1. Field
The present disclosure relates to automatic and dynamic adjustment of information provided by a device, and more particularly to a system and a method for generating and providing automatic and dynamic adjustment of spatial information for blind users.
2. Description of the Related Art
Navigation systems are capable of providing navigation instructions to a user based on a current location and a desired destination. Typically, these navigation systems are used in vehicles for providing driving directions. These navigation systems commonly utilize Global Positioning System (GPS) technology for estimating the current location of the vehicle.
More recently, portable navigation systems have been integrated into mobile devices, such as smartphones. Users can now use these portable navigation systems when riding a bicycle, walking, or otherwise proceeding along a route at a slower speed relative to a vehicle. These portable navigation systems, like their vehicle-based counterparts, use GPS technology for estimating a current location of the navigation system. Navigation systems may provide turning instructions as a user approaches a turn, and output the instructions in terms of standardized units of length, such as feet, meters, or yards.
However, individuals having certain disabilities, such as blindness, may not be able to accurately gauge distance in terms of standard measurements, such as feet, meters, or yards. In order for these individuals to gain the most benefit from a navigation system, the navigation system should output the instruction in a unit more intuitive to the user. Furthermore, navigation systems solely using GPS technology may not be as effective indoors, as the margin for error with GPS is too high to provide location information at a sufficiently accurate level. Therefore, navigation systems using solely GPS technology may not be usable or optimal for disabled users, particularly disabled users indoors.
Thus, there is a need for systems and methods for providing more intuitive, more accurate navigation and spatial information to users.
What is described is a system for providing spatial information to a user. The system includes a camera configured to detect image data. The system also includes an accelerometer configured to determine step data. The system also includes a processor connected to the camera and the accelerometer. The processor is configured to determine a distance travelled per step of the user based on the image data and the step data. The processor is also configured to determine a distance to a reference point based on the image data. The processor is also configured to determine a number of steps corresponding to the distance to the reference point based on the distance travelled per step of the user. The system also includes an output unit connected to the processor. The output unit is configured to output the spatial information indicating the number of steps corresponding to the distance to the reference point.
Also described is a device for providing spatial information to a user. The device includes a camera configured to detect image data. The device includes an accelerometer configured to determine step data and a memory configured to store step distance data for establishing a baseline distance travelled per step. The device also includes a processor connected to the camera and the accelerometer. The processor is configured to determine a distance to a reference point based on the image data. The processor is also configured to determine a number of steps corresponding to the distance to the reference point based on the baseline distance travelled per step. The processor is also configured to determine a distance travelled per step of the user based on the image data and the step data. The processor is also configured to determine an updated distance to the reference point. The processor is also configured to determine an updated number of steps corresponding to the updated distance to the reference point based on the distance travelled per step of the user. The device also includes an output unit connected to the processor. The output unit is configured to output the spatial information indicating the number of steps corresponding to the distance to the reference point. The output unit is also configured to output the updated number of steps corresponding to the updated distance to the reference point.
Also described is a method for providing spatial information to a user. The method includes detecting, by a camera, image data and determining, by an accelerometer, step data. The method includes determining, by a processor, a distance travelled per step of the user based on the image data and the step data. The method includes determining, by the processor, a distance to a reference point based on the image data. The method also includes determining, by the processor, a number of steps corresponding to the distance to the reference point based on the distance travelled per step of the user. The method also includes outputting, by an output unit, the spatial information indicating the number of steps corresponding to the distance to the reference point.
Other systems, methods, features, and advantages of the present invention will be or will become apparent to one of ordinary skill in the art upon examination of the following figures and detailed description. It is intended that all such additional systems, methods, features, and advantages be included within this description, be within the scope of the present invention, and be protected by the accompanying claims. Component parts shown in the drawings are not necessarily to scale, and may be exaggerated to better illustrate the important features of the present invention. In the drawings, like reference numerals designate like parts throughout the different views, wherein:
Disclosed herein are systems and methods for providing spatial information to a user. The systems and methods provide several benefits and advantages, such as providing a more intuitive indication of distance between a user and a reference point by using steps instead of traditional units of measurement for distance. The benefits and advantages are particularly more significant for disabled individuals, who may have a harder time gauging a given distance. These benefits are achieved by outputting spatial information unique to the user in terms of the user's steps and distance travelled per step. Determining a number of steps to a reference point based on the user's distance travelled per step (e.g., pace, or stride) provides benefits and advantages such as the ability to output information to a user based on individual characteristics of the user. This is advantageous because different users walk with different stride lengths and speeds, so a number of steps determined for one user may not be accurate for another user. For example, a first user who is 5 feet 6 inches tall may have a stride length (e.g., distance travelled per step, or pace) of 2.3 feet and a second user who is 6 feet 10 inches tall may have a stride length of 2.8 feet. If a distance to a point of reference is 50 feet away, the number of steps for the first user is 22 steps and the number of steps for the second user is 18 steps. Providing the number of steps determined for the first user to the second user may result in a high level of inaccuracy based on the difference in stride lengths. As such, more personal and more accurate information is provided by using a number of steps tailored to the user.
Automatically adjusting or calibrating the spatial information based on the user's distance travelled per step provides additional benefits and advantages such as allowing the number of steps to be travelled to change as characteristics of the user or the user's environment change. The systems and methods provide additional benefits and advantages such as the information being tailored to various walking environments of the user such as an incline, decline, crowded environments, empty environments, etc., and also tailored to the particular speed of the user, such as brisk walking, leisurely walking, jogging, running, etc. further allowing accurate information to be communicated to the user. For example, a user may be 50 feet away from a point of reference, walking leisurely, and the system provides spatial information indicating the point of reference is 22 steps away. However, after 10 steps, the user may encounter a situation causing the user to slow down, such as an inclined walkway or a crowd of people. The system may automatically adjust the number of steps and provide updated spatial information indicating the user is now 15 steps away from the point of reference, compared to the 12 steps the user would have thought, if the original distance per step was used.
An exemplary system includes a camera capable of detecting image data corresponding to an environment of a user. The system further includes an accelerometer that is capable of determining step data of a user, such as when the user has taken a step. The system further includes a processor connected to the camera and the accelerometer. The processor is capable of determining a distance travelled per step of the user based on the image data and the step data. The processor is also capable of determining a distance to a reference point based on the image data. The processor is also capable of determining a number of steps corresponding to the distance to the reference point based on the pace of the user. The system further includes an output unit connected to the processor and configured to output the spatial information indicating the number of steps corresponding to the distance to the reference point.
With reference now to
In
The device 104 identifies a reference point 108. In some embodiments, the reference point 108 is dynamically chosen based on the surroundings of the user. In some embodiments, the system may recognize a location based on the image data detected by the camera and provide spatial information to the user associated with the location. For example, a user may frequently patronize a chain of coffee shops, and when the device 104 recognizes a location associated with the chain of coffee shops, the device 104 may provide spatial information to the user, such as “Coffee Shop X is 30 steps away to your right.”
In some embodiments, the reference point 108 is a destination being navigated to and is specified by the user. In some embodiments, the reference point 108 is a checkpoint, an intermediate location or a landmark relative to a destination being navigated to.
Once the device 104 identifies the reference point 108, the device 104 determines a distance 110 to the reference point 108. The device 104 may determine the distance 110 to the reference point 108 using one or more of an inertial measurement unit (IMU), a camera, stereo cameras offset by a stereo distance and information associated with the environment, such as a map.
The device 104 determines a number of steps to the reference point 108 based on the determined distance travelled per step and the determined distance 110 to the reference point 108. The device 104 provides an output 114 of the number of steps to the reference point 108, to the user 102. In some embodiments, the output 114 is an audio output. In some embodiments, the audio output is communicated through a speaker 318 on the device 104. In some embodiments, the audio output includes an identification of the reference point 108 and the number of steps to the reference point 108. For example, if the distance 110 to the reference point 108 is 100 feet, and the user travels 2.5 feet per step, the output 114 may be an audio output of “Store X approaching in 40 steps to your right.” In some embodiments, the output is a tactile output. In some embodiments, the device 104 includes a vibration unit 320 and may communicate information to the user 102 using varying lengths and combinations of vibration tones.
By providing the output in terms of number of steps, the device 104 provides more intuitive, more useful information to the user 102, especially if the user 102 is disabled or otherwise unable to accurately determine distances.
The user 102 may travel a distance 112 toward the reference point 108. Upon traveling this distance 112, the device 104 may provide an updated number of steps to the reference point 108. In some embodiments, the device 104 determines an updated number of steps by decrementing the number of steps communicated previously in the output 114 by a number of steps taken by the user in the distance 112 travelled toward the reference point 108. In some embodiments, the device 104 determines an updated number of steps by determining an updated distance travelled per step by the user 102 and determining an updated distance 118 to the reference point 108, and using those values to determine the updated number of steps to the reference point 108.
Upon determining the updated number of steps to the reference point 108, the device 104 provides an updated output 116 to the user with the updated number of steps to the reference point 108. The updated output 116 may be provided in the same manner or a different manner as described with respect to the output 114. For example, the output 114 may be an audio output and when the user 102 is within a threshold distance of the reference point 108, the updated output 116 may be a vibration indicating the user 102 is a number of steps away from the reference point 108, such as five vibration pulses indicating the user 102 is five steps away. In another example, the output 114 and the updated output 116 may be communicated in the same manner, for purposes of consistency. Output preferences may be determined by the user 102 and may be changed by the user at any time.
The device 104 may update the number of steps to the reference point 108 periodically. In some embodiments, the device 104 updates the number of steps to the reference point 108 every five minutes, every minute, every 30 seconds, etc. The device 104 may also update the number of steps to the reference point 108 when a step distance adjustment trigger is detected. In some embodiments, a step distance adjustment trigger is a change in speed that exceeds a threshold change in speed, as detected by an accelerometer 312 or an IMU 324. In some embodiments, a step distance adjustment trigger is a change in the environment, such as an inclined walking surface, a declined walking surface, or an increase in presence of other people or things around the user 102, as detected by a camera 308, stored map data, or an IMU 324.
The device 104 may determine the distance travelled by the user 102 per step based on one step, or may wait to collect a threshold number of samples of distance travelled per step before making a determination of the distance travelled by the user 102 per step. The device 104 may provide an initial estimate of the number of steps based on the step distance data stored in a memory 304. The step distance data may include a baseline distance travelled per step, for purposes of providing an initial estimate. In some embodiments, the stored step distance data is based on historical data associated with the user 102. In some embodiments, the stored step distance data is based on historical data of many users, and associated with the location. In some embodiments, the memory 304 is local to the device 104. In some embodiments, the memory is remotely located, such as on a cloud-based storage, and may be accessed by the device 104 remotely, such as via Wi-Fi or via a cellular radio network. The distance travelled per step may initially be provided by the user 102 or may initially be determined from attributes of the user 102, such as height, weight, and gender.
In some embodiments, the device 104 may discard or ignore outliers. For example, if the user 102 stumbles, pauses, or takes small steps to negotiate an obstacle, such as litter on the ground, the distance travelled by the user per step may be skewed or inaccurate. The device 104 may also discard distance data associated with climbing up and down stairs, as the distance travelled per step while climbing up and down stairs may not be representative of the user's distance travelled per step for flat (or substantially flat) surfaces. The device 104 may detect climbing up or down stairs based on a combination of accelerometer data, camera image data, IMU data and/or map data associated with the environment of the user 102. In some embodiments, if stairs are between the user 102 and a reference point, the number of steps in the stairs may be presented to the user in the output. The number of steps in the stairs may be determined by the camera or by map data associated with the environment.
With reference now to
The device 104 may determine the number of steps from a location 205 to a reference point 207 by determining a distance travelled per step and determining a distance 216 to the reference point 207, as described herein. The device 104 may determine a distance per step value based on the user's distance travelled per step for the session or may determine the distance per step value based on a distance per step value stored in a memory 304.
Once the user 202 has reached the reference point 207, the device 104 may provide an output 208 that notifies the user 202 to perform the next step in the directions, such as turn 90 degrees to the right hand side. Once the user 202 has turned 90 degrees to the right hand side, the device 104 provides an output 210 indicating a number of steps corresponding to a new or remaining distance 218 to the destination 212. In some embodiments, the device 104 determines that the user has performed a turn using an IMU 324 or a gyroscope. The device 104 determines the number of steps corresponding to the distance 218 to the destination 212 based on the distance travelled per step of the user 202 and the distance 218 to the destination, each determined as described herein.
In one implementation and with reference to
The processor 302 may be a computer processor such as an ARM processor, DSP processor, distributed processor, microprocessor, controller, or other processing device. The processor 302 may be located in the device 104, may be a remote processor or it may be a pairing of a local and a remote processor.
The memory 304 may be one or any combination of the following: a RAM or other volatile or nonvolatile memory, a non-transitory memory or a data storage device, such as a hard disk drive, a solid state disk drive, a hybrid disk drive or other appropriate data storage. The memory 304 may further store machine-readable instructions which may be loaded into or stored in the memory 304 and executed by the processor 302. As with the processor 302, the memory 304 may be positioned on the device 104, may be positioned remote from the device 104 or may be a pairing of a local and a remote memory. The memory 304 may also store step distance data and information associated with the environment, such as map data.
The sensor array 306 includes a camera 308, stereo cameras 310, an accelerometer 312, a sensor 314, a GPS unit 326, and an IMU 324. The stereo cameras 310 may be a stereo camera pair including two cameras offset by a stereo distance, and configured to detect image data to be used by the processor 302 for determining a distance to an object. The stereo cameras 310 may be used instead of or in conjunction with the camera 308 to detect image data. The sensor 314 may be one or more sensors which provide further information about the environment in conjunction with the rest of the sensor array 306 such as one or more of a temperature sensor, an air pressure sensor, a moisture or humidity sensor, a gas detector or other chemical sensor, a sound sensor, a pH sensor, a smoke detector, an altimeter, a depth gauge, a compass, a motion detector, a light sensor, or other sensor. The GPS unit 326 may be used to determine a geographical location. As is described herein, locations determined using the GPS unit 326 may not provide enough accuracy to be a basis for providing step numbers, but may be accurate enough to determine a location, such as a particular mall or a particular office building. The IMU 324 may include the accelerometer 312 or may be a separate device.
The output unit 316 includes a speaker 318 and a vibration unit 320. The speaker 318 may be one or more speakers or other devices capable of producing sounds and/or vibrations. The vibration unit 320 may be one or more vibration motors or actuators capable of providing haptic and tactile output.
The transceiver 322 can be a receiver and/or a transmitter configured to receive and transmit data from a remote data storage or other device. The transceiver 322 may include an antenna capable of transmitting and receiving wireless communications. For example, the antenna may be a Bluetooth or Wi-Fi antenna, a cellular radio antenna, a radio frequency identification (RFID) antenna or reader and/or a near field communication (NFC) unit.
With reference now to
The image data is detected by the camera 308 and/or the stereo cameras 310 of the device 104 (step 402). In some embodiments, the image data includes data regarding the environment of the device 104. The step data is detected by the accelerometer 312 of the device 104 (step 404). In some embodiments, the step data includes an indication of when the user took a step.
A distance travelled per step is determined by the processor 302 (step 406). The processor 302 determines the distance travelled per step based on the image data and the step data by comparing the image data when steps are taken to determine a change in distance travelled between steps. For example, the user may be walking through a shopping mall and the image data may include a series of images of stores and objects near the user, with each image taken when the user takes a step. The processor 302 compares consecutive images within the series of images to determine a change in distance travelled by the user. Since the images were taken when the user took a step, the determined change in distance between consecutive images provides a distance travelled per step. In some embodiments, map data associated with the location of the user that is stored in the memory 304 is also used to determine the distance travelled between steps by comparing the image data to the map data.
A distance to a reference point is determined by the processor 302 (step 408). The distance to the reference point is determined based on the image data. In some embodiments, the map data is also used to determine the distance to the reference point. A number of steps corresponding to the distance to the reference point is determined by the processor 302 (step 410). The number of steps corresponding to the distance to the reference point is determined using the distance travelled per step and the distance to the reference point.
The spatial information is output to the user, including the determined number of steps to the reference point (step 412). As described herein, the output of the spatial information indicating the number of steps may be an audio output provided by the speaker 316, or it may be a series of vibrations provided by the vibration unit 320.
With reference now to
A baseline distance travelled per step is determined by the processor 302 (step 502). In some embodiments, the baseline distance travelled per step is determined based on historical step distance data associated with the user. In some embodiments, the baseline distance travelled per step is determined based on historical step distance data associated with the location of the user. For example, the distance travelled per step of all users in a particular mall may be aggregated and the mean or median may be calculated in order to determine a baseline distance travelled per step for a user at the particular mall.
A distance to the reference point is determined by the processor 302 (step 504). As described herein, a camera 308 and/or stereo cameras 310 may be used to determine the distance to the reference point. In some embodiments, the reference point is a place or an object recognized by the device 104 based on a comparison of stored images and image data detected by the camera 308 and/or the stereo cameras 310. In some embodiments, the reference point is a location identified by the user.
A number of steps corresponding to the distance to the reference point is determined by the processor 302 based on the determined baseline distance travelled per step and the determined distance to the reference point (step 506). The number of steps is output by the output unit 316 (step 508). As described herein, the output may be an audio output provided by a speaker 318 or a tactile output provided by a vibration unit 320.
The device 104 collects image data and step data using the camera 308 and the accelerometer 312, respectively (step 509). It is determined whether enough data has been collected to determine a distance travelled per step (step 510). In some embodiments, the processor 302 determines whether a threshold number of data points of distance travelled per step have been collected. In some embodiments, the threshold number is predetermined by the user or is a value associated with the device 104.
When enough data has been collected, a distance travelled per step is determined by the processor 302 (step 512). The distance travelled per step is determined based on the image data and the step data. A distance to the reference point is determined based on the image data (step 514). In some embodiments, the distance determined in step 504 is different than the distance determined in step 514, as the user may have moved closer to the reference point or farther away.
An updated number of steps to the reference point is determined by the processor 302 (step 516). The number of steps is determined based on the distance travelled per step determined in step 512 and the updated distance to the reference point determined in step 514. The output unit 316 provides an output including the updated number of steps to the reference point, determined in step 516 (step 518).
It is determined whether a step distance adjustment trigger is detected (step 520). In some embodiments, the step distance adjustment trigger is detected by the processor 302. In some embodiments, the processor 302 compares data received from one or more elements of the sensor array 306 with a list or table of step distance adjustment triggers. When there is a match, the processor 302 determines a step distance adjustment trigger is detected. For example, the accelerometer 312 may provide device acceleration data to the processor 302. The device acceleration data is compared to a list or table including an acceleration threshold, and when the device acceleration data exceeds the acceleration threshold, the step distance adjustment trigger is detected, as an increase in acceleration may indicate that the user of the device 104 has begun moving faster (e.g., walking at a faster rate, jogging, or running) and the distance between steps may have increased accordingly. Conversely, a deceleration may be detected, and when the deceleration exceeds a deceleration threshold, the step distance adjustment trigger is detected, as deceleration may indicate that the user of the device 104 has slowed down (e.g., going from running to jogging, running to walking, or from a brisk walk to a slow walk) and the distance between steps may have decreased accordingly.
When the step distance adjustment trigger is detected by the processor 302, the process proceeds to step 512, where the distance travelled per step is updated (step 512), the distance to the reference point is updated (step 514), the number of steps corresponding to the updated distance to the reference point is updated (step 516), and the output is provided indicating the updated number of steps (step 518).
When the step distance adjustment trigger is not detected, it is determined whether a time to update the number of steps is reached (step 522). In some embodiments, the number of steps to the reference point is periodically updated and the updated number of steps is provided to the user to keep the user apprised as to the user's progress toward the reference point. In some embodiments, the frequency by which the number of steps to the reference point is updated is determined by the user.
When the time to update the number of steps is reached, the process proceeds to step 512, where the distance travelled per step is updated (step 512), the distance to the reference point is updated (step 514), the number of steps corresponding to the updated distance to the reference point is updated (step 516), and the output is provided indicating the updated number of steps (step 518).
With reference now to
Each of the various locations 606 and environment categories 608 may be distinguished based on various characteristics. The locations 606 may correspond to particular geographical locations, such as a particular mall (Mall X), a particular subway station (Subway Station X), or a particular office building (Office Building X). The locations 606 may also correspond to general locations such as a supermarket. The locations 606 may be identified using geographic coordinates or may be identified based on image data detected by camera 308 and/or stereo cameras 310. For example, the image data may capture a name of a subway station or a series of store names in a mall, allowing the device 104 to identify a particular location. The locations 606 may also be identified using GPS data received by the GPS unit 326.
The environment categories 608 may correspond to conditions, such as whether the device is indoors or outdoors or whether the environment is crowded or empty. In some embodiments, the environment category 608 to apply is determined based on the image data from the camera 308. For example, the camera 308 and/or the stereo cameras 310 may detect the image data indicating the user is indoors or in a crowded environment. In some embodiments, the sensor data from the sensor 314 is used to determine the environment category to apply.
As described herein, the location 606 and the environment categories 608 may have associated step distance data for a general user 602 and a particular user 604. The data for the general user 602 may be aggregated and determined based on the step distance data for all users in the particular location or the environment category. In contrast, the data for the particular user 604 is based on the step distance data for the particular user only.
In some embodiments, the device 104 will determine whether stored step distance data is available for the particular user 604 for the current location and/or the current type of environment. When step distance data for the particular user 604 is available, the user's step distance data is used to establish a baseline distance travelled per step for the particular user 604. When step distance data for the particular user 604 in the current location and the current type of environment is unavailable, the general user's 602 step distance data is used to establish the baseline distance travelled per step for the user. In an example embodiment, when the device 104 detects that the particular user 604 is at the Mall X, and a baseline distance travelled per step is to be determined, 2.6 feet per step is used as the distance travelled per step, for purposes of determining the number of steps to reference points. When the device 104 detects that the particular user 604 is at Subway Station X, there is no stored step distance data for the particular user 604 at Subway Station X, so 2.7 feet per step is used, which corresponds to the stored step distance data for the general user 602.
In some embodiments, more than one of the locations 606 and environments 608 may apply, such as a crowded indoor mall. The corresponding stored step distance data for the applicable conditions may be averaged, or the median may be used. In an example embodiment, if the particular user 604 is at Mall X and it is crowded, the values of 2.6 and 1.9 may be averaged to determine a baseline distance travelled per step for the user.
The step distance data may be updated based on determined distance travelled per step while the user is within a particular category. For example, if the database 600 is used, and the device 104 detects the particular user 604 is at Subway Station X and it is crowded, and the particular user 604 averages 2.5 feet per step while the user is at Subway Station X, then the values associated with the particular user 604 for Subway Station X and for a crowded environment may be added or modified. In the example database 600, there is no value for the particular user 604 at Subway Station X, so 2.5 is stored in the corresponding entry. For the particular user 604 in crowded environments, a value of 1.9 is currently stored, but it may be modified by the 2.5 feet per step the particular user 604 averaged in this session.
In some embodiments, additional environment categories 608 and locations 606 may be added. For example, if the user goes to a location not listed in the locations 606 more than a threshold number of times, the particular location may be added to the list of locations 606.
In some embodiments, when there is no value associated with the particular user 604 for a location 606 or environment category 608, an average distance travelled per step of the particular user 604 for all locations and environments is used. In some embodiments, the average distance travelled per step of the particular user 604 for all locations and environments is averaged with the general user 602 data for the corresponding location 606 and/or environment category 608.
Exemplary embodiments of the methods/systems have been disclosed in an illustrative style. Accordingly, the terminology employed throughout should be read in a non-limiting manner. Although minor modifications to the teachings herein will occur to those well versed in the art, it shall be understood that what is intended to be circumscribed within the scope of the patent warranted hereon are all such embodiments that reasonably fall within the scope of the advancement to the art hereby contributed, and that that scope shall not be restricted, except in light of the appended claims and their equivalents.
Number | Name | Date | Kind |
---|---|---|---|
4520501 | DuBrucq | May 1985 | A |
4586827 | Hirsch et al. | May 1986 | A |
4786966 | Hanson | Nov 1988 | A |
5047952 | Kramer | Sep 1991 | A |
5097856 | Chi-Sheng | Mar 1992 | A |
5129716 | Holakovsky et al. | Jul 1992 | A |
5233520 | Kretsch et al. | Aug 1993 | A |
5265272 | Kurcbart | Nov 1993 | A |
5463428 | Lipton et al. | Oct 1995 | A |
5508699 | Silverman | Apr 1996 | A |
5539665 | Lamming et al. | Jul 1996 | A |
5543802 | Villevieille | Aug 1996 | A |
5544050 | Abe | Aug 1996 | A |
5568127 | Bang | Oct 1996 | A |
5636038 | Lynt | Jun 1997 | A |
5659764 | Sakiyama | Aug 1997 | A |
5701356 | Stanford et al. | Dec 1997 | A |
5733127 | Mecum | Mar 1998 | A |
5807111 | Schrader | Sep 1998 | A |
5872744 | Taylor | Feb 1999 | A |
5953693 | Sakiyama | Sep 1999 | A |
5956630 | Mackey | Sep 1999 | A |
5982286 | Vanmoor | Nov 1999 | A |
6009577 | Day | Jan 2000 | A |
6055048 | Langevin et al. | Apr 2000 | A |
6067112 | Wellner et al. | May 2000 | A |
6199010 | Richton | Mar 2001 | B1 |
6229901 | Mickelson et al. | May 2001 | B1 |
6230135 | Ramsay | May 2001 | B1 |
6230349 | Silver et al. | May 2001 | B1 |
6285757 | Carroll et al. | Sep 2001 | B1 |
6307526 | Mann | Oct 2001 | B1 |
6323807 | Golding et al. | Nov 2001 | B1 |
6349001 | Spitzer | Feb 2002 | B1 |
6466232 | Newell | Oct 2002 | B1 |
6477239 | Ohki | Nov 2002 | B1 |
6542623 | Kahn | Apr 2003 | B1 |
6580999 | Maruyama et al. | Jun 2003 | B2 |
6594370 | Anderson | Jul 2003 | B1 |
6603863 | Nagayoshi | Aug 2003 | B1 |
6619836 | Silvant et al. | Sep 2003 | B1 |
6701296 | Kramer | Mar 2004 | B1 |
6774788 | Balfe | Aug 2004 | B1 |
6825875 | Strub et al. | Nov 2004 | B1 |
6826477 | Ladetto et al. | Nov 2004 | B2 |
6834373 | Dieberger | Dec 2004 | B2 |
6839667 | Reich | Jan 2005 | B2 |
6857775 | Wilson | Feb 2005 | B1 |
6920229 | Boesen | Jul 2005 | B2 |
D513997 | Wilson | Jan 2006 | S |
7027874 | Sawan et al. | Apr 2006 | B1 |
D522300 | Roberts | Jun 2006 | S |
7069215 | Bangalore | Jun 2006 | B1 |
7106220 | Gourgey et al. | Sep 2006 | B2 |
7228275 | Endo | Jun 2007 | B1 |
7299034 | Kates | Nov 2007 | B2 |
7308314 | Havey et al. | Dec 2007 | B2 |
7336226 | Jung et al. | Feb 2008 | B2 |
7356473 | Kates | Apr 2008 | B2 |
7413554 | Kobayashi et al. | Aug 2008 | B2 |
7417592 | Hsiao et al. | Aug 2008 | B1 |
7428429 | Gantz et al. | Sep 2008 | B2 |
7463188 | McBurney | Dec 2008 | B1 |
7496445 | Mohsini | Feb 2009 | B2 |
7501958 | Saltzstein et al. | Mar 2009 | B2 |
7525568 | Raghunath | Apr 2009 | B2 |
7564469 | Cohen | Jul 2009 | B2 |
7565295 | Hernandez-Rebollar | Jul 2009 | B1 |
7598976 | Sofer et al. | Oct 2009 | B2 |
7618260 | Daniel et al. | Nov 2009 | B2 |
D609818 | Tsang et al. | Feb 2010 | S |
7656290 | Fein et al. | Feb 2010 | B2 |
7659915 | Kurzweil et al. | Feb 2010 | B2 |
7743996 | Maciver | Jun 2010 | B2 |
D625427 | Lee | Oct 2010 | S |
7843351 | Bourne | Nov 2010 | B2 |
7843488 | Stapleton | Nov 2010 | B2 |
7848512 | Eldracher | Dec 2010 | B2 |
7864991 | Espenlaub et al. | Jan 2011 | B2 |
7938756 | Rodetsky et al. | May 2011 | B2 |
7991576 | Roumeliotis | Aug 2011 | B2 |
8005263 | Fujimura | Aug 2011 | B2 |
8035519 | Davis | Oct 2011 | B2 |
D649655 | Petersen | Nov 2011 | S |
8123660 | Kruse et al. | Feb 2012 | B2 |
D656480 | McManigal et al. | Mar 2012 | S |
8138907 | Barbeau et al. | Mar 2012 | B2 |
8150107 | Kurzweil et al. | Apr 2012 | B2 |
8177705 | Abolfathi | May 2012 | B2 |
8239032 | Dewhurst | Aug 2012 | B2 |
8253760 | Sako et al. | Aug 2012 | B2 |
8300862 | Newton et al. | Oct 2012 | B2 |
8325263 | Kato et al. | Dec 2012 | B2 |
D674501 | Petersen | Jan 2013 | S |
8359122 | Koselka et al. | Jan 2013 | B2 |
8395968 | Vartanian et al. | Mar 2013 | B2 |
8401785 | Cho et al. | Mar 2013 | B2 |
8414246 | Tobey | Apr 2013 | B2 |
8418705 | Ota et al. | Apr 2013 | B2 |
8428643 | Lin | Apr 2013 | B2 |
8483956 | Zhang | Jul 2013 | B2 |
8494507 | Tedesco et al. | Jul 2013 | B1 |
8494859 | Said | Jul 2013 | B2 |
8538687 | Plocher et al. | Sep 2013 | B2 |
8538688 | Prehofer | Sep 2013 | B2 |
8571860 | Strope | Oct 2013 | B2 |
8583282 | Angle et al. | Nov 2013 | B2 |
8588464 | Albertson et al. | Nov 2013 | B2 |
8588972 | Fung | Nov 2013 | B2 |
8591412 | Kovarik et al. | Nov 2013 | B2 |
8594935 | Cioffi et al. | Nov 2013 | B2 |
8606316 | Evanitsky | Dec 2013 | B2 |
8610879 | Ben-Moshe et al. | Dec 2013 | B2 |
8630633 | Tedesco et al. | Jan 2014 | B1 |
8676274 | Li | Mar 2014 | B2 |
8676623 | Gale et al. | Mar 2014 | B2 |
8694251 | Janardhanan et al. | Apr 2014 | B2 |
8704902 | Naick et al. | Apr 2014 | B2 |
8718672 | Xie et al. | May 2014 | B2 |
8743145 | Price | Jun 2014 | B1 |
8750898 | Haney | Jun 2014 | B2 |
8768071 | Tsuchinaga et al. | Jul 2014 | B2 |
8786680 | Shiratori | Jul 2014 | B2 |
8797141 | Best et al. | Aug 2014 | B2 |
8797386 | Chou et al. | Aug 2014 | B2 |
8803699 | Foshee et al. | Aug 2014 | B2 |
8805929 | Erol et al. | Aug 2014 | B2 |
8812244 | Angelides | Aug 2014 | B2 |
8814019 | Dyster et al. | Aug 2014 | B2 |
8825398 | Alexandre | Sep 2014 | B2 |
8836532 | Fish, Jr. et al. | Sep 2014 | B2 |
8836580 | Mendelson | Sep 2014 | B2 |
8836910 | Cashin et al. | Sep 2014 | B2 |
8902303 | Na'Aman et al. | Dec 2014 | B2 |
8909534 | Heath | Dec 2014 | B1 |
D721673 | Park et al. | Jan 2015 | S |
8926330 | Taghavi | Jan 2015 | B2 |
8930458 | Lewis et al. | Jan 2015 | B2 |
8981682 | Delson et al. | Mar 2015 | B2 |
8994498 | Agrafioti et al. | Mar 2015 | B2 |
D727194 | Wilson | Apr 2015 | S |
9004330 | White | Apr 2015 | B2 |
9025016 | Wexler et al. | May 2015 | B2 |
9042596 | Connor | May 2015 | B2 |
9053094 | Yassa | Jun 2015 | B2 |
9076450 | Sadek | Jul 2015 | B1 |
9081079 | Chao et al. | Jul 2015 | B2 |
9081385 | Ferguson | Jul 2015 | B1 |
D736741 | Katz | Aug 2015 | S |
9111545 | Jadhav et al. | Aug 2015 | B2 |
D738238 | Pede et al. | Sep 2015 | S |
9137484 | DiFrancesco et al. | Sep 2015 | B2 |
9137639 | Garin et al. | Sep 2015 | B2 |
9140554 | Jerauld | Sep 2015 | B2 |
9148191 | Teng et al. | Sep 2015 | B2 |
9158378 | Hirukawa | Oct 2015 | B2 |
D742535 | Wu | Nov 2015 | S |
D743933 | Park et al. | Nov 2015 | S |
9185489 | Gerber et al. | Nov 2015 | B2 |
9190058 | Klein | Nov 2015 | B2 |
9104806 | Stivoric et al. | Dec 2015 | B2 |
9230430 | Civelli et al. | Jan 2016 | B2 |
9232366 | Charlier et al. | Jan 2016 | B1 |
9267801 | Gupta et al. | Feb 2016 | B2 |
9269015 | Boncyk | Feb 2016 | B2 |
9275376 | Barraclough et al. | Mar 2016 | B2 |
9304588 | Aldossary | Apr 2016 | B2 |
D756958 | Lee et al. | May 2016 | S |
D756959 | Lee et al. | May 2016 | S |
9335175 | Zhang et al. | May 2016 | B2 |
9341014 | Oshima et al. | May 2016 | B2 |
9355547 | Stevens et al. | May 2016 | B2 |
20010023387 | Rollo | Sep 2001 | A1 |
20020067282 | Moskowitz et al. | Jun 2002 | A1 |
20020071277 | Starner et al. | Jun 2002 | A1 |
20020075323 | O'Dell | Jun 2002 | A1 |
20020173346 | Wang | Nov 2002 | A1 |
20020178344 | Bourguet | Nov 2002 | A1 |
20030026461 | Arthur Hunter | Feb 2003 | A1 |
20030133008 | Stephenson | Jul 2003 | A1 |
20030133085 | Tretiakoff | Jul 2003 | A1 |
20030179133 | Pepin | Sep 2003 | A1 |
20040056907 | Sharma et al. | Mar 2004 | A1 |
20040232179 | Chauhan | Nov 2004 | A1 |
20040267442 | Fehr et al. | Dec 2004 | A1 |
20050020845 | Suzuki et al. | Jan 2005 | A1 |
20050140544 | Hamel | Jun 2005 | A1 |
20050221260 | Kikuchi | Oct 2005 | A1 |
20050259035 | Iwaki | Nov 2005 | A1 |
20050283752 | Fruchter | Dec 2005 | A1 |
20060004512 | Herbst | Jan 2006 | A1 |
20060028550 | Palmer | Feb 2006 | A1 |
20060029256 | Miyoshi | Feb 2006 | A1 |
20060129308 | Kates | Jun 2006 | A1 |
20060171704 | Bingle et al. | Aug 2006 | A1 |
20060177086 | Rye et al. | Aug 2006 | A1 |
20060184318 | Yoshimine | Aug 2006 | A1 |
20060292533 | Selod | Dec 2006 | A1 |
20070001904 | Mendelson | Jan 2007 | A1 |
20070052672 | Ritter et al. | Mar 2007 | A1 |
20070173688 | Kim | Jul 2007 | A1 |
20070182812 | Ritchey | Aug 2007 | A1 |
20070202865 | Moride | Aug 2007 | A1 |
20070230786 | Foss | Oct 2007 | A1 |
20070296572 | Fein | Dec 2007 | A1 |
20080024594 | Ritchey | Jan 2008 | A1 |
20080068559 | Howell | Mar 2008 | A1 |
20080120029 | Zelek et al. | May 2008 | A1 |
20080144854 | Abreu | Jun 2008 | A1 |
20080145822 | Bucchieri | Jun 2008 | A1 |
20080174676 | Squilla et al. | Jul 2008 | A1 |
20080198222 | Gowda | Aug 2008 | A1 |
20080198324 | Fuziak | Aug 2008 | A1 |
20080208455 | Hartman | Aug 2008 | A1 |
20080251110 | Pede | Oct 2008 | A1 |
20080260210 | Kobeli | Oct 2008 | A1 |
20090012788 | Gilbert | Jan 2009 | A1 |
20090040215 | Afzulpurkar | Feb 2009 | A1 |
20090058611 | Kawamura | Mar 2009 | A1 |
20090106016 | Athsani et al. | Apr 2009 | A1 |
20090118652 | Carlucci | May 2009 | A1 |
20090122161 | Bolkhovitinov | May 2009 | A1 |
20090122648 | Mountain et al. | May 2009 | A1 |
20090157302 | Tashev et al. | Jun 2009 | A1 |
20090177437 | Roumeliotis | Jul 2009 | A1 |
20090189974 | Deering | Jul 2009 | A1 |
20090210596 | Furuya | Aug 2009 | A1 |
20100041378 | Aceves | Feb 2010 | A1 |
20100042322 | Won | Feb 2010 | A1 |
20100080418 | Ito | Apr 2010 | A1 |
20100109918 | Liebermann | May 2010 | A1 |
20100110368 | Chaum | May 2010 | A1 |
20100179452 | Srinivasan | Jul 2010 | A1 |
20100182242 | Fields et al. | Jul 2010 | A1 |
20100182450 | Kumar | Jul 2010 | A1 |
20100198494 | Chao | Aug 2010 | A1 |
20100199232 | Mistry et al. | Aug 2010 | A1 |
20100241350 | Cioffi et al. | Sep 2010 | A1 |
20100245585 | Fisher et al. | Sep 2010 | A1 |
20100267276 | Wu | Oct 2010 | A1 |
20100292917 | Emam et al. | Nov 2010 | A1 |
20100298976 | Sugihara et al. | Nov 2010 | A1 |
20100305845 | Alexandre et al. | Dec 2010 | A1 |
20100308999 | Chornenky | Dec 2010 | A1 |
20110066383 | Jangle | Mar 2011 | A1 |
20110071830 | Kim | Mar 2011 | A1 |
20110092249 | Evanitsky | Apr 2011 | A1 |
20110124383 | Garra et al. | May 2011 | A1 |
20110125735 | Petrou | May 2011 | A1 |
20110181422 | Tran | Jul 2011 | A1 |
20110187640 | Jacobsen | Aug 2011 | A1 |
20110211760 | Boncyk | Sep 2011 | A1 |
20110216006 | Litschel | Sep 2011 | A1 |
20110221670 | King, III et al. | Sep 2011 | A1 |
20110234584 | Endo | Sep 2011 | A1 |
20110246064 | Nicholson | Oct 2011 | A1 |
20110260681 | Guccione | Oct 2011 | A1 |
20110307172 | Jadhav et al. | Dec 2011 | A1 |
20120016578 | Coppens | Jan 2012 | A1 |
20120053826 | Slamka | Mar 2012 | A1 |
20120062357 | Slamka | Mar 2012 | A1 |
20120069511 | Azera | Mar 2012 | A1 |
20120075168 | Osterhout et al. | Mar 2012 | A1 |
20120082962 | Schmidt | Apr 2012 | A1 |
20120085377 | Trout | Apr 2012 | A1 |
20120092161 | West | Apr 2012 | A1 |
20120092460 | Mahoney | Apr 2012 | A1 |
20120123784 | Baker et al. | May 2012 | A1 |
20120136666 | Corpier et al. | May 2012 | A1 |
20120143495 | Dantu | Jun 2012 | A1 |
20120162423 | Xiao et al. | Jun 2012 | A1 |
20120194552 | Osterhout et al. | Aug 2012 | A1 |
20120206335 | Osterhout et al. | Aug 2012 | A1 |
20120206607 | Morioka | Aug 2012 | A1 |
20120207356 | Murphy | Aug 2012 | A1 |
20120214418 | Lee | Aug 2012 | A1 |
20120220234 | Abreu | Aug 2012 | A1 |
20120232430 | Boissy et al. | Sep 2012 | A1 |
20120249797 | Haddick et al. | Oct 2012 | A1 |
20120252483 | Farmer et al. | Oct 2012 | A1 |
20120316884 | Rozaieski et al. | Dec 2012 | A1 |
20120323485 | Mutoh | Dec 2012 | A1 |
20120327194 | Shiratori | Dec 2012 | A1 |
20130002452 | Lauren | Jan 2013 | A1 |
20130044005 | Foshee et al. | Feb 2013 | A1 |
20130046541 | Klein et al. | Feb 2013 | A1 |
20130066636 | Singhal | Mar 2013 | A1 |
20130079061 | Jadhav | Mar 2013 | A1 |
20130090133 | D'Jesus Bencci | Apr 2013 | A1 |
20130115578 | Shiina et al. | May 2013 | A1 |
20130115579 | Taghavi | May 2013 | A1 |
20130116559 | Levin | May 2013 | A1 |
20130127980 | Haddick | May 2013 | A1 |
20130128051 | Velipasalar et al. | May 2013 | A1 |
20130131985 | Weiland et al. | May 2013 | A1 |
20130141576 | Lord et al. | Jun 2013 | A1 |
20130144629 | Johnston et al. | Jun 2013 | A1 |
20130155474 | Roach et al. | Jun 2013 | A1 |
20130157230 | Morgan | Jun 2013 | A1 |
20130184982 | DeLuca | Jul 2013 | A1 |
20130201344 | Sweet, III et al. | Aug 2013 | A1 |
20130204605 | Illgner-Fehns | Aug 2013 | A1 |
20130211718 | Yoo et al. | Aug 2013 | A1 |
20130218456 | Zelek et al. | Aug 2013 | A1 |
20130202274 | Chan | Sep 2013 | A1 |
20130228615 | Gates et al. | Sep 2013 | A1 |
20130229669 | Smits | Sep 2013 | A1 |
20130243250 | France et al. | Sep 2013 | A1 |
20130245396 | Berman et al. | Sep 2013 | A1 |
20130250078 | Levy | Sep 2013 | A1 |
20130250233 | Blum et al. | Sep 2013 | A1 |
20130253818 | Sanders et al. | Sep 2013 | A1 |
20130265450 | Barnes, Jr. | Oct 2013 | A1 |
20130271584 | Wexler et al. | Oct 2013 | A1 |
20130290909 | Gray | Oct 2013 | A1 |
20130307842 | Grinberg et al. | Nov 2013 | A1 |
20130311179 | Wagner | Nov 2013 | A1 |
20130328683 | Sitbon et al. | Dec 2013 | A1 |
20130332452 | Jarvis | Dec 2013 | A1 |
20140009561 | Sutherland | Jan 2014 | A1 |
20140031081 | Vossoughi | Jan 2014 | A1 |
20140031703 | Rayner | Jan 2014 | A1 |
20140031977 | Goldenberg et al. | Jan 2014 | A1 |
20140032596 | Fish et al. | Jan 2014 | A1 |
20140037149 | Zetune | Feb 2014 | A1 |
20140055353 | Takahama | Feb 2014 | A1 |
20140071234 | Millett | Mar 2014 | A1 |
20140081631 | Zhu et al. | Mar 2014 | A1 |
20140085446 | Hicks | Mar 2014 | A1 |
20140098018 | Kim et al. | Apr 2014 | A1 |
20140100773 | Cunningham et al. | Apr 2014 | A1 |
20140125700 | Ramachandran | May 2014 | A1 |
20140132388 | Alalawi | May 2014 | A1 |
20140133290 | Yokoo | May 2014 | A1 |
20140160250 | Pomerantz | Jun 2014 | A1 |
20140172361 | Chiang | Jun 2014 | A1 |
20140184384 | Zhu et al. | Jul 2014 | A1 |
20140184775 | Drake | Jul 2014 | A1 |
20140204245 | Wexler | Jul 2014 | A1 |
20140222023 | Kim et al. | Aug 2014 | A1 |
20140228649 | Rayner | Aug 2014 | A1 |
20140233859 | Cho | Aug 2014 | A1 |
20140236932 | Ikonomov | Aug 2014 | A1 |
20140249847 | Soon-Shiong | Sep 2014 | A1 |
20140251396 | Subhashrao et al. | Sep 2014 | A1 |
20140253702 | Wexler | Sep 2014 | A1 |
20140278070 | McGavran | Sep 2014 | A1 |
20140281943 | Prilepov | Sep 2014 | A1 |
20140287382 | Villar Cloquell | Sep 2014 | A1 |
20140309806 | Ricci | Oct 2014 | A1 |
20140313040 | Wright, Sr. | Oct 2014 | A1 |
20140335893 | Ronen | Nov 2014 | A1 |
20140343846 | Goldman et al. | Nov 2014 | A1 |
20140345956 | Kojina | Nov 2014 | A1 |
20140347265 | Aimone | Nov 2014 | A1 |
20140368412 | Jacobsen | Dec 2014 | A1 |
20140369541 | Miskin | Dec 2014 | A1 |
20140379251 | Tolstedt | Dec 2014 | A1 |
20140379336 | Bhatnager | Dec 2014 | A1 |
20150002808 | Rizzo, III | Jan 2015 | A1 |
20150016035 | Tussy | Jan 2015 | A1 |
20150058237 | Bailey | Feb 2015 | A1 |
20150063661 | Lee | Mar 2015 | A1 |
20150081884 | Maguire | Mar 2015 | A1 |
20150099946 | Sahin | Apr 2015 | A1 |
20150109107 | Gomez et al. | Apr 2015 | A1 |
20150120186 | Heikes | Apr 2015 | A1 |
20150135310 | Lee | May 2015 | A1 |
20150141085 | Nuovo et al. | May 2015 | A1 |
20150141873 | Fei | May 2015 | A1 |
20150142891 | Haque | May 2015 | A1 |
20150154643 | Artman et al. | Jun 2015 | A1 |
20150125831 | Chandrashekhar Nair et al. | Jul 2015 | A1 |
20150196101 | Dayal et al. | Jul 2015 | A1 |
20150198454 | Moore et al. | Jul 2015 | A1 |
20150198455 | Chen | Jul 2015 | A1 |
20150199566 | Moore et al. | Jul 2015 | A1 |
20150201181 | Moore et al. | Jul 2015 | A1 |
20150211858 | Jerauld | Jul 2015 | A1 |
20150219757 | Boelter et al. | Aug 2015 | A1 |
20150223355 | Fleck | Aug 2015 | A1 |
20150256977 | Huang | Sep 2015 | A1 |
20150257555 | Wong | Sep 2015 | A1 |
20150260474 | Rublowsky | Sep 2015 | A1 |
20150262509 | Labbe | Sep 2015 | A1 |
20150279172 | Hyde | Oct 2015 | A1 |
20150324646 | Kimia | Nov 2015 | A1 |
20150330787 | Cioffi et al. | Nov 2015 | A1 |
20150336276 | Song | Nov 2015 | A1 |
20150338917 | Steiner et al. | Nov 2015 | A1 |
20150341591 | Kelder et al. | Nov 2015 | A1 |
20150346496 | Haddick et al. | Dec 2015 | A1 |
20150350845 | Patel | Dec 2015 | A1 |
20150356345 | Velozo | Dec 2015 | A1 |
20150356837 | Pajestka | Dec 2015 | A1 |
20150364943 | Vick | Dec 2015 | A1 |
20150367176 | Bejestan | Dec 2015 | A1 |
20150375395 | Kwon | Dec 2015 | A1 |
20160007158 | Venkatraman | Jan 2016 | A1 |
20160028917 | Wexler | Jan 2016 | A1 |
20160042228 | Opalka | Feb 2016 | A1 |
20160078289 | Michel et al. | Mar 2016 | A1 |
20160098138 | Park | Apr 2016 | A1 |
20160156850 | Werblin et al. | Jun 2016 | A1 |
20160166197 | Venkatraman | Jun 2016 | A1 |
20160198319 | Huang | Jul 2016 | A1 |
20160350514 | Rajendran | Dec 2016 | A1 |
20170227574 | Theytaz | Aug 2017 | A1 |
Number | Date | Country |
---|---|---|
201260746 | Jun 2009 | CN |
101527093 | Sep 2009 | CN |
201440733 | Apr 2010 | CN |
101803988 | Aug 2010 | CN |
101647745 | Jan 2011 | CN |
102316193 | Jan 2012 | CN |
102631280 | Aug 2012 | CN |
202547659 | Nov 2012 | CN |
202722736 | Feb 2013 | CN |
102323819 | Jun 2013 | CN |
103445920 | Dec 2013 | CN |
102011080056 | Jan 2013 | DE |
102012000587 | Jul 2013 | DE |
102012202614 | Aug 2013 | DE |
1174049 | Sep 2004 | EP |
1721237 | Nov 2006 | EP |
2364855 | Sep 2011 | EP |
2371339 | Oct 2011 | EP |
2127033 | Aug 2012 | EP |
2581856 | Apr 2013 | EP |
2751775 | Jul 2016 | EP |
2885251 | Nov 2006 | FR |
2401752 | Nov 2004 | GB |
10069539 | Mar 1998 | JP |
2001304908 | Oct 2001 | JP |
201012529 | Jan 2010 | JP |
2010182193 | Aug 2010 | JP |
4727352 | Jul 2011 | JP |
2013169611 | Sep 2013 | JP |
100405636 | Nov 2003 | KR |
20080080688 | Sep 2008 | KR |
20120020212 | Mar 2012 | KR |
1250929 | Apr 2013 | KR |
WO1995004440 | Feb 1995 | WO |
WO 9949656 | Sep 1999 | WO |
WO 0010073 | Feb 2000 | WO |
WO 0038393 | Jun 2000 | WO |
WO 0179956 | Oct 2001 | WO |
WO 2004076974 | Sep 2004 | WO |
WO 2006028354 | Mar 2006 | WO |
WO 2006045819 | May 2006 | WO |
WO 2007031782 | Mar 2007 | WO |
WO 2008008791 | Jan 2008 | WO |
WO 2008015375 | Feb 2008 | WO |
WO 2008035993 | Mar 2008 | WO |
WO 2008096134 | Aug 2008 | WO |
WO2008127316 | Oct 2008 | WO |
WO 2010062481 | Jun 2010 | WO |
WO 2010109313 | Sep 2010 | WO |
WO 2012040703 | Mar 2012 | WO |
WO2012163675 | Dec 2012 | WO |
WO 2013045557 | Apr 2013 | WO |
WO 2013054257 | Apr 2013 | WO |
WO 2013067539 | May 2013 | WO |
WO 2013147704 | Oct 2013 | WO |
WO 2014104531 | Jul 2014 | WO |
WO 2014138123 | Sep 2014 | WO |
WO 2014172378 | Oct 2014 | WO |
WO 2015065418 | May 2015 | WO |
WO2015092533 | Jun 2015 | WO |
WO 2015108882 | Jul 2015 | WO |
WO2015127062 | Aug 2015 | WO |
Entry |
---|
Zhang, Shanjun; Yoshino, Kazuyoshi; A Braille Recognition System by the Mobile Phone with Embedded Camera; 2007; IEEE. |
Diallo, Amadou; Sep. 18, 2014; Apple iOS8: Top New Features, Forbes Magazine. |
N. Kalar, T. Lawers, D. Dewey, T. Stepleton, M.B. Dias; Iterative Design of a Braille Writing Tutor to Combat Illiteracy; Aug. 30, 2007; IEEE. |
Bharathi et al.; “Effective Navigation for Visually Impaired by Wearable Obstacle Avoidance System;” 2012 International Conference on Computing, Electronics and Electrical Technologies (ICCEET); pp. 956-958; 2012. |
Pawar et al.; “Review Paper on Multitasking Stick for Guiding Safe Path for Visually Disable People;” IJPRET; vol. 3, No. 9; pp. 929-936; 2015. |
Ram et al.; “The People Sensor: A Mobility Aid for the Visually Impaired;” 2012 16th International Symposium on Wearable Computers; pp. 166-167; 2012. |
Singhal; “The Development of an Intelligent Aid for Blind and Old People;” Emerging Trends and Applications in Computer Science (ICETACS), 2013 1st International Conference; pp. 182-185; Sep. 13, 2013. |
Aggarwal et al.; “All-in-One Companion for Visually Impaired;” International Journal of Computer Applications; vol. 79, No. 14; pp. 37-40; Oct. 2013. |
“Light Detector” Every Ware Technologies; 2 pages; Jun. 18, 2016. |
Arati et al. “Object Recognition in Mobile Phone Application for Visually Impaired Users;” IOSR Journal of Computer Engineering (IOSR-JCE); vol. 17, No. 1; pp. 30-33; Jan. 2015. |
Yabu et al.; “Development of a Wearable Haptic Tactile Interface as an Aid for the Hearing and/or Visually Impaired;” NTUT Education of Disabilities; vol. 13; pp. 5-12; 2015. |
Mau et al.; “BlindAid: An Electronic Travel Aid for the Blind;” The Robotics Institute Carnegie Mellon University; 27 pages; May 2008. |
Shidujaman et al.; “Design and navigation Prospective for Wireless Power Transmission Robot;” IEEE; Jun. 2015. |
Wu et al. “Fusing Multi-Modal Features for Gesture Recognition”, Proceedings of the 15th ACM on International Conference on Multimodal Interaction, Dec. 9, 2013, ACM, pp. 453-459. |
Pitsikalis et al. “Multimodal Gesture Recognition via Multiple Hypotheses Rescoring”, Journal of Machine Learning Research, Feb. 2015, pp. 255-284. |
Shen et al. “Walkie-Markie: Indoor Pathway Mapping Made Easy” 10th USENIX Symposium on Networked Systems Design and Implementation (NSDI'13); pp. 85-98, 2013. |
Tu et al. “Crowdsourced Routing II D2.6” 34 pages; 2012. |
De Choudhury et al. “Automatic Construction of Travel Itineraries Using Social Breadcrumbs” pp. 35-44; Jun. 2010. |
The Nex Band; http://www.mightvcast.com/#faq; May 19, 2015; 4 pages. |
Cardonha et al.; “A Crowdsourcing Platform for the Construction of Accessibility Maps”; W4A'13 Proceedings of the 10th International Cross-Disciplinary Conference on Web Accessibility; Article No. 26; 2013; 5 pages. |
Bujacz et al.; “Remote Guidance for the Blind—A Proposed Teleassistance System and Navigation Trials”; Conference on Human System Interactions; May 25-27, 2008; 6 pages. |
Rodriguez et al; “CrowdSight: Rapidly Prototyping Intelligent Visual Processing Apps”; AAAI Human Computation Workshop (HCOMP); 2011; 6 pages. |
Chaudary et al.; “Alternative Navigation Assistance Aids for Visually Impaired Blind Persons”; Proceedings of Iceapvi; Feb. 12-14 2015; 5 pp. |
Garaj et al.; “A System for Remote Sighted Guidance of Visually Impaired Pedestrians”; the British Journal of Visual Impairment; vol. 21, No. 2, 2003; 9 pp. |
Coughlan et al.; “Crosswatch: a System for Providing Guidance to Visually Impaired Travelers at Traffic Intersections”; Journal of Assistive Technologies 7.2; 2013; 17 pp. |
Sudol et al.; “LookTel — a Comprehensive Platform for Computer-Aided Visual Assistance”; Computer Vision and Pattern Recognition Workshops (Cvprw), 2010 IEEE Computer Society Conference; Jun. 13-18, 2010; 8 pp. |
Paladugu et al.; “GoingEasy® with Crowdsourcing in the Web 2.0 World for Visually Impaired Users: Design and User Study”; Arizona State University; 8 pp. |
Kammoun et al.; “Towards a Geographic Information System Facilitating Navigation of Visually Impaired Users”; Springer Berlin Heidelberg; 2012; 8 pp. |
Bigham et al.; “Viz Wiz: Nearly Real-Time Answers to Visual Questions” Proceedings of the 23nd annual Acm symposium on User interface software and technology; 2010; 2 pp. |
Guy et al; “CrossingGuard: Exploring Information Content in Navigation Aids for Visually Impaired Pedestrians” Proceedings of the Sigchi Conference on Human Factors in Computing Systems; May 5-10, 2012; 10 pp. |
Zhang et al.; “A Multiple Sensor-Based Shoe-Mounted User Interface Designed for Navigation Systems for the Visually Impaired”; 5th Annual Icst Wireless Internet Conference (Wicon); Mar. 1-3, 2010; 9 pp. |
Shoval et al.; “Navbelt and the Guidecane - Robotics-Based Obstacle Avoidance Systems for the Blind and Visually Impaired”; IEEE Robotics & Automation Magazine, vol. 10, Issue 1; Mar. 2003; 12 pp. |
Dowling et al.; “Intelligent Image Artificial Vision”; 8th Australian (Anziis); Dec. 10-12, 2003; Processing Constraints for Blind Mobility Facilitated Through Systems Conference. |
Heyes, Tony; “The Sonic Pathfinder an Electronic Travel Aid for the http://members.optuszoo.com.au/aheyew40/pa/pf blerf.html; Dec. Vision Impaired”;. |
Lee et al.; “Adaptive Power Control of Obstacle Avoidance System Using Via Motion Context for Visually Impaired Person.” International Conference on Cloud Computing and Social Networking (Icccsn), Apr. 26-27, 2012 4 pp. |
Wilson, Jeff, et al. “Swan: System for Wearable Audio Navigation”; 11th IEEE International Symposium on Wearable Computers; Oct. 11-13, 2007; 8 pp. |
Borenstein et al.; “The GuideCane - a Computerized Travel Aid for the Active Guidance of Blind Pedestrians”; IEEE International Conference on Robotics and Automation; Apr. 21-27, 1997; 6 pp. |
Bhatlawande et al.; “Way-finding Electronic Bracelet for Visually Impaired People”; IEEE Point-of-Care Healthcare Technologies (Pht), Jan. 16-18, 2013; 4 pp. |
Blenkhorn et al.; “An Ultrasonic Mobility Device with Minimal Audio Feedback”; Center on Disabilities Technology and Persons with Disabilities Conference; Nov. 22, 1997; 5 pp. |
Maim et al.; “Blind Navigation with a Wearable Range Camera and Vibrotactile Helmet”; 19th Acm International Conference on Multimedia; Nov. 28, 2011; 4 pp. |
Shoval et al.; “The Navbelt — a Computerized Travel Aid for the Blind”; Resna Conference, Jun. 12-17, 1993; 6 pp. |
Kumar et al.; “An Electronic Travel Aid for Navigation of Visually Impaired Persons”; Communications Systems and Networks (Comsnets), 2011 Third International Conference; Jan. 2011; 5 pp. |
Pawar et al.; “Multitasking Stick for Indicating Safe Path to Visually Disable People”; Iosr Journal of Electronics and Communication Engineering (Iosr-Jece), vol. 10, Issue 3, Ver. Ii; May-Jun 2015; 5 pp. |
Pagliarini et al.; “Robotic Art for Wearable”; Proceedings of Eurosiam: European Conference for the Applied Mathematics and Informatics 2010; 10 pp. |
Greenberg et al.; “Finding Your Way: a Curriculum for Teaching and Using the Braillenote with Sendero Gps 2011”; California School for the Blind; 2011; 190 pp. |
Helal et al.; “Drishti: an Integrated Navigation System for Visually Impaired and Disabled”; Fifth International Symposium on Wearable Computers; Oct. 8-9, 2001; 8 pp. |
Parkes, Don; “Audio Tactile Systems for Designing and Learning Complex Environments as a Vision Impaired Person: Static and Dynamic Spatial Information Access”; EdTech-94 Proceedings; 1994; 8 pp. |
Zeng et al.; “Audio-Haptic Browser for a Geographical Information System”; Icchp 2010, Part Ii, Lncs 6180; Jul. 14-16, 2010; 8 pp. |
AiZuhair et al.; “Nfc Based Applications for Visually Impaired People —a Review”; IEEE International Conference on Multimedia and Expo Workshops (Icmew), Jul. 14, 2014; 7 pp. |
Graf, Christian; “Verbally Annotated Tactile Maps — Challenges and Approaches”; Spatial Cognition Vii, vol. 6222; Aug. 15-19, 2010; 16 pp. |
Hamid, Nazatul Naquiah Abd; “Facilitating Route Learning Using Interactive Audio-Tactile Maps for Blind and Visually Impaired People”; Chi 2013 Extended Abstracts; Apr. 27, 2013; 6 pp. |
Ramya, et al.; “Voice Assisted Embedded Navigation System for the Visually Impaired”; International Journal of Computer Applications; vol. 64, No. 13, Feb. 2013; 7 pp. |
Caperna et al.; “A Navigation and Object Location Device for the Blind”; Tech. rep. University of Maryland College Park; May 2009; 129 pp. |
Burbey et al.; “Human Information Processing with the Personal Memex”; Ise 5604 Fall 2005; Dec. 6, 2005; 88 pp. |
Ghiani, et al.; “Vibrotactile Feedback to Aid Blind Users of Mobile Guides”; Journal of Visual Languages and Computing 20; 2009; 13 pp. |
Guerrero et al.; “An Indoor Navigation System for the Visually Impaired”; Sensors vol. 12, Issue 6; Jun. 13, 2012; 23 pp. |
Nordin et al.; “Indoor Navigation and Localization for Visually Impaired People Using Weighted Topological Map”; Journal of Computer Science vol. 5, Issue 11; 2009; 7 pp. |
Hesch et al.; “Design and Analysis of a Portable Indoor Localization Aid for the Visually Impaired”; International Journal of Robotics Research; vol. 29; Issue 11; Sep. 2010; 15 pgs. |
Joseph et al.; “Visual Semantic Parameterization — to Enhance Blind User Perception for Indoor Navigation”; Multimedia and Expo Workshops (Icmew), 2013 IEEE International Conference; Jul. 15/2013; 7 pp. |
Katz et al; “Navig: Augmented Reality Guidance System for the Visually Impaired”; Virtual Reality (2012) vol. 16; 2012; 17 pp. |
Rodriguez et al.; “Assisting the Visually Impaired: Obstacle Detection and Warning System by Acoustic Feedback”; Sensors 2012; vol. 12; 21 pp. |
Treuillet; “Outdoor/Indoor Vision-Based Localization for Blind Pedestrian Navigation Assistance”; Wspc/Instruction File; May 23, 2010; 16 pp. |
Ran et al.; “Drishti: an Integrated Indoor/Outdoor Blind Navigation System and Service”; Proceeding Percom '04 Proceedings of the Second IEEE International Conference on Pervasive Computing and Communications (PerCorn'04); 2004; 9 pp. |
Wang, et al.; “Camera-Based Signage Detection and Recognition for Blind Persons”; 13th International Conference (Icchp) Part 2 Proceedings; Jul. 11-13, 2012; 9 pp. |
Krishna et al.; “A Systematic Requirements Analysis and Development of an Assistive Device to Enhance the Social Interaction of People Who are Blind or Visually Impaired”; Workshop on Computer Vision Applications for the Visually Impaired; Marseille, France; 2008; 12 pp. |
Lee et al.; “A Walking Guidance System for the Visually Impaired”; International Journal of Pattern Recognition and Artificial Intelligence; vol. 22; No. 6; 2008; 16 pp. |
Ward et al.; “Visual Experiences in the Blind Induced by an Auditory Sensory Substitution Device”; Journal of Consciousness and Cognition; Oct. 2009; 30 pp. |
Merino-Garcia, et al.; “A Head-Mounted Device for Recognizing Text in Natural Sciences”; Cbdar'll Proceedings of the 4th International Conference on Camera-Based Document Analysis and Recognition; Sep. 22, 2011; 7 pp. |
Yi, Chucai; “Assistive Text Reading from Complex Background for Blind Persons”; Cbdar'll Proceedings of the 4th International Conference on Camera-Based Document Analysis and Recognition; Sep. 22, 2011; 7 pp. |
Yang, et al.; “Towards Automatic Sign Translation”; the Interactive Systems Lab, Carnegie Mellon University; 2001; 5 pp. |
Meijer, Dr. Peter B.L.; “Mobile Ocr, Face and Object Recognition for www.seeingwithsound.com/ocr.htm; Apr. 18, 2014; 7 pp.. the Blind”; the vOICe,. |
Omron; Optical Character Recognition Sensor User's Manual; 2012; 450 pp. |
Park, Sungwoo; “Voice Stick”; www.yankodesign.com/2008/08/21/voice-stick; Aug. 21, 2008; 4 pp. |
Rentschler et al.; “Intelligent Walkers for the Elderly: Performance and Safety Testing of Va-Pamaid Robotic Walker”; Department of Veterans Affairs Journal of Rehabilitation Research and Development; vol. 40, No. 5; Sep./Oct. 2013; 9pages. |
Science Daily; “Intelligent Walker Designed to Assist the Elderly and People Undergoing Medical Rehabilitation”; http://www.sciencedaily.com/releases/2008/11/081107072015.htm; Jul. 22, 2014; 4 pages. |
Glover et al.; “A Robotically-Augmented Walker for Older Adults”; Carnegie Mellon University, School of Computer Science; Aug. 1, 2003; 13 pp. |
OrCam; www.orcam.com; Jul. 22, 2014; 3 pp. |
Eccles, Lisa; “Smart Walker Detects Obstacles”; Electronic Design; http://electronicdesign.comJelectromechanical/smart-walker-detects-obstacles; Aug. 20, 2001; 2 pp. |
Graft, Birgit; “An Adaptive Guidance System for Robotic Walking Aids”; Journal of Computing and Information Technology - Cit 17; 2009; 12 pp. |
Frizera et al.; “The Smart Walkers as Geriatric Assistive Device. The Simbiosis Purpose”; Gerontechnology, vol. 7, No. 2; Jan. 30, 2008; 6 pp. |
Rodriquez-Losada et al.; “Guido, the Robotic Smart Walker for the Frail Visually Impaired”; IEEE International Conference on Robotics and Automation (Icra); Apr. 18-22, 2005; 15 pp. |
Kayama et al.; “Outdoor Environment Recognition and Semi-Autonomous Mobile Vehicle for Supporting Mobility of the Elderly and Disabled People”; National Institute of Information and Communications Technology, vol. 54, No. 3; Aug. 2007; 11 pp. |
Kalra et al.; “A Braille Writing Tutor to Combat Illiteracy in Developing Communities”; Carnegie Mellon University Research Showcase, Robotics Institute; 2007; 10 pp. |
Blaze Engineering; “Visually Impaired Braille”; Braille 'n. Speak Manual; Resource Guide: Assistive Technology http://www.blaize.com; Nov. 17, 2014; for Students who use 5 pages. |
AppleVis; an Introduction to Braille Screen Input on 10S 8; http://www.applevis.com/guides/braille-ios/introduction-braille-screen-input-ios-8, Nov. 16, 2014; 7 pages. |
Dias et al.; “Enhancing an Automated Braille Writing Tutor”; IEEE/Rsj International Conference on Intelligent Robots and Systems; Oct. 11-15 2009; 7 pp. |
D'Andrea, Frances Mary; “More than a Perkins Brailler: a Review of the Mountbatten Brailler, Part 1”; Afb AccessWorld Magazine; vol. 6, No. 1, Jan. 2005; 9 pp. |
Trinh et al.; “Phoneme-based Predictive Text Entry Interface”; Proceedings of the 16th International Acm Sigaccess Conference on Computers & Accessibility; Oct. 2014; 2 pgs. |
Merri et al.; “The Instruments for a Blind Teacher of English: the challenge of the board”; European Journal of Psychology of Education, vol. 20, No. 4 (Dec. 2005), 15 pp. |
Kirinic et al.; “Computers in Education of Children with Intellectual and Related Developmental Disorders”; International Journal of Emerging Technologies in Learning, vol. 5, 2010, 5 pp. |
Campos et al.; “Design and Evaluation of a Spoken-Feedback Keyboard”; Department of Information Systems and Computer Science, Inesc-Id/Ist/Universidade Tecnica de Lisboa, Jul. 2004; 6 pp. |
Ebay; Maven (Made in Korea) Neoprene Canon Dslr Camera Curved Neck Strap #6782; http://www.ebay.com/itm/Matin-Made-in-Korea-Neoprene-Canon-Dslr-Camera-Curved-.Neck-Strap-67824281608526018?hash=item41912d18c2:g:---pMAAOSwe-FU6zDa ; 4 pp. |
Newegg; Motorola S10-Hd Bluetooth Stereo Headphone w/ Comfortable Sweat Proof Design; http://www.newegg.com/Product/Product.aspx?Item=9SIAONW2G39901&Tpk=9sia0nw2g39901;. |
Newegg; Motorola Behind the Neck Stereo Bluetooth Headphone Black/Red Bulk (S9) - Oem; http://www.newegg.com/Product/Product.aspx?Item=N82E16875982212&Tpk=n82e16875982212;. |
Number | Date | Country | |
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20170261334 A1 | Sep 2017 | US |