Professional workout simulator

Information

  • Patent Grant
  • 9474933
  • Patent Number
    9,474,933
  • Date Filed
    Monday, July 13, 2015
    9 years ago
  • Date Issued
    Tuesday, October 25, 2016
    8 years ago
Abstract
The systems and methods described herein are directed towards collecting workout-based information from professional athletes and providing the collected workout-based information to users. The workout-based information of the professional athletes are collected through the use of wearable devices and stored in a workout-based information network. The users (e.g., fans, other professional athletes) may subsequently download workout-based data of one or more professional athletes onto their user device. The workout-based data may be used by the users to compare their own personal progress with the professional athletes.
Description
BACKGROUND OF THE INVENTION

1. Field of Invention


The present invention generally relates to wearable devices. More specifically, the present invention relates to providing users with workout-based information from one or more professional athletes for comparison.


2. Description of the Related Art


Wearable technology may include any type of mobile electronic device that can be worn on the body, attached to or embedded in clothes and accessories of an individual and currently exist in the consumer marketplace. Processors and sensors associated with the wearable technology can display, process or gather information. Such wearable technology has been used in a variety of areas, including monitoring health data of the user as well as other types of data and statistics. These types of devices may be readily available to the public and may be easily purchased by consumers. Examples of some wearable technology in the health arena include Fit Bit, Nike Fuel Band, and the Apple Watch.


Professional athletes may utilize wearable technology to track their own personal progress during workouts. Through the use of wearable technology, professional athletes can monitor health-based data including number of calories burned, steps taken, and pulse/heart rate. The use of this information for each athlete may be beneficial to ensure that each professional athlete undertakes the necessary preparations so that they are prepared for their respective sports.


Presently there is no available way for fans to obtain access to the workout-based data of one or more professional athletes. Users of wearable devices are interested in comparing their own personal workout-based results with one or more pros. In some cases, professional athletes may also be interested in comparing their personal workout-based results with other professional athletes.


SUMMARY OF THE CLAIMED INVENTION

A method for comparing workout-based information between a user and one or more professional athletes is claimed. The method first stores workout-based information from one or more professional athletes in a workout-based network. Users can then select one or more of the workout-based information of professional athletes stored in the network to be downloaded. The users download the workout-based information of the selected professional athletes onto their user device. The users also provide their user workout-based information. The user device then evaluates the workout-based information of the user and the user selected professional athletes. The user device finally outputs information comparing the workout-based information of the user and user selected professional athletes onto a display that the user can view.


A system for comparing workout-based information between a user and one or more professional athletes is also claimed. The system includes a user interface, a database, and a processor. The database stores workout-based information of one or more professional athletes in a workout-based network. The processor executes instructions stored in memory to select one or more professional athletes having stored workout-based information associated with the workout-based network. The processor can then download the stored workout-based information of the user selected professional athletes and subsequently receive the user workout-based information. Evaluation of the workout-based information of the user and the professional athletes is performed in order to output information comparing the workout-based information of the user and user selected professional athletes. The information can be displayed for the user to view





BRIEF DESCRIPTION OF THE DRAWINGS


FIG. 1 illustrates a system for sharing workout-based information of professional athletes with interested users.



FIG. 2 illustrates the workout pro network and corresponding stats database used to store workout-based information of professional athletes.



FIG. 3 illustrates the workout compare software.



FIG. 4 illustrates a flowchart for the sharing of workout-based information of professional athletes with interested users





DETAILED DESCRIPTION

The systems and methods described herein are directed towards collecting workout-based information from professional athletes and providing the collected workout-based information to interested users. The workout-based information of the professional athletes are collected through the use of wearable devices and stored in a workout-based information network. Interested users (e.g., fans, other professional athletes) may subsequently download workout-based data from one or more professional athletes onto their user device. The workout-based data may be used by the interested users to compare their own personal progress with one or more other professional athletes. It should be noted that the workout-based data is updated in real-time, for example, based on when a particular professional athlete most recently undergoes a workout session. The workout-based data may also be cumulative over time.



FIG. 1 illustrates a system 100 for sharing workout-based information of professional athletes with interested users. The system 100 includes a plurality of interested users 105 (e.g., fans) and a plurality of professional athletes. The system 100 also includes databases and networks that are used to facilitate the sharing of workout-based information of professional athletes with interested users. Further details pertaining to the elements of the system 100 are provided below.


As illustrated in FIG. 1, each of the interested users 105 has a corresponding user device 110 (e.g., smartphone). The user devices 110 include one or more applications or programs compatible with the system 100. In particular the user devices 110 would have an application or program (referenced as the workout compare software in FIG. 1) directed at comparing workout-based information of one or more professional athletes with workout-based information of the user 115. As illustrated in the figure, the workout compare software is represented via a black square that can be found within the user device 110. The workout-based information of the user, which is referenced by the workout compare software, may be manually inputted into the user device 110 or obtained through the use of one or more wearable devices 115. The workout-based information can then be compared by the workout compare software in each of the user devices 110 with one or more workout-based information from one or more professional athletes 120 obtained from the workout pro network.


It should be noted that each of the interested users 105 may have one or more wearable devices 115. The wearable devices 115 may be used to obtain health-based sensor data corresponding to relevant workout-based information. For example, when the interested user 105 undergoes a workout session, the wearable device 115 can be used to obtain health-based sensor data (e.g., biometric parameters). The health-based sensor data can be subsequently processed to evaluate the effects of a particular workout session. The wearable devices 115 may be capable of measuring a variety of different biometric parameters belonging to a particular interested user 105 including calories burned and heart-rate/pulse. These wearable devices 115 may be wearable devices that are readily available to the public (e.g., FitBit).


The system 100 also includes a plurality of professional athletes 120. These professional athletes 120 may be professional athletes across any sport (e.g., football, basketball, baseball). It should be noted that each professional athlete may participate in different workout sessions, for example, to maintain or improve on a particular aspect of their performance within their respective sport (e.g., endurance, muscle mass, weight loss). The professional athletes 120 may similarly have user devices 125 (e.g., smart phones) and wearable devices 130 (e.g., BodyMedia, Fitbit) as described above with respect to the interested users 105.


Workout-based information from each of the professional athletes 120 may be obtained from their corresponding wearable devices 130. The workout-based information can then be transmitted to the user device 125 associated with the professional athlete 120. The user device 125 of the professional athlete 120 then connects with the workout pro network 135 and uploads their respective workout-based information into the network 135 for storage. The workout pro network 135 is capable of storing workout-based information of the various professional athletes 120 in a stats database 140. It should be noted that the information provided to the workout pro network 135 and stored in the stats database 140 may be updated on a regular basis (e.g., real-time, hourly, daily). For example, once a workout session has been completed, obtained workout-based information from the professional athlete may be provided to the workout pro network 135 immediately.


Each of the interested users 105 and professional athletes 120 are capable of connecting to the workout pro network 135 to download workout based information. More specifically, the user devices 110, 125 of the interested users 105 and professional athletes 120, respectively are capable of communicating with the workout pro network 135 via the cloud or internet 140. Once connected, for example, the interested user 105 may download workout-based information for one or more professional athletes onto their user device 110. In some embodiments, the interested user 105 may be capable of selecting workout-based information for a particular professional athlete or for a particular group of professional athletes (e.g., workout-based information for basketball players). The workout-based information downloaded into the user device 110 can then be used by the workout compare software to evaluate workout-based information of the user 105 and the professional athlete 125.


It may be possible that vendors/manufacturers that are associated with a particular brand of a wearable device 115, 130 may have the ability to control who can access the workout-based information and when others can access the workout-based information. For example, a vendor/manufacturer may provide selected users (e.g., interested users and/or professional athletes) using their brand of wearable devices early access to workout-based information obtained by the same branded wearable devices of professional athletes. The early access may be associated with a period of time before the workout pro network 135 is capable of updating the stats database 140 with the recently received workout based information of one or more professional athletes.



FIG. 2 illustrates the workout pro network 200. As illustrated in the figure, the workout pro network 200 includes a database 205, a communication port 210 used to communicate with the internet or cloud 215, a sign-up process 220 and a download process 225. Further details relating to the different elements of the workout pro network 200 are provided below.


The database 205 associated with the workout pro network 200 is a database that includes information (e.g., personal information) about each professional athlete that uploads their respective workout-based information to the workout pro network 205. The information provided from each professional athlete is received by the communication port 210. As illustrated in the figure, the database 205 may include personal information such as their name and what wearable device they are using. Other types of information may also be stored in the database 205 such as information from their user device (e.g., smart phone) including their location (i.e. GPS) and technology the professional athlete is using (e.g., programs, applications). It may be possible that the professional athlete may provide further information to be stored in the database 205 as well, for example, their diet. It should be noted that the information stored in the database 205 of the workout pro network 200 may also be helpful in evaluating the workout-based data between the professional athlete and, for example, the interested user.


The sign-up process 220 facilitates users (e.g., interested users and/or professional athletes) with the use of the workout-based information associated with the workout pro network 200. Generally, users would need to sign-up using the sign-up process 220 (e.g., create an account, user profile). The users may be charged a fee (e.g., one-time, monthly-subscription) for use of the workout pro network 200. The sign-up process 220 may facilitate payment from the user. In some embodiments, the sign-up process 220 can also take as input names of particular professional athletes the user would like to download workout-based information about. The names of the professional athletes may be saved and associated with the user.


After the sign-up process 220, the user is allowed to download workout-based information about one or more pros associated with the workout pro network 200 to their respective user device using the download process 225. The download process may be a manual request performed by the user. In some cases, the user may be allowed to automatically request via the user device updated workout-based information regarding one or more professional athletes on a regular basis. In this case, the download process can provide the requested updated workout-based information without any further action from the user.



FIG. 3 illustrates the workout compare software 300. As noted above, the workout compare software 300 is found, for example, in the user devices associated with the interested users and/or the professional athletes. The workout compare software 300 is used to compare workout-based information obtained from a user workout session with workout-based information of one or more professional athletes downloaded from the workout pro network.


As illustrated in the figure, the workout compare software 300 includes a communication device 305. The communication device 305 is connected to the cloud or Internet 310. Through the communication device 305, the workout compare software 300 can obtain workout-based information of one or more professional athletes. The workout-based information of the professional athletes may be stored 315 in the workout compare software 300. The download process, sign-up process and process of selecting one or more professional athletes may also be included in the workout compare software 300 to facilitate the obtaining of desired workout-based information of the one or more professional athletes from the workout pro network.


The workout compare software 300 may also store workout-based information related to the user 320. This workout-based information of the user may be manually inputted into the user interface. In some embodiments, the workout-based information of the user may also be obtained from a corresponding wearable device 325. The wearable device 325 may be any wearable device capable of obtaining health-based sensor data (e.g., biometric parameters) that can be used to evaluate the effect of a workout session.


The workout compare software 300 can then compare the stored workout-based information of the user 320 and one or more professional athletes 315 via the compare data process 330. The compare data process 330 can process and evaluate the stored workout-based information stored in the workout compare software 300 between the user and the professional athlete.


The workout compare software 300 can then output a graphical user interface (GUI) 335 that displays the comparison between the workout-based information of the user and the professional athlete(s) chosen by the user. The GUI 335 may include a table which includes workout-based information of the user and the professional athlete(s) including calories, steps taken, pulse and calorie intake. It should be noted that other types of workout-based information may also be displayed in the GUI 335.


The GUI 335 may include additional features such as stats and GPS. The stats feature may provide further information relating to the workout session of the professional athlete. For example, the stats may provide the duration of the workout session. The GPS (global positioning system) feature may also be included with the GUI 335. The GPS feature may be provided to indicate information about where the particular professional athlete performed the workout session. The GPS feature, for example, may indicate that the professional athlete worked out at a gym. It should be noted that other features may also be included in the GUI 335 that can further provide details and context about workout-based information of one or more athletes.



FIG. 4 illustrates a flowchart 400 for the sharing of workout-based information of professional athletes with interested users. More specifically, the flowchart illustrates the steps associated with providing the workout-based information from the professional athletes to the workout pro network that will subsequently be downloaded by the interested users for comparison.


In step 410, workout-based information from the various professional athletes are stored in the workout pro network. The workout-based information may be obtained from one or more sensors associated with a wearable device worn by the professional athlete. The sensor data can then be transmitted to the user device associated with the wearable device. The workout-based information may also be manually inputted into the user device of the professional athlete. The workout-based information, once provided to the user device, can transmit the workout-based information to the workout pro network to be stored.


In step 420, the user can select one or more professional athletes having stored workout-based information in the workout pro network to be downloaded. In some embodiments, the user can specify a sport or genre of professional athletes (e.g., football players) and the workout pro network can generate one or more professional athletes for the user to choose.


It should be noted that the user, before being allowed to select desired professional athletes, may be required to sign up and obtain authorization to use the workout pro network. In some cases, a fee (e.g., one-time, monthly subscription) may be required.


In step 430, the user can download the workout-based information of the one or more selected professional athletes from the workout pro network. The workout-based information associated with the one or more selected professional athletes are stored, for example, in the user device of the user. The workout-based information associated with the one or more selected professional athletes will be used to compare with the user workout-based information.


In step 440, the user can provide the workout-based information of the user for the user device to use. The workout-based information can be manually inputted into the user device, for example, through an application, program or GUI. In other embodiments, a wearable device having one or more sensors may obtain sensor data that can be transmitted to the user device and processed into workout-based information. The user workout-based information will be compared with the workout-based information from one or more selected professional athletes.


In step 450, the user device (i.e. the workout compare software) processes the workout-based information of the user and the selected one or more professional athletes. The workout compare software can also evaluate health-based data of the user and the professional athletes and determine the relative effects of the workouts for the user and the professional athlete.


In step 460, the output of the evaluation performed in step 450 is displayed for the user to view. The output may be displayed, for example, via a graphical user interface on the user device. The information detailing the comparison between the workout-based information of the user and the selected one or more professional athletes may be displayed via a graph, chart or any other possible way of illustrating a comparison between the various data sets.


The foregoing detailed description of the technology herein has been presented for purposes of illustration and description. It is not intended to be exhaustive or to limit the technology to the precise form disclosed. Many modifications and variations are possible in light of the above teaching. The described embodiments were chosen in order to best explain the principles of the technology and its practical application to thereby enable others skilled in the art to best utilize the technology in various embodiments and with various modifications as are suited to the particular use contemplated. It is intended that the scope of the technology be defined by the claim.


It should be noted that the technology can be used in a variety of different events and venues including entertainment or cultural events presented at a theater, gymnasium, stadium or other facility involving a group of people. Such events may also include a variety of sporting events such as football (American and global), baseball, basketball, soccer, ice hockey, lacrosse, rugby, cricket, tennis, track and field, golf, cycling, motor sports such as automobile or motorcycle racing, horse racing, Olympic games, and the like; cultural events such as concerts, music festivals, plays, or the opera, and the like; religious events; and more permanent exhibitions such as museums or historic homes.

Claims
  • 1. A method for comparing user workout information and professional athlete workout information, the method comprising: storing professional athlete workout information in a professional athlete workout database, the professional athlete workout information associated with one or more professional athletes;receiving a selection from a user device, the selection identifying a set of selected professional athletes, the set of selected professional athletes including at least a subset of the one or more professional athletes associated with the professional athlete workout database, the set of selected professional athletes corresponding to a set of selected professional athlete workout information that includes at least a subset of the stored professional athlete workout information;retrieving the set of selected professional athlete workout information from the professional athlete workout database, the set of selected professional athlete workout information including at least a subset of the professional athlete workout information corresponding to the set of selected professional athletes;receiving user workout information from the user device;generating a comparison visualization identifying one or more differences between the user workout information and the set of selected professional athlete workout information; andtransmitting at least the comparison visualization to the user device, thereby displaying at least the comparison visualization at the user device.
  • 2. The method of claim 1, wherein the professional athlete workout information includes sensor-based professional athlete data received from one or more professional athlete wearable devices and is recorded by one or more sensors associated with the one or more professional athlete wearable devices, the one or more professional athlete wearable devices having been worn by at least a subset of the one or more professional athletes.
  • 3. The method of claim 1, wherein the professional athlete workout information includes manual-input-based professional athlete data received from the user device after being received by the user device via manual input.
  • 4. The method of claim 1, wherein the user workout information includes sensor-based user data obtained via one or more sensors associated with one or more wearable devices that transmitted the data to the user device, the one or more wearable devices having been worn by a user associated with the user device.
  • 5. The method of claim 1, wherein the user workout information includes manual-input-based user data input received by the user device via manual input.
  • 6. The method of claim 1, wherein the comparison visualization is one of a chart or a graph.
  • 7. A system for comparing user workout information and professional athlete workout information, the system comprising: a memory storing at least a professional athlete workout database that includes professional athlete workout information associated with one or more professional athletes;a communication transceiver in communicative contact with at least a user device; anda processor coupled to the memory and to the communication transceiver, wherein execution of instructions stored in the memory by the processor: receives the selection from the user device, the selection identifying a set of selected professional athletes, the set of selected professional athletes including at least a subset of the one or more professional athletes associated with the professional athlete workout database, the set of selected professional athletes corresponding to a set of selected professional athlete workout information that includes at least a subset of the stored professional athlete workout information,retrieves the set of selected professional athlete workout information from the professional athlete workout database, the set of selected professional athlete workout information including at least a subset of the professional athlete workout information corresponding to the set of selected professional athletes;receives user workout information from the user device,generates a comparison visualization identifying one or more differences between the user workout information and the set of selected professional athlete workout information, andtransmits at least the comparison visualization to the user device, thereby displaying at least the comparison visualization at the user device.
  • 8. The system of claim 7, wherein the professional athlete workout information includes sensor-based professional athlete data received from one or more professional athlete wearable devices and is recorded by one or more sensors associated with the one or more professional athlete wearable devices, the one or more professional athlete wearable devices having been worn by at least a subset of the one or more professional athletes.
  • 9. The system of claim 7, wherein the professional athlete workout information includes manual-input-based professional athlete data received from the user device after being received by the user device via manual input.
  • 10. The system of claim 7, wherein the user workout information includes sensor-based user data obtained via one or more sensors associated with one or more wearable devices that transmitted the data to the user device, the one or more wearable devices having been worn by a user associated with the user device.
  • 11. The system of claim 7, wherein the user workout information includes manual-input-based user data input received by the user device via manual input.
  • 12. The system of claim 7, wherein the comparison visualization is one of a a chart or a graph.
  • 13. A non-transitory computer-readable storage medium, having embodied thereon a program executable by a processor to perform a method for comparing user workout information and professional athlete workout information, the method comprising: storing professional athlete workout information in a professional athlete workout database, the professional athlete workout information associated with one or more professional athletes;receiving a selection from a user device, the selection identifying a set of selected professional athletes, the set of selected professional athletes including at least a subset of the one or more professional athletes associated with the professional athlete workout database, the set of selected professional athletes corresponding to a set of selected professional athlete workout information that includes at least a subset of the stored professional athlete workout information;retrieving the set of selected professional athlete workout information from the professional athlete workout database, the set of selected professional athlete workout information including at least a subset of the professional athlete workout information corresponding to the set of selected professional athletes;receiving user workout information from the user device;generating a comparison visualization identifying one or more differences between the user workout information and the set of selected professional athlete workout information; andtransmitting at least the comparison visualization to the user device, thereby displaying at least the comparison visualization at the user device.
CROSS-REFERENCE TO RELATED APPLICATIONS

The present application claims the priority benefit of U.S. provisional application No. 62/023,472 filed Jul. 11, 2014 and entitled “Workout like a Pro,” the disclosure of which is incorporated herein by reference.

US Referenced Citations (207)
Number Name Date Kind
4763284 Carlin Aug 1988 A
4771394 Cavanagh Sep 1988 A
5293354 Costabile Mar 1994 A
5462275 Lowe et al. Oct 1995 A
6013007 Root et al. Jan 2000 A
6181236 Schneider Jan 2001 B1
6389368 Hampton May 2002 B1
6603711 Calace Aug 2003 B2
6760276 Karr Jul 2004 B1
6836744 Asphahani et al. Dec 2004 B1
7020336 Cohen-Solal et al. Mar 2006 B2
7031225 McDonald Apr 2006 B2
7115053 Meichner Oct 2006 B2
7173533 Beron et al. Feb 2007 B1
7174277 Vock et al. Feb 2007 B2
7561494 Stern Jul 2009 B2
7561723 Goldberg et al. Jul 2009 B2
7602301 Stirling et al. Oct 2009 B1
7618312 Kasten Nov 2009 B1
7634662 Monroe Dec 2009 B2
7693668 Vock et al. Apr 2010 B2
7715723 Kagawa et al. May 2010 B2
7805149 Werner et al. Sep 2010 B2
7920052 Costabile Apr 2011 B2
8054174 Uehran Nov 2011 B1
8098881 Camp et al. Jan 2012 B2
8239146 Vock et al. Aug 2012 B2
8253586 Matak Aug 2012 B1
8257084 Kreiner et al. Sep 2012 B1
8257228 Quatrochi et al. Sep 2012 B2
8289185 Alonso Oct 2012 B2
8326136 Clark Dec 2012 B1
8396687 Vock et al. Mar 2013 B2
8477046 Alonso Jul 2013 B2
8485879 Lin et al. Jul 2013 B2
8554495 Mack et al. Oct 2013 B2
8554509 Crisco et al. Oct 2013 B2
8579632 Crowley Nov 2013 B2
8589667 Mujtaba et al. Nov 2013 B2
8611930 Louboutin et al. Dec 2013 B2
8620344 Huang et al. Dec 2013 B2
8626465 Moore et al. Jan 2014 B2
8630216 Deivasigamani et al. Jan 2014 B2
8660501 Sanguinetti Feb 2014 B2
8684819 Thomas et al. Apr 2014 B2
8702504 Hughes et al. Apr 2014 B1
8706044 Chang et al. Apr 2014 B2
8724723 Panicker et al. May 2014 B2
8750207 Jeong et al. Jun 2014 B2
8793094 Tam et al. Jul 2014 B2
8816868 Tan et al. Aug 2014 B2
8831529 Toh et al. Sep 2014 B2
8831655 Burchill et al. Sep 2014 B2
8836851 Brunner Sep 2014 B2
8843158 Nagaraj Sep 2014 B2
8849308 Marti et al. Sep 2014 B2
8862060 Mayor Oct 2014 B2
8873418 Robinson et al. Oct 2014 B2
8874090 Abuan et al. Oct 2014 B2
8917632 Zhou et al. Dec 2014 B2
8934921 Marti et al. Jan 2015 B2
8994498 Agrafioti et al. Mar 2015 B2
9305441 Cronin Apr 2016 B1
9398213 Cronin Jul 2016 B1
20010003715 Jutzi et al. Jun 2001 A1
20010048484 Tamir et al. Dec 2001 A1
20030163287 Vock et al. Aug 2003 A1
20030210612 Stern Nov 2003 A1
20050046584 Breed Mar 2005 A1
20050117022 Marchant Jun 2005 A1
20050162257 Gonzalez Jul 2005 A1
20050242508 Meichner Nov 2005 A1
20050277466 Lock Dec 2005 A1
20060052147 Matthews Mar 2006 A1
20060109089 Boehm et al. May 2006 A1
20060180073 Nakamoto Aug 2006 A1
20060208169 Breed et al. Sep 2006 A1
20060281061 Hightower et al. Dec 2006 A1
20070003113 Goldberg Jan 2007 A1
20070135264 Rosenberg Jun 2007 A1
20070269203 Awazu Nov 2007 A1
20080082311 Meijer et al. Apr 2008 A1
20080129825 DeAngelis et al. Jun 2008 A1
20080146302 Olsen et al. Jun 2008 A1
20090023122 Lieberman et al. Jan 2009 A1
20090029754 Slocum et al. Jan 2009 A1
20090111582 Schuler et al. Apr 2009 A1
20090256912 Rosenberg Oct 2009 A1
20100026809 Curry Feb 2010 A1
20100030350 House et al. Feb 2010 A1
20100102938 Delia et al. Apr 2010 A1
20100105503 Daisher et al. Apr 2010 A1
20100144414 Edis et al. Jun 2010 A1
20100185398 Berns et al. Jul 2010 A1
20100283630 Alonso Nov 2010 A1
20110013087 House et al. Jan 2011 A1
20110064281 Chan Mar 2011 A1
20110169959 DeAngelis et al. Jul 2011 A1
20110181418 Mack et al. Jul 2011 A1
20110184320 Shipps et al. Jul 2011 A1
20120002509 Saguin et al. Jan 2012 A1
20120029666 Crowley et al. Feb 2012 A1
20120052947 Yun Mar 2012 A1
20120063272 Dorais et al. Mar 2012 A1
20120081531 DeAngelis et al. Apr 2012 A1
20120099405 Lidor et al. Apr 2012 A1
20120116548 Goree et al. May 2012 A1
20120120201 Ward May 2012 A1
20120124720 Evans et al. May 2012 A1
20120166449 Pitaliya Jun 2012 A1
20120197998 Kessel et al. Aug 2012 A1
20120202594 Bistis et al. Aug 2012 A1
20120212505 Burroughs et al. Aug 2012 A1
20120223833 Thomas et al. Sep 2012 A1
20120324491 Bathiche et al. Dec 2012 A1
20130018494 Amini Jan 2013 A1
20130045806 Bloodworth Feb 2013 A1
20130060168 Chu et al. Mar 2013 A1
20130066448 Alonso Mar 2013 A1
20130080222 Quinn Mar 2013 A1
20130091209 Bennett et al. Apr 2013 A1
20130095924 Geisner et al. Apr 2013 A1
20130126713 Haas et al. May 2013 A1
20130138590 Huke et al. May 2013 A1
20130139068 Bowring May 2013 A1
20130141555 Ganick et al. Jun 2013 A1
20130166048 Werner et al. Jun 2013 A1
20130222133 Schultz et al. Aug 2013 A1
20130235702 Saguin et al. Sep 2013 A1
20130249708 Moll-Carrillo Sep 2013 A1
20130279917 Son et al. Oct 2013 A1
20130303192 Louboutin Nov 2013 A1
20130316837 Coiner, Jr. Nov 2013 A1
20130317835 Mathew Nov 2013 A1
20130322689 Carmichael Dec 2013 A1
20130324239 Ur et al. Dec 2013 A1
20130328917 Zambetti et al. Dec 2013 A1
20130331087 Shoemaker Dec 2013 A1
20130331118 Chhabra Dec 2013 A1
20130331137 Burchill Dec 2013 A1
20130332108 Patel Dec 2013 A1
20130332156 Tackin Dec 2013 A1
20130335635 Ghanem et al. Dec 2013 A1
20130336662 Murayama et al. Dec 2013 A1
20130343762 Murayama et al. Dec 2013 A1
20140004939 Kasten Jan 2014 A1
20140039354 Greenwald et al. Feb 2014 A1
20140039355 Crisco et al. Feb 2014 A1
20140039651 Crowley Feb 2014 A1
20140062773 MacGougan Mar 2014 A1
20140065962 Le Mar 2014 A1
20140068847 Kitowski Mar 2014 A1
20140071221 Dave Mar 2014 A1
20140080638 Feng et al. Mar 2014 A1
20140088454 Mack Mar 2014 A1
20140105084 Chhabra Apr 2014 A1
20140105466 Botes et al. Apr 2014 A1
20140107817 Ellis Apr 2014 A1
20140111352 Doherty Apr 2014 A1
20140125702 Santillan et al. May 2014 A1
20140139380 Ouyang May 2014 A1
20140141803 Marti May 2014 A1
20140143940 Luliano et al. May 2014 A1
20140155178 Bloodworth Jun 2014 A1
20140162628 Bevelacqua Jun 2014 A1
20140167794 Nath Jun 2014 A1
20140168170 Lazarescu Jun 2014 A1
20140168477 David Jun 2014 A1
20140171114 Marti Jun 2014 A1
20140180820 Louboutin Jun 2014 A1
20140191979 Tsudik Jul 2014 A1
20140200053 Balasubramanian Jul 2014 A1
20140218184 Grant et al. Aug 2014 A1
20140222335 Piemonte Aug 2014 A1
20140232633 Shultz Aug 2014 A1
20140232634 Piemonte Aug 2014 A1
20140241730 Jovicic et al. Aug 2014 A1
20140247279 Nicholas Sep 2014 A1
20140247280 Nicholas Sep 2014 A1
20140269562 Burchill Sep 2014 A1
20140270375 Canavan et al. Sep 2014 A1
20140274150 Marti Sep 2014 A1
20140278218 Chang Sep 2014 A1
20140283135 Shepherd Sep 2014 A1
20140293959 Singh Oct 2014 A1
20140361906 Hughes et al. Dec 2014 A1
20140363168 Walker Dec 2014 A1
20140364089 Lienhart Dec 2014 A1
20140364148 Block Dec 2014 A1
20140365120 Vulcano Dec 2014 A1
20140365640 Wohl et al. Dec 2014 A1
20140371887 Hoffman Dec 2014 A1
20140375217 Feri et al. Dec 2014 A1
20150011242 Nagaraj Jan 2015 A1
20150026623 Horne et al. Jan 2015 A1
20150031397 Jouaux Jan 2015 A1
20150081713 Alonso et al. Mar 2015 A1
20150131845 Forouhar et al. May 2015 A1
20150187188 Raskin Jul 2015 A1
20150296272 Sonabend et al. Oct 2015 A1
20150306457 Crankson Oct 2015 A1
20160001159 Riley Jan 2016 A1
20160008693 Cronin Jan 2016 A1
20160012810 Cronin Jan 2016 A1
20160073010 Cronin Mar 2016 A1
20160096074 Moll-Carrillo Apr 2016 A1
20160107064 Hoffman Apr 2016 A1
Foreign Referenced Citations (16)
Number Date Country
2014100006 Feb 2014 AU
102527007 Jul 2012 CN
102843186 Dec 2012 CN
2 407 218 Jan 2012 EP
WO 2008030484 Mar 2008 WO
WO 2009104921 Aug 2009 WO
WO 2011004381 Jan 2011 WO
WO 2012100053 Jul 2012 WO
WO 2013011259 Jan 2013 WO
WO 2013166456 Nov 2013 WO
WO 2014008134 Jan 2014 WO
WO 2014052874 Apr 2014 WO
WO 2014100519 Jun 2014 WO
WO 2016007969 Jan 2016 WO
WO 2016007970 Jan 2016 WO
WO 2016039991 Mar 2016 WO
Non-Patent Literature Citations (100)
Entry
“About Head Case”, Head Case Company, Sep. 24, 2013.
“Adidas' miCoach SPEED—CELL and miCoach Football App Aim to Advance the Performance of Next-Generation Athletes Through New Technology”, miCoach, Nov. 22, 2011.
“Advanced E-Team: Automatic Sports Time Stopping Whistle”, Rose-Hulman Institute of Technology, 2002, NCIIA Funded Advanced E-Teams. Date of Download: Jun. 14, 2014. http://www.nciia.org/WebObjects/NciiaResources.woa/wa/View/GrantProfile?n=1000037.
“Affordable Concussion Management System for Young Athletes Offered by Head Case”, Head Case Company, Sep. 24, 2013.
Ancona et al., N.; “Goal detection in football by using Support Vector Machines for classification” Neural Networks, vol. 1, pp. 611-616, 2001.
“AutoScout” ADSC Illinous at Singapore Pte Ltd. Sep. 21, 2015.
Belzer, Jason; “NFL Partners With Zebra Technologies to Provide Next Generation Player Tracking”, Forbes/Sports Money, Jul. 31, 2014.
Brolinson et al., P. Gunner; “Analysis of Linear Head Accelerations from Collegiate Football Impacts”, Current Sports Medicine Reports, 2006, vol. 5:23-28.
“Chapter 29. Outdoor Laser Operations”, U.S. Department of Transportation, Feb. 9, 2012.
Cooley, Chris; “MMQB: Smart Football”, The Official Blog of Chris Cooley, Jul. 13, 2009.http://chriscooley47.blogspot.com/2009/07/mmqb-smart-football.html.
“Create Innovative Services with Play Apps”, Date of Download: Jan. 16, 2014, http://www.oledcomm.com/LIFI.html, Oledcomm—France LiFi.
Danakis, C et al.; “Using a CMOS Camera Sensor for Visible Light Communication”; 3rd IEEE Workshop on Optical Wireless Communications; [online], Dec. 3-7, 2012 [retrieved Aug. 14, 2015]. Retrieved from the Internet: <URL: https://195.134.65.236/IEEE—Globecom—2012/papers/p1244-danakis.pdf> pp. 1244-1248.
Dawson, Keith; “LiFi in the Real World” All LED Lighting—Illuminating the Led Community, Jul. 31, 2013.
Delgado, Rick; “Why Fantasy Football is Embracing Big Data”, Sporttechie, Jan. 3, 2014.
“Dutch Football Fans Get the Ajax Experience With AV Technology From Electrosonic”, Electrosonic Press Release, May 14, 2012.
FAQ, Go Pro Workouts, Date of Download: Apr. 30, 2014 https://www.goproworkouts.com/faqs.
“First Down Laser Systems to enhance game of football and fans in-stadium experience with green line”, Sports Techie, Sep. 9, 2013.
“Football Workout Programs”, Go Pro Workouts. Date of Download: Apr. 27, 2014 https://www.goproworkouts.com/workouts/football.
Freeman, Mark; “Frickin' Laser Beams”, River Valley Leader, Feb. 19, 2013.
Gerhardt, Ryan; “Concussion Sensing Helmet Could Save Athletes”, PSFK, Oct. 28, 2013.
Gerhardt, Ryan; “Vibrating Jersey Lets Fans Feel What Players Do on the Field”, PSFK.com, Mar. 13, 2014.
“GoalControl to provide goal-line system at World Cup in Brazil”, BBC Sport, Apr. 2, 2013.
Gorman, Michael; “Outstanding Technology brings visible light communication to phones and tablets via dongle and LEDs”, Edgadget International Editions, Jul. 16, 2012.
“Growing data sets alter Sportsvision's real-time viewing experience”, Sports Illustrated, More Sports, Nov. 29, 2013.
Haas, Harald; “Delivering safe and secure wireless communications”, pureLiFi. Date of download: Jan. 16, 2014 http://purelifi.co.uk/.
“How to compare personal stats with the Pros?”, Support Home Discussions Training with miCoach. Jul. 4, 2012.
“How to wear the Stride Sensor (inside the shoe)”, by micoach, Guides & Tutorials, May 29, 2014.
Inamoto et al., Naho; “Immersive Observation of Virtualized Soccer Match at Real Stadium Model”, Proceedings of the Second IEEE and ACM International Symposium on Mixed and Augmented Reality (ISMAR '03), 2003.
“Intel, NFL Legend Jerry Rice and others Team Up to “Look Inside the Huddle” On and Off the Field”, by INTELPR in Intel Newsroom, Aug. 28, 2013.
Kumar, Navin; “Visible Light Communications Systems Conception and VIDAS”, IETE Technical Review, vol. 25, Issue 6, Nov.-Dec. 2008. Date of download: Nov. 19, 2009. http://www.tr.ietejournals.org.
La Confora, Jason; “NFL collecting data that could revolutionize websites, video games”, CBS Sports—Insider, Nov. 25, 2012.
Laviers, Kennard R.; Sukthankar, Gita; “Using Opponent Modeling to Adapt Team Play in American Football”, Plan, Activity, and Recognition, Elsevier, 2014. School of ECE, Air Force Institute of Technology. Preprint submitted: Oct. 31, 2013.
LiFi Overview—Green wireless mobile communication—LiFi Technology. Date of download: Jan. 16, 2014.
Li, Yang et al., “VICO: A Framework for Configuring Indoor Visible Light Communication Networks” Aug. 11, 2012, Mobile Adhoc and Sensor Systems (MASS), 2012 IEEE 9th International Conference, Las Vegas, NV.
Macleod, Robert; “New football helmet sensors monitor brain injuries”, The Globe and Mail, Nov. 14, 2013.
Madden, Lance; “Pro Athletes Share Personal Workout Secrets With Startup ‘Go Pro Workouts’”, Forbes.com, SportsMoney. Mar. 4, 2013.
Maricle, Charles; “Federal rules for outdoor laser user in the U.S. (FAA authority over airspace)”, Laser PointerSafety.com, Apr. 23, 2014.
“Methods to Our Madness”, Football Outsiders Information, Innovative Statistics, Intelligent Analysis, http://www.footballoutsiders.com/info/methods, Date of Download: Apr. 10, 2014.
Miller, Mark J.; “NFL Sensors Will Track Player Stats for Fans, but What About Safety?”, Sports in the Spotlight—brandchannel, Aug. 11, 2014.
Montero, Eric, “Design and Implementation of Color-Shift Keying for Visible Light Communications”, Sep. 2013, McMaster University.
Morgan, Debra; “Referee Uses Capital Idea to Stop Game Clocks on a Whistle”, Loca News. Nov. 18, 1999. http://www.wral.com/news/local/story/138889.
Naidu, Vinaya; “Watched the IPL? Now Find and Tag Yourself in the Stadium With Vodafone Fancam”, Business 2 Community, May 22, 2013.
“New courtside technology unveiled at PISD tourney”, Precision Time Systems—New Inventions That Prevent Human Errors in Sports Timekeeping, Date of Download: Apr. 23, 2014.
Nguyen et al., “A Novel like switching scheme using pre-scanning and RSS prediction in visible light communication networks”, EURASIP Journal on Wireless Communications and Networking, 2013.
“Nike+ SportBand User's Guide”, by nikeplus.com, Jun. 7, 2014.
“Nokia Lumia 920 pricing compared to iPhone 5 and Samsung Galaxy SIII”, by Nokia, Sep. 30, 2012.
Ogawa; “Article about VLC Guidance developed”, Visible Light Communications Consortium (VLCC), Aug. 31, 2012.
Ogawa; “iPhone app from CASIO”, Visible Light Communications Consortium (VLCC), Apr. 26, 2012.
Ogus, Simon; “SportIQ Announces a Game Changing Real-Time Basketball Analytics Platform”, Sporttechie.com, Mar. 7, 2014.
“Omega introduces new timing equipment for ice hockey at Sochi 2014 Olympic Winter Games”, OMEGA Watches, Feb. 16, 2014.
“Outdoor Laser Operations”, Advisory Circular, U.S. Department of Transportation, Dec. 30, 2014.
Perin et al., Charles; “Real-Time Crowdsourcing of Detailed Soccer Data”, IEEE, Oct. 2013.
Povey, Gordon, “VLC for Location, positioning and navigation”, Jul. 27, 2011, http://visiblelightcomm.com/vlc-for-location-positioning-and-n . . . .
“Riddell InSite Impact Response System”, Riddell InSite. Oct. 18, 2013.
Roble, Bob; “Inside the Huddle: How Big Data is Unlocking Fantasy Football Insights”, IQ Sports—Sports Technology, Sep. 3, 2013.
Saag, Tonis; “You can compare your training data with friends again”, SportlyzerBlog, Feb. 20, 2013.
“What is SafeBrain”, SafeBrain Systems Inc. May 14, 2014.
Schoonmaker, Aaron; “NCAA ignoring own clock recommendations in tourney”, WRALSportsFan.com, Mar. 25, 2014 http://www.wralsportsfan.com/ncaa-ignoring-own-clock-recommendations-in-tourney/13510770/.
“Smartabase—The complete solution for athlete data management”, Fusion Sport, www.fusionsport.com, Jul. 21, 2011.
“Sports Event Services—Quality Information is the first gold medal at any event”, Infostrada Sports, May 24, 2013.
Stein, Anne; “Devices help alert teams to potential concussions on the field”, Tribune Newspapers, Jun. 27, 2012.
Thanigavel, M.; “Li-Fi Technology in Wireless Communication”, International Journal of Engineering Research & Technology (IJERT), ISSN: 2278-0181, vol. 2 Issue 10, Oct. 2013.
“The Head Case Impact Sensor”, Head Case Company, Sep. 24, 2013.
“The System Models & How They Work”, Precision Time Systems—New Inventions That Prevent Human Errors in Sports Timekeeping, Date of Download: Apr. 24, 2014.
“The Wearables Coaching an Optimal Version of You”, by PSFK Labs, iQ, Feb. 24, 2014.
“Train like professional athletes”, Go Pro Workouts. Date of Download: Apr. 30, 2014 https://www.goproworkouts.com/.
“Viewing other miCoach stats”, Support Home Discussions Training with miCoach, Jun. 26, 2012.
WKO—Hunter Allen—Peaks Coaching Group Oct. 14, 2015.
“Wirless Whistle System”, Bodet Sport, Sport Display—Timer. Date of Download: Jun. 23, 2014 file:///C|/king/AOP/Wireless%20Whistle%20system.htm[Jun. 23, 2014 7:32:06 PM].
Won, Eun Tae; “Visible Light Communication: Tutorial”, Project: IEEE P802.15 Working Group for Wireless Personal Area Networks (WPANs), Mar. 9, 2008.
“Link: Would You Like to See the Goal-Post Lengthened in Height in College Football”, TideFans.com, May 6, 2014. http://www.tidefans.com/forums/showthread.php?t=222422&page=4.
PCT Application No. PCT/US2015/033613 International Search Report and Written Opinion mailed Sep. 1, 2015.
PCT Application No. PCT/US2015/040228 International Search Report and Written Opinion mailed Sep. 30, 2015.
PCT Application No. PCT/US2015/040229 International Search Report and Written Opinion mailed Oct. 1, 2015.
PCT Application No. PCT/US2015/047059 International Search Report and Written Opinion mailed Nov. 9, 2015.
U.S. Appl. No. 14/798,049 Office Action mailed Nov. 3, 2015.
U.S. Appl. No. 14/798,081 Office Action mailed Sep. 28, 2015.
U.S. Appl. No. 14/798,091 Office Action mailed Sep. 22, 2015.
U.S. Appl. No. 14/788,728 Office Action mailed Sep. 17, 2015.
U.S. Appl. No. 14/788,742 Office Action mailed Sep. 2, 2015.
U.S. Appl. No. 15/091,139, John E. Cronin, Sensor Experience Garment, filed Apr. 5, 2016.
U.S. Appl. No. 14/798,049 Final Office Action mailed Mar. 22, 2016.
U.S. Appl. No. 14/798,091 Office Action mailed Mar. 28, 2016.
U.S. Appl. No. 14/798,035 Office Action mailed Nov. 24, 2015.
U.S. Appl. No. 14/798,068 Office Action mailed Nov. 23, 2015.
U.S. Appl. No. 14/798,131 Office Action mailed Jan. 12, 2016.
U.S. Appl. No. 14/798,204 Office Action mailed Jan. 22, 2016.
U.S. Appl. No. 14/798,190 Office Action mailed Jan. 12, 2016.
U.S. Appl. No. 14/829,598 Office Action mailed Feb. 2, 2016.
U.S. Appl. No. 14/788,728 Final Office Action mailed Feb. 1, 2016.
U.S. Appl. No. 14/788,742 Final Office Action mailed Jan. 6, 2016.
U.S. Appl. No. 14/798,068 Final Office Action mailed May 5, 2016.
U.S. Appl. No. 14/798,131 Final Office Action mailed May 23, 2016.
U.S. Appl. No. 14/798,204 Final Office Action mailed May 11, 2016.
U.S. Appl. No. 14/788,742 Office Action mailed May 11, 2016.
U.S. Appl. No. 15/187,100, filed Jun. 20, 2016, John E. Cronin, Smart Field Goal Detector.
U.S. Appl. No. 14/798,091 Office Action mailed Aug. 8, 2016.
U.S. Appl. No. 14/798,190 Final Office Action mailed Jul. 25, 2016.
U.S. Appl. No. 14/829,598 Final Office Action mailed Jul. 18, 2016.
U.S. Appl. No. 14/788,728 Office Action mailed Jul. 13, 2016.
Provisional Applications (1)
Number Date Country
62023472 Jul 2014 US