Abstract: Motion capture system with a motion capture element that uses two or more sensors to measure a single physical quantity, for example to obtain both wide measurement range and high measurement precision. For example, a system may combine a low-range, high precision accelerometer having a range of ?24 g to +24 g with a high-range accelerometer having a range of ?400 g to +400 g. Data from the multiple sensors is transmitted to a computer that combines the individual sensor estimates into a single estimate for the physical quantity. Various methods may be used to combine individual estimates into a combined estimate, including for example weighting individual estimates by the inverse of the measurement variance of each sensor. Data may be extrapolated beyond the measurement range of a low-range sensor, using polynomial curves for example, and combined with data from a high-range sensor to form a combined estimate.

Abstract: Enables coupling or retrofitting a golf club with active motion capture electronics that are battery powered, passive or active shot count components, for example a passive RFID, and/or a visual marker on the cap for use with visual motion capture cameras. Does not require modifying the golf club. Electronics package and battery can be easily removed and replaced, for example without any tools. May utilize a weight that is removed when inserting the electronic package in the mount, wherein the weight element may have the same weight as an electronics package, for no net change or minimal change in club weight. May be implemented with a shaft enclosure and expander that may be coupled with a screw aligned along an axis parallel to the axis of the shaft. May utilize non-permanently and/or friction coupling between the mount and shaft. Cap may include a visual marker and/or logo.

Abstract: A system that analyzes data from sensors and video cameras to generated synchronized event videos and to automatically select or generate tags for an event. Enables creating, transferring, obtaining, and storing concise event videos generally without non-event video. Events stored in the database identifies trends, correlations, models, and patterns in event data. Tags may represent for example activity types, players, performance levels, or scoring results. The system may analyze social media postings to confirm or augment event tags. Users may filter and analyze saved events based on the assigned tags. The system may create highlight and fail reels filtered by metrics and by tags.

Abstract: Portable wireless mobile device motion capture data mining system and method configured to display motion capture/analysis data on a mobile device. System obtains data from motion capture elements, analyzes data and store data in database for data mining, which may be charged for. Enables unique displays associated with the user, such as 3D overlays onto images of the user to visually depict the captured motion data including ratings. Predicted ball flight path data can be calculated and shown on a time line showing relative peaks of velocity for the user's body parts. User can determine equipment that fits best and immediately purchase the equipment, via the mobile device. Custom equipment may be ordered on the mobile device from a vendor that can assemble-to-order customer built equipment and ship the equipment. Includes active and passive golf shot count capabilities.

Abstract: A sensor event detection and tagging system that analyzes data from multiple sensors to detect an event and to automatically select or generate tags for the event. Sensors may include for example a motion capture sensor and one or more additional sensors that measure values such as temperature, humidity, wind or elevation. Tags and event detection may be performed by a microprocessor associated with or integrated with the sensors, or by a computer that receives data from the microprocessor. Tags may represent for example activity types, players, performance levels, or scoring results. The system may analyze social media postings to confirm or augment event tags. Users may filter and analyze saved events based on the assigned tags. The system may create highlight and fail reels filtered by metrics and by tags.

Abstract: Motion capture system with a motion capture element that uses two or more sensors to measure a single physical quantity, for example to obtain both wide measurement range and high measurement precision. For example, a system may combine a low-range, high precision accelerometer having a range of ?24 g to +24 g with a high-range accelerometer having a range of ?400 g to +400 g. Data from the multiple sensors is transmitted to a computer that combines the individual sensor estimates into a single estimate for the physical quantity. Various methods may be used to combine individual estimates into a combined estimate, including for example weighting individual estimates by the inverse of the measurement variance of each sensor. Data may be extrapolated beyond the measurement range of a low-range sensor, using polynomial curves for example, and combined with data from a high-range sensor to form a combined estimate.

Abstract: A sensor event detection and tagging system that analyzes data from multiple sensors to detect an event and to automatically select or generate tags for the event. Sensors may include for example a motion capture sensor and one or more additional sensors that measure values such as temperature, humidity, wind or elevation. Tags and event detection may be performed by a microprocessor associated with or integrated with the sensors, or by a computer that receives data from the microprocessor. Tags may represent for example activity types, players, performance levels, or scoring results. The system may analyze social media postings to confirm or augment event tags. Users may filter and analyze saved events based on the assigned tags. The system may create highlight and fail reels filtered by metrics and by tags.

Abstract: A system that analyzes data from sensors and video cameras to generated synchronized event videos and to automatically select or generate tags for an event. Enables creating, transferring, obtaining, and storing concise event videos generally without non-event video. Events stored in the database identifies trends, correlations, models, and patterns in event data. Tags may represent for example activity types, players, performance levels, or scoring results. The system may analyze social media postings to confirm or augment event tags. Users may filter and analyze saved events based on the assigned tags. The system may create highlight and fail reels filtered by metrics and by tags.

Abstract: Enables detection and tagging of events using sensor data combined with data from servers such as social media sites. Sensors may measure values such as motion, temperature, humidity, wind, pressure, elevation, light, sound, or heart rate. Sensor data and event tags may be utilized to curate text, images, video, sound and post the results to social networks, for example in a dedicated feed. Event tags generated by the system may represent for example activity types, players, performance levels, or scoring results. The system may analyze social media postings to confirm or augment event tags. Users may filter and analyze saved events based on the assigned tags. The system may create highlight and fail reels filtered by metrics and by tags.

Abstract: Enables detection of events using motion capture sensors and potentially other sensors electromagnetic field, temperature, humidity, wind, pressure, elevation, light, sound, or heart rate sensors to confirm and post events, differentiate similar types of motion events to determine the type of equipment or activity or quality of the event, such proficiency. Enables motion capture data and other sensor data to be utilized to curate text, images, video, sound and post the results to social networks, for example in a dedicated feed. Embodiments of the system also may post or filter to social media sites using any other filter besides location and time and the text in the social media posts for example. May use motion or other sensor data to define and event, eliminate false positive events, post true events, and/or correlate the events with social media to confirm the events, or post the events in a particular channel.

Abstract: Intelligent motion capture element that includes sensor personalities that optimize the sensor for specific movements and/or pieces of equipment and/or clothing and may be retrofitted onto existing equipment or interchanged therebetween and automatically detected for example to switch personalities. May be used for low power applications and accurate data capture for use in healthcare compliance, sporting, gaming, military, virtual reality, industrial, retail loss tracking, security, baby and elderly monitoring and other applications for example obtained from a motion capture element and relayed to a database via a mobile phone. System obtains data from motion capture elements, analyzes data and stores data in database for use in these applications and/or data mining. Enables unique displays associated with the user, such as 3D overlays onto images of the user to visually depict the captured motion data. Enables performance related equipment fitting and purchase.

Abstract: A sensor event detection system including a motion capture element with a memory, sensor, microprocessor, first communication interface and another sensor. The sensor captures values associated with an orientation, position, velocity and acceleration of the motion capture element. The first communication interface receives other values associated with a temperature, humidity, wind and elevation, and the other sensor locally captures the other values. The microprocessor collects data that includes sensor values from the sensor, stores the data in the memory, and recognizes an event within the data to determine event data. The microprocessor correlates the data or event data with the other values to determine a false positive event or a type of equipment the motion capture element is coupled with, or a type of activity indicated by the data or event data, and transmits the data or event data associated with the event via the first communication interface.

Abstract: A system that analyzes data from multiple sensors, potentially of different types, that track motions of players, equipment, and projectiles such as balls. Data from different sensors is combined to generate integrated metrics for events and activities. Illustrative sensors may include inertial sensors, cameras, radars, and light gates. As an illustrative example, a video camera may track motion of a pitched baseball, and an inertial sensor may track motion of a bat; the system may use the combined data to analyze the effectiveness of the swing in hitting the pitch. The system may also use sensor data to automatically select or generate tags for an event; tags may represent for example activity types, players, performance levels, or scoring results. The system may analyze social media postings to confirm or augment event tags. Users may filter and analyze saved events based on the assigned tags.

Abstract: Enables event analysis from sensors including environmental, physiological and motion capture sensors. Also enables displaying information based on events recognized using sensor data associated with a user, piece of equipment or based on previous motion analysis data from the user or other user(s) or other sensors. Enables intelligent analysis, synchronization, and transfer of generally concise event videos synchronized with motion data from motion capture sensor(s) coupled with a user or piece of equipment. Enables creating, transferring, obtaining, and storing concise event videos generally without non-event video. Events stored in the database identifies trends, correlations, models, and patterns in event data. Greatly saves storage and increases upload speed by uploading event videos and avoiding upload of non-pertinent portions of large videos. Creates highlight and fail reels filtered by metrics and can sort by metric.

Abstract: A method that integrates sensor data and video analysis to analyze object motion. Motion capture elements generate motion sensor data for objects of interest, and cameras generate video of these objects. Sensor data and video data are synchronized in time and aligned in space on a common coordinate system. Sensor fusion is used to generate motion metrics from the combined and integrated sensor data and video data. Integration of sensor data and video data supports robust detection of events, generation of video highlight reels or epic fail reels augmented with metrics that show interesting activity, and calculation of metrics that exceed the individual capabilities of either sensors or video analysis alone.

Abstract: Enables a fitting system for sporting equipment using an application that executes on a mobile phone for example to prompt and accept motion inputs from a given motion capture sensor to measure a user's size, range of motion, speed and then utilizes that same sensor to capture motion data from a piece of equipment, for example to further optimize the fit of, or suggest purchase of a particular piece of sporting equipment. Utilizes correlation or other data mining of motion data for size, range of motion, speed of other users to maximize the fit of a piece of equipment for the user based on other user's performance with particular equipment. For example, this enables a user of a similar size, range of motion and speed to data mine for the best performance equipment, e.g., longest drive, lowest putt scores, highest winning percentage, etc., associated with other users having similar characteristics.

Abstract: Enables recognition of events within motion data obtained from portable wireless motion capture elements and video synchronization of the events with video as the events occur or at a later time, based on location and/or time of the event or both. May use integrated camera or external cameras with respect to mobile device to automatically generate generally smaller event videos of the event on the mobile device or server. Also enables analysis or comparison of movement associated with the same user, other user, historical user or group of users. Provides low memory and power utilization and greatly reduces storage for video data that corresponds to events such as a shot, move or swing of a player, a concussion of a player, or other medical related events or events, such as the first steps of a child, or falling events.

Abstract: A shatter proof enclosure and mount for a motion capture element that couples to equipment, where the enclosure and optionally the mount is shatter proof or shatter resistant. Exposed areas of the enclosure or mount or both that are subject to impact may be covered with a protective layer that prevents fragments of the enclosure or internal components from exiting the layer, even in the event of an impact. For example, the protective layer may incorporate flexible materials such as silicone rubber. Alternatively, the protective layer may be rigid but effectively unbreakable, using materials such as polycarbonate. The protective layer may also include a mesh that prevents internal components from existing the enclosure.

Abstract: A motion sensor package with an elastomer layer that encases the sensor electronics, including the sensors, a processor, an antenna, and a battery. The elastomer layer may provide shock isolation and water resistance to protect the enclosed electronics. Embodiments may also include an outer housing into which the elastomer encased package is installed. The outer housing may for example comprise two cylindrical sections that screw together to close the outer housing. In one or more embodiments part of the outer housing may be integrated into an item of sports equipment. Embodiments for golf may also include a golf club grip adapter that is inserted into the top of a grip, and which attaches to the outer housing containing the elastomer enclosed sensor package.

Abstract: Portable wireless mobile device motion capture and analysis system and method configured to display motion capture/analysis data on a mobile device. System obtains data from motion capture elements and analyzes the data. Enables unique displays associated with the user, such as 3D overlays onto images of the user to visually depict the captured motion data. Ratings associated with the captured motion can also be displayed. Predicted ball flight path data can be calculated and displayed. Data shown on a time line can also be displayed to show the relative peaks of velocity for various parts of the user's body. Based on the display of data, the user can determine the equipment that fits the best and immediately purchase the equipment, via the mobile device. Custom equipment may be ordered through an interface on the mobile device from a vendor that can assemble-to-order customer built equipment and ship the equipment.