Patent Publication Number: US-2016246368-A1

Title: Piezoelectric sensor assembly for wrist based wearable virtual keyboard

Description:
RELATED APPLICATIONS 
     This application is a continuation-in-part of U.S. patent application Ser. No. 14/142,711, to Comacho-Perez, et al., entitled WRIST BASED WEARABLE VIRTUAL KEYBOARD, filed Dec. 27, 2013, the entire disclosure of which is incorporated herein by reference. 
    
    
     BACKGROUND 
     The subject matter described herein relates generally to the field of electronic devices and more particularly to a piezoelectric sensor assembly for a wrist based virtual keyboard which may be used with electronic devices. 
     Many electronic devices such as tablet computers, mobile phones, electronic readers, computer-equipped glasses, etc., lack conventional keyboards. In some circumstances it may be useful to communicate with such electronic devices using a keyboard-like interface. Accordingly systems and techniques to provide for virtual keyboards may find utility. 
    
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
       The detailed description is described with reference to the accompanying figures. 
         FIG. 1A  is a schematic illustration of wrist-based wearable virtual keyboard which may be adapted to work with electronic devices in accordance with some examples. 
         FIG. 1B  is a schematic illustration of an architecture for a wrist-based wearable virtual keyboard which may be adapted to work with electronic devices in accordance with some examples. 
         FIG. 2  is a schematic illustration of components of an electronic device in accordance which may be adapted to work with a wrist-based wearable virtual keyboard in accordance with some examples. 
         FIGS. 3A-3C  are schematic illustrations of gestures which may be used with a wrist-based wearable virtual keyboard in accordance with some examples. 
         FIG. 4  is a series of graphs illustrating response curves from sensors which may be used with a wrist-based wearable virtual keyboard in accordance with some examples. 
         FIG. 5  is a series of graphs illustrating mel-frequency cepstral coefficients of responses from sensors device which may be used with a wrist-based wearable virtual keyboard in accordance with some examples. 
         FIG. 6A  is a schematic illustration of a finger-based keyboard mapping which may be used with a wrist-based wearable virtual keyboard in accordance with some examples. 
         FIG. 6B  is a schematic illustration of a remote electronic device which may be used with a wrist-based wearable virtual keyboard in accordance with some examples. 
         FIGS. 7A-7B, 8A-8B, and 9A-9B  are flowcharts illustrating operations in a method to use a wrist-based wearable virtual keyboard for electronic devices in accordance with some examples. 
         FIG. 10A  is a schematic, top view of a piezoelectric sensor assembly for a wrist based wearable virtual keyboard for electronic devices in accordance with some examples. 
         FIG. 10B  is a schematic, end view of a piezoelectric sensor assembly for a wrist based wearable virtual keyboard for electronic devices in accordance with some examples. 
         FIG. 10C  is a schematic, side view of a piezoelectric sensor assembly for a wrist based wearable virtual keyboard for electronic devices in accordance with some examples. 
         FIG. 11  is a schematic, cross-sectional view of a piezoelectric sensor assembly for a wrist based wearable virtual keyboard for electronic devices in accordance with some examples. 
         FIG. 12  is a schematic, cross-sectional view of a piezoelectric sensor assembly for a wrist based wearable virtual keyboard for electronic devices in accordance with some examples. 
     
    
    
     DETAILED DESCRIPTION 
     Described herein are exemplary systems and methods to implement intelligent recording in electronic devices. In the following description, numerous specific details are set forth to provide a thorough understanding of various examples. However, it will be understood by those skilled in the art that the various examples may be practiced without the specific details. In other instances, well-known methods, procedures, components, and circuits have not been illustrated or described in detail so as not to obscure the particular examples. 
     Briefly, the subject matter described here addresses the concerns set forth above at least in part by wrist based wearable virtual keyboard which may be used with electronic devices. In some examples the wrist based wearable virtual keyboard may comprise a member which may be adapted to fit around a wrist of a user. The member may comprise a plurality of sensors positioned to generate signals in response to parameters such as motion, orientation, or position of the user&#39;s hand and fingers. A controller is coupled to the sensors and includes logic to analyze the signals generated in response to movements of the users to associate a symbol with the signals. The symbol may be transmitted to one or more electronic devices, which may present the symbol on a display. 
     Specific features and details will be described with reference to  FIGS. 1-12 , below. 
       FIG. 1A  is a schematic illustration of wrist-based wearable virtual keyboard  100  which may be adapted to work with electronic devices in accordance with some examples, and  FIG. 1B  is a schematic illustration of an architecture for a wrist-based wearable virtual keyboard which may be adapted to work with electronic devices in accordance with some examples. 
     Referring to  FIGS. 1A-1B , in some examples a wrist based virtual keyboard  100  may comprise a member  110  and a plurality of sensors  120  disposed along the length of the member  110 . The sensors  120  are communicatively coupled to a control logic  130  by a suitable communication link. Control logic  130  may be communicatively coupled to one or more remote electronic devices  200  by a suitable communication link. 
     For example, control logic  130  may be a controller, an application specific integrated circuit (ASIC), a general purpose processor, a graphics accelerator, an application processor, or the like. 
     For example, member  110  may be formed from any suitable rigid or flexible material such as a polymer, metal, cloth or the like. Member  110  may comprise an elastic or other material which allows the member  110  to fit snugly on a proximal side of a user&#39;s wrist, such that the sensors  120  are positioned proximate the wrist of a user. 
     Sensors  120  may comprise one or more sensors adapted to detect at least one of an acceleration, an orientation, or a position of the sensor, or combinations thereof. For example, sensors  120  may comprise one or more accelerometers  122 , gyroscopes,  124 , magnetometers  126 , piezoelectric sensors  128 , or the like. 
     Control logic  130  may be embodied as a general purpose processor, a network processor (that processes data communicated over a computer network  603 ), or other types of a processor (including a reduced instruction set computer (RISC) processor or a complex instruction set computer (CISC)). The specific implementation of control logic  130  is not critical. 
     Control logic  130  may comprise, or be coupled to, one or more input/output interfaces  136 . In some examples input/output interface(s) may include, or be coupled to an RF transceiver  138  to transceive RF signals. RF transceiver may implement a local wireless connection via a protocol such as, e.g., Bluetooth or 802.11X. IEEE 802.11a, b or g-compliant interface (see, e.g., IEEE Standard for IT-Telecommunications and information exchange between systems LAN/MAN—Part II: Wireless LAN Medium Access Control (MAC) and Physical Layer (PHY) specifications Amendment 4: Further Higher Data Rate Extension in the 2.4 GHz Band, 802.11G-2003). Another example of a wireless interface would be a general packet radio service (GPRS) interface (see, e.g., Guidelines on GPRS Handset Requirements, Global System for Mobile Communications/GSM Association, Ver. 3.0.1, December 2002) or other cellular type transceiver that can send/receive communication signals in accordance with various protocols, e.g., 2G, 3G, 4G, LTE, etc. 
     Control logic  130  may comprise, or be coupled to, a memory  134 . Memory  134  may be implemented using volatile memory, e.g., static random access memory (SRAM), a dynamic random access memory (DRAM), or non-volatile memory, e.g., phase change memory, NAND (flash) memory, ferroelectric random-access memory (FeRAM), nanowire-based non-volatile memory, memory that incorporates memristor technology, three dimensional (3D) cross point memory such as phase change memory (PCM), spin-transfer torque memory (STT-RAM) or NAND flash memory. 
     Control logic  130  further comprises an analysis module  132  to analyze signals generated by the sensors  120  and to determine a symbol associated with the signals. The signal may be transmitted to a remote electronic device  200  via the input/output interface  136 . In some examples the analysis module may be implemented as logic instructions stored in non-transitory computer readable medium such as memory  134  and executable by the control logic  130 . In other examples the analysis module  132  may be reduced to microcode or even to hard-wired circuitry on control logic  130 . 
     A power supply  140  may be coupled to sensors  120  and control logic  130 . For example, power supply  140  may comprise one or more energy storage devices, e.g., batteries or the like. 
       FIG. 2  is a schematic illustration of components of an electronic device in accordance which may be adapted to work with a wrist-based wearable virtual keyboard in accordance with some examples. In some aspects electronic device  200  may be embodied as a mobile telephone, a tablet computing device, a personal digital assistant (PDA), a notepad computer, a video camera, a wearable device like a smart watch, smart wrist band, smart headphone, or the like. The specific embodiment of electronic device  200  is not critical. 
     In some examples electronic device  200  may include an RF transceiver  220  to transceive RF signals and a signal processing module  222  to process signals received by RF transceiver  220 . RF transceiver  220  may implement a local wireless connection via a protocol such as, e.g., Bluetooth or 802.11X. IEEE 802.11a, b or g-compliant interface (see, e.g., IEEE Standard for IT-Telecommunications and information exchange between systems LAN/MAN—Part II: Wireless LAN Medium Access Control (MAC) and Physical Layer (PHY) specifications Amendment 4: Further Higher Data Rate Extension in the 2.4 GHz Band, 802.11G-2003). Another example of a wireless interface would be a general packet radio service (GPRS) interface (see, e.g., Guidelines on GPRS Handset Requirements, Global System for Mobile Communications/GSM Association, Ver. 3.0.1, December 2002). 
     Electronic device  200  may further include one or more processors  224  and a memory module  240 . As used herein, the term “processor” means any type of computational element, such as but not limited to, a microprocessor, a microcontroller, a complex instruction set computing (CISC) microprocessor, a reduced instruction set (RISC) microprocessor, a very long instruction word (VLIW) microprocessor, or any other type of processor or processing circuit. In some examples, processor  224  may be one or more processors in the family of Intel® PXA27x processors available from Intel® Corporation of Santa Clara, Calif. Alternatively, other processors may be used, such as Intel&#39;s Itanium®, XEON™, ATOM™, and Celeron® processors. Also, one or more processors from other manufactures may be utilized. Moreover, the processors may have a single or multi core design. 
     In some examples, memory module  240  includes random access memory (RAM); however, memory module  240  may be implemented using other memory types such as dynamic RAM (DRAM), synchronous DRAM (SDRAM), and the like. Memory  240  may comprise one or more applications including a recording manager  242  which execute on the processor(s)  222 . 
     Electronic device  200  may further include one or more input/output interfaces such as, e.g., a keypad  226  and one or more displays  228 , speakers  234 , and one or more recording devices  230 . By way of example, recording device(s)  230  may comprise one or more cameras and/or microphones An image signal processor  232  may be provided to process images collected by recording device(s)  230 . 
     In some examples electronic device  200  may include a low-power controller  270  which may be separate from processor(s)  224 , described above. In the example depicted in  FIG. 2  the controller  270  comprises one or more processor(s)  272 , a memory module  274 , an I/O module  276 , and a virtual keyboard manager  278 . In some examples the memory module  274  may comprise a persistent flash memory module and the authentication module  276  may be implemented as logic instructions encoded in the persistent memory module, e.g., firmware or software. The I/O module  276  may comprise a serial I/O module or a parallel I/O module. Again, because the adjunct controller  270  is physically separate from the main processor(s)  224 , the controller  270  can operate independently while the processor(s)  224  remains in a low-power consumption state, e.g., a sleep state. Further, the low-power controller  270  may be secure in the sense that the low-power controller  270  is inaccessible to hacking through the operating system. 
     As described briefly above, a wrist based wearable virtual keyboard  100  may be disposed about a user&#39;s wrist and used to detect motion, position, and orientation, or combinations thereof.  FIGS. 3A-3C  are schematic illustrations of gestures which may be used with a wrist based wearable virtual keyboard in accordance with some examples. For example, a wrist based wearable virtual keyboard  100  may be used to detect a finger tap on a surface  310  or a finger slide on a surface  310 , as illustrated in  FIG. 3A . Alternatively, or in addition, a wrist based wearable virtual keyboard  100  may be used to detect contact with a hand or arm of the user proximate the wrist based wearable virtual keyboard  100 , as illustrated in  FIG. 3B . Alternatively, or in addition, the wrist based wearable virtual keyboard  100  may be used to detect particular patterns of contact with the fingers of a user, as illustrated in  FIG. 3C . 
     The sensors  120  generate characteristic response curves in response to the various types of contact depicted in  FIGS. 3A-3C . For example,  FIG. 4  is a series of graphs illustrating response curves from sensors  120  which may be used with a wrist-based wearable virtual keyboard in accordance with some examples. The curves denote the output from specific sensors made in response to specific movements by specific fingers of a user. In operation, data from the response curves may be stored in memory, e.g., memory  134 , to construct a profile of response curves for a user of a wrist based wearable virtual keyboard  100 . 
     Similarly,  FIG. 5  is a series of graphs illustrating mel-frequency cepstral coefficients of responses from sensors device which may be used with a wrist-based wearable virtual keyboard  100  in accordance with some examples. Referring to  FIG. 5 , acceleration/vibration data from a dragging or a rubbing motion such as when a user rubs a finger against a surface or rubs an object against a hand or arm may be processed by analysis module  132  to generate mel-frequency cepstral coefficients (MFCCs) associated with the dragging motion. Data characterizing the mel-frequency cepstral coefficients may be stored in memory, e.g., memory  134  to construct a profile of response curves for a user of a wrist based wearable virtual keyboard  100 . 
     With data representing the various sensor responses to different hand motions, positions, and orientations stored in memory a virtual keyboard mapping may be generated.  FIG. 6A  is a schematic illustration of a finger-based keyboard mapping which may be used with a wrist-based wearable virtual keyboard in accordance with some examples. 
     Referring to  FIG. 6A , in some examples a set of symbols may be assigned to each finger. A symbol may be selected by tapping or scratching each finger a predetermined number of times. Additional symbols or functions may be mapped to alternative hand gestures, e.g., specific motions or orientations of a user&#39;s hand. 
       FIG. 6B  is a schematic illustration of a remote electronic device which may be used with a wrist-based wearable virtual keyboard in accordance with some examples. As illustrated in  FIG. 6B , in some examples the symbol assignment may be presented on a display of an electronic device  200 . 
     Having described various structures to implement intelligent recording in electronic devices, operating aspects will be explained with reference to  FIGS. 7A-7B, 8A-8B, and 9A-9B , which are flowcharts illustrating operations in a method to use a wrist-based wearable virtual keyboard for electronic devices in accordance with some examples. Some operations depicted in the flowchart of  FIGS. 7A-7B, 8A-8B , and  9 A- 9 B may be implemented by the analysis module  132 . 
     In some examples a user may be prompted to execute a series of training exercises for the wearable virtual keyboard  100 . The training exercises may be designed to obtain measurements from sensors  120  when the user implements hand motions corresponding to various symbols. One example of a training methodology is depicted in  FIG. 7A . Referring to  FIG. 7A , at operation  710  the virtual keyboard manager  242 / 278  in electronic device  200  presents a virtual keyboard and a symbol mapping on a display  228  of electronic device  200 . 
     At operation  715  the virtual keyboard manager  242 / 278  prompts a user to follow the mapping of the virtual keyboard. By way of example, virtual keyboard manager  242 / 278  may present a series of graphics on the display  228  of electronic device prompting a user to implement gestures (e.g., finger taps, drags, hand rotations, etc.) which correspond to a symbol. 
     At operation  720  the control logic  130  of wearable virtual keyboard  100  receives signals from the sensors  120  in response to the gesture implemented by the user. The control logic  130  may sample the responses from all of the sensors  120  or only from a subset of the sensors  120 . For example, the control logic may sample only the sensors closest to a finger that is being tapped or otherwise used in a training exercise. In some examples the data may comprise acceleration, either from movement of a finger or arm, or from movement of skin, e.g., a vibration, response curves of the type depicted in  FIG. 4 . In other examples the data my comprise orientation data which may be stored alone or in combination with the acceleration data. In further examples the acceleration data may be processed to determine one or more characteristics such as a mel-frequency cepstral coefficient of the acceleration data. 
     At operation  725  signal data from the sensor(s)  120  and associated data stored in memory  134 . In some examples the data may be stored in association with the symbol that was presented on the display  228  of the electronic device  200 . 
     The operations depicted in  FIG. 7A  may be repeated to complete a mapping between hand movements and symbols representative of a conventional QWERTY keyboard. Additional keyboard functions (e.g., backspace, delete, escape, etc.) may be mapped to specific movements or gestures. The mapping may be stored in memory  134 . 
     With the mapping stored in memory  134  the virtual wearable keyboard  100  may be used as an input/output device with an electronic device  200 . Referring to  FIG. 7B , at operation  750  the control logic  130  in wearable virtual keyboard  100  receives a first signal from sensors  120 . By way of example, a user may implement a movement associated with a symbol as defined in the training process depicted in  FIG. 7A , e.g., a finger tap, double tap, triple tap, a finger drag, a hand rotation, or the like. 
     At operation  755  the analysis module  132  determines a symbol associated with the first signal received in operation  750 , and at operation  760  the analysis module  132  transmits one or more signals which comprises the symbol associated with the signal received in operation  750  to the electronic device  200 . At operation  765  the electronic device  200  receives the signal(s) and at operation  770  the electronic device presents the symbol on the display  228 . 
     The analysis module  132  may use a number of different techniques to make the determination depicted in operation  755 .  FIGS. 8A-8B and 9A-9B  depict operations associated with various techniques. In one example the analysis module matches acceleration data received from sensors  120  with acceleration data stored in memory  134  to select a symbol. Referring first to  FIG. 8A , at operation  810  the control logic  130  in wearable virtual keyboard  100  receives acceleration data from sensors  120 . At operation  815  the analysis module  132  compares the acceleration data to acceleration data stored in memory  134 . If, at operation  820 , a data record selected in memory does not match the acceleration data received from sensors  120  then control passes back to operation  815  and another data record is selected for comparison. 
     By contrast, if at operation  820  there is a match between the data record selected in memory and the acceleration data received from sensors  120  then control passes to operation  825  and the analysis module  132  selects the symbol associated with the matching data. 
     In another example the analysis module matches mel-frequency cepstral coefficient data derived from acceleration data received from sensors  120  with mel-frequency cepstral coefficient data stored in memory  134  to select a symbol. Referring to  FIG. 8B , at operation  850  the control logic  130  in wearable virtual keyboard  100  receives acceleration data from sensors  120 . At operation  855  the analysis module determines mel-frequency cepstral coefficient data from the acceleration data received from the sensors  120 . At operation  860  the analysis module  132  compares the mel-frequency cepstral coefficient data to mel-frequency cepstral coefficient data stored in memory  134 . If, at operation  865 , a data record selected in memory does not match the mel-frequency cepstral coefficient data determined from acceleration data received from sensors  120  then control passes back to operation  860  and another data record is selected for comparison. 
     By contrast, if at operation  865  there is a match between the data record selected in memory and the mel-frequency cepstral coefficient determined from the acceleration data received from sensors  120  then control passes to operation  870  and the analysis module  132  selects the symbol associated with the matching data. 
     In another example the analysis module  132  matches orientation data derived from acceleration data received from sensors  120  with orientation data stored in memory  134  to select a symbol. Referring to  FIG. 9A , at operation  910  the control logic  130  in wearable virtual keyboard  100  receives orientation data from sensors  120 . At operation  915  the analysis module  132  compares orientation data to orientation data stored in memory  134 . If, at operation  920 , orientation data associated with a data record selected in memory does not match orientation data determined from orientation data received from sensors  120  then control passes back to operation  860  and another data record is selected for comparison. 
     By contrast, if at operation  865  there is a match between the orientation data in the data record selected in memory and the orientation data received from sensors  120  then control passes to operation  870  and the analysis module  132  selects the symbol associated with the matching data. 
     In another example the analysis module  132  matches combined acceleration and orientation data derived from acceleration data received from sensors  120  with combined acceleration and orientation data stored in memory  134  to select a symbol. Referring to  FIG. 9A , at operation  950  the control logic  130  in wearable virtual keyboard  100  receives combined acceleration and orientation data from sensors  120 . At operation  955  the analysis module  132  compares combined acceleration and orientation data to orientation data stored in memory  134 . If, at operation  960 , combined acceleration and orientation data associated with a data record selected in memory does not match combined acceleration and orientation data determined from orientation data received from sensors  120  then control passes back to operation  955  and another data record is selected for comparison. 
     By contrast, if at operation  960  there is a match between the orientation data in the data record selected in memory and the orientation data received from sensors  120  then control passes to operation  965  and the analysis module  132  selects the symbol associated with the matching data. 
     Thus, the operations depicted in  FIGS. 7A-7B, 8A-8B, and 9A-9B  enable the a wearable virtual keyboard  100  to function as an input/output device for an electronic device  200 . In examples in which the sensors  120  comprise piezoelectric devices the sensors  120  may provide a user with tactile feedback, e.g., by vibrating, in response to one or more conditions. For example, a piezoelectric sensor  128  may vibrate when a user correctly enters a motion to generate a symbol. 
     In further examples the subject matter described herein includes a holder for a sensor such as a piezoelectric sensor  128  which may be used as described above. Examples of a holder  1000  are described with reference to  FIGS. 10A-10C  and  FIGS. 11-12 . In some examples a holder  1000  for a piezoelectric sensor comprises a body  1010  comprising a first surface  1012  and a second surface  1014 , opposite the first surface. In some examples the body  1010  further includes a recess  1030  formed in the first surface  1012  of the body to receive the piezoelectric sensor  128 . 
     In some examples the body  1010  is formed from a semi-rigid polymer material. Examples of suitable materials include any synthetic polymers such as poly (methyl methacrylate) commonly known as acrylic. 
     In some examples the body  1010  comprises at least one rounded edge  1016  proximate the first surface  1012 . In the examples depicted in  FIGS. 10A-10C and 11-12  all edges of the holder  1000  are rounded. However, in other embodiments only the edges  1016  surrounding the first surface  1012  of the holder are rounded. At least in part, the rounded edges serve to enhance the comfort and fit of the holder  1012  when pressed against the skin of a user. 
     In some examples the body  1010  is formed to a length indicated by the arrow labeled L in the figures which measures between 22 millimeters and 26 millimeters, a width indicated by the arrow labeled W which measures between 13 millimeters and 16 millimeters, and a thickness indicated by the arrow labeled T which measures between 2 millimeters and 4 millimeters. The specific measurements are not critical. 
     In some examples the piezoelectric sensor  128  is cylindrical in shape and has a thickness which measures between 0.07 millimeters and 0.17 millimeters the recess  1030  in the first surface is cylindrical in shape and has a depth which measures between 0.17 millimeters and 0.22 millimeters such that a surface  1052  of the piezoelectric sensor  128  is flush with the first surface  1012  of the holder when the piezoelectric sensor  128  is positioned in the recess  1030 . The specific measurements are not critical. 
     In some examples the recess is dimensioned to leave a gap which measures between 0.1 millimeters and 1.0 millimeters between an edge of the piezoelectric sensor  128  and the walls of the body  1030  that define the recess In some examples the piezoelectric sensor  128  is cylindrical in shape and has a diameter which measures between 9.8 millimeters and 10.1 millimeters. Similarly, the recess  1030  in the first surface is cylindrical in shape and has a diameter which measures between 10.2 millimeters and 10.4 millimeters. The specific measurements are not critical. In some examples at least a portion of the gap is filled with an adhesive material. 
     In some examples the body  1030  further comprises a channel  1040  formed in the first surface  1012  which extends from the recess to an edge of the holder  1000 . The channel  1040  may be dimensioned to receive one or more lead wires which couple the piezoelectric transducer to a remote device. 
     The following pertains to further examples. 
     Example 1 is a holder for a piezoelectric sensor, comprising a body comprising a first surface and a second surface, opposite the first surface and a recess formed in the first surface of the body to receive the piezoelectric sensor. 
     In Example 2, the subject matter of Example 1 can optionally include an arrangement in which the body is formed from a semi-rigid polymer material. 
     In Example 3, the subject matter of any one of Examples 1-2 can optionally include an arrangement in which the body comprises at least one rounded edge proximate the first surface. 
     In Example 4, the subject matter of any one of Examples 1-3 can optionally include an arrangement in which the piezoelectric sensor is cylindrical in shape and has a thickness which measures between 0.07 millimeters and 0.17 millimeters and the recess in the first surface is cylindrical in shape and has a depth which measures between 0.17 millimeters and 0.22 millimeters. 
     In Example 4, the subject matter of any one of Examples 1-3 can optionally include an arrangement in which a surface of the piezoelectric sensor is flush with the first surface of the holder. 
     In Example 6, the subject matter of any one of Examples 1-5 can optionally include an arrangement in which the piezoelectric sensor is cylindrical in shape and has a diameter which measures between 9.8 millimeters and 10.1 millimeters and the recess in the first surface is cylindrical in shape and has a diameter which measures between 10.2 millimeters and 10.4 millimeters. 
     In Example 7, the subject matter of any one of Examples 1-6 can optionally include an arrangement in which the recess is dimensioned to leave a gap between an edge of the piezoelectric sensor and the body, wherein the measures between 0.1 millimeters and 1.0 millimeters. 
     In Example 8, the subject matter of any one of Examples 1-7 can optionally include an arrangement in which at least a portion of the gap is filled with an adhesive material. 
     In Example 9, the subject matter of any one of Examples 1-8 can optionally include a channel formed in the first surface. 
     In Example 10, the subject matter of any one of Examples 1-9 can optionally include an arrangement in which the channel extends from the recess to an edge of the holder. 
     Example 11 is a wearable virtual keyboard comprising a member configured to be worn on a body segment of a user, the member comprising at least one holder for a piezoelectric sensor, comprising a body comprising a first surface and a second surface, opposite the first surface and a recess formed in the first surface of the body to receive the piezoelectric sensor, at least one piezoelectric sensor positioned in the recess of the holder. 
     In Example 12, the subject matter of Examples 11 can optionally include an arrangement in which the wherein the member is adapted to fit on a proximal side of a wrist of a user. 
     In Example 13, the subject matter of any one of Examples 11-12 can optionally include logic, at least partially including hardware logic, configured to receive a first signal from the at least one piezoelectric sensor, wherein the first signal represents first acceleration data associated with the at least one piezoelectric sensor over a predetermined time period and in response to the first signal, to determine a symbol associated with the first acceleration data and transmit a signal identifying the symbol to a remote electronic device. 
     In Example 14, the subject matter of any one of Examples 11-13 can optionally include logic to compare the first acceleration data to acceleration data stored in memory. 
     In Example 15, the subject matter of any one of Examples 11-14 can optionally include logic, at least partially including hardware logic, configured to determine a mel-frequency cepstral coefficient associated with the first acceleration data, determine a symbol associated with the mel-frequency cepstral coefficient, and transmit a signal identifying the symbol to a remote electronic device. 
     In Example 16, the subject matter of any one of Examples 11-15 can optionally include logic to compare the mel-frequency cepstral coefficient associated with the first acceleration data to a mel-frequency cepstral coefficient stored in memory. 
     In Example 17, the subject matter of any one of Examples 11-16 can optionally include logic, to receive a second signal from the at least one piezoelectric sensor, wherein the second signal represents first orientation data associated with the at least one piezoelectric sensor over a predetermined time period and in response to the second signal, to determine a symbol associated with the first orientation data and transmit a signal identifying the symbol to a remote electronic device. 
     In Example 18, the subject matter of any one of Examples 11-17 can optionally include logic, to determine a symbol associated a combination of the first orientation data and the first acceleration data and transmit a signal identifying the symbol to a remote electronic device. 
     In Example 19, the subject matter of any one of Examples 11-18 can optionally include logic, to determine a symbol associated a combination of the first orientation data and the first acceleration data and transmit a signal identifying the symbol to a remote electronic device. 
     The terms “logic instructions” as referred to herein relates to expressions which may be understood by one or more machines for performing one or more logical operations. For example, logic instructions may comprise instructions which are interpretable by a processor compiler for executing one or more operations on one or more data objects. However, this is merely an example of machine-readable instructions and examples are not limited in this respect. 
     The terms “computer readable medium” as referred to herein relates to media capable of maintaining expressions which are perceivable by one or more machines. For example, a computer readable medium may comprise one or more storage devices for storing computer readable instructions or data. Such storage devices may comprise storage media such as, for example, optical, magnetic or semiconductor storage media. However, this is merely an example of a computer readable medium and examples are not limited in this respect. 
     The term “logic” as referred to herein relates to structure for performing one or more logical operations. For example, logic may comprise circuitry which provides one or more output signals based upon one or more input signals. Such circuitry may comprise a finite state machine which receives a digital input and provides a digital output, or circuitry which provides one or more analog output signals in response to one or more analog input signals. Such circuitry may be provided in an application specific integrated circuit (ASIC) or field programmable gate array (FPGA). Also, logic may comprise machine-readable instructions stored in a memory in combination with processing circuitry to execute such machine-readable instructions. However, these are merely examples of structures which may provide logic and examples are not limited in this respect. 
     Some of the methods described herein may be embodied as logic instructions on a computer-readable medium. When executed on a processor, the logic instructions cause a processor to be programmed as a special-purpose machine that implements the described methods. The processor, when configured by the logic instructions to execute the methods described herein, constitutes structure for performing the described methods. Alternatively, the methods described herein may be reduced to logic on, e.g., a field programmable gate array (FPGA), an application specific integrated circuit (ASIC) or the like. 
     In the description and claims, the terms coupled and connected, along with their derivatives, may be used. In particular examples, connected may be used to indicate that two or more elements are in direct physical or electrical contact with each other. Coupled may mean that two or more elements are in direct physical or electrical contact. However, coupled may also mean that two or more elements may not be in direct contact with each other, but yet may still cooperate or interact with each other. 
     Reference in the specification to “one example” or “some examples” means that a particular feature, structure, or characteristic described in connection with the example is included in at least an implementation. The appearances of the phrase “in one example” in various places in the specification may or may not be all referring to the same example. 
     Although examples have been described in language specific to structural features and/or methodological acts, it is to be understood that claimed subject matter may not be limited to the specific features or acts described. Rather, the specific features and acts are disclosed as sample forms of implementing the claimed subject matter.