US20180060532A1 - Processing Data of a User Performing an athletic Activity to Estimate Energy Expenditure - Google Patents

Abstract

Example embodiments may relate to a system, method, apparatus, and computer readable media configured for prompting a user to perform an exercise, monitoring form of the user while performing the exercise, and calculating an energy expenditure estimate for the user performing the exercise based on a type of the exercise and on the form of the user.

Description

CROSS REFERENCE TO RELATED APPLICATIONS
• This application is a continuation of U.S. patent application Ser. No. 13/324,812 filed Dec. 13, 2011 titled “Processing Data of a User Performing an Athletic Activity to Estimate Energy Expenditure, which is continuation-in-part of U.S. patent application Ser. No. 13/290,359 filed Nov. 7, 2011 titled “Method and System for Automated Personal Training,” issued as U.S. Pat. No. 9,283,429 on Mar. 15, 2016, which is a continuation-in-part of U.S. patent application Ser. No. 13/304,064 filed Nov. 23, 2011 titled “Method and System for Automated Personal Training That Includes Training Programs,” issued as U.S. Pat. No. 9,457,256 on Oct. 4, 2016, and continuation-in-part of U.S. patent application Ser. No. 13/304,056 filed Nov. 23, 2011 titled “Fatigue Indices and Uses Thereof,” issued as U.S. Pat. No. 9,223,936 on Dec. 29, 2015. This application claims the benefit of, and priority to, U.S. Provisional Patent 61/422,511 filed Dec. 13, 2010, 61/432,472 filed Jan. 13, 2011, and 61/433,792 filed Jan. 18, 2011, each of which is entitled “Method and System for Automated Personal Training.” The contents of each of the above-identified applications are expressly incorporated herein by reference in its entirety for any and all non-limiting purposes.
BACKGROUND
• While most people appreciate the importance of physical fitness, many have difficulty finding the motivation required to maintain a regular exercise program. Some people find it particularly difficult to maintain an exercise regimen that involves continuously repetitive motions, such as running, walking and bicycling.
• Additionally, individuals may view exercise as work or a chore and thus, separate it from enjoyable aspects of their daily lives. Often, this clear separation between athletic activity and other activities reduces the amount of motivation that an individual might have toward exercising. Further, athletic activity services and systems directed toward encouraging individuals to engage in athletic activities might also be too focused on one or more particular activities while an individual's interest are ignored. This may further decrease a user's interest in participating in athletic activities or using the athletic activity services and systems.
• Therefore, improved systems and methods to address these and other shortcomings in the art are desired.
BRIEF SUMMARY
• The following presents a simplified summary in order to provide a basic understanding of some aspects of the disclosure. The summary is not an extensive overview of the disclosure. It is neither intended to identify key or critical elements of the disclosure nor to delineate the scope of the disclosure. The following summary merely presents some concepts of the disclosure in a simplified form as a prelude to the description below.
• Aspects of this disclosure relate to processing of data taken while a user performs an athletic activity to determine an estimate of energy expenditure such as, for example, an amount of calories burned.
• Example embodiments may relate to a system, method, apparatus, and computer readable media configured for prompting a user to perform an exercise, monitoring form of the user while performing the exercise, and calculating an energy expenditure estimate for the user performing the exercise based on a type of the exercise and on the form of the user. In other embodiments, expenditure estimate may be, or comprise, for example, an estimate of calories burned by the user. In certain embodiments, energy expenditure calculations comprise determinations relating to: effort, oxygen consumed, and/or oxygen kinetics of the user.
• In various aspects, a system, method, apparatus, and/or computer readable media may be configured for processing data captured of a user performing an athletic activity over a time interval, and determining a location of a center of mass of a body part, body region, or entire body of the user at a first time instant and at a second time instant within the time interval. In further aspects, a system, method, apparatus, and/or computer readable media may be configured for identifying a change in the location of the center of mass from the first time instant to the second time instant, and calculating an energy expenditure estimate for the user due to the change.
• These and other aspects of the embodiments are discussed in greater detail throughout this disclosure, including the accompanying drawings.
BRIEF DESCRIPTION OF THE DRAWINGS
• The present disclosure is illustrated by way of example and not limited in the accompanying figures in which like reference numerals indicate similar elements and in which:
• FIGS. 1A-B illustrate an example of a system for providing personal training in accordance with example embodiments, whereinFIG. 1A illustrates an example network configured to monitor athletic activity, andFIG. 1B illustrates an example computing device in accordance with example embodiments.
• FIGS. 2A-B illustrate example sensor assemblies that may be worn by a user in accordance with example embodiments.
• FIG. 3 illustrates an example flow diagram of a method for calculating an energy expenditure estimate for a user that accounts for a user's form while exercising as part of the estimate, in accordance with example embodiments.
• FIG. 4 illustrates example points on a user's body for monitoring during exercising in accordance with example embodiments.
• FIG. 5 illustrates an example posture assessment in accordance with example embodiments.
• FIG. 6 illustrates example displays of a virtual avatar of a user performing an exercise in accordance with example embodiments.
• FIGS. 7A-B illustrate example displays of a virtual avatar of a user performing a squat in accordance with example embodiments.
• FIG. 8 illustrates an example flow diagram of a method for calculating an energy expenditure estimate for a user while performing an athletic activity based on monitoring changes in potential energy, in accordance with example embodiments.
• FIGS. 9, 10A-B, and11 illustrate example locations of centers of mass for a virtual avatar of user, in accordance with example embodiments.
DETAILED DESCRIPTION
• In the following description of the various embodiments, reference is made to the accompanying drawings, which form a part hereof, and in which is shown by way of illustration various embodiments in which the disclosure may be practiced. It is to be understood that other embodiments may be utilized and structural and functional modifications may be made without departing from the scope and spirit of the present disclosure. Further, headings within this disclosure should not be considered as limiting aspects of the disclosure. Those skilled in the art with the benefit of this disclosure will appreciate that the example embodiments are not limited to the example headings.
I. Example Personal Training System
• A. Illustrative Computing Devices
• FIG. 1A illustrates an example of apersonal training system100 in accordance with example embodiments.Example system100 may include one or more electronic devices, such ascomputer102.Computer102 may comprise a mobile terminal, such as a telephone, music player, tablet, netbook or any portable device. In other embodiments,computer102 may comprise a set-top box (STB), desktop computer, digital video recorder(s) (DVR), computer server(s), and/or any other desired computing device. In certain configurations,computer102 may comprise a gaming console, such as for example, a Microsoft® XBOX, Sony® Playstation, and/or a Nintendo® Wii gaming consoles. Those skilled in the art will appreciate that these are merely example consoles for descriptive purposes and this disclosure is not limited to any console or device.
• Turning briefly toFIG. 1B,computer102 may include computing unit104, which may comprise at least one processing unit106. Processing unit106 may be any type of processing device for executing software instructions, such as for example, a microprocessor device.Computer102 may include a variety of non-transitory computer readable media, such as memory108. Memory108 may include, but is not limited to, random access memory (RAM) such asRAM110, and/or read only memory (ROM), such as ROM112. Memory108 may include any of: electronically erasable programmable read only memory (EEPROM), flash memory or other memory technology, CD-ROM, digital versatile disks (DVD) or other optical disk storage, magnetic storage devices, or any other medium that can be used to store the desired information and that can be accessed bycomputer102.
• The processing unit106 and the system memory108 may be connected, either directly or indirectly, through a bus114 or alternate communication structure to one or more peripheral devices. For example, the processing unit106 or the system memory108 may be directly or indirectly connected to additional memory storage, such as a hard disk drive116, a removable magnetic disk drive, anoptical disk drive118, and a flash memory card. The processing unit106 and the system memory108 also may be directly or indirectly connected to one or more input devices120 and one or more output devices122. The output devices122 may include, for example, adisplay device136, television, printer, stereo, or speakers. In some embodiments one or more display devices may be incorporated into eyewear. The display devices incorporated into eyewear may provide feedback to users. Eyewear incorporating one or more display devices also provides for a portable display system. The input devices120 may include, for example, a keyboard, touch screen, a remote control pad, a pointing device (such as a mouse, touchpad, stylus, trackball, or joystick), a scanner, a camera or a microphone. In this regard, input devices120 may comprise one or more sensors configured to sense, detect, and/or measure athletic movement from a user, such asuser124, shown inFIG. 1A.
• Looking again toFIG. 1A, image-capturingdevice126 and/orsensor128 may be utilized in detecting and/or measuring athletic movements ofuser124. In one embodiment, data obtained from image-capturingdevice126 orsensor128 may directly detect athletic movements, such that the data obtained from image-capturingdevice126 orsensor128 is directly correlated to a motion parameter. For example, and with reference toFIG. 4, image data from image-capturingdevice126 may detect that the distance betweensensor locations402gand402ihas decreased and therefore, image-capturingdevice126 alone may be configured to detect that user's124 right arm has moved. Yet, in other embodiments, data from image-capturingdevice126 and/orsensor128 may be utilized in combination, either with each other or with other sensors to detect and/or measure movements. Thus, certain measurements may be determined from combining data obtained from two or more devices. Image-capturingdevice126 and/orsensor128 may include or be operatively connected to one or more sensors, including but not limited to: an accelerometer, a gyroscope, a location-determining device (e.g., GPS), light sensor, temperature sensor (including ambient temperature and/or body temperature), heart rate monitor, image-capturing sensor, moisture sensor and/or combinations thereof. Example uses ofillustrative sensors126,128 are provided below in Section I.C, entitled “Illustrative Sensors.”Computer102 may also use touch screens or image capturing device to determine where a user is pointing to make selections from a graphical user interface. One or more embodiments may utilize one or more wired and/or wireless technologies, alone or in combination, wherein examples of wireless technologies include Bluetooth® technologies, Bluetooth® low energy technologies, and/or ANT technologies.
• B. Illustrative Network
• Still further,computer102, computing unit104, and/or any other electronic devices may be directly or indirectly connected to one or more network interfaces, such as example interface130 (shown inFIG. 1B) for communicating with a network, such asnetwork132. In the example ofFIG. 1B, network interface130, may comprise a network adapter or network interface card (NIC) configured to translate data and control signals from the computing unit104 into network messages according to one or more communication protocols, such as the Transmission Control Protocol (TCP), the Internet Protocol (IP), and the User Datagram Protocol (UDP). These protocols are well known in the art, and thus will not be discussed here in more detail. An interface130 may employ any suitable connection agent for connecting to a network, including, for example, a wireless transceiver, a power line adapter, a modem, or an Ethernet connection.Network132, however, may be any one or more information distribution network(s), of any type(s) or topology(s), alone or in combination(s), such as internet(s), intranet(s), cloud(s), LAN(s).Network132 may be any one or more of cable, fiber, satellite, telephone, cellular, wireless, etc. Networks are well known in the art, and thus will not be discussed here in more detail.Network132 may be variously configured such as having one or more wired or wireless communication channels to connect one or more locations (e.g., schools, businesses, homes, consumer dwellings, network resources, etc.), to one or moreremote servers134, or to other computers, such as similar or identical tocomputer102. Indeed,system100 may include more than one instance of each component (e.g., more than onecomputer102, more than onedisplay136, etc.).
• Regardless of whethercomputer102 or other electronic device withinnetwork132 is portable or at a fixed location, it should be appreciated that, in addition to the input, output and storage peripheral devices specifically listed above, the computing device may be connected, such as either directly, or throughnetwork132 to a variety of other peripheral devices, including some that may perform input, output and storage functions, or some combination thereof. In certain embodiments, a single device may integrate one or more components shown inFIG. 1A. For example, a single device may includecomputer102, image-capturingdevice126,sensor128,display136 and/or additional components. In one embodiment,sensor device138 may comprise a mobile terminal having adisplay136, image-capturingdevice126, and one ormore sensors128. Yet, in another embodiment, image-capturingdevice126, and/orsensor128 may be peripherals configured to be operatively connected to a media device, including for example, a gaming or media system. Thus, it goes from the foregoing that this disclosure is not limited to stationary systems and methods. Rather, certain embodiments may be carried out by auser124 in almost any location.
• C. Illustrative Sensors
• Computer102 and/or other devices may comprise one ormore sensors126,128 configured to detect and/or monitor at least one fitness parameter of auser124.Sensors126 and/or128 may include, but are not limited to: an accelerometer, a gyroscope, a location-determining device (e.g., GPS), light sensor, temperature sensor (including ambient temperature and/or body temperature), sleep pattern sensors, heart rate monitor, image-capturing sensor, moisture sensor and/or combinations thereof.Network132 and/orcomputer102 may be in communication with one or more electronic devices ofsystem100, including for example,display136, an image capturing device126 (e.g., one or more video cameras), andsensor128, which may be an infrared (IR) device. In oneembodiment sensor128 may comprise an IR transceiver. For example,sensors126, and/or128 may transmit waveforms into the environment, including towards the direction ofuser124 and receive a “reflection” or otherwise detect alterations of those released waveforms. In yet another embodiment, image-capturingdevice126 and/orsensor128 may be configured to transmit and/or receive other wireless signals, such as radar, sonar, and/or audible information. Those skilled in the art will readily appreciate that signals corresponding to a multitude of different data spectrums may be utilized in accordance with various embodiments. In this regard,sensors126 and/or128 may detect waveforms emitted from external sources (e.g., not system100). For example,sensors126 and/or128 may detect heat being emitted fromuser124 and/or the surrounding environment. Thus, image-capturingdevice126 and/orsensor128 may comprise one or more thermal imaging devices. In one embodiment, image-capturingdevice126 and/orsensor128 may comprise an IR device configured to perform range phenomenology. As a non-limited example, image-capturing devices configured to perform range phenomenology are commercially available from Flir Systems, Inc. of Portland, Oreg. Althoughimage capturing device126 andsensor128 anddisplay136 are shown in direct (wirelessly or wired) communication withcomputer102, those skilled in the art will appreciate that any may directly communicate (wirelessly or wired) withnetwork132.
• 1. Multi-Purpose Electronic Devices
• User124 may possess, carry, and/or wear any number of electronic devices, includingsensory devices138,140,142, and/or144. In certain embodiments, one ormore devices138,140,142,144 may not be specially manufactured for fitness or athletic purposes. Indeed, aspects of this disclosure relate to utilizing data from a plurality of devices, some of which are not fitness devices, to collect, detect, and/or measure athletic data. In one embodiment,device138 may comprise a portable electronic device, such as a telephone or digital music player, including an IPOD®, IPAD®, or iPhone®, brand devices available from Apple, Inc. of Cupertino, Calif. or Zune® or Microsoft® Windows devices available from Microsoft of Redmond, Wash. As known in the art, digital media players can serve as both an output device for a computer (e.g., outputting music from a sound file or pictures from an image file) and a storage device. In one embodiment,device138 may becomputer102, yet in other embodiments,computer102 may be entirely distinct fromdevice138. Regardless of whetherdevice138 is configured to provide certain output, it may serve as an input device for receiving sensory information.Devices138,140,142, and/or144 may include one or more sensors, including but not limited to: an accelerometer, a gyroscope, a location-determining device (e.g., GPS), light sensor, temperature sensor (including ambient temperature and/or body temperature), heart rate monitor, image-capturing sensor, moisture sensor and/or combinations thereof. In certain embodiments, sensors may be passive, such as reflective materials that may be detected by image-capturingdevice126 and/or sensor128 (among others). In certain embodiments, sensors144 may be integrated into apparel, such as athletic clothing. For instance, theuser124 may wear one or more on-body sensors144a-b. Sensors144 may be incorporated into the clothing ofuser124 and/or placed at any desired location of the body ofuser124. Sensors144 may communicate (e.g., wirelessly) withcomputer102,sensors128,138,140, and142, and/orcamera126. Examples of interactive gaming apparel are described in U.S. patent application Ser. No. 10/286,396, filed Oct. 30, 2002, and published as U.S. Pat. Pub, No. 2004/0087366, the contents of which are incorporated herein by reference in its entirety for any and all non-limiting purposes. In certain embodiments, passive sensing surfaces may reflect waveforms, such as infrared light, emitted by image-capturingdevice126 and/orsensor128. In one embodiment, passive sensors located on user's124 apparel may comprise generally spherical structures made of glass or other transparent or translucent surfaces which may reflect waveforms. Different classes of apparel may be utilized in which a given class of apparel has specific sensors configured to be located proximate to a specific portion of the user's124 body when properly worn. For example, golf apparel may include one or more sensors positioned on the apparel in a first configuration and yet soccer apparel may include one or more sensors positioned on apparel in a second configuration.
• Devices138-144 may communicate with each other, either directly or through a network, such asnetwork132. Communication between one or more of devices138-144 may communicate throughcomputer102. For example, two or more of devices138-144 may be peripherals operatively connected to bus114 ofcomputer102. In yet another embodiment, a first device, such asdevice138 may communicate with a first computer, such ascomputer102 as well as another device, such asdevice142, however,device142 may not be configured to connect tocomputer102 but may communicate withdevice138. Those skilled in the art will appreciate that other configurations are possible.
• Some implementations of the example embodiments may alternately or additionally employ computing devices that are intended to be capable of a wide variety of functions, such as a desktop or laptop personal computer. These computing devices may have any combination of peripheral devices or additional components as desired. Also, the components shown inFIG. 1B may be included in theserver134, other computers, apparatuses, etc.
• 2. Illustrative Apparel/Accessory Sensors
• In certain embodiments,sensory devices138,140,142 and/or144 may be formed within or otherwise associated with user's124 clothing or accessories, including a watch, armband, wristband, necklace, shirt, shoe, or the like. Examples of shoe-mounted and wrist-worn devices (devices140 and142, respectively) are described immediately below, however, these are merely example embodiments and this disclosure should not be limited to such.
• i. Shoe-Mounted Device
• In certain embodiments,sensory device140 may comprise footwear which may include one or more sensors, including but not limited to: an accelerometer, location-sensing components, such as GPS, and/or a force sensor system.FIG. 2A illustrates one example embodiment of asensor system202. In certain embodiments,system202 may include asensor assembly204.Assembly204 may comprise one or more sensors, such as for example, an accelerometer, location-determining components, and/or force sensors. In the illustrated embodiment,assembly204 incorporates a plurality of sensors, which may include force-sensitive resistor (FSR)sensors206. In yet other embodiments, other sensor(s) may be utilized.Port208 may be positioned within asole structure209 of a shoe.Port208 may optionally be provided to be in communication with an electronic module210 (which may be in a housing211) and a plurality ofleads212 connecting theFSR sensors206 to theport208. Module210 may be contained within a well or cavity in a sole structure of a shoe. Theport208 and the module210 includecomplementary interfaces214,216 for connection and communication.
• In certain embodiments, at least one force-sensitive resistor206 shown inFIG. 2A may contain first and second electrodes orelectrical contacts218,220 and a force-sensitive resistive material222 disposed between theelectrodes218,220 to electrically connect theelectrodes218,220 together. When pressure is applied to the force-sensitive material222, the resistivity and/or conductivity of the force-sensitive material222 changes, which changes the electrical potential between theelectrodes218,220. The change in resistance can be detected by thesensor system202 to detect the force applied on the sensor216. The force-sensitive resistive material222 may change its resistance under pressure in a variety of ways. For example, the force-sensitive material222 may have an internal resistance that decreases when the material is compressed, similar to the quantum tunneling composites described in greater detail below. Further compression of this material may further decrease the resistance, allowing quantitative measurements, as well as binary (on/off) measurements. In some circumstances, this type of force-sensitive resistive behavior may be described as “volume-based resistance,” and materials exhibiting this behavior may be referred to as “smart materials.” As another example, the material222 may change the resistance by changing the degree of surface-to-surface contact. This can be achieved in several ways, such as by using microprojections on the surface that raise the surface resistance in an uncompressed condition, where the surface resistance decreases when the microprojections are compressed, or by using a flexible electrode that can be deformed to create increased surface-to-surface contact with another electrode. This surface resistance may be the resistance between the material222 and theelectrode218,220222 and/or the surface resistance between a conducting layer (e.g., carbon/graphite) and a force-sensitive layer (e.g., a semiconductor) of a multi-layer material222. The greater the compression, the greater the surface-to-surface contact, resulting in lower resistance and enabling quantitative measurement. In some circumstances, this type of force-sensitive resistive behavior may be described as “contact-based resistance.” It is understood that the force-sensitive resistive material222, as defined herein, may be or include a doped or non-doped semiconducting material.
• Theelectrodes218,220 of the FSR sensor216 can be formed of any conductive material, including metals, carbon/graphite fibers or composites, other conductive composites, conductive polymers or polymers containing a conductive material, conductive ceramics, doped semiconductors, or any other conductive material. The leads212 can be connected to theelectrodes218,220 by any suitable method, including welding, soldering, brazing, adhesively joining, fasteners, or any other integral or non-integral joining method. Alternately, theelectrode218,220 and associatedlead212 may be formed of a single piece of the same material.
• ii. Wrist-Worn Device
• As shown inFIG. 2B, device226 (which may resemble or besensory device142 shown inFIG. 1A) may be configured to be worn byuser124, such as around a wrist, arm, ankle or the like. Device226 may monitor athletic movements of a user, including all-day activity ofuser124. In this regard, device assembly226 may detect athletic movement during user's124 interactions withcomputer102 and/or operate independently ofcomputer102. For example, in one embodiment, device226 may be an-all day activity monitor that measures activity regardless of the user's proximity or interactions withcomputer102. Device226 may communicate directly withnetwork132 and/or other devices, such asdevices138 and/or140. In other embodiments, athletic data obtained from device226 may be utilized in determinations conducted bycomputer102, such as determinations relating to which exercise programs are presented touser124. In one embodiment, device226 may also wirelessly interact with a mobile device, such asdevice138 associated withuser124 or a remote website such as a site dedicated to fitness or health related subject matter. At some predetermined time, the user may wish to transfer data from the device226 to another location.
• As shown inFIG. 2B, device226 may include an input mechanism, such as adepressible input button228 assist in operation of the device226. Theinput button228 may be operably connected to acontroller230 and/or any other electronic components, such as one or more of the elements discussed in relation tocomputer102 shown inFIG. 1B.Controller230 may be embedded or otherwise part ofhousing232.Housing232 may be formed of one or more materials, including elastomeric components and comprise one or more displays, such as display234. The display may be considered an illuminable portion of the device226. The display234 may include a series of individual lighting elements or light members such as LED lights234 in an exemplary embodiment. The LED lights may be formed in an array and operably connected to thecontroller230. Device226 may include anindicator system236, which may also be considered a portion or component of the overall display234. It is understood that theindicator system236 can operate and illuminate in conjunction with the display234 (which may have pixel member235) or completely separate from the display234. Theindicator system236 may also include a plurality of additional lighting elements orlight members238, which may also take the form of LED lights in an exemplary embodiment. In certain embodiments, indicator system may provide a visual indication of goals, such as by illuminating a portion oflighting members238 to represent accomplishment towards one or more goals.
• Afastening mechanism240 can be unlatched wherein the device226 can be positioned around a wrist of theuser124 and thefastening mechanism240 can be subsequently placed in a latched position. The user can wear the device226 at all times if desired. In one embodiment,fastening mechanism240 may comprise an interface, including but not limited to a USB port, for operative interaction withcomputer102 and/ordevices138,140.
• In certain embodiments, device226 may comprise a sensor assembly (not shown inFIG. 2B). The sensor assembly may comprise a plurality of different sensors. In an example embodiment, the sensor assembly may comprise or permit operative connection to an accelerometer (including in the form of a multi-axis accelerometer), heart rate sensor, location-determining sensor, such as a GPS sensor, and/or other sensors. Detected movements or parameters from device's142 sensor(s), may include (or be used to form) a variety of different parameters, metrics or physiological characteristics including but not limited to speed, distance, steps taken, and energy expenditure such as calories, heart rate, sweat detection, effort, oxygen consumed, and/or oxygen kinetics. Such parameters may also be expressed in terms of activity points or currency earned by the user based on the activity of the user.
• I. Illustrative Athletic Monitoring Methods
• System100 may prompt a user to perform one or more exercises, monitor user movement while performing the exercises, and provide the user with an energy expenditure estimate based on their movement.System100 may analyze a user's form to determine if the user is making an exercise more or less difficult, and adjust the energy expenditure estimate accordingly. Energy expenditure estimates may be, or comprise, an estimate of calories burned by the user. In certain embodiments, energy expenditure determinations may be based on, and/or conveyed as a point system. In one embodiment, calories may be converted to a point system, yet in other embodiments, measurements may be directly obtained in one or more point systems. In one implementation, activity points may be based upon: form, body movements, and/or completion of certain activities. In further embodiments, energy expenditure calculations may comprise determinations relating to: effort, oxygen consumed, and/or oxygen kinetics of the user. In one embodiment,computer102,camera126,sensor128, and display136 may be implemented within the confines of a user's residence, although other locations, including gyms and/or businesses are contemplated. Further, as discussed above,computer102 may be a portable device, such as a cellular telephone, therefore, one or more aspects discussed herein may be conducted in almost any location. In this regard, the example embodiments of this disclosure are discussed in the context of being implemented with one or more of the example components ofsystem100. Those skilled in the art will appreciate that reference(s) to a particular component, such ascomputer102, is not meant to be limiting, but rather to provide an illustrative example of one of many possible implementations. Thus, although certain components may be referenced, it is to be assumed that other components ofsystem100 may be utilized unless expressly disclaimed or physically impossible. Further, aspects disclosed herein are not limited toexample system100.
• A. Monitoring User Movements
• While exercising, thesystem100 may use one or more techniques to monitor user movement.FIG. 3 illustrates an example flow diagram of a method for calculating an energy expenditure estimate for a user that accounts for a user's form while exercising as part of the estimate, in accordance with example embodiments. The method may be implemented by a computer, such as, for example,computer102,device138,140 and/or142, as well as or other apparatuses. The blocks shown inFIG. 3 may be rearranged, some blocks may be removed, additional blocks may be added, each block may be repeated one or more times, and the flow diagram may be repeated one or more times. The flow diagram may begin atblock302.
• 1. Perform User Assessment
• Inblock302, the method may include performing an initial assessment of the user. A user, such asuser124, may be positioned in range of a sensor, such as in front of theimage capturing device126 and/orsensor128, which may comprise an infrared transceiver.Display136 may present a representation ofuser124 that may be a “mirror-image” or depict a virtual avatar, such as a user avatar, that moves to correspond with user movement.Computer102 may prompt the user to move into a certain region relative to theimage capturing device126 and/or relative to theinfrared transceiver128 so that the user is within frame and/or range. When properly positioned,system100 may process movement of the user. Although the term “initial” has been utilized, this assessment may occur each time the user initiatessystem100, performs certain movements, upon passage of time, or for any other reason. Thus, references to assessments herein are not limited to a single assessment.
• a. Identify Sensory Locations
• System100 may process sensory data to identify user movement data. In one embodiment, sensory locations on a user's body may be identified. With reference toFIG. 4,sensory locations402a-402omay correspond to locations of interest on the user's124 body (e.g., ankles, elbows, shoulders, etc.). For example, images of recorded video, such as fromcamera126, may be utilized in an identification of thesensory locations402a-402o. For example, the user may stand a certain distance, which may or may not be predefined, from thecamera126, andsystem100 may process the images to identify theuser124 within the video, for example, using disparity mapping techniques. In an example,image capturing device126 may be a stereo camera having two or more lenses that are spatially offset from one another and that simultaneously capture two or more images of the user.System100 may process the two or more images taken at a same time instant to generate a disparity map for determining a location of certain parts of the user's body in each image (or at least some of the images) in the video using a coordinate system (e.g., Cartesian coordinates). The disparity map may indicate a difference between an image taken by each of the offset lenses.
• In a second example, one or more sensors may be located on or proximate to the user's124 body at thesensory locations402a-402oor theuser124 may wear a suit having sensors situated at various locations. Yet, in other embodiments, sensor locations may be determined from other sensory devices, such asdevices138,140 and/or142. In this regard, sensors may be physical sensors located on a user's clothing, yet in other embodiments,sensor locations402a-402omay be based upon identification of relationships between two moving body parts. For example,sensor location402amay be determined by identifying motions ofuser124. In this regard, the overall shape or portion of a user's body may permit identification of certain body parts. Regardless of whether a camera, such ascamera126, is utilized and/or a physical sensor located on theuser124, such as sensors within device(s)138,140,142 are utilized, the sensors may sense a current location of a body part and/or track movement of the body part.
• In certain embodiments, a time stamp may be added to the data collected (such as collected part ofblock302 inFIG. 3) indicating a specific time when a body part was at a certain location. Sensor data may be received at computer102 (or other device) via wireless or wired transmission. A computer, such ascomputer102 and/ordevices138,140,142, may process the time stamps to determine the locations of the body parts using a coordinate system (e.g., Cartesian coordinates) within each (or at least some) of the images in the video. Data received fromcamera126 may be corrected, modified, and/or combined with data received from one or moreother devices138,140, and142.
• In a third example,system100 may use infrared pattern recognition to detect user movement and locations of body parts of theuser124. For example,sensor128 may include an infrared transceiver, which may be part ofcamera126, or another device, that may emit an infrared signal to illuminate the user's124 body using infrared signals. Theinfrared transceiver128 may capture a reflection of the infrared signal from the body ofuser124. Based on the reflection, thesystem100 may identify a location of certain parts of the user's body using a coordinate system (e.g., Cartesian coordinates) at particular instances in time. Which and how body parts are identified may be predetermined based on a type or types of exercise a user is requested to perform.
• As part of a workout routine,system100 may make an initial postural assessment of theuser124 as part of the initial user assessment inblock302 ofFIG. 3. With reference toFIG. 5,system100 may analyze front and side images of auser124 to determine a location of one or more of a user's shoulders, upper back, lower back, hips, knees, and ankles. On-body sensors and/or infrared techniques may also be used, either alone or in conjunction withcamera126, to determine the locations of various body parts for the postural assessment. For example,system100 may determineassessment lines124a-gand/or regions502-512 to determine the locations of a various points on a user's body, such as, for example, ankles, knees, hips, upper back, lower back, and shoulders.
• b. Identify Sensory Regions
• In further embodiments,system100 may identify sensory regions (see, e.g., block302). In one embodiment,assessments lines124a-gmay be utilized to divide the user's body into regions. For example,lines124b-fmay be horizontal axes. For example, a “shoulders” region502 may correlate to a body portion having a lower boundary around the user's shoulders (seeline124b), region504 may correlate to the body portion between the shoulders (line124b) and about half the distance to the hips (see line124c) and thus be an “upper back” region, and region506 may span the area between line124cto the hips (see line124d) to comprise a “lower back region.” Similarly, region508 may span the area between the “hips” (line124d) and the “knees” (see line124e), region510 may span between lines124eand124fand region512 (see “ankles”) may have an upper boundary around line124fRegions502-512 may be further divided, such as into quadrants, such as by using axes124aand124g. To aid in the identification of one or more sensory regions,system100 may prompt the user to make one or more specific movements. For example,system100 may prompt a user to move a specific body part or region (e.g., wave their right arm, or wave the left arm in a specific pattern) to aid the system100 (e.g., computer algorithm processing information received from the infrared transceiver128) in determining which body part or region is in a specific location within a coordinate system.
• c. Categorize Locations or Regions
• In certain embodiments, body parts or regions that are not proximate to each other may nonetheless be categorized into the same movement category (see, e.g., block302). For example, as shown inFIG. 5, the “upper back”, “hips”, and “ankles”regions504,508,512 may be categorized as belonging to a “mobility” category. In another embodiment, the “lower back” and “knees” regions506,510 may be categorized as belonging to a “stability” category. The categorizations are merely examples, and in other embodiments, a location or region may belong to multiple categories. For example, a “center of gravity” region may be formed from regions504 and506. In one embodiment, a “center of gravity” may comprise portions of regions504 and506. In another embodiment, a “center of moment” category may be provided, either independently, or alternatively, as comprising a portion of at least another category. In one embodiment, a single location may be weighted in two or more categories, such as being 10% weighted in a “stability” category and 90% weighted in a “mobility” category.
• System100 may also process the image to determine a color of clothing of the user or other distinguishing features to differentiate the user from their surroundings. After processing,system100 may identify a location of multiple points on the user's body and track locations of those points, such aslocations402 inFIG. 4.System100 may also prompt the user to answer questions to supplement the postural assessment, such as, for example, age, weight, etc. Again, block302 is optional and is not required in accordance with various embodiments.
• 2. Providing Form
• With reference again toFIG. 3, inblock304, various embodiments may include demonstrating proper form for an exercise and prompting the user to perform the exercise. For example, after or in addition to the initial postural assessment, the system100 (such as with computer102) may cause thedisplay136 to present a virtual trainer demonstrating an exercise to instruct the user on proper form and/or may present a depiction and/or an actual video of a real person demonstrating proper form for an exercise.System100 may then prompt the user to begin performing the exercise.
• With reference toFIG. 3, inblock306, various embodiments may include monitoring form of a user performing the exercise. As seen inFIG. 6,system100, such as throughcomputer102, may cause thedisplay136 to present avirtual avatar602 of the user. Thevirtual avatar602 may move in synchronism with theuser124. Also, thedisplay136 may present video of the actual user, rather thanavatar602.System100 may process one or more frames in the video to determine at least some of thesensory locations402, or may receive data from sensors worn on-body by the user. As shown inFIG. 6,sensory locations402 may be displayed on the virtual avatar.
• For proper form during many exercise routines, a user may proceed through multiple positions during a repetition of an exercise. Certain aspects disclosed herein relate to defining one or more measurement positions and/or desired locations for one or moresensory locations402. For example, a measurement position may refer to a particular relationship between various body parts during a repetition. For example, a measurement position may indicate a desired location for a user's body part (e.g., desired location of user's left elbow) and may indicate a desired relationship between multiple body parts (e.g., angle between a user's torso and thigh). For a movement or series of movements (such as an exercise routine),system100 may define one or more measurement positions and/or desired locations for one or more of thesensory locations402 for a measurement position. In various implementations, each repetition of an exercise can be broken down into one or more measurement positions.
• System100, such as throughcomputer102, may process video or sensor data of a user performing an exercise to determine when a user's body has reached a measurement position. For each measurement position,system100 may compare the measured sensory locations to desired sensory locations to monitor the user's form while performing the exercise. For example,frame1 ofFIG. 6 may correspond to a first measurement position andframe2 may correspond to a second measurement position.System100 may determine a distance betweensensory locations402cand402dat each measurement position. Other relationships between sensory locations may be specified (e.g., certain angle, certain position, etc.)
• With reference again toFIG. 3, inblock308, various embodiments may include calculating an energy expenditure estimate for the user. Calculations may be based on a type of the exercise and/or on the form of the user. The energy expenditure estimate may be, or comprise, for example, an estimate of calories burned by the user. In certain embodiments, energy expenditure calculations comprise determinations relating to: effort, oxygen consumed, and/or oxygen kinetics of the user. During a workout session or upon its completion, thesystem100 may inform the user of energy expended. In one embodiment,system100 may provide an indication of a quantity of calories they have burned. To provide a more accurate calories burned estimate,system100 may account for a user's form while performing an exercise as well as the type of exercise that was performed. Further embodiments may utilize user attributes to more accurately identify a number of calories burned by a user. Example user attributes may be height, weight, age, etc. One or more sensors may determine the user attributes, or the user may input the user attributes via an interface to a computer, such ascomputer102.
• System100 may use information fromsensory locations402 detected at measurement positions of an exercise in combination with one or more known values to obtain a more accurate determination of calories burned. In one embodiment, a known value may comprise or be part of a Metabolic Equivalent of Task (MET) table. A MET table, for example, may be defined for a particular exercise (e.g., squat, lunge, etc.) and used to determine how many calories a user burned during a workout.System100 may store or have access to multiple MET tables corresponding to different exercises (e.g., squat, lunge, jumping rope, push up, running, etc.).System100 may process data from the video and/or sensors to determine a number of repetitions of an exercise that a user has performed or duration of an exercise, and may estimate a number of calories burned by the user based on the repetitions and/or duration information and the one or more known values, such as may be obtained from MET tables.
• MET tables, however, are statistical averages and are not as accurate as they could be. Thus, conventional calorie measurement systems that rely on MET tables merely provide a user with a rough estimate of how many calories they burned during a workout. Although embodiments of this disclosure may utilize one or more values from a MET table, aspects of this disclosure are not limited by the deficiencies of prior measurements systems. For example, in one embodiment the user's form may be accounted for.System100 may apply a scaling factor to a calories burned estimate based on detected sensory location information. The scaling factor may reflect how well a user has performed an exercise and in certain embodiments may consider attributes of the user. For example, the scaling factor may be a function of one or more of the sensory location information, a duration during which the user performed an exercise, information reported by the user (e.g., age, weight), a user's heart rate taken by a heart rate monitor, a pressure measurement, and/or other data. A pressure measurement may be obtained frompressure sensor140 located in a shoe, for example, to determine how much force a user exerts during movement. For example, a user may be holding a weight in each hand and thepressure sensor140 may monitor pressure at the shoe. Thepressure sensor140 may also indicate how quickly a user changes direction (e.g., how hard a user made a cut) or how much power was exerted when jumping.
• To determine the scaling factor,system100 may monitor for relationships between one or more body parts at one or more measurement positions during a repetition of an exercise. Modifications to these relationships may make an exercise easier or harder to perform. The scaling factor may consider factors indicative of whether a user is making the exercise more or less difficult to complete, and may adjust a calories burned estimate accordingly. In a squat, for example, relationships may be defined for a first angle between a user's torso and thighs, and a second angle between a user's thighs and shin while performing the squat.System100 may process sensory location information to measure the first and second angle of the user over time for comparison with the desired first and second angle.
• In an example, with reference toFIGS. 7A-B, avirtual avatar702 of a user is displayed performing a squat.Virtual avatar702 is depicted as a stick figure, and proper technique for an exercise is shown as ashaded region704. At the lowest part of the squat (for example, as shown inFIG. 7A), the desired form may specify a relationship between a user's thigh and shin, between a user's back and arms, and/or any other two parts or locations the user. In one embodiment, the desired form may specify a first predetermined angle between a location or part. For example, a user's upper leg and lower leg, and/or a second predetermined angle between a user's back and arms.System100 may process the sensory location information to compare the user's form to the desired form. For example,system100 may process the sensory location information to determine an angle between the user's thigh and shin, and an angle between the user's back and arms when performing a squat.
• System100 may define thresholds for the relationships between various body parts for adjusting the scaling factor. The thresholds may permit the user's form to differ by a certain amount from the desired form. For a preferred threshold,system100 may determine that the user has good form that does not require any adjustment of the scaling factor (e.g., less than a 5% difference between angle between the user's upper leg and lower leg and desired angle). For an acceptable threshold, thesystem100 may nominally adjust the scaling factor upward or downward to reflect increased or reduced effort by the user (e.g., 5-15% difference between angle between the user's upper leg and lower leg and desired angle). For an unacceptable threshold, thesystem100 may determine that the user's form has reduced the amount of effort to perform the exercise and may downwardly adjust the scaling factor (e.g., greater than a 15% difference between angle between the user's upper leg and lower leg and desired angle).
• System100 may also adjust the scaling factor based on omissions or additions a user makes when performing an exercise. For example, a user may not be doing an arm movement in an exercise that requires movement of both arms and legs. Also, if the user is performing an additional movement beyond what is specified for an exercise, thesystem100 may adjust the scaling factor to increase the calorie estimate.
• Upon determining the scaling factor, thesystem100 may determine an amount of calories burned as a function of the scaling factor(s) and the calorie estimate. The function may be a multiplication of the calorie estimate by the scaling factor, or via other relationships. For example, the scaling factor may be adjustments to a number of variables in a mathematical equation for adjusting calories burned by one or more of multiplication, addition, and subtraction. In further embodiments,system100 may cease determinations relating to caloric expenditure if the user deviates from a threshold. For example, a user may be interrupted during a workout routine and either forget or be too distracted to “pause” the determination, thus, certain embodiments may cease determining caloric expenditure upon detecting that a user is not performing an exercise. Further embodiments may cease or otherwise alter determinations of caloric expenditure if one or more variation thresholds are exceeded, such as for example, if a user is over-extending or under-extending a body region or part. In certain embodiments, if a user's movements are prone to cause injury, measurements and/or determinations relating to caloric expenditure may be stopped. In one implementation,system100 may provide cues and/or instructions to correct the user's deficiencies or incorrect movements.
• The following provides an example equation for calculating an amount of calories burned by a user during a workout.
• 
  Calories burned=BMR*(Activity modifier)*(Completeness modifier).  Equation (1):
• In equation (1), BMR is an acronym for Basal Metabolic Rate. Thesystem100 may calculate the BMR using the Mifflin-St. Jeor Equation, BMR=(10*w)+(6.25*h)−(5.0*a)+(5 for men, −161 for women), where “*” is the multiplication symbol, “w”=weight in kilograms, “h”=height in centimeters, “a”=age in years. Thesystem100 may also use the Harris-Benedict equation instead of or, in addition to, the Mifflin-St. Jeor Equation.
• The activity modifier may be an adjustment corresponding to a type of exercise being performed by a user. The activity modifier may be larger for more strenuous exercises, and smaller for less strenuous.System100 may store a file containing activity modifiers, where each activity modifier may have a value for a particular exercise type. Two or more exercises may have activity modifiers with a same value, or certain exercise may have a unique value for the activity modifier. The activity modifier may have a default value. In one example embodiment, the default value may be 0.1. In a second embodiment, the default value may be 1.0. The default value may be any value, including 0.0.System100 may update the default value to correspond to the activity modifier for an exercise currently being performed by the user. Over a duration of the workout,system100 may use different ones of the activity modifiers to calculate calories burned using equation (1) corresponding to different exercises the user is prompted to perform. One or more factors may contribute to the activity modifier and/or adjustment of the modifier. Examples include, but are not limited to: pace, type of exercise, duration, and combinations thereof. Further, activity modifiers and/or variation of activity modifiers may be determined from predetermined values (such as a value assigned to an exercise or movement that a user is prompted to perform), the user's performance, information from a MET table on a particular exercise, and combinations thereof.
• The completeness modifier may be used for adjusting the BMR based on how well a user's form corresponds to a desired form when performing an exercise. In an example, the completeness modifier may indicate what percentage of full movement was achieved for each repetition when performing an exercise (e.g., determine a percentage of a measured angle between the user's torso and thighs for a particular repetition of an exercise relative to a desired angle), or may be an average of the percentage of full movement for a predetermined number of repetitions (e.g., last three exercises, last five exercises, all exercises, etc.). The completeness modifier may have a default value. In one example embodiment, the default value may be 0.1. In a second embodiment, the default value may be 1.0. The default value may be any value, including 0.0.System100 may update the completeness modifier over time based on how well the user's form conforms to a desired form. One or more factors may contribute to the activity modifier and/or adjustment of the modifier. Examples include, but are not limited to: pace, type of exercise, duration, and combinations thereof. Further, activity modifiers and/or variation of activity modifiers may be determined from predetermined values (such as a value assigned to an exercise or movement that a user is prompted to perform), the user's performance, and combinations thereof.
• Equation (2), provided below, may be utilized in further embodiments.
• 
  Calories burned=BMR*(Activity modifier)*(Completeness modifier)*(Multiply Modifier)+(Addition Modifier)  Equation (2):
• Values for BMR, Activity Modifier, and/or Completeness Modifier of Equation (2) may be determined in accordance with one or more embodiments described above in reference to Equation (1). In one embodiment, the value of the Multiply Modifier may be defined for each type of exercise. In one example embodiment, the default value may be 0.1. In a second embodiment, the default value may be 1.0. The default value may be any value, including 0.0.System100 may update the Multiply Modifier during a workout to correspond to a type of exercise the user is prompted to perform. In certain embodiments, the Activity Modifier may be obtained (either partially or entirely) from empirical data.
• In certain embodiments, the value of the Addition Modifier may be defined for each type of exercise. In one example embodiment, the default value may be 0.1. In a second embodiment, the default value may be 1.0. The default value may be any value, including 0.0.System100 may update the Addition Modifier during a workout to correspond to a type of exercise the user is prompted to perform. In certain embodiments, the Activity Modifier may be obtained (either partially or entirely) from empirical data.
• System100 may calculate the calories burned over a duration of a workout, which may incorporate the utilization of equations (1) or (2).System100 may cause thedisplay136 to display a running total of calories burned. In certain embodiments, the total may be determined for one or more completed repetitions and one or more completed sets of each exercise.System100 may also calculate and cause display of calories burned by type of exercise performed. Other information such as, for example, peak/minimum/average calorie burning rate by workout, by repetition, by set, or by exercise type may also be calculated and displayed.System100 may periodically determine an amount of calories burned by the user while exercising using equation (1).System100 may indicate a current amount of calories burned that is continually updated over a workout (e.g., a running total), or may update the calories burned amount at predetermined times (e.g., user completes a set of a first type of exercise and begins a set of second type of exercise, at the end of the workout session, etc.).System100 may also inform the user how many calories were burned during each repetition as well as in each set of an exercise.
• One or more of the inputs and/or variables used in the determination of caloric expenditure (such as with equation (1)) may remain the same regardless of the type of exercise being performed by the user, yet others may vary. For example, the BMR may be the same over the entire workout as a user's weight, height, and age do not change appreciably over the course of a workout. Further, one or more of the Activity modifier, Completeness modifier, Multiply Modifier, and Addition Modifier may vary over the workout. The values (and/or variation) of the values may depend on the type exercise currently being performed by the user.
• The Completeness modifier may vary from repetition to repetition. As noted above,system100 may generate the Completeness modifier based on monitoring a user's form while they perform an exercise. Generally, an exercise includes a sequence of motions to perform one repetition, and a user typically performs a set that includes two or more repetitions. A user's form may vary from repetition to repetition, and so may the Completeness modifier.
• System100 may determine calories burned using equation (1) based on a Completeness modifier that varies from repetition to repetition, or based on a filtered version of the Completeness modifier. To filter the Completeness modifier, thesystem100 may, for example, determine a Completeness modifier for one or more repetitions, may average some or all of the Completeness modifiers, and may use the average in equation (1).
• Also,system100 may generate the Completeness modifier as a weighted average, where Completeness modifiers of some repetitions may be given greater weight than others. For example,system100 may apply a decaying function where more recent Completeness modifiers are weighted more heavily than less recent when generating an average.
• System100 may also allow a user to make desired movements, and calculate an amount of calories burned for such movement. In one embodiment, all detected movements may be utilized in calculations. Yet in other embodiments, only certain (e.g., system supported and/or those prompted to be performed) movements may be considered.System100 may process data fromimage capturing device126 and/or from various sensors to attempt to classify a user's movement. For example,system100 may compare the user's movement to other known movements for which a MET table has been defined. If a user's movement corresponds to a known movement for which a MET table has been defined, thensystem100 may use the identified MET table for calculating an amount of calories burned.
• If the user's movement does not match an exercise defined by a MET table, thesystem100 may identify one or more exercises that include movements similar to the movement being performed by the user. For example,system100 may determine that the user's lower body moves similar to a squat and upper body moves similar to a pushup.System100 may calculate the number of calories the user would burn using the identified MET tables as if the users were doing a squat, and as if they were doing a pushup, as approximations for the amount of calories burned by the user. In further embodiments, a new entry may be created. In this regard, certain embodiments may permit the entry and later identification of new movements and/or exercises. In certain embodiments, the user may provide inputs regarding an approximate caloric expenditure for an unidentified movement/exercise. Yet in other embodiments,system100 may calculate caloric expenditure, such as from one or more sensors as discussed herein. In still yet further embodiments,system100 may utilize one or more sensor readings as well as an input from a user (and/or third-party) in determining attributes, such as caloric expenditure, for previously unknown movements or exercises.
• Examples of estimating caloric expenditure without MET tables, may include but are not limited to, determining changes in potential energy. Examples of using changes in potential energy are provided in the next section.
• System100 may be configured to transmit calories burned estimates to a social networking website. The users may be ranked based on their total number of calories burned for a desired time interval (e.g., rank by day, week, month, year, etc.). With reference again toFIG. 3, the method may end or may return to any of the preceding blocks.
• i. Energy Expenditure Estimate Based on Changes in Potential Energy
• System100 may also calculate an energy expenditure estimate of a user for physical activities not defined by a MET table. For example,system100 may calculate an amount of calories burned by a user performing any desired combination of movements. During a workout, a user may be exposed to their own body weight and gravity. A location of a user's center of mass, or of a center of mass of a particular body part, may be utilized in estimating an amount of calories burned by the user performing an athletic activity.
• FIG. 8 illustrates an example flow diagram of a method for calculating an energy expenditure estimate for a user while performing an athletic activity based on monitoring changes in potential energy, in accordance with example embodiments. The method may be implemented by a computer, such as, for example,computer102,device138,140 and/or142 as well as other apparatuses. The blocks shown inFIG. 8 may be rearranged, some blocks may be removed, additional blocks may be added, each block may be repeated one or more times, and the flow diagram may be repeated one or more times. The flow diagram may begin atblock802.
• Inblock802, various embodiments may involve processing data captured of a user performing an athletic activity over a time interval. In an example,system100 may prompt a user to perform ten repetitions of a lunge and may process data captured of the user performing the lunge. The data may be video captured by thecamera126 or may be captured by theinfrared transceiver128, and/or by theother device sensors138,140, and142.
• Inblock804, various embodiments may involve determining a location of a center of mass of a body part, body region, or of an entire body of the user at a first time instant and at a second time instant within the time interval. Yet in other embodiments, a center of movement may be utilized. For simplicity purposes, however, a center of mass will be discussed. In an example,system100 may instruct the user to place sensors at locations of corresponding to a center of mass for one or more body parts of the user. With reference toFIG. 9, one or more of center of mass locations may be atexample locations904A-D and906, or at other locations on the user's body. Any number of locations may be monitored. At least one sensor may wirelessly transmit sensor data indicating a time and a location of the sensor (or location of a body part as detected by the sensor). A location may be coordinates in a coordinate system (e.g., Cartesian coordinate system) and may be associated with a time stamp indicating when the sensor was at a particular coordinate. In certain embodiments,system100 may process the sensor data to periodically determinelocations904A-D and906. For example,system100 may receive sensor data, such as fromdevice sensors138,140 and/or142. Computer102 (or another component of system100) may process data as part of determining locations (such aslocations904A-D and906). In one embodiment, data may be processed on a routine ongoing-basis, such as four times per second. In another example, computer102 (or another component of system100) may process data fromimage capturing device126 to determinelocations904A-D and/or906.
• Inblock806, various embodiments may involve identifying a change in the location of the center of mass from the first time instant to a second time instant. As discussed above,system100 may determinelocations904A-D and906 at one time and at a subsequent time. For example and with reference toFIGS. 10A-B, a user is shown performing a lunge.FIG. 10A corresponds to a first time instant andFIG. 10B corresponds to a second time instant. InFIG. 10A, alocation906 of a user's center of mass is at a height “h1” (designated by908A) off of the ground. InFIG. 10B, alocation906 of a user's center of mass is at a height “h2” (designated by908A) off of the ground. One or more components ofsystem100 may determine a difference between height “h1” and “h2” to determine a change in alocation906 of the center of mass.System100 may also calculate changes tolocations904A-D of centers of mass for other body parts, or changes to other locations of body parts or body regions of the user.System100 may also process video of a user taken from different angles, as shown inFIG. 11, to determinelocations904A-D and906. For example,system100 may determine height “h1” forlocation906 in a perspective view and height “h2” forlocation906 in a front view of the user.System100 may average the different height measurements, or may use one or the other.
• With reference again toFIG. 8, inblock808, various embodiments may calculate an energy expenditure estimate for the user due to the change. In an example, the physics concept of potential energy may be used to estimate the amount of work done by the user, and to calculate calories burned based on work.
• In an example, one or more components ofsystem100 may determine changes of alocation906 from one time instant to another to determine an amount of work performed by the user. Potential Energy (PE)=m*g*h, where m=mass of the user (or body part), g=the acceleration due to gravity, and h=height above ground. Work (W)=−ΔPE, where Δ is represents a change in potential energy. Substituting m*g*h, Work (W)=−m*g*Δh. Based on the above example inFIGS. 10A-B, W=−m*g*(h1−h2).System100 may determine an amount of calories burned as a function of work multiplied by physiology of human efficiency.System100 may determine the amount of calories burned based on the amount of work and a physiology of human efficiency (PHE) scaling factor. Thesystem100 may determine the PHE scaling factor as a function of one or more of the user's heart rate, pressure sensor data, and other information input by the user (e.g., age, weight, etc.)
• System100 may keep and/or transmit a running total of calories burned between subsequent time instants and inform the user of a total amount of calories burned up to that point in an exercise session. For example,system100 may determine a height h oflocation906 at a certain frequency (e.g., 2 times per second), and may calculate calories burned based on a difference in calories burned between each determination of height h. Thesystem100 may also track a total number of calories burned over a predetermined time range covering one or more workouts. A time range may include a week, month, year, cumulative time since a user began working out, or other defined metrics. One or metrics may comprise default values, predefined values, user-selectable values, and/or user-defined values. For example,system100 may inform the user of how many calories they have burned during a specified time period, such as a day, week, month, and/or year.System100 may also maintain data on average number of calories burned per workout, average number of calories burned based on a type of workout, a greatest number of calories burned during a single workout or during a predetermined time interval (e.g., month where highest amount of calories were burned), or other types of data.
• In another example,system100 may determine calories burned by movement of a particular body part or by a collection of body parts. For instance, a user may desire to know how many calories were burned by movement of their right leg. Using the above relationship between work and potential energy, and with reference again toFIG. 9,system100 may monitor changes in thelocation904A of the center of mass of the user's right leg (e.g.,height908B) from one time instant to a different time instant to calculate work.System100 may estimate the mass of the user's right leg based on the user's weight and proportions.System100 may then determine an amount of calories burned as a function of work multiplied by physiology of human efficiency, as described above. During an exercise session,system100 may display, such as throughdisplay136, a running total of calories burned attributable to movement of the user's right leg.System100 may similarly determine calories burned based onlocations904B-D for the other limbs of the user. During an exercise session,system100 may display a running total of calories burned by a user's entire body, as well by each limb.
• System100 may also permit a user to review an exercise session to determine how many calories were burned at certain times. For example, an exercise may involve performing repetitive motions (e.g., pushups).System100 may identify each repetition within a set (e.g., each pushup within a set of 10), as well as a number of calories burned during each repetition. Over a set, one or more components ofsystem100 may identify the repetition where the user burned a highest number of calories as well as a lowest number of calories. In further embodiments,system100 may estimate an average number of calories. These are merely exemplary statistics and those skilled in the art will readily appreciate that other analysis may be conducted without departing from the scope of this disclosure.
• If an exercise session involves different types of exercises,system100 may rank the exercise types based on the amount of calories burned by type. For example, an exercise session may involve3 different types of exercises (e.g., pushups, sit-ups, squats). After completing the exercise session,system100 may determine how many calories were burned by each exercise type (e.g., 10 calories for pushups, 13 calories for sit-ups, and 18 calories for squats), and rank the exercise types based on the number of calories burned (e.g., first squats, second sit-ups, third pushups). In further embodiments, energy expenditure (e.g., a quantity of calories burned) may be ranked as percentage over an ideal value or range for an exercise or routine. For example, if perfectly performing an exercise would burn about 100 calories, a first user who burned 90 calories may be assigned a better ranking than second user who only burned 85 for the same exercise. The users could have different ideal values or ranges, thus the determinations may utilize the percentage of the detected and/or estimated values as a percentage for that user's ideal value. In further embodiments, a user who is closer to 100% of their ideal value may be ranked higher than users who have over 100% of the ideal quantity of calories burned. In this regard, a user who expends more energy than estimated or calculated for an activity (e.g., exercise) may indicate improper movements, inefficiency, increased likelihood of injury, and/or combinations thereof. In certain implementations, the method ofFIG. 8 may then end, or may return to any of the preceding blocks and/or other processes.
• System100 may also determine calories expended from pre-recorded videos. For example, a user may upload video of a professional basketball player dunking a basketball tosystem100. One or more components ofsystem100 may process the video to determine locations of a center of mass of the player, or of particular body parts, at various points in time, and determine the amount of calories expended during the physical activity (e.g., by the player during the dunk) using the work-based calorie determination, described above.
CONCLUSION
• Providing an activity environment having one or more of the features described herein may provide a user with an immersive experience that will encourage and motivate the user to engage in athletic activities and improve his or her fitness. Users may further communicate through social communities and challenge one another to reach various levels of fitness, and to view their fitness level and activity.
• Aspects of the embodiments have been described in terms of illustrative embodiments thereof. Numerous other embodiments, modifications and variations within the scope and spirit of the appended claims will occur to persons of ordinary skill in the art from a review of this disclosure. For example, one of ordinary skill in the art will appreciate that the steps illustrated in the illustrative figures may be performed in other than the recited order, and that one or more steps illustrated may be optional in accordance with aspects of the embodiments.

Claims (20)

What is claimed is:

1. A method comprising:

receiving, by a computing device and from one or more sensors, first activity data for a user;

determining, by the computing device and based on the first activity data, an initial postural assessment of the user;

receiving, from the one or more sensors, second activity data for the user, wherein the second activity data is collected by the one or more sensors during a performance of an exercise by the user;

calculating, by the computing device and based on the second activity data, a relationship between a first body part of the user and a second body part of the user;

determining, by the computing device and based on the relationship, an actual form of the user;

determining, by the computing device, an activity modifier for the user, wherein the activity modifier is determined in part based on a type of the exercise performed by the user;

determining, by the computing device, a completeness modifier for the user, wherein the completeness modifier is determined in part based on a comparison of the actual form of the user to a desired form; and

calculating, by the computing device, an energy expenditure estimate for the user based on the completeness modifier and the activity modifier.

2. The method ofclaim 1, wherein the activity modifier is further based on a duration of the exercise performed by the user.

3. The method ofclaim 1, wherein the determining the actual form of the user is based on processing of video of the user performing the exercise.

4. The method ofclaim 1, wherein the comparison of the actual form to the desired form comprises determining a percentage of a measured angle between the first body part and the second body part relative to a desired angle.

5. The method ofclaim 1, wherein the second activity data is collected by the one or more sensors during a performance of a first repetition of the exercise by the user, the method further comprising:

receiving, from the one or more sensors, third activity data for the user, wherein the third activity data is collected by the one or more sensors during a performance of a second repetition of the exercise by the user;

determining, by the computing device and based on the third activity data, an updated completeness modifier for the user; and

calculating, by the computing device, an updated energy expenditure estimate for the user based on the updated completeness modifier and the activity modifier.

6. The method ofclaim 5, wherein the calculating the updated completeness modifier comprises adjusting the completeness modifier based on the third activity data.

7. The method ofclaim 1, further comprising displaying the energy expenditure estimate on an output device.

8. The method ofclaim 1, wherein the calculating of the energy expenditure estimate is determined utilizing a metabolic equivalent of task (MET) table for the type of the exercise.

9. The method ofclaim 1, wherein the energy expenditure estimate is based on a basal metabolic rate of the user.

10. A non-transitory computer-readable medium comprising computer-executable instructions that, when executed, perform a method comprising:

receiving, by a computing device and from one or more sensors, first activity data for a user;

determining, by the computing device and based on the first activity data, an initial postural assessment of the user;

receiving, from the one or more sensors, second activity data for the user, wherein the second activity data is collected by the one or more sensors during a performance of an exercise by the user;

calculating, by the computing device and based on the second activity data, a relationship between a first body part of the user and a second body part of the user;

determining, by the computing device and based on the relationship, an actual form of the user;

determining, by the computing device, an activity modifier for the user, wherein the activity modifier is determined in part based on a type of the exercise performed by the user;

determining, by the computing device, a completeness modifier for the user, wherein the completeness modifier is determined in part based on a comparison of the actual form of the user to a desired form; and

calculating, by the computing device, an energy expenditure estimate for the user based on the completeness modifier and the activity modifier.

11. The non-transitory computer-readable medium ofclaim 10, wherein the activity modifier is further based on a duration of the exercise performed by the user.

12. The non-transitory computer-readable medium ofclaim 10, wherein the determining the actual form of the user is based on processing of video of the user performing the exercise.

13. The non-transitory computer-readable medium ofclaim 10, wherein the comparison of the actual form to the desired form comprises determining a percentage of a measured angle between the first body part and the second body part relative to a desired angle.

14. The non-transitory computer-readable medium ofclaim 10, wherein the second activity data is collected by the one or more sensors during a performance of a first repetition of the exercise by the user, the method further comprising:

receiving, from the one or more sensors, third activity data for the user, wherein the third activity data is collected by the one or more sensors during a performance of a second repetition of the exercise by the user;

determining, by the computing device and based on the third activity data, an updated completeness modifier for the user; and

calculating, by the computing device, an updated energy expenditure estimate for the user based on the updated completeness modifier and the activity modifier.

15. An apparatus configured to be worn on a body of a user comprising:

one or more processors; and

memory storing instructions that, when executed, cause the apparatus to:

receive, from one or more sensors, first activity data for a user;

determine, based on the first activity data, an initial postural assessment of the user;

receive, from the one or more sensors, second activity data for the user, wherein the second activity data is collected by the one or more sensors during a performance of an exercise by the user;

calculate, based on the second activity data, a relationship between a first body part of the user and a second body part of the user;

determine, based on the relationship, an actual form of the user;

determine an activity modifier for the user, wherein the activity modifier is determined in part based on a type of the exercise performed by the user;

determine a completeness modifier for the user, wherein the completeness modifier is determined in part based on a comparison of the actual form of the user to a desired form; and

calculate an energy expenditure estimate for the user based on the completeness modifier and the activity modifier.

16. The apparatus ofclaim 15, wherein the activity modifier is further based on a duration of the exercise performed by the user.

17. The apparatus ofclaim 15, wherein the comparison of the actual form to the desired form comprises determining a percentage of a measured angle between the first body part and the second body part relative to a desired angle.

18. The apparatus ofclaim 15, wherein the second activity data is collected by the one or more sensors during a performance of a first repetition of the exercise by the user, wherein the instructions, when executed, cause the apparatus to:

receive, from the one or more sensors, third activity data for the user, wherein the third activity data is collected by the one or more sensors during a performance of a second repetition of the exercise by the user;

determine, based on the third activity data, an updated completeness modifier for the user; and

calculate an updated energy expenditure estimate for the user based on the updated completeness modifier and the activity modifier.

19. The apparatus ofclaim 18, wherein the calculating the updated completeness modifier comprises adjusting the completeness modifier based on the third activity data.

20. The apparatus ofclaim 15, wherein the energy expenditure estimate is based on a basal metabolic rate of the user.

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