Measurement of facial muscle EMG potentials for predictive analysis using a smart wearable system and method

Information

  • Patent Grant
  • 12045390
  • Patent Number
    12,045,390
  • Date Filed
    Wednesday, May 24, 2023
    a year ago
  • Date Issued
    Tuesday, July 23, 2024
    4 months ago
  • Inventors
  • Original Assignees
  • Examiners
    • Hong; Richard J
    Agents
    • Goodhue, Coleman & Owens, P.C.
Abstract
A system includes at least one wearable device having a housing, at least one sensor disposed within the housing, at least one output device disposed within the housing, and at least one processor operatively connected to the sensors and output devices, wherein one or more sensors are configured to detect electrical activity from a user's facial muscles and to transmit a data signal concerning the electrical activity of the user's facial muscles to one of more of the processors. A method of controlling a wearable device includes determining facial muscular electrical data of a facial gesture made by a user, interpreting the facial muscular electrical data to determine a user response, and performing an action based on the user response.
Description
FIELD OF THE INVENTION

The present invention relates to wearable devices. More particularly, but not exclusively, the present invention relates to wearable devices that may be modified by facial gestures.


BACKGROUND

Gestural based control systems have their limitations. Precision spatial location is essential for the proper determination of the gestural command. If the position of the measured segment of the body is not in optimal location, errors may occur. Given these issues, what is needed are improved methods, apparatus, and systems for wireless control systems based on gestures.


SUMMARY

According to one aspect, electromyogram (EMG) technology is used to measure the electrical activity of a user's facial muscles. Most people are able to control their facial muscles to such a degree as to permit monitoring by an electronic sensor in order to control a wearable device. In addition, the electrical activity of the muscles of the head and neck region may also be measured to provide additional levels of control to the wearable device. Data collected may be used to provide improved gesture control. Data collected may be combined with data from inertial sensors.


Therefore, it is a primary object, feature, or advantage to improve over the state of the art.


It is a further object, feature, or advantage to assist paralyzed individuals In participating in the activities of life through recognition of control patterns based on facial EMG presets.


It is a still further object, feature, or advantage to allow a user to select EMG control settings in lieu of, or in addition to other control inputs including gesture based controls via accelerometer macros.


Another object, feature, or advantage is to provide greater precision in fine tuning the control functions of a device.


Yet another object, feature, or advantage is the transmission of EMG functional data to receptor devices. This allows the receptor device or devices to better respond to the inputs/commands of the user.


A further object, feature, or advantage is to provide bio-medical monitoring of the user through the use of sensor array systems.


A still further object, feature, or advantage is to augment accelerometer based solutions for control of macros.


One or more of these and/or other objects, features, or advantages of the present invention will become apparent from the specification and claims that follow. No single embodiment need provide each and every object, feature, or advantage. Different embodiments may have different objects, features, or advantages. Therefore, the present invention is not to be limited to or by any object, features or advantage stated herein.


According to one aspect a system includes at least one wearable device, wherein each wearable device includes a processor, a gesture control interface operatively connected to the processor, at least one sensor configured to detect electrical activity from a user's facial muscles, the at least one sensor operatively connected to the processor, and wherein the processor is configured to interpret the electrical activity from the user's facial muscles as a first command to perform action according to a pre-determined user setting. The at least one sensor may be an electromyogram (EMG) sensor. Each wearable device may further include a transceiver operatively connected to the processor. The at least one wearable device may include a set of earpieces comprising a first earpiece and a second earpiece. The first earpiece may further include at least one microphone operatively connected to the processor and at least one speaker operatively connected to the processor. The first earpiece may be further configured not to interpret the electrical activity from the user's facial muscles as a command if the user is talking as determined using the at least one microphone. The first earpiece may further include an inertial sensor operatively connected to the processor and wherein the processor is configured to interpret the electrical activity from the user's facial muscles in combination with at least one of head orientation or movement as a second command. The at least one wearable device may include a set of earphones. The system may further include a software application executing on a mobile device configured to provide for modifying the pre-determined user setting.


According to another aspect, a method for using facial muscle electromyogram (EMG) potential as input may include providing at least one wearable device, wherein each wearable device includes a processor, a gesture control interface operatively connected to the processor, at least one EMG sensor configured to detect electrical activity from a user's facial muscles, the at least one EMG sensor operatively connected to the processor. The is configured to interpret the electrical activity from the user's facial muscles as a first command to perform an action according to a pre-determined user setting. The method may further include receiving the facial muscle EMG potentials at the at least one EMG sensor and interpreting at the processor the facial muscle EMG potentials as a first command to perform the action according to a pre-determined user setting.





BRIEF DESCRIPTION OF THE DRAWINGS


FIG. 1 includes a block diagram of one embodiment of the system.



FIG. 2 illustrates a block diagram of a second embodiment of the system.



FIG. 3 illustrates a set of wireless earpieces in communication with a mobile device executing a software application.



FIG. 4 illustrates one example of an earpiece seated in an ear.



FIG. 5 illustrates a portion of an earphone with a plurality of EMG sensors.





DETAILED DESCRIPTION


FIG. 1 illustrates one example of a wearable device in the form of a set of wireless earpieces 10 which includes a right earpiece 12A and a left earpiece 12B. The set of wireless earpieces are configured to detect muscle contractions such as through use of one or more EMG sensors 36. The one or more EMG sensors 36 may contact one or more muscles to detect muscle contractions. For example, changes such as tightening or loosening of the jaw by the associated muscles may be detected. The placement of the one or more EMG sensors 36 determines which muscle contractions may be sensed. The muscle contractions may be deliberate by a user with the user making the muscle contractions for the purpose of providing input into the wearable device.


The EMG sensors 36 may be combined with additional forms of user input. This may include one or more inertial sensors 74, a gesture control interface 38, one or more air microphones 32, and one or more bone microphones 34. The one or more inertial sensors 74 may include a 9-axis inertial sensor which includes a 3-axis accelerometer, a 3-axis gyrometer, and a 3-axis compass.


The wireless earpiece 12B may also include a radio transceiver 26 such as a BLE, BLUETOOTH, Wi-Fi, or other type of radio transceiver, one or more speakers 16, and one or more processors 18. The one or more processors 18 may be operatively connected to the other components including the one or more EMG sensors 36, the one or more air microphones 32, the inertial sensor 74, the one or more bone microphones 34, the gesture control interface 38, the one or more speakers 16, and the radio transceiver 38.


Where one or more bone conduction microphones 34 and/or one or more air microphones 32 are present, signals from the microphones 34, 32 may be used to determine when certain muscle movement detected with the EMG sensors 36 is associated with speech of the user and when it is not. Thus, for example, when speaking a user would be moving their mouth which requires engaging a number of different muscles. The wireless earpiece may associate the readings from the one or more EMG sensors 36 with speech and thus not consider input received through the EMG sensors 36 to be user input to perform particular actions.



FIG. 2 is a block diagram further illustrating one example of an earpiece 12. The earpiece 12 has a housing 14. Disposed within the housing 14 is one or more processors 18 which may include microprocessors, digital signal processors, mixed signal processors, or other types of processors. The processor 18 is operatively connected to a plurality of sensors 28. The plurality of sensors 28 may include one or more air microphones 32, one or more bone microphones 34, one or more inertial sensors 74, and one or more EMG sensors 76. One or more speakers 16 are also operatively connected to the processor 18. One or more LEDs may be operatively connected to the processor to display status or other purposes. A radio transceiver 26 is operatively connected to the processor and a transceiver 40 may also be operatively connected to the processor 18. The transceiver 40 may be a near field magnetic induction (NFMI) transceiver or other type of transceiver. In some embodiments, the transceiver 40 may be used to communicate between a left earpiece and a right earpiece. In such an embodiment, only one earpiece 12 within a set of earpieces would need to have a radio transceiver 26. The gesture control interface 38 is also operative connected to the one or more processors 18. The gesture control interface 38 may include one or more emitters 82 and one or more detectors 84 to emit and detect an energy field. For example, the one or more emitters 82 may emit light and the one or more detectors 84 may detect reflected light. A user may perform gestures proximate the gesture control interface 30 in order to provide user input. For example, a user may perform one or more taps, holds, swipes, or other gestures to provide user input. Other technologies may be used to emit and detect other types of energy field.


It is also to be understood that in order to provide user input, a user may combine one more gestures as determined by the gesture control interface 38 with one or more facial expressions as determined by the one or more EMG sensors 76 in addition to one or more head movements or head orientations as determined by the one or more inertial sensors 74. Thus, complex input from a user may be quickly communicated using a combination of modalities and in a manner that may be more private than providing voice commands.



FIG. 3 illustrates one example of a set of wireless earpieces 10 which includes a first earpiece 12A and a second earpiece 12B, the first earpiece 12A having a first earpiece housing 14A and the second earpiece 12B having a second earpiece housing 14B. A receptor device such as a mobile device 2 such as a mobile phone is also shown. The mobile device 2 includes a display 4. A software application may execute on a processor of the mobile device 2 for controlling settings associated with the set of wireless earpieces 10. The settings may allow for a user to map different muscle movement or different facial expressions or gestures to different actions. The facial gesture may be a wink, a wince, a smile, one or more blinks, or any facial expression a user is capable of making, and need not be limited to a single gesture. It should also be understood that the gesture or associated muscle contractions being detected may be on the user's face or neck. The electrical reading may be from anywhere on the user's face or neck and need not be performed in a single step. For example, a series of muscle contractions may be indicative of a particular gesture, or a combination of different muscle contractions may be indicative of a particular gesture. One or more processors then interprets the facial muscular electrical data to determine a user response. The wearable device may then perform an action based on the user response.


It is also to be understood that instead of performing processing of EMG sensor data on one or more of the earpieces, this data may be communicated such as over a wireless communication linkage such as a BLE or BLUETOOTH connection to the mobile device 2. The mobile device 2 may then perform processing and return results to the set of wireless earpieces 10. Alternatively, the mobile device 2 may communicate the sensor data over a network to a remote location such as to a cloud computing service which may analyze the data and return the results of the analysis to the mobile device 2 and then in turn to the set of wireless earpieces 10 if so desired. It is also contemplated that the same data may be analyzed in multiple locations and that different types of analysis may occur depending on the location. For example, the most computationally intensive forms of analyses may be performed at a remote location with greater computation resources than present in the set of wireless earpieces 10.



FIG. 4 illustrates the earpiece 12A inserted into an ear of a user and illustrates an external auditory canal 48 and tympanic membrane 40. One or more EMG sensors 36 may be placed at an external surface of the earpiece housing 14A so as to contact a skin surface of the user in order to detect electrical activity associated with muscle movement. Although particular positions are shown, it is to be understood that any number of other positions may be used as may be appropriate depending upon the muscles to be monitored and the size, shape, and configuration of the ear piece or other wearable device.


Because a human is able to control the muscles of facial expression to impressive degrees, the precise control allows the user to transfer nuances of the human emotion spectrum. Such slight movement of the muscles of facial expression can be monitored, and their activity harnessed. Additionally, larger muscles of the head and neck may be able to be activated in order to provide other levels of biometric EMG control inputs to the device. These device inputs may also be preset such as via a software application executing on a mobile device. Thus, user settings may be modified using the software application. Any number of actions may be performed as determined by a user. This may, for example, include actions to initiate a phone call to a particular person or place, listen to a particular song or other audio selection, begin an activity, or any number of other actions which the wearable device may perform.


Biometric data from the EMG sensors may also be relayed to receptor devices without the need or requirement for EMG controls. The array of biometric EMG sensors may be used to better understand the emotional and physiologic status of the user. Such data may be used predictively as well as eliciting a pre-programmed response. In particular, instead of relying upon pre-determined user settings to associate facial expressions with specific commands, the facial expressions may be used to predict user actions or user needs. For example, where voice feedback is being provided to a user of an earpiece presenting options to a user and a user winces in response to an option, the facial expression may be interpreted as a “no”.



FIG. 5 illustrates an inside portion of an ear cup housing of a set of earphones. A plurality of EMG sensors 36 are positioned around the ear cup housing and may be used to sense muscle activity. More or fewer EMG sensors 36 may be present and the EMG sensors may be of varying sizes and shapes. It is to be understood that the EMG sensors may be associated with other types of wearable devices as well.


Although various methods, systems, and apparatuses have been shown and described herein, the present invention contemplates any number of options, variations, and alternative embodiments. For example, it is contemplated that the wearable device may be of any number of types of devices and any number of different facial gestures may be recognized.

Claims
  • 1. A system comprising: a set of earpieces comprising a first earpiece and a second earpiece, wherein each earpiece comprises:a) an earpiece housing;b) a processor disposed within the earpiece housing,c) at least one sensor, located at an external surface of the earpiece housing, configured to detect electrical activity from a user's facial muscles, the at least one sensor operatively connected to the processor and wherein the at least one sensor is an electromyogram (EMG) sensor,d) wherein the processor is configured to interpret the electrical activity from the user's facial muscles as a first command to perform action according to a pre-determined user setting,e) an inertial sensor operatively connected to the processor and wherein the processor is further configured to interpret the electrical activity from the user's facial muscles in combination with at least one of head orientation or movement as a second command,f) at least one microphone operatively connected to the processor;g) at least one speaker operatively connected to the processor.
  • 2. The system of claim 1 wherein each of the first earpiece and the second earpiece device further comprise a transceiver operatively connected to the processor.
  • 3. The system of claim 1 wherein the first earpiece is configured not to interpret the electrical activity from the user's facial muscles as a command if the user is talking as determined using the at least one microphone.
  • 4. The system of claim 1 further comprising a software application executing on a mobile device configured to provide for modifying the pre-determined user setting.
  • 5. The system of claim 1 wherein the processor is configured to interpret the electrical activity from the user's facial muscles as mapping to a wink.
  • 6. The system of claim 1 wherein the processor is configured to interpret the electrical activity from the user's facial muscle as mapping to a wince.
  • 7. The system of claim 1 wherein the processor is configured to interpret the electrical activity from the user's facial muscle as mapping to a smile.
  • 8. The system of claim 1 wherein the processor is configured to interpret the electrical activity from the user's facial muscle as mapping to a blink.
  • 9. The system of claim 1 wherein the processor is configured to interpret the electrical activity from the user's facial muscle as mapping to a facial expression.
  • 10. A method for using facial muscle electromyogram (EMG) potential as input for a set of earpieces comprising a first earpiece and a second earpiece, the first earpiece comprising: a) an earpiece housing,b) a processor disposed within the earpiece housing,c) at least one EMG sensor, placed on an external surface of the earpiece housing, configured to detect electrical activity from a user's facial muscles, the at least one EMG sensor operatively connected to the processor, andd) at least one inertial sensor configured to detect a user's head movement, the at least one inertial sensor operatively connected to the processor,e) at least one microphone operatively connected to the processor and at least one speaker operatively connected to the processor,generating voice feedback at the at least one speaker;receiving the facial muscle EMG potentials at the at least one EMG sensor in response to the voice feedback;receiving audio input from the at least one microphone at the processor in response to the voice feedback;receiving inertial data indicative of the user's head movement from the at least one inertial sensor at the processor in response to the voice feedback; andinterpreting at the processor the facial muscle EMG potentials, the audio input, and the inertial data to determine occurrence of a command to perform an action according to a pre-determined user setting.
  • 11. The method of claim 10 wherein the first earpiece further comprises a transceiver operatively connected to the processor.
  • 12. The method of claim 10 wherein the interpreting at the processors includes determining if the user is talking and if the user is talking determining the facial muscle EMG potentials are not indicative of the occurrence of the command.
  • 13. The method of claim 10 wherein the earpiece further comprises a gesture control interface.
  • 14. The method of claim 13 further comprising detecting a user's gesture at the gesture control interface.
  • 15. A method for using facial muscle electromyogram (EMG) potential as input for an earpiece, the method comprising: receiving facial muscle EMG potentials by at least one EMG sensor of the earpiece;receiving audio input from at least one microphone of the earpiece at a processor of the earpiece;receiving inertial data indicative of the user's head movement from the at least one inertial sensor of the earpiece at the processor of the earpiece; andinterpreting at the processor of the earpiece the facial muscle EMG potentials, the audio input, and the inertial data to determine occurrence of a command to perform an action according to a pre-determined user setting.
  • 16. The method of claim 15 wherein the first earpiece comprises a transceiver operatively connected to the processor.
  • 17. The method of claim 15 wherein the interpreting at the processor of the earpiece includes determining if the user is talking and if the user is talking determining the facial muscle EMG potentials are not indicative of the occurrence of the command.
  • 18. The method of claim 15 wherein the processor is disposed within an earpiece housing of the earpiece.
  • 19. The method of claim 15 wherein the at least one EMG sensor of the earpiece is placed on an external surface of the earpiece housing.
  • 20. The method of claim 15 wherein the interpreting at the processor of the earpiece the facial muscle EMG potentials comprises interpreting that the facial muscle EMG potentials map to a facial expression.
PRIORITY STATEMENT

This application is a continuation of U.S. Non-Provisional patent application Ser. No. 17/700,248, filed on Mar. 21, 2022 which is a continuation of U.S. Non-Provisional patent application Ser. No. 17/102,864, filed on Nov. 24, 2020 now patented as U.S. Pat. No. 11,294,466 which is a continuation of U.S. Non-Provisional patent application Ser. No. 15/703,811, filed on Sep. 13, 2017 now patented as U.S. Pat. No. 10,852,829 and claims priority to U.S. Provisional patent application Ser. No. 62/393,926, filed on Sep. 13, 2016, and all entitled “Measurement of Facial Muscle EMG Potentials for Predictive Analysis Using a Smart Wearable System and Method”, hereby incorporated by reference in their entireties.

US Referenced Citations (289)
Number Name Date Kind
2325590 Carlisle et al. Aug 1943 A
2430229 Kelsey Nov 1947 A
3047089 Zwislocki Jul 1962 A
D208784 Sanzone Oct 1967 S
3586794 Michaelis Jun 1971 A
3934100 Harada Jan 1976 A
3983336 Malek et al. Sep 1976 A
4069400 Johanson et al. Jan 1978 A
4150262 Ono Apr 1979 A
4334315 Ono et al. Jun 1982 A
D266271 Johanson et al. Sep 1982 S
4375016 Harada Feb 1983 A
4588867 Konomi May 1986 A
4617429 Bellafiore Oct 1986 A
4654883 Iwata Mar 1987 A
4682180 Gans Jul 1987 A
4791673 Schreiber Dec 1988 A
4852177 Ambrose Jul 1989 A
4865044 Wallace et al. Sep 1989 A
4934378 Perry Jun 1990 A
4984277 Bisgaard et al. Jan 1991 A
5008943 Arndt et al. Apr 1991 A
5185802 Stanton Feb 1993 A
5191602 Regen et al. Mar 1993 A
5201007 Ward et al. Apr 1993 A
5201008 Arndt et al. Apr 1993 A
D340286 Seo Oct 1993 S
5280524 Norris Jan 1994 A
5295193 Ono Mar 1994 A
5298692 Ikeda et al. Mar 1994 A
5343532 Shugart Aug 1994 A
5347584 Narisawa Sep 1994 A
5363444 Norris Nov 1994 A
D367113 Weeks Feb 1996 S
5497339 Bernard Mar 1996 A
5606621 Reiter et al. Feb 1997 A
5613222 Guenther Mar 1997 A
5654530 Sauer et al. Aug 1997 A
5692059 Kruger Nov 1997 A
5721783 Anderson Feb 1998 A
5748743 Weeks May 1998 A
5749072 Mazurkiewicz et al. May 1998 A
5771438 Palermo et al. Jun 1998 A
D397796 Yabe et al. Sep 1998 S
5802167 Hong Sep 1998 A
D410008 Almqvist May 1999 S
5929774 Charlton Jul 1999 A
5933506 Aoki et al. Aug 1999 A
5949896 Nageno et al. Sep 1999 A
5987146 Pluvinage et al. Nov 1999 A
6021207 Puthuff et al. Feb 2000 A
6054989 Robertson et al. Apr 2000 A
6081724 Wilson Jun 2000 A
6084526 Blotky et al. Jul 2000 A
6094492 Boesen Jul 2000 A
6111569 Brusky et al. Aug 2000 A
6112103 Puthuff Aug 2000 A
6157727 Rueda Dec 2000 A
6167039 Karlsson et al. Dec 2000 A
6181801 Puthuff et al. Jan 2001 B1
6208372 Barraclough Mar 2001 B1
6230029 Yegiazaryan et al. May 2001 B1
6270466 Weinstein et al. Aug 2001 B1
6275789 Moser et al. Aug 2001 B1
6339754 Flanagan et al. Jan 2002 B1
D455835 Anderson et al. Apr 2002 S
6408081 Boesen Jun 2002 B1
6424820 Burdick et al. Jul 2002 B1
D464039 Boesen Oct 2002 S
6470893 Boesen Oct 2002 B1
D468299 Boesen Jan 2003 S
D468300 Boesen Jan 2003 S
6542721 Boesen Apr 2003 B2
6560468 Boesen May 2003 B1
6654721 Handelman Nov 2003 B2
6664713 Boesen Dec 2003 B2
6690807 Meyer Feb 2004 B1
6694180 Boesen Feb 2004 B1
6718043 Boesen Apr 2004 B1
6738485 Boesen May 2004 B1
6748095 Goss Jun 2004 B1
6754358 Boesen et al. Jun 2004 B1
6784873 Boesen et al. Aug 2004 B1
6823195 Boesen Nov 2004 B1
6852084 Boesen Feb 2005 B1
6879698 Boesen Apr 2005 B2
6892082 Boesen May 2005 B2
6920229 Boesen Jul 2005 B2
6952483 Boesen et al. Oct 2005 B2
6987986 Boesen Jan 2006 B2
7010137 Leedom et al. Mar 2006 B1
7113611 Leedom et al. Sep 2006 B2
D532520 Kampmeier et al. Nov 2006 S
7136282 Rebeske Nov 2006 B1
7203331 Boesen Apr 2007 B2
7209569 Boesen Apr 2007 B2
7215790 Boesen et al. May 2007 B2
D549222 Huang Aug 2007 S
D554756 Sjursen et al. Nov 2007 S
7403629 Aceti et al. Jul 2008 B1
D579006 Kim et al. Oct 2008 S
7463902 Boesen Dec 2008 B2
7508411 Boesen Mar 2009 B2
D601134 Elabidi et al. Sep 2009 S
7825626 Kozisek Nov 2010 B2
7965855 Ham Jun 2011 B1
7979035 Griffin et al. Jul 2011 B2
7983628 Boesen Jul 2011 B2
D647491 Chen et al. Oct 2011 S
8095188 Shi Jan 2012 B2
8108143 Tester Jan 2012 B1
8140357 Boesen Mar 2012 B1
D666581 Perez Sep 2012 S
8300864 Müllenborn et al. Oct 2012 B2
8406448 Lin et al. Mar 2013 B2
8436780 Schantz et al. May 2013 B2
D687021 Yuen Jul 2013 S
8493286 Agrama Jul 2013 B1
8719877 VonDoenhoff et al. May 2014 B2
8774434 Zhao et al. Jul 2014 B2
8831266 Huang Sep 2014 B1
8891800 Shaffer Nov 2014 B1
8994498 Agrafioti et al. Mar 2015 B2
D728107 Martin et al. Apr 2015 S
9013145 Castillo et al. Apr 2015 B2
9037125 Kadous May 2015 B1
D733103 Jeong et al. Jun 2015 S
9081944 Camacho et al. Jul 2015 B2
9372533 Agrama Jun 2016 B1
9510159 Cuddihy et al. Nov 2016 B1
D773439 Walker Dec 2016 S
D775158 Dong Dec 2016 S
D777710 Palmborg Jan 2017 S
D788079 Son et al. May 2017 S
10852829 Rüdiger Dec 2020 B2
11294466 Rüdiger Apr 2022 B2
20010005197 Mishra et al. Jun 2001 A1
20010027121 Boesen Oct 2001 A1
20010043707 Leedom Nov 2001 A1
20010056350 Calderone et al. Dec 2001 A1
20020002413 Tokue Jan 2002 A1
20020007510 Mann Jan 2002 A1
20020010590 Lee Jan 2002 A1
20020030637 Mann Mar 2002 A1
20020046035 Kitahara et al. Apr 2002 A1
20020057810 Boesen May 2002 A1
20020076073 Taenzer et al. Jun 2002 A1
20020118852 Boesen Aug 2002 A1
20030002705 Boesen Jan 2003 A1
20030065504 Kraemer et al. Apr 2003 A1
20030100331 Dress et al. May 2003 A1
20030104806 Ruef et al. Jun 2003 A1
20030115068 Boesen Jun 2003 A1
20030125096 Boesen Jul 2003 A1
20030218064 Conner et al. Nov 2003 A1
20030220584 Honeyager et al. Nov 2003 A1
20040070564 Dawson et al. Apr 2004 A1
20040160511 Boesen Aug 2004 A1
20050017842 Dematteo Jan 2005 A1
20050043056 Boesen Feb 2005 A1
20050094839 Gwee May 2005 A1
20050125320 Boesen Jun 2005 A1
20050148883 Boesen Jul 2005 A1
20050165663 Razumov Jul 2005 A1
20050196009 Boesen Sep 2005 A1
20050251455 Boesen Nov 2005 A1
20050266876 Boesen Dec 2005 A1
20060029246 Boesen Feb 2006 A1
20060073787 Lair et al. Apr 2006 A1
20060074671 Farmaner et al. Apr 2006 A1
20060074808 Boesen Apr 2006 A1
20060166715 Engelen et al. Jul 2006 A1
20060166716 Seshadri et al. Jul 2006 A1
20060220915 Bauer Oct 2006 A1
20060258412 Liu Nov 2006 A1
20080076972 Dorogusker et al. Mar 2008 A1
20080090622 Kim et al. Apr 2008 A1
20080146890 LeBoeuf Jun 2008 A1
20080166005 Terlizzi et al. Jul 2008 A1
20080254780 Kuhl et al. Oct 2008 A1
20080255430 Alexandersson et al. Oct 2008 A1
20090003620 McKillop et al. Jan 2009 A1
20090005700 Joshi et al. Jan 2009 A1
20090008275 Ferrari et al. Jan 2009 A1
20090017881 Madrigal Jan 2009 A1
20090073070 Rofougaran Mar 2009 A1
20090097689 Prest et al. Apr 2009 A1
20090105548 Bart Apr 2009 A1
20090191920 Regen et al. Jul 2009 A1
20090245559 Boltyenkov et al. Oct 2009 A1
20090261114 McGuire et al. Oct 2009 A1
20090296968 Wu et al. Dec 2009 A1
20100033313 Keady et al. Feb 2010 A1
20100203831 Muth Aug 2010 A1
20100210212 Sato Aug 2010 A1
20100320961 Castillo et al. Dec 2010 A1
20110140844 McGuire et al. Jun 2011 A1
20110239497 McGuire et al. Oct 2011 A1
20110286615 Olodort et al. Nov 2011 A1
20120057740 Rosal Mar 2012 A1
20120116537 Liebetanz May 2012 A1
20120149467 Heck Jun 2012 A1
20120229248 Parshionikar et al. Sep 2012 A1
20130123656 Heck May 2013 A1
20130274583 Heck Oct 2013 A1
20130316642 Newham Nov 2013 A1
20130346168 Zhou et al. Dec 2013 A1
20140079257 Ruwe et al. Mar 2014 A1
20140106677 Altman Apr 2014 A1
20140122116 Smythe May 2014 A1
20140153768 Hagen et al. Jun 2014 A1
20140160248 Pomerantz et al. Jun 2014 A1
20140163771 Demeniuk Jun 2014 A1
20140185828 Helbling Jul 2014 A1
20140219467 Kurtz Aug 2014 A1
20140222462 Shakil et al. Aug 2014 A1
20140235169 Parkinson et al. Aug 2014 A1
20140270227 Swanson Sep 2014 A1
20140270271 Dehe et al. Sep 2014 A1
20140335908 Krisch et al. Nov 2014 A1
20140348367 Vavrus et al. Nov 2014 A1
20150028996 Agrafioti et al. Jan 2015 A1
20150110587 Hori Apr 2015 A1
20150148989 Cooper et al. May 2015 A1
20150245127 Shaffer Aug 2015 A1
20150261298 Li Sep 2015 A1
20150324645 Jang et al. Nov 2015 A1
20150360030 Cartledge Dec 2015 A1
20150366471 LeBoeuf et al. Dec 2015 A1
20160033280 Moore Feb 2016 A1
20160072558 Hirsch et al. Mar 2016 A1
20160073189 Lindén et al. Mar 2016 A1
20160100676 Sandanger Apr 2016 A1
20160109961 Parshionikar Apr 2016 A1
20160125892 Bowen et al. May 2016 A1
20160353195 Lott Dec 2016 A1
20160360350 Watson et al. Dec 2016 A1
20170041699 Mackellar Feb 2017 A1
20170059152 Hirsch et al. Mar 2017 A1
20170060256 Heck et al. Mar 2017 A1
20170060262 Hviid et al. Mar 2017 A1
20170060269 Förstner et al. Mar 2017 A1
20170061751 Loermann et al. Mar 2017 A1
20170062913 Hirsch et al. Mar 2017 A1
20170064426 Hviid Mar 2017 A1
20170064428 Hirsch Mar 2017 A1
20170064432 Hviid et al. Mar 2017 A1
20170064437 Hviid et al. Mar 2017 A1
20170078780 Qian et al. Mar 2017 A1
20170078785 Qian et al. Mar 2017 A1
20170108918 Boesen Apr 2017 A1
20170109131 Boesen Apr 2017 A1
20170110124 Boesen et al. Apr 2017 A1
20170110899 Boesen Apr 2017 A1
20170111723 Boesen Apr 2017 A1
20170111725 Boesen et al. Apr 2017 A1
20170111726 Martin et al. Apr 2017 A1
20170111740 Hviid et al. Apr 2017 A1
20170151447 Boesen Jun 2017 A1
20170151668 Boesen Jun 2017 A1
20170151918 Boesen Jun 2017 A1
20170151930 Boesen Jun 2017 A1
20170151957 Boesen Jun 2017 A1
20170151959 Boesen Jun 2017 A1
20170153114 Boesen Jun 2017 A1
20170153636 Boesen Jun 2017 A1
20170154532 Boesen Jun 2017 A1
20170155985 Boesen Jun 2017 A1
20170155992 Perianu et al. Jun 2017 A1
20170155993 Boesen Jun 2017 A1
20170155997 Boesen Jun 2017 A1
20170155998 Boesen Jun 2017 A1
20170156000 Boesen Jun 2017 A1
20170164089 Lee et al. Jun 2017 A1
20170178631 Boesen Jun 2017 A1
20170180842 Boesen Jun 2017 A1
20170180843 Perianu et al. Jun 2017 A1
20170180897 Perianu Jun 2017 A1
20170188127 Perianu et al. Jun 2017 A1
20170188132 Hirsch et al. Jun 2017 A1
20170195829 Belverato et al. Jul 2017 A1
20170208393 Boesen Jul 2017 A1
20170214987 Boesen Jul 2017 A1
20170215016 Dohmen et al. Jul 2017 A1
20170230752 Dohmen et al. Aug 2017 A1
20170257698 Boesen et al. Sep 2017 A1
20170339484 Kim Nov 2017 A1
20170347177 Masaki et al. Nov 2017 A1
20180107275 Chen et al. Apr 2018 A1
Foreign Referenced Citations (19)
Number Date Country
204244472 Apr 2015 CN
104683519 Jun 2015 CN
104837094 Aug 2015 CN
1469659 Oct 2004 EP
1017252 May 2006 EP
2903186 Aug 2015 EP
2074817 Nov 1981 GB
2508226 May 2014 GB
2008103925 Aug 2008 WO
2007034371 Nov 2008 WO
2011001433 Jan 2011 WO
2012071127 May 2012 WO
2013134956 Sep 2013 WO
2014046602 Mar 2014 WO
2014043179 Jul 2014 WO
2015061633 Apr 2015 WO
2015110577 Jul 2015 WO
2015110587 Jul 2015 WO
2016032990 Mar 2016 WO
Non-Patent Literature Citations (48)
Entry
Akkermans, “Acoustic Ear Recognition for Person Identification”, Automatic Identification Advanced Technologies, 2005 pp. 219-223.
Announcing the $3,333,333 Stretch Goal (Feb. 24, 2014) pp. 1-14.
Ben Coxworth: “Graphene-based ink could enable low-cost, foldable electronics”, “Journal of Physical Chemistry Letters”, Northwestern University, (May 22, 2013), pp. 1-7.
Blain: “World's first graphene speaker already superior to Sennheiser MX400”, htt://www.gizmag.com/graphene-speaker-beats-sennheiser-mx400/31660, (Apr. 15, 2014).
BMW, “BMW introduces BMW Connected—The personalized digital assistant”, “http://bmwblog.com/2016/01/05/bmw-introduces-bmw-connected-the-personalized-digital-assistant”, (Jan. 5, 2016).
BRAGI Is On Facebook (2014), pp. 1-51.
BRAGI Update—Arrival Of Prototype Chassis Parts—More People—Awesomeness (May 13, 2014), pp. 1-8.
BRAGI Update—Chinese New Year, Design Verification, Charging Case, More People, Timeline(Mar. 6, 2015), pp. 1-18.
BRAGI Update—First Sleeves From Prototype Tool—Software Development Kit (Jun. 5, 2014), pp. 1-8.
BRAGI Update—Let's Get Ready To Rumble, A Lot To Be Done Over Christmas (Dec. 22, 2014), pp. 1-18.
BRAGI Update—Memories From April—Update On Progress (Sep. 16, 2014), pp. 1-15.
BRAGI Update—Memories from May—Update On Progress—Sweet (Oct. 13, 2014), pp. 1-16.
BRAGI Update—Memories From One Month Before Kickstarter—Update On Progress (Jul. 10, 2014), pp. 1-17.
BRAGI Update—Memories From The First Month of Kickstarter—Update on Progress (Aug. 1, 2014), pp. 1-16.
BRAGI Update—Memories From The Second Month of Kickstarter—Update On Progress (Aug. 22, 2014), pp. 1-15.
BRAGI Update—New People @BRAGI—Prototypes (Jun. 26, 2014), pp. 1-9.
BRAGI Update—Office Tour, Tour To China, Tour to CES (Dec. 11, 2014), pp. 1-14.
BRAGI Update—Status On Wireless, Bits and Pieces, Testing—Oh Yeah, Timeline(Apr. 24, 2015), pp. 1-18.
BRAGI Update—The App Preview, The Charger, The SDK, BRAGI Funding and Chinese New Year (Feb. 11, 2015), pp. 1-19.
BRAGI Update—What We Did Over Christmas, Las Vegas & CES (Jan. 19, 2014), pp. 1-21.
BRAGI Update—Years of Development, Moments of Utter Joy and Finishing What We Started(Jun. 5, 2015), pp. 1-21.
BRAGI Update—Alpha 5 and Back To China, Backer Day, On Track(May 16, 2015), pp. 1-15.
BRAGI Update—Beta2 Production and Factory Line(Aug. 20, 2015), pp. 1-16.
BRAGI Update—Certifications, Production, Ramping Up (Nov. 13, 2015), pp. 1-15.
BRAGI Update—Developer Units Shipping and Status(Oct. 5, 2015), pp. 1-20.
BRAGI Update—Developer Units Started Shipping and Status (Oct. 19, 2015), pp. 1-20.
BRAGI Update—Developer Units, Investment, Story and Status(Nov. 2, 2015), pp. 1-14.
BRAGI Update—Getting Close(Aug. 6, 2015), pp. 1-20.
BRAGI Update—On Track, Design Verification, How It Works and What's Next(Jul. 15, 2015), pp. 1-17.
BRAGI Update—On Track, On Track and Gems Overview (Jun. 24, 2015), pp. 1-19.
BRAGI Update—Status On Wireless, Supply, Timeline and Open House@BRAGI(Apr. 1, 2015), pp. 1-17.
BRAGI Update—Unpacking Video, Reviews On Audio Perform and Boy Are We Getting Close(Sep. 10, 2015), pp. 1-15.
Healthcare Risk Management Review, “Nuance updates computer-assisted physician documentation solution” (Oct. 20, 2016), pp. 1-2.
Hoyt et. al., “Lessons Learned from Implementation of Voice Recognition for Documentation in the Military Electronic Health Record System”, The American Health Information Management Association (2017), pp. 1-8.
Hyundai Motor America, “Hyundai Motor Company Introduces A Health + Mobility Concept For Wellness In Mobility”, Fountain Valley, Californa (2017), pp. 1-3.
International Search Report & Written Opinion, PCT/EP2016/070231 (Nov. 18, 2016) 12 pages.
Last Push Before The Kickstarter Campaign Ends on Monday 4pm CET (Mar. 28, 2014), pp. 1-7.
Nigel Whitfield: “Fake tape detectors, ‘from the stands’ footie and UGH? Internet of Things in my set-top box”; http://www.theregister.co.uk/2014/09/24/ibc_round_up_object_audio_dlna_iot/ (Sep. 24, 2014).
Staab, Wayne J., et al., “A One-Size Disposable Hearing Aid is Introduced”, The Hearing Journal 53(4):36-41) Apr. 2000.
Stretchgoal—It's Your Dash (Feb. 14, 2014), pp. 1-14.
Stretchgoal—The Carrying Case for The Dash (Feb. 12, 2014), pp. 1-9.
Stretchgoal—Windows Phone Support (Feb. 17, 2014), pp. 1-17.
The Dash + The Charging Case & The BRAGI News (Feb. 21, 2014), pp. 1-12.
The Dash—A Word From Our Software, Mechanical and Acoustics Team + An Update (Mar. 11, 2014), pp. 1-7.
Update From BRAGI—$3,000,000—Yipee (Mar. 22, 2014), pp. 1-11.
Wikipedia, “Gamebook”, https://en.wikipedia.org/wiki/Gamebook, Sep. 3, 2017, 5 pages.
Wikipedia, “Kinect”, “https://en.wikipedia.org/wiki/Kinect”, 18 pages, (Sep. 9, 2017).
Wikipedia, “Wii Balance Board”, “https://en.wikipedia.org/wiki/Wii_Balance_Board”, 3 pages, (Jul. 20, 2017).
Related Publications (1)
Number Date Country
20230297169 A1 Sep 2023 US
Provisional Applications (1)
Number Date Country
62393926 Sep 2016 US
Continuations (3)
Number Date Country
Parent 17700248 Mar 2022 US
Child 18322993 US
Parent 17102864 Nov 2020 US
Child 17700248 US
Parent 15703811 Sep 2017 US
Child 17102864 US