be substantial. Accordingly, an application may be employed to provide for the activation and/or deactivation of the vibration source  414  depending on the power needs of the media device  400 . In certain embodiments, the vibration source driver circuit  328  and/or  418  is configured to adjust at least one of the frequency of vibration, strength of vibration in one or more pre-selected or defined sequences and/or patterns. 
       FIG. 5  is a perspective transparent view of an three-dimensional acceleration sensor or accelerometer  502  within a media device  500  according to an illustrative embodiment of the invention. In certain embodiments, the POM sensor  416  includes an acceleration sensor and/or accelerometer  502  that detects an acceleration in three axial directions of the media device  500 , i.e., the up-down direction (Y-axis), the left-right direction (X-axis), and the front-rear direction (the Z-axis). The acceleration sensor allows the inclinations and movements of the media device  500  in the X-axis, Y-axis and Z-axis directions to be determined. In one embodiment, acceleration data detected by the acceleration sensor  502  is transmitted to the processor  302  for processing to enable determination of the position, orientation, and movement of the media device  500 . 
     In one embodiment, the media device  500  includes a three-axis or three-dimensional, linear acceleration sensor  502  that detects linear acceleration in each of the three axial directions shown in  FIG. 5 . In an alternative embodiment, a two-axis linear accelerometer is employed that detects linear acceleration along each of the X-axis and Y-axis (or other pair of axes). A two-axis sensor may be sufficient depending on the types of positions, orientations, and movements that are desired to be detected and/or used to control the media device  500 . By way of example, the three-axis or two-axis linear accelerometer  502  may be of the type available from Analog Devices, Inc. or STMicroelectronics®. The acceleration sensor  502  may be electrostatic capacitance or capacitance-coupling type that is based on silicon micro-machined MEMS (microelectromechanical systems) technology. In certain embodiments, other forms of accelerometer technology such as, without limitation, piezoelectric or piezoresistance based sensors may be employed to provide three-axis or two-axis acceleration detection. 
     Because the linear acceleration sensor  502 , may only be capable of detecting acceleration along a straight line corresponding to each axis of the acceleration sensor, the acceleration sensor  502  may not be capable of directly detecting movement in the form of a non-linear (e.g. circular) path, a rotation, a rotational movement, an angular displacement, a tilt, a position, an attitude or another physical characteristic. Accordingly, in certain embodiments, through additional processing of the linear acceleration signals output from the acceleration sensor  502 , additional information relating to the position, orientation, or movement of the media device  500  may be inferred or calculated by an application running on the processor  302 . 
     For example, by detecting a static, linear acceleration (e.g., gravity), the linear acceleration output of the acceleration sensor  502  may be used to infer or calculate tilt or inclination of the media device  500  relative to the gravity vector by correlating tilt angles with detected linear acceleration. In this way, the acceleration sensor  502  may be used in combination with the processor  302  (or another processor) to determine tilt, altitude or position of the media device  502 . Similarly, various movements, patterns of movement, and/or positions of the media device may be calculated or inferred through processing of the linear acceleration signals generated by the acceleration sensor  502  when the media device  500  is subjected to dynamic accelerations by, for example, the hand of a user. In one embodiment, the acceleration sensor  502  may include an embedded signal processor or other type of dedicated processor for performing any desired processing of the acceleration signals output from the acceleration sensor  502  and/or other accelerometers in the media device  500  prior to outputting signals to the processor  302 . In certain embodiments, the embedded or dedicated processor or processors may convert the detected acceleration signal to a corresponding tilt angle when the acceleration sensor  502  is intended to detect static acceleration (e.g., gravity). 
     In certain embodiments, a pair of two-dimensional accelerometers may be employed within a media device  500  instead of using a single three-dimensional accelerometer. The two two-dimensional accelerometers may be arranged in relation to each other so as to enable three-dimensional sensing of the position, orientation, and movement of the media device  500 . 
     In certain embodiments, at least two three-dimensional accelerometers may be employed within a media device  500  for enhanced sensing capabilities. Thus, a plurality of accelerometers may be positioned within the media device  500  at any one of a plurality of locations. 
       FIG. 6  shows a perspective transparent view of a plurality of environmental sensors  602 ,  604 , and  606  within or attached to a media device  600  according to an illustrative embodiment of the invention. In one embodiment, a gyro-sensor or gyroscope  602  may be employed instead of or in addition to an acceleration sensor  604 . In certain embodiments, the gyro-sensor  602  may include a rotating or vibrating element. Exemplary MEMS gyro-sensors that may be used in this embodiment are available from Analog Devices, Inc. Unlike the linear acceleration sensor  604 , a gyro-sensor  602  is capable of directly detecting rotation (or angular rate) around an axis defined by the gyroscopic element (or elements) of the gyro-sensor  602 . Because there are fundamental differences between a gyro-sensor  602  and a linear acceleration sensor  604  (e.g., angle-based vs. vector-based output), different processing operations are performed on the output signals from these different sensor devices. 
     For example, when tilt or inclination is calculated using a gyro-sensor  602  instead of the acceleration sensor, different algorithms and/or applications may be employed by the processor  302  to determine position, orientation, and/or movement of the media device  600 . In one embodiment, when using a gyro-sensor  602 , the value of inclination is initialized at the start of detection. Then, data on the angular velocity which is output from the gyroscope  602  is integrated. Furthermore, a change amount in inclination from the value of inclination previously initialized is calculated. In this case, the calculated inclination corresponds to an angle. In contrast, when an acceleration sensor  604  is used, the inclination may be calculated by comparing the value of the acceleration of gravity of each axial component with a predetermined reference. Accordingly, the calculated inclination may be represented as a vector and, without initialization, an absolute direction may be determined with an accelerometer. In certain embodiments, one or more environmental sensors may be employed to detect at least one of absolute and relative position, orientation, and movement information. 
     The type of the value calculated as an inclination may also be different between a gyroscope  602  and an accelerometer  604 . For example, the value may be an angle when a gyroscope  602  is used, but a vector when an acceleration sensor  604  is used. Accordingly, when a gyroscope  602  is used instead of an acceleration sensor  604  or vice versa, the sensor data on inclination may be processed by a predetermined conversion that takes into account the fundamental differences between a gyro-sensor  602  and an accelerometer  604 . Due to the fact that the nature of gyroscopes is known to one skilled in the art, as well as the fundamental differences between linear accelerometers and gyroscopes, further details are not provided herein. While gyro-sensors provide certain advantages due to their ability to directly detect rotation, linear acceleration sensors may be more cost effective when used in connection with portable media device  600 . 
     In certain embodiments, the media device  600  may include an environmental or POM sensor  606  in addition to at least one of an accelerometer  604  and a gyro-sensor  602 . The additional sensor  606  may be a light sensor, an infrared (IR) sensor, proximity sensor, capacitive proximity sensor, acoustic sensor, a microphone, sonic or sonar sensor, radar sensor, image sensor, video sensor, global positional system (GPS) detector, RF detector, RF triangulation detector, magnetometer, RF or acoustic doppler detector, or other like environment sensor. In one embodiment, the media device  600  employs a plurality of POM, environmental and/or other sensors  602 ,  604 , and  606  to determine the position, orientation, and/or movement of the media device  600 . In one embodiment, the media device  600  employs a GPS sensor in combination with one or more other sensors. The media device  600  may employ a GPS sensor as described in U.S. patent application Ser. No. 12/005,822, filed on Dec. 28, 2007, entitled “Event-Based Modes For Electronic Devices”the entire contents of which are incorporated herein by reference. 
     In one embodiment, a microphone or other audio input sensor is configured to detect an audio signal at a particular frequency, e.g., ultrasonic signal, or a sequence of audio signals and, in response to detecting such signal or signals, controlling the operation of the media device. For example, a particular venue, such as a movie theater, hospital, or court room, may use an emitter that emits an ultrasonic signal or other signal. This signal may be undetectable by humans, but detectable by a microphone, and provide a proximal indicator to a media device to operate in a particular manner. Thus, when the media device detects the signal, the media device may perform at least one of turn off, change its alert mode, and generate a user notification to allow a user to perform a function such as turn off the media device. 
     In certain embodiments, the media device  600  includes an environmental or POM sensor that generates a sensor signal based on at least one of a position, orientation, and movement of the media device. The media device may also include a processor that receives the environmental or POM sensor signal and controls one or more operations of the media device based at least in part on the sensor signal. For example, by performing one or more defined or pre-selected movements of the media device, a user can control various operations of the media device. In one embodiment, a user controls an output characteristic, e.g., an alert characteristic, by affecting the position, orientation, and/or movement of the media device  600 . 
       FIG. 7  is a diagram of a computer processing environment  700  including various applications or routines running within a media device according to an illustrative embodiment of the invention. The processing environment  700  may include a decision application  702 , an input control application  704 , an output control application  706 , environmental data  708 , temporal data  710 , event data  712 , a condition vector database  714 , an alert pattern database  716 , and/or an input/output interface configuration database  746 . The environmental data  708  may include, without limitation, POM data  718 , ambient noise or sound data  720 , ambient light data  722 , geographic location data  724 , proximity data  726 , and/or other environmental data  728 . The temporal data  710  may include time data  730 , date data  732 , and/or other time-based data  734 . The event data  712  may include user-initiated response data  736  and/or other event-related data  738 . 
     In certain embodiments, the input control application  704 , output control application  706 , and/or another application configure the input and/or output characteristics of a media device based on a determination of the associated conditions for the media device by the decision application  702 . The decision application  702  may determine the associated conditions for the media device by comparing received condition data with a known set of condition vectors. The decision application  702  may include a decision model  740 , a condition recognition application  742 , and/or a condition training application  744 . In one embodiment, the model  740  includes a statistical model and/or predictive model for determining a user&#39;s desired input or output characteristics based on the received condition data. An output characteristic may include an alert characteristic. 
       FIG. 8  is a diagram of a condition vector  800  including various associated conditions according to an illustrative embodiment of the invention. The condition vector  800  may include one or more elements such as, without limitation, time data  802 , date data  804 , POM data  806 , ambient sound data  808 , ambient light data  810 , geographic location data  812 , proximity (to user) data  814 , and/or user-response/user-initiated event data  816 . In certain embodiments, the environmental data  708 , temporal data  710 , and event data  712  are combined, arranged, organized, referenced, and/or referred to as a condition vector  800 . 
     In one embodiment, a media device generates an environmental sensor signal and/or signals including environmental data  708 , generates a temporal signal and/or signals including temporal data  710 , and/or generates an event signal and/or signals including event data  712 . The various data  708 ,  710 , and  712  from the various signals may be combined to form a received condition vector. The decision application  702  may compare the received condition vector with one or more known condition vectors that are stored within the database and/or data store  714  to determine associated conditions for a media device. Accordingly, the condition vector  800  may be representative of a received condition vector formed from the detected and/or sensed associated conditions of a media device at a particular instant or over a particular period. Alternatively, the condition vector  800  may be representative of a known or stored condition vector within the database  714 . 
     In one embodiment, the condition vector  800  includes one or more known and/or stored condition vectors that operate as a rule set and/or rule sets to determine input and/or output characteristics of a media device. In certain embodiments, the input control application  704  determines an input interface feature and/or characteristic based on a decision signal from the decision application  702 . In certain embodiments, the output control application  706  determines an output interface feature and/or characteristic based on a decision signal from the decision application  702 . In one embodiment, the output control application  706  determines an alert pattern and/or characteristic based on a decision signal from the decision application  702 . 
     In one embodiment, any element of a known and/or stored condition vector  800 , e.g. time data element  802 , may include a range of values. Accordingly, a known condition vector may function as a rule set that defines a period of time for which an expected input or output characteristic is to be configured. For example, the time data  802  field or element may specify a time range associated with normal work hours, e.g., 9am-5pm. Thus, a received condition vector having a time stamp and/or time data set at 10:30 am would satisfy or fall within the work hours time range set within the known condition time data element  802 . Depending on the type of decision model employed by a model application  740 , the model application  740  could select a particular input and/or output characteristic based at least in part on whether the received time data element was in the defined range of the time data element  802  of a known condition vector or rule set. 
     Other elements of a known condition vector or rule set may include ranges of values. For example, the date data element  804  could specify a range of days in the week, e.g., weekdays. The POM data element  806  could specify a range of movements or range of rates of movement, e.g., speed of tilting a media device. The ambient noise data element  808  could specify a threshold amount of sound intensity, e.g., whether it is noisy or quiet. The ambient light data element  810  could specify a threshold amount of light intensity, e.g., whether it is night or day. The geographic location data element  812  could specify a threshold distance from a particular geographic point, e.g., the location of a courthouse. The proximity data element  814  could specify a threshold proximity to a media device user. The event data element  816  could specify a range of user response types or affects to a media device. 
     In one embodiment, the known condition vector  800  and/or rule set includes an event counter element. The event counter element may include a count of the number of times that an event has occurred, has not occurred, or should have occurred. For example, if a user fails to answer a call after several alert instances of the same vibration pattern or after several attempted calls using the same vibration pattern, the decision application  702  may, after a threshold and/or limit of instances is reached, change the alert to a different vibration pattern and/or other alert pattern. Because there may be instances where a media device user may become desensitized to a particular alert pattern, by employing the event counter, the decision application  702  can advantageously adjust and/or change a particular alert pattern to make it less likely that a user will ignore subsequent alert patterns. In another embodiment, the decision application  702  may periodic change the alert pattern in a deterministic and/or random manner after a period of time so the alert pattern continuously changes. Such continuously and/or periodic changing of the alert pattern may be more readily perceivable by a user. 
       FIG. 9  is a diagram of a database  900  including one or more lists associating condition vectors with input or output interface configurations and/or characteristics  908  of one or more applications  902 ,  904 , and  906  within a media device according to an illustrative embodiment of the invention. In one embodiment, an output interface configuration includes an alert pattern. An output interface configuration may include, without limitation, a display setting, an audio setting, a GUI configuration, a video output setting, a vibration output setting, a communications output setting, an RF output setting, and/or any other output from a media device. An input configuration setting may include, without limitation, a display setting, a GUI configuration, an audio input setting, a video input setting, a communications input setting, an RF input setting, a POM input setting, and/or any other form of input setting. A setting may include an intensity level setting, an on/off setting, a pattern arrangement, a sequence arrangement, type of protocol, and/or any other characteristic of an interface input or output signal or representation. For example, for a speaker output, the setting may include an audio volume setting. For a microphone, the setting may include an input gain level of received audio signals. The database  900  may include multiple lists  902 ,  904 , and  906  of configurations  908  where each list is associated with a particular application of a media device such as media device  100 . 
     In operation, in one embodiment, configurations  1  through N are associated with condition vectors  1  through N respectively. Thus, when the application  902  is running, the application  902  may continuously compare received sensor signals and other condition signals with the list of condition vectors associated with application  902  to determine when one or more of the input or output configurations is to be selected. By monitoring the sensor signal inputs from the environmental sensors, the time data, and/or event data, the application  902  may recognize that the associated conditions for a media device match condition vector  1 . Therefore, the output configuration  1  associated with condition vector  1  is selected. Configuration  1  may be, for example, an alert pattern that is appropriate for the detected associated conditions of the media device at that instant or period of time. 
       FIGS. 10A-C  include a flow diagram of an exemplary process  1000  for determining an alert pattern for a telephone application of a media device based on associated conditions of the media device according to an illustrative embodiment of the invention. In one embodiment, the media device employs a decision application  702  that uses a matching algorithm and/or decision tree to determine associated conditions of the media device and, thereby, to determine a particular output alert pattern or characteristics for such associated conditions. First, the media device receives and incoming cellular telephone call [Step  1002 ]. The media device may be running a telephone application including a decision routine such as decision application  702  of  FIG. 7 . Alternatively, the telephone application uses one or more procedure calls to the decision application  702  to enable the decision application  702  to determine the desired alert pattern based on the associated conditions of the media device. 
     In one embodiment, the decision application  702  compares the received data with one or more condition vectors  800  and/or rule sets such as in database  714  and/or in the database  900 . At step  1004 , the decision application  702  determines whether the received date data is a weekday. If yes, the application  702  determines whether the received time data is during work hours at step  1006 . If yes, the application  702  determines whether the received proximity data indicates that the media device is in proximity to the user at step  1008 . If in close proximity, the decision application  702  determines that the alert pattern should vibrate the media device. If the application  702  determines that the device is not in close proximity, then the application  702  determines whether the media device is at rest at step  1010 . If yes, the application  702  determines whether the media device display is oriented and/or facing in an upward direction at step  1012 . If yes, the application  702  determines whether the ambient noise and/or sound level is above normal based on the received ambient noise data at step  1014 . If yes, the application  702  determines that the alert pattern includes a loud ringtone or ring. If no, the application  702  determines whether the ambient noise and/or sound level is below normal based on the received ambient noise data at step  1016 . If yes, the application  702  determines that the alert pattern include a low and/or quiet ringtone or ring. If no, the application  702  determines that the alert pattern include a normal volume ringtone or ring. 
     In certain embodiments, any type of time criteria may be used. For example, the decision application  702  may check for, without limitation, a particular day of the week, date in the year, time of day, date and time, date and time range, range of days in a week, range of times in a day, or other like period. 
     Once an incoming call alert is detected by a media device user, the user may wish to affect the alert by taking an action such as manipulating the POM of the media device. Such action may be detectable as an event by the media device. Accordingly, after a ringtone or ring is generated at either step  1014  or  1016 , the user may initiate a subsequent event at step  1018  that is detected by at least one environmental sensor of the media device. At least one environmental sensor may then send a sensor signal to the decision application  702 . The decision application may then compare the event signal or data  712  with an event vector element  816  to determine whether the alert pattern and/or output is to be adjusted. For example, at step  1020 , the decision application  702  determines whether an environmental sensor detected a user word. For instance, a user may say “silence” when the media device is ringing. If yes, the alert pattern is changed to a silent mode. If no, the alert pattern remains at one of the setting/patterns determined by steps  1014  or  1016 . 
     By way of another example, a user may turn the media device over so that its display is face down. A sensor may detect the change in orientation of the media device and send an event signal or data  712  to the decision application  702 . The decision application may then compare the event signal or data  712  with an event vector element  816  to determine whether the alert pattern and/or output is to be adjusted. At step  1022 , the decision application  702  determines that the media device display is face down, resulting in the alert pattern being adjusted to silent mode. By way of a further example, a user may simply touch a display screen of the media device to silence the alert output at step  1024 . In one embodiment, a user may touch the media device at any location, such as a key on a keypad, to cause the media device to silence the alert. Again, the display contact is detected by a display element, causing an event signal or data  716  to be sent to the decision application  702 . The decision application then determines that the subsequent display touch event occurred, resulting in the alert output being adjusted to silent mode. 
     In certain embodiments, a condition vector  800  may include ambient noise spectrum data. Accordingly, the decision application  702  may have the capability to determine a particular frequency range, ranges, and/or tones of ringtone or ring alert outputs that are more readily detectable by a user in comparison to the ambient noise spectrum. In one embodiment, the acoustic tuning and/or equalization of a speaker is dynamically adjusted in response to the surrounding ambient noise spectrum to enhance a user ability to hear, understand, and/or detect an alert or other audio output. In certain embodiments, an alert output setting, e.g., ring volume, is adjusted according to a discrete set of volume levels. In other embodiments, an output and/or input setting may be adjusted relative to a received or detected environment signal. For example, the alert ringtone volume may be adjusted such that the output volume is at least about 5, 10, 20, 30, 40, 50, 60, 70, 80, 90, 100 decibels (db), or any other suitable decibel level above the detected ambient noise volume. 
     The  FIG. 10A-C  process is exemplary in that the desired input or output characteristic settings may be configured differently depending on the preferences of a particular user. While one user may desire that a media device ring loudly under one set of conditions, another user, under the same conditions, may desire that the media device vibrate in a particular pattern along with periodically flashing an incoming caller identifier. In certain embodiments, a user can configure a plurality of combinations of alert patterns. An alert pattern may include, without limitation, one or more vibration patterns, one or more audio patterns, one or more display patterns, one or more text sequences, one or more caller identifiers, one or more communications sender identifiers, one or more light emitting sequences, one or more video sequences, one or more audio voice terms, and one or more combinations of the foregoing alert patterns. An identifier may include, without limitation, a telephone number, an email address, a name, a photograph, a video, an image, a URL, an Internet Protocol (IP) address, and/or a serial number. 
     Referring to  FIG. 7 , the decision application  702  may employ one or more types of decision models  740  to select an input and/or output characteristic of a media device. The sophistication of the implemented decision model  740  and/or models may vary depending on desired selectivity and available processing power of a media device, among other factors. 
     In one embodiment, as discussed above, the decision application  702  employs a condition vector  800  matching model. Using this model, the decision application  702  may compare a received condition vector with one or more known condition vectors  800 . In one embodiment, if all of the conditions of each element of the received condition vector match and/or satisfy all of the conditions of the known condition vector  800 , then the decision application  702  identifies the associated conditions of the media device and related desired input and/or output characteristic configuration. If, for example, the associated conditions match the condition vector  1  in the database  900 , then the decision application  702  determines that the associated input or output characteristics are to be set to configuration  1  which is associated with the condition vector  1  in the database  900 . In one embodiment, if there is no match of all elements with a known condition vector, the decision application  702  may designate a default configuration. In another embodiment, if there is no match of all elements with a known condition vector, the decision application  702  may select the closest condition vector and its associated configuration. In a further embodiment, the decision application  702  may apply another model such as, for example, a predictive and/or statistical model, to determine the most appropriate input or output characteristic configuration  908  for the associated conditions of the media device. 
     In another embodiment, the decision application  702  employs a weighted vector matching model  740 . Accordingly, the application  702  may assign different weights for each element of a condition vector  800  depending on the type of input, output, and/or application that is running on the media device. For example, the decision application  702  may assign a boolean value of 1 for each element of a received condition vector that matches an associated element of a known condition vector. Depending on the type of input, output, or application of the media device, the decision application  702  uses multipliers or co-factors that increase or decrease the relative value one element with respect to another element. For example, if the interface output of interest is speaker volume, then the ambient noise element  808  may be assigned a higher value and/or higher value multiplier than, for example, the POM element  806 . This may be the case because the orientation of the media device may be less important than the need to ensure that the volume level is adequate for the surrounding ambient noise conditions. 
     In one embodiment, the decision application  702  selects the closest matching condition vector  800  to the received condition vector. However, where there are multiple close condition vectors, the decision application  702  may distinguish among such condition vectors by accounting for the different weighting of the condition vector  800  elements. For example, if two known condition vectors have six matching elements to a received condition vector, the decision application  702  may then compare the elements to determine whether any are different between the two known condition vectors  800 . If, for instance, condition vector  1  has a matching ambient noise element, but no matching POM element while condition vector  2  has a matching POM element, but no matching ambient noise element, the decision application  702  may select condition vector  1  as the closest for the speaker output volume configuration because the noise element has a higher weight for such output characteristic. In another embodiment, the decision application  702  computes a total score based on the weighted values for all of the matching elements of condition vectors  1  and  2 , and selects the condition vector having the highest score. 
     In another embodiment, the decision application  702  employs a predictive and/or statistical model  740  to determine the desired input and/or output characteristics for particular associated conditions of a media device. To a certain extent, the predictive and/or statistical model  740  may employ more sophisticated decision approaches based on decision trees, matching techniques, data and/or factor weighing. The decision model  740  may include at least one of a linear regression model, a non-linear regression model, a logistic regression model, a Bayesian network model, a Markov model, a fuzzy model, and a propensity score to select one or more input or output characteristics. The decision model may assign a weight to each of the sensor signals and/or elements of a condition vector  800 . 
     In one embodiment, the decision application  702  employs prospective modeling to predict desired input or output characteristics for a given set of associated conditions of a media device. In one embodiment, the application  702  uses demographic user IO preference information from a population of media device users. In another embodiment, the application  702  uses personal user IO preference information from the particular user of a media device. In certain embodiments, numerous variables may be used in developing a predictive model  740  based on user IO preferences that may include variables based on user age, gender, education, musical preferences, social preferences, technical preferences, and other like demographic profiles. 
     In certain embodiments, the decision application  702  employs a condition recognition routine  742  and/or condition training routine  744  to enable the identification of associated conditions of a media device. 
       FIG. 11  is a flow diagram of a process  1100  for inputting and identifying condition vectors  800  associated with particular input/output characteristic configurations based on one or more pattern recognition algorithms according to an illustrative embodiment of the invention. In certain embodiments, the condition recognition application  742  and condition training application  744  employ one or more pattern recognition algorithms and/or techniques to identify various associated conditions and/or condition vectors of a media device. First, the media device  100  is subjected to associated conditions including its surrounding physical environment [Step  1102 ]. The media device  100  employs one or more environmental sensors to measure associated conditions. In certain embodiments, the applications  742  and  744  account for bandwidth, resolution, sensitivity, distortion, signal-to-noise ratio, latency, and other issues with regard to data acquisition using the one or more environmental sensors [Step  1104 ]. The applications  742  and  744  may perform pre-processing of the sensor signals to remove noise and/or to isolate patterns of interest from background information [Steps  1106  and  1120 ]. Then, the applications  742  and  744  may perform feature extraction by finding new representations in terms of identified features of sensor signals [Steps  1108  and  1122 ]. Particular features of sensor signals and/or condition vector elements may be identified as being more relevant for pattern identification [Steps  1110  and  1124 ]. Feature selection may include identifying discriminative features of sensor signals such as similar values for similar patterns or different values for different patterns. Feature selection may include identifying invariant features such as with respect to translation, rotation, and/or scale or sensor signals. Feature selection may include identifying robust features with respect to occlusion, distortion, deformation, and variations in environment. 
     The training application  744  may capture training data in the form of an input from the user [Step  1118 ]. In one embodiment, an application may provide an option that enables a user to input a condition vector into the database  900  associated with the current conditions of the media device. For example, whenever a user receives a call, once the call is completed, the user may be presented with the option to set a desired alert pattern associated with the conditions of the media device at the time when the call was received. In another embodiment, the decision application  702  allows a user to define or adjust element settings of known condition vectors. After pre-processing, feature extraction, and selection, the application  744  may then perform model learning and estimation whereby the application  744  learns to map between features and pattern groups and categories of sensor signals [Step  1126 ]. The application  744  may select a pattern recognition model that is parametric or non-parametric. The application  744  may select a type of model that include at least one of templates, decision-theoretic or statistical, syntactic or structural, neural, and hybrid forms of pattern recognition analysis [Step  1128 ]. 
     Once a particular model is selected, the condition recognition application  742  performs a classification and/or matching of the received sensor signals and/or received condition vector using features and learned models from the condition training application  744  to assign the received condition vector to a category of patterns. The application  742  may then compare the received sensor signals and/or condition vector with the set of known condition vectors  800  in the database  900  to find the closest match between the received condition vector and the stored array of known condition vectors [Step  1112 ]. The application  742  may perform post-processing by evaluating its confidence in the decision [Step  1114 ]. The application  742  may then decide which input and/or output characteristic configuration of the database  900  corresponds to the received condition vector [Step  1116 ]. 
     In certain embodiments, the features of the known condition vectors  800  may be limited to minimize costs in processing power and storage. Accordingly, the selectivity of identifying particular associated conditions of a media device may vary depending on the number of elements, points, or features stored or used for each known condition vector. In another embodiment, the known condition vector can be pre-generated and stored in the media device by the manufacturer or another entity. 
     The condition recognition application  742  may perform pattern recognition based on at least one of Bayes Decision Theory, Generative methods, discriminative methods, non-metric methods, algorithm-independent machine learning, unsupervised learning and clustering, and like techniques. The Bayes Decision techniques may include, without limitation, at least one of Bayes Decision Rule, minimum error rate classification, normal density and discriminant functions, error integrals and bounds, Bayesian networks, and compound decision theory. The Generative methods may include, without limitation, at least one of maximum likelihood and Bayesian parameter estimation, sufficient statistics, various common statistical distributions, dimensionality and computational complexity, principal components analysis, fisher linear discriminant, expectation maximization, sequential data, hidden Markov models, and non-parametric techniques including density estimation. The discriminative methods may include, without limitation, distance-based methods, nearest neighbor classification, metrics and tangent distance, fuzzy classification, linear discriminant functions (hyperplane geometry, gradient descent and perceptrons, minimum squared error procedures, and support vector machines), and artificial neural networks. The non-metric methods may include, without limitation, recognition with strings and string matching. The algorithm-independent machine learning techniques may include, without limitation, no-free lunch theorem, bias and variance, re-sampling for estimation, bagging and boosting, estimation of misclassification, and classifier combinations. 
     The media device may support input and/or output interfacing control for numerous applications including, without limitation, e-mail, texting, word processing, interface navigation, data searching, web surfing, database management, remote control systems, or any application operating with a media device. 
     It will be apparent to those of ordinary skill in the art that methods involved in the present invention may be embodied in a computer program product that includes a computer usable and/or readable medium. For example, such a computer usable medium may consist of a read only memory device, such as a CD ROM disk or conventional ROM devices, or a random access memory, such as a hard drive device or a computer diskette, or flash memory device having a computer readable program code stored thereon. 
     It is understood that the various features, elements, or processes of the foregoing figures and description are interchangeable or combinable to realize or practice the invention describe herein. Those skilled in the art will appreciate that the invention can be practiced by other than the described embodiments, which are presented for purposes of illustration rather than of limitation, and the invention is limited only by the claims which follow.

Metadata:
Filing Date: 20071228
Publication Date: 20140916
Grant Date: 20140916
Priority Date: 20071228
Inventors: CULBERT MICHAEL
TUPMAN DAVID JOHN
KEEN DANIEL SHAWN
GUETTA ANTHONY JOSEPH
DU BOIS RYAN JEFFREY
TISCARENO VICTOR M.
HARRINGTON DAVID
CHICK STEPHEN JOHN
MINOO JAHAN
LAEFER JAY STEVEN
SAUL KEVIN
FORSTALL SCOTT
Assignee: APPLE INC
CPC Classifications: [{"code": "H04M2250/12", "inventive": false, "first": false, "tree": "[]"}, {"code": "H04M1/72451", "inventive": false, "first": false, "tree": "[]"}, {"code": "H04M1/72457", "inventive": false, "first": false, "tree": "[]"}, {"code": "H04M1/72454", "inventive": true, "first": true, "tree": "[]"}, {"code": "H04M2250/12", "inventive": false, "first": false, "tree": "[]"}, {"code": "H04M1/72457", "inventive": false, "first": false, "tree": "[]"}, {"code": "H04M1/72451", "inventive": false, "first": false, "tree": "[]"}, {"code": "H04M1/72454", "inventive": true, "first": true, "tree": "[]"}, {"code": "H04M2250/12", "inventive": false, "first": false, "tree": "[]"}, {"code": "H04M1/72572", "inventive": false, "first": false, "tree": "[]"}, {"code": "H04M1/72569", "inventive": true, "first": true, "tree": "[]"}, {"code": "H04M1/72566", "inventive": false, "first": false, "tree": "[]"}]
Family ID: 40797540