Patent Description:
Some wearable computers (e.g., smartwatch, fitness band) include a fitness application that uses a digital pedometer to track a user's daily movements and provide customized notifications related to progress and workout results, such as distance traveled and calories burned. Some fitness applications also monitor the user's heart rate, which can be used to calculate calories burned. A typical digital pedometer relies on accelerometer data from an accelerometer to determine when a step is taken. If the wearable computer is worn on the wrist, accelerations due to arm swing may cause inaccurate step counts, resulting in inaccurate distance traveled measurements. The heart rate measurement, however, is often accurate due to the device being worn on the user's wrist where the user's heartbeat can be accurately measured.

When a user works out in a gym, they will often use a fitness machine that includes a processor that monitors the workout and generates fitness metrics summarizing the workout. For example, a treadmill may display to the user the total distance traveled, elapsed time and total calories burned during the workout. The total distance travelled is typically accurate because it is based on rotation of the treadmill motor shaft rather than accelerometer data, but the total calories burned is often an estimate based on a model that does not include the actual heart rate of the user.

Embodiments are disclosed for a wearable computer with fitness machine connectivity for improved activity monitoring.

In an embodiment, a method comprises: establishing, by a processor of a wearable computer, a wireless communication connection with a fitness machine;obtaining, by the processor, machine data from the fitness machine, the machine data specifying a type of the fitness machine and comprising fitness metrics;determining, by the processor, a workout session according to the machine data;initiating the workout session on the wearable computer;during the workout session:obtaining, by the processor, a metabolic equivalent of tasks based at least in part on the machine data comprising the type of fitness machine and the fitness metrics;obtaining, from a sensor of the wearable computer, physiological data of a user of the fitness machine;determining, by the processor, fitness data for the user based at least in part on a combination of the physiological data and the metabolic equivalent of tasks, wherein the fitness data includes calories burned by the user.

Other embodiments can include an apparatus, computing device and non-transitory, computer-readable storage medium.

The details of one or more implementations of the subject matter are set forth in the accompanying drawings and the description below. Other features, aspects and advantages of the subject matter will become apparent from the description, the drawings and the claims.

<CIT> discloses to wearable devices and, more particularly, to wearable devices that support to monitor user exercise routines. The automatic adjustment of the calorie calculation in the wearable device taking into account the currently, wirelessly connected fitness machine in use is not disclosed in this document.

<FIG> illustrates an operating environment <NUM> for an improved activity monitoring system that includes wearable computer <NUM> wirelessly connected to fitness machine <NUM>, according to an embodiment. User <NUM> is wearing computer <NUM> on her wrist while she runs on fitness machine <NUM>, which in this example is a treadmill. Other examples of fitness machines include but are not limited to: cross-trainers (elliptical trainers), step/stair climbers, indoor bikes, indoor rowing machines and skiing machines. Wearable computer <NUM> can be a smart watch, fitness band, chest band, headband, earbud, activity/fitness tracker, headset, smart glasses, or any other wearable computer capable of communicating with fitness machine <NUM> and calculating a fitness metric. Wearable computer <NUM> establishes a bidirectional, wireless communication session <NUM> with a processor in fitness machine <NUM> using a wireless communication protocol. In an embodiment, session <NUM> can be a Bluetooth session or near field communication (NFC) session, which can be established using a "pairing" process, as described in reference to <FIG> and <FIG>. In an embodiment, fitness machine <NUM> is authenticated and the user's consent to share data is confirmed before bidirectional data sharing is allowed between wearable computer <NUM> and fitness machine <NUM>.

Wearable computer <NUM> includes a processor and memory that includes instructions for running a fitness application that can be executed by the processor. The fitness application runs on wearable computer <NUM> during the user's workout session on fitness machine <NUM>. A processor in fitness machine <NUM> monitors the workout session and computes various data (hereinafter referred to as "machine data") related to the workout session, including but not limited to: total energy used, total distance run, elapsed time, instantaneous speed, average speed, inclination and positive elevation gain. The machine data is transferred over link <NUM> to computer <NUM> where it is used by the fitness application, together with data known to computer <NUM> (hereinafter referred to as "wearable computer data"), to calculate one or more fitness metrics, such as calories burned. As described in further detail below, wearable computer <NUM> can include a heart rate monitor for determining the user's heart rate, which can be combined with machine data to determine calories burned.

During the workout session, one or more fitness metrics calculated by wearable computer <NUM> are transferred back to fitness machine <NUM> where the metrics are displayed on a monitor of fitness machine <NUM>. During the workout session and/or after the workout session ends, a workout summary including the fitness metrics is transferred to computer <NUM>. The user can view the details of the workout session at any time on fitness machine <NUM>, or on wearable computer <NUM>. In an embodiment, wearable computer <NUM> displays an in-session view with metrics received from fitness machine <NUM>, as well as heart rate and calories (total/active) computed by wearable computer <NUM>. The user can use computer <NUM> to transfer the workout summary to another device by syncing directly with the other device or indirectly through a network (e.g., the Internet). In an embodiment, the workout session summary can be shared with other user devices in the gym through a wireless local area network (WLAN) or a multi-peer ad hoc mesh network. In this manner, users can compare their fitness metrics with friends, trainers and other individuals for a particular fitness machine while in the gym. In an embodiment, and with the consent of users, anonymous summary data can be processed by a server computer to provide workout statistics for a particular fitness machine over a large sample set. Such statistics can be used by gym operators, fitness machine manufacturers and other interested entities to determine what machines are most popular, the average time spent on a machine and other useful information.

In addition to calculating fitness metrics, wearable computer <NUM> can use machine data to calibrate a digital pedometer running on wearable computer <NUM>. For example, the total distance traveled during a workout session computed by fitness machine <NUM> can be used with an estimated distance traveled during the workout session based on pedometer step count to determine a calibration factor (e.g., a ratio of the two numbers). The calibration factor can be used to scale the estimated distance traveled calculated by computer <NUM> to correct out the error in the estimate.

<FIG> is a block diagram of an example activity monitoring system for improved activity monitoring using wearable computer data combined with fitness machine data, according to an embodiment. System <NUM> can be implemented in wearable computer <NUM>, such as a smartwatch or fitness band. System <NUM> includes wireless interface <NUM>, motion sensor(s) <NUM> (e.g., accelerometers, gyros, magnetometer), fitness application <NUM>, digital pedometer <NUM>, activity data <NUM>, physiological sensor(s) <NUM> and pedometer data <NUM>. System <NUM> can be wired or wirelessly coupled to network <NUM> through WLAN access point <NUM> (e.g., a Wi-Fi router) to transfer data and/or sync with activity data <NUM> through network server computers <NUM>.

In an embodiment, wireless interface <NUM> includes a wireless transceiver and other hardware (e.g., an antenna) and software (e.g., a software communication stack) for establishing, maintaining and ending a wireless communication session with fitness machine <NUM>, as described in reference to <FIG>. In an embodiment, wireless interface <NUM> can also be configured to establish, maintain and end a wireless communication session with WLAN access point <NUM>, and/or other devices <NUM> through a multi-peer ad hoc mesh network.

In an embodiment, motion sensors, such as accelerometers provide acceleration data that can be used by digital pedometer <NUM> to determine step count and calculate an estimated distance traveled based on the step count and a stride length of the user. The stride length can be based on average stride length for the user given the gender and height of the user, or it can be determined automatically based on sensor data. Pedometer data <NUM> including step count and distance traveled can be stored on wearable computer <NUM> (e.g., stored in flash memory).

Fitness application <NUM> can be a software program that is executed by one or more processors of wearable computer <NUM>. Fitness application <NUM> use pedometer data <NUM> to track a user's daily movements and provide customize notifications related to progress and workout results, such as distance traveled and calories burned. Fitness application <NUM> also monitors the user's heart rate and other physiology of the user, which can be calculated from sensor data provided by physiological sensor(s) <NUM>. Some examples of physiological sensors <NUM> include but are not limited to: heart rate (pulse) sensors, blood pressure sensors, skin temperature and/or conductance response sensors and respiratory rate sensors. In an embodiment, physiological sensor(s) <NUM> include a heart rate sensor comprising a number of light emitting diodes (LEDs) paired with photodiodes that can sense light. The LEDs emit light toward a user's body part (e.g., the user's wrist), and the photodiodes measure the reflected light. The difference between the sourced and reflected light is the amount of light absorbed by the user's body. Accordingly, the user's heart beat modulates the reflected light, which can be processed to determine the user's heart rate. The measured heart rate can be averaged over time to determine an average heart rate.

A heart rate monitor (HRM) does not measure caloric expenditure. Rather, the HRM estimates caloric expenditure during steady-state cardiovascular exercise using a relationship between heart rate and oxygen uptake (VO2). A commonly accepted method for measuring the calories burned for a particular activity is to measure oxygen uptake (VO2). During steady-state aerobic exercise, oxygen is utilized at a relatively consistent rate depending on the intensity of the exercise. There is an observable and reproducible relationship between heart rate and oxygen uptake. When workload intensity increases, heart rate increases and vice versa. If the user's resting heart rate, maximum heart rate, maximum oxygen uptake and weight are known, caloric expenditure can be estimated based on a percentage of their maximum heart rate or a percentage of their heart rate reserve.

The metabolic equivalent of tasks (MET) is the ratio of the rate of energy expended during a specific physical activity to the rate of energy expended at rest. By convention, the resting metabolic rate (RMR) is <NUM> O<NUM>·kg-<NUM>·min-<NUM>, and <NUM> MET is defined by Equation <NUM>: <MAT>.

Using Equation [<NUM>], a <NUM> MET activity expends <NUM> times the energy used by the body at rest. If a person does a <NUM> MET activity for <NUM> minutes she has done <NUM> x <NUM> = <NUM> MET-minutes of physical activity. Since the rate of energy expenditure is dependent on the intensity of the physical activity, it follows that the energy expenditure is also dependent on the type of fitness machine used in the workout session. For example, a vigorous jog on a treadmill may have a MET greater than <NUM> and a light workout on a stationary indoor bike may have a MET of <NUM> or less.

In an embodiment, a look-up table of MET values can be stored as activity data <NUM>. During a workout session, fitness machine <NUM> sends machine data includes the fitness machine type that can be used by fitness application <NUM> to identify the physical activity and select a suitable MET for the physical activity. For example, if the fitness machine type indicates a treadmill, then a MET that is suitable for jogging on a treadmill can be selected for calculation of calories expended C using Equation [<NUM>]: <MAT> where MET is the MET associated with a particular fitness activity and can be retrieved from, for example, a look-up table stored by wearable computer <NUM>.

Published MET values and values used by fitness machines for specific physical activities are often averages that are experimentally or statistically derived from a sample of people. The level of intensity at which the user performs a specific physical activity (e.g., walking pace, running speed) will deviate from the average MET values. To personalize caloric expenditure to the user, a more accurate model can be used on wearable computer <NUM> to calculate caloric expenditure that uses the user's own historical workout data on a particular machine to determine a MET that is personalized to the user. For example, the conventional conversion of <NUM> O<NUM>·kg-<NUM>·min-<NUM> can be adjusted based on the user's resting metabolic rate (RMR).

<FIG> is an example process flow <NUM> for connecting a wearable computer with a fitness machine, according to an embodiment. There are four use cases for connecting a wearable computer with a fitness machine: <NUM>) the user pairs first with the fitness machine, then starts their workout, <NUM>) the user starts their workout with the wearable computer and then pairs with the fitness machine, <NUM>) the user starts their workout with the fitness machine and then pairs with the wearable computer, and <NUM>) the user has simultaneous workouts on the wearable computer and the fitness machine. Each use case will be described in turn.

In the first use case, the user visits the gym and finds a fitness machine with a badge (e.g., an RFID tag) indicating the machine can be paired to a wearable computer, which in this example is a smartwatch strapped to the user's wrist. The user starts a new workout session (<NUM>) by placing their wearable computer near the badge to begin pairing. When the wearable computer is near the badge (e.g., less <NUM>) its proximity to the badge is detected using, for example, magnetic induction between loop antennas located in the wearable computer and the badge.

If it is the user's first time pairing with the fitness machine, the user is requested to consent to share data (<NUM>) with the fitness machine. The request for consent can be in the form of a GUI affordance presented on a display of the wearable computer. If the user has already consented (e.g., based on a previous connection with the fitness machine), the user will be requested to pair with the fitness machine. Since, in this first use case, the user is not in a current workout session, step <NUM> is not applicable. If the user agrees to pair, a pairing/authentication process begins (<NUM>). If an error occurs during the pairing/authentication the error is reported to the user (<NUM>). An error can be due to a connection failure and/or an authentication failure.

Since personal physiological data is being transferred to a public fitness machine, the wearable computer and fitness machine perform an authentication procedure before sharing of the user's personal fitness data is allowed. During the authentication process, and in an embodiment that uses public-private key encryption, the fitness machine generates and securely stores a public key-private key pair, which can be in the format of elliptical curve digital signature algorithm (ECDSA) or any other suitable digital signature algorithm. The fitness machine then calculates a message digest (e.g., a SHA256 message digest) using the private key and other data. The other data can be, for example, a random number, a connection confirmation value, local name data, etc. The fitness machine then uses the encoded public key and message digest to perform the authentication process. Upon successful authentication of the fitness machine, the wearable computer and fitness machine begin pairing.

After successful pairing, the user begins the physical workout on the fitness machine (<NUM>) by, for example, starting the machine (e.g., starting die treadmill). During the workout session, the wearable computer displays an affordance indicating that the wearable computer and fitness machine are paired and the workout session is active. During an active workout session all of the current metrics are displayed by die wearable computer. If the fitness machine is paused, the workout session on the wearable computer is also paused, and the wearable computer displays a GUI stating that the workout on the wearable computer cannot pause. If the pause is extended (<NUM>) (e.g., more than <NUM> minutes), the workout session ends (<NUM>) and a workout session summary is displayed to the user (<NUM>). If the wearable computer becomes disconnected from the fitness machine during the workout session, the wearable computer reports to the user that it has disconnected from the fitness machine. If die disconnect is extended (<NUM>) (e.g., more than <NUM> minutes), the workout session ends (<NUM>) and a workout session summary is displayed to the user (<NUM>). In an embodiment, a GUI affordance is displayed by the wearable computer that allows the user to disconnect and end the active workout session on the wearable computer without effecting the workout on the fitness machine.

In the second use case, the user is already in a workout session on their wearable computer. For example, the user may have entered the gym after an outdoor run with a workout session running on their wearable computer. In this second use case, the user starts a new workout session (<NUM>) by placing the wearable computer near the badge on the fitness machine. In an embodiment, if the user already consented to share data, the user is prompted with an affordance to end and save the current workout session and begin pairing with the fitness machine. If the user agrees, the current workout session is terminated and saved (<NUM>) and the pairing/authentication process begins (<NUM>). If the user does not agree, the pairing/authentication is not performed and the current workout session remains active on the wearable computer. In an embodiment, the current workout session is automatically terminated and saved by the wearable computer, and a pairing screen is displayed on the wearable computer.

After a successful pairing/authentication process, the user begins the physical workout (<NUM>). When the new workout session ends (<NUM>) (including by extended pause <NUM> or extended disconnect <NUM>), data from both the previous and current workout sessions are displayed in a workout session summary (<NUM>).

In an embodiment, if the user did not consent to share data, the user is prompted with a GUI affordance requesting the user's consent to share data (<NUM>), end and save their current workout session and begin the pairing/authentication process. If the user consents to share data, the current workout session is terminated and saved (<NUM>) and the pairing/authentication process begins (<NUM>). If the user does not consent to share data, the pairing/authentication process ends and the current workout session remains active on the wearable computer. In an embodiment, the current workout session is automatically terminated and saved by the wearable computer, and a pairing screen is displayed on the wearable computer.

In the third use case, the user starts a new workout session (<NUM>) on the fitness machine but not the wearable computer. During the workout session, the user notices the badge and places their wearable computer near the badge. If the user already consented to share data, the user is prompted to pair. If the user agrees to pair, the pairing/authentication process begins (<NUM>). If the pairing/authentication process is successful, the wearable computer and fitness machine are paired. The user can continue their physical workout on the fitness machine (<NUM>). The fitness data accrued by the user on the fitness machine is ingested into the wearable computer so that the user does not lose any data, even though they may have started the workout session on the wearable computer after they started the workout session on the fitness machine. When the workout session ends (<NUM>) (including by extended pause <NUM> or extended disconnect <NUM>), a summary of the workout session is displayed (<NUM>).

If the user did not previously consent to share data, the user is requested to consent (<NUM>). If the user consents, pairing begins (<NUM>). If the pairing/authentication process is successful, the wearable computer and fitness machine are paired. The user continues the physical workout on the fitness machine (<NUM>). When the workout session ends (<NUM>) (including by extended pause <NUM> or extended disconnect <NUM>) a summary of the workout session is displayed (<NUM>). If the user does not consent to share data, pairing/authentication is not performed and the user can continue with the physical workout on the fitness machine without the wearable computer running a workout session.

In the fourth use case, the user is simultaneously engaged in a fitness machine workout and a wearable computer workout. The user starts a new workout (<NUM>) by placing their wearable computer near a badge on the fitness machine. In an embodiment, if the user has already consented to share data, the user is prompted to end and save their current workout and begin pairing. If the user agrees, the current workout is terminated and saved (<NUM>) and pairing/authentication begins (<NUM>). If the user does not agree, the pairing/authentication process is not performed. In an embodiment, the current workout session is automatically terminated and saved by the wearable computer, and a pairing screen is displayed on the wearable computer. If the pairing/authentication process is successful, the wearable computer and fitness machine are paired. When the new workout session ends (<NUM>) (including by extended pause <NUM> or extended disconnect <NUM>), both the summary of the previously saved workout session and the new workout session are displayed (<NUM>).

If the user has not consented to share data, the user is requested to end and save the current workout session (<NUM>) and consent to sharing data (<NUM>), if the user agrees, the current workout session ends, a summary of the workout session is saved and pairing begins (<NUM>). If the pairing/authentication process is successful, the user begins the new workout (<NUM>). When the new workout session ends (<NUM>) (including by extended pause <NUM> or extended disconnect <NUM>), a summary of the saved workout session and the new workout session are displayed (<NUM>).

<FIG> is a swim lane diagram illustrating example connection establishment procedures using NFC, according to an embodiment. In the diagram there are three actors including user <NUM>, wearable computer <NUM> and fitness machine <NUM>. Each step in the diagram is indicated by a letter, starting with the letter "a" and ending with the letter "q".

The connection establishment procedures begin when user <NUM> signals to fitness machine <NUM> their intent to pair with fitness machine <NUM> (step "a") by placing the wearable computer near the badge on the fitness machine.

During a timed connecting interval TconnectionReady, fitness machine <NUM> is detected by wearable computer <NUM> (step "b"), wearable computer <NUM> sends a SessionlD (e.g., a unique number per pairing attempt) and out-of-band (OOB) secret data (unique per connection) to fitness machine <NUM> (step "c") and fitness machine <NUM> calculates an identify digital signature (step "d") using for example, ECDSA. In an embodiment, the OOB secret data can comply with Security Manager Specification of Bluetooth Core Specification, Volume <NUM>, Part H. Fitness machine <NUM> can include an NFC reader for reading the SessionID and OOB secret data.

During a timed discovery interval Tdiscovery, fitness machine <NUM> advertises a fitness machine service (FTMS) and the Session ID (step "e"). Wearable computer <NUM> discovers fitness machine <NUM> via the advertisement (step "f') and provides a public key and signature request (step "g").

Fitness machine <NUM> sends to wearable computer <NUM> the public key and a signature response (step "h"). Wearable computer <NUM> sends a consent request to user <NUM> (step "i"), user <NUM> grants the request (step "j").

During a timed pairing interval Tpair, wearable computer <NUM> sends an OOB pairing request (step "k'') to fitness machine <NUM> and fitness machine <NUM> sends an OOB pairing response to wearable computer <NUM> (step "<NUM>").

During a timed authentication interval TaccessoryAuth, wearable computer <NUM> sends an authentication challenge to fitness machine <NUM> (step "m") and receives an authentication response from fitness machine <NUM> (step "n").

Upon successful authentication, user <NUM> starts the workout (step "o"), machine data (e.g., fitness machine type, total energy used, elapsed time, total distance) is sent to wearable computer <NUM> (step "p") and fitness data (e.g., instantaneous and average heart rate, active and total calories) is sent from wearable computer <NUM> to fitness machine <NUM> (step "q"). The data is communicated using, for example, NFC or Bluetooth standard protocols (e.g., Bluetooth Core Specification version <NUM>, NFC Suite B version <NUM>).

<FIG> is a diagram illustrating an example state machine <NUM> implemented by a fitness machine processor for connecting and establishing a session with a wearable computer, according to an embodiment. Each state is indicated by a letter, starting from "a" and ending with "f".

The fitness machine starts in a discovery state <NUM> (state "a") where the fitness machine is idle and its NFC reader is ready to rea a user's tag. When a user intent to connect is detected ("tap"), state <NUM> transitions to connectable advertising state <NUM> (state "b") and the fitness machine advertises at a timed interval TconnectionAdv. Included in the advertising packet is the SessionID and FTMS. When a pairing request is received from a wearable computer, state <NUM> transitions to pairing state <NUM> (state "c"). In state <NUM>, the fitness machine responds to an identity verification request, authentication challenge and pairing request.

When pairing is complete, state <NUM> transitions to connected discoverable state <NUM> (state "d"), where the fitness machine is paired to the wearable computer. If the link is lost, connected discoverable state <NUM> transitions to a disconnected advertising state <NUM> (step "e"). In state <NUM>, the fitness machine is no longer able to communicate with the wearable computer and starts advertising as non-discoverable to facilitate reconnection. When a reconnect time Treconnect expires, disconnected advertising state <NUM> transitions to unpairing state <NUM> (step "f"). In state <NUM>, the fitness machine deletes its current pairing record.

If the fitness machine is in the connected discoverable state <NUM>, and the user initiates a disconnect, the connected discoverable <NUM> transitions to the unpairing state <NUM>. If the fitness machine is in the disconnected advertising state <NUM>, and the wearable computer initiates a reconnect, the disconnected advertising state <NUM> transitions to the disconnected discoverable state <NUM>. If the fitness machine is in the pairing state <NUM>, and a pairing time Tpair expires, the pairing state <NUM> transitions to the discoverable state <NUM>. If the fitness machine is in the connectable advertising state <NUM>, and a discovery time Tdiscovery expires, the connectable advertising state <NUM> transitions to the discoverable state <NUM>.

In an embodiment, the user may determine how pairing will operate on their wearable computer. The user can select various pairing options using one or more GUI affordances or hardware input mechanisms. For example, a switch can allows the user to turn auto pairing on and off. Auto pairing is where the user does not have to say yes to pairing if they have accepted pairing with a fitness machine in the past. Another switch allows the user to select automatic pairing to be always turned on or turned on only when the user has launched the fitness application on the wearable computer. If automatic pairing is only allowed when the workout application is launched, the user will have to launch the workout application to pair with a fitness machine. In an embodiment, if the wearable computer determines that the user has completed at least one workout session on the wearable computer, then automatic pairing remains turned on regardless of whether or not the fitness application is launched. If the user has not completed a workout session, the user will need to launch the fitness application to turn on automatic pairing.

In an embodiment, a GUI affordance or hardware input mechanism can be used to clear a particular fitness machine, or all fitness machines, listed in a pairing record stored on the wearable computer. If, however, the wearable computer was paired with a particular fitness machine in the past, and die user attempts to pair within x days (e.g., <NUM> days) from the last pairing, the wearable computer will auto-connect with the fitness machine. Otherwise, the user will be prompted to perform a pairing/authentication process with the fitness machine, as described in reference to <FIG>.

<FIG> is a flow diagram of an example process performed by a wearable computer for calculating fitness data, according to an embodiment. Process <NUM> can be implemented by architecture <NUM>, as described in reference to <FIG>.

Process <NUM> can begin by establishing wireless communication with a fitness machine (<NUM>). For example, a Bluetooth or NFC session can be established with the fitness machine, as described in reference to <FIG>. A unique SessionID and OOB secret data can be calculated on the wearable computer and sent to the fitness machine for use in pairing and authentication.

Process <NUM> continues after pairing by obtaining machine data from the fitness machine (<NUM>). After successful pairing and authentication, machine data can be transferred to the wearable computer using Bluetooth or NFC session data packets. The machine data can include, for example, data that describes the fitness machine, including but not limited to: manufacturer name, model number, hardware revision, software revision, vendor ID, product ID. Additionally, various fitness metrics can be included in the machine data, such as total energy, total distance and elapsed time. Some examples of fitness metrics for different types of fitness machines is described in Table I below.

Process <NUM> continues by determining a workout session according to the machine data (<NUM>). Based on the machine data, the wearable computer learns the specific physical activity the user will be engaged in during the workout session. For example, if the fitness machine is a treadmill then the wearable computer will know what fitness metrics may be received from the fitness machine and how to calculate fitness data for the workout. This can include adjusting parameters of a calorie model, such as, for example, determining an appropriate MET for calculating calorie expenditure.

Process <NUM> continues by initiating a workout session (<NUM>). For example, the user starts the fitness machine. Process <NUM> continues by obtaining, during the workout, the user's physiological data (<NUM>). The physiological data can be any data that measures the physiology of the user during the workout, including but not limited to: heart rate sensors, pulse detectors, blood pressure sensors, skin temperature and/or conductance response sensors, respiratory rate sensors, etc. The sensors can be included in any suitable housing, including but not limited to: a smartwatch or watchband, fitness band, chest band, headband, finger clip, ear clip, earbud, strapless heart rate monitor, etc..

Process <NUM> continues by determining fitness data, during the workout session, for the user based on the physiological data, machine data and user characteristic(s) (<NUM>). For example, calories burned can be calculated using knowledge of the physical activity, the total energy, total distance, elapsed time any other data shown in Table I, that can be used in a calorie expenditure model. Any suitable calorie expenditure model can be used, including models that are dependent on MET and not dependent MET, and models that include any type and combination of user characteristics, such as height, weight, age and gender.

Process <NUM> continues by sending the fitness data, during the workout session, to the fitness machine (<NUM>). After calculating the fitness data, the wearable computer sends the fitness data to the fitness machine where it can be displayed on a monitor of the fitness machine. In an embodiment, the fitness data is also stored on the wearable computer. The stored fitness data can be synced to another device including a network-based server computer and shared with other devices through a client-server architecture. In an embodiment, die fitness data can be shared directly with other devices (e.g., devices owned by friends, trainers, etc.) in a multi-peer ad hoc mesh network.

<FIG> is a flow diagram of an example process <NUM> performed by a wearable computer to calibrate a digital pedometer, according to an embodiment. Process <NUM> can be implemented by architecture <NUM>, as described in reference to <FIG>.

Process <NUM> begins by establishing wireless communication with a fitness machine (<NUM>). For example, a Bluetooth or NFC session can be established with the fitness machine, as described in reference to <FIG> and <FIG>.

Process <NUM> continues by launching a pedometer calibration application on the wearable computer (<NUM>). The pedometer application can measure step counts based on sensor data, such as accelerometer data provided by an accelerometer on the wearable computer.

Process <NUM> continues by obtaining machine data from the fitness machine (<NUM>). After a successful pairing/authentication process, the fitness machine can send data to the wearable computer that indicates the specific physical activity engaged in by the user during the workout. Additionally, the machine data can include information that can be used to calibrated the digital pedometer, such as total distance data from a treadmill.

Process <NUM> continues by obtaining pedometer data (<NUM>). Pedometer data can include step count or distance traveled which can be calculated from the step count and the user's stride length.

Process <NUM> continues by determining a pedometer calibration factor based on the machine data and the pedometer data (<NUM>). For example, a ratio can be formed from the total distance provided in the machine data over the estimated distance provided by the digital pedometer. The ratio can be used as a calibration scale factor to correct future pedometer measurements by scaling the estimated distance by the ratio. Process <NUM> continues by storing the calibration factor (<NUM>). The calibration can be performed each time the user uses a treadmill.

<FIG> illustrates example wearable computer architecture <NUM> implementing the features and operations described in reference to <FIG>. Architecture <NUM> can include memory interface <NUM>, one or more data processors, image processors and/or processors <NUM> and peripherals interface <NUM>. Memory interface <NUM>, one or more processors <NUM> and/or peripherals interface <NUM> can be separate components or can be integrated in one or more integrated circuits.

Sensors, devices and subsystems can be coupled to peripherals interface <NUM> to provide multiple functionalities. For example, one or more motion sensors <NUM>, light sensor <NUM> and proximity sensor <NUM> can be coupled to peripherals interface <NUM> to facilitate motion sensing (e.g., acceleration, rotation rates), lighting and proximity functions of the wearable computer. Location processor <NUM> can be connected to peripherals interface <NUM> to provide geo-positioning. In some implementations, location processor <NUM> can be a GNSS receiver, such as the Global Positioning System (GPS) receiver. Electronic magnetometer <NUM> (e.g., an integrated circuit chip) can also be connected to peripherals interface <NUM> to provide data that can be used to determine the direction of magnetic North. Electronic magnetometer <NUM> can provide data to an electronic compass application. Motion sensor(s) <NUM> can include one or more accelerometers and/or gyros configured to determine change of speed and direction of movement of the wearable computer. Barometer <NUM> can be configured to measure atmospheric pressure around the mobile device.

Heart rate monitoring subsystem <NUM> for measuring the heartbeat of a user who is wearing the computer on their wrist. In an embodiment, subsystem <NUM> includes LEDs paired with photodiodes for measuring the amount of light reflected from die wrist (not absorbed by the wrist) to detect a heartbeat.

Communication functions can be facilitated through wireless communication subsystems <NUM>, which can include radio frequency (RF) receivers and transmitters (or transceivers) and/or optical (e.g., infrared) receivers and transmitters. The specific design and implementation of the communication subsystem <NUM> can depend on the communication network(s) over which a mobile device is intended to operate. For example, architecture <NUM> can include communication subsystems <NUM> designed to operate over a GSM network, a GPRS network, an EDGE network, a Wi-Fi™ network and a Bluetooth™ network. In particular, the wireless communication subsystems <NUM> can include hosting protocols, such that the mobile device can be configured as a base station for other wireless devices.

Audio subsystem <NUM> can be coupled to a speaker <NUM> and a microphone <NUM> to facilitate voice-enabled functions, such as voice recognition, voice replication, digital recording and telephony functions. Audio subsystem <NUM> can be configured to receive voice commands from the user.

I/O subsystem <NUM> can include touch surface controller <NUM> and/or other input controller(s) <NUM>. Touch surface controller <NUM> can be coupled to a touch surface <NUM>. Touch surface <NUM> and touch surface controller <NUM> can, for example, detect contact and movement or break thereof using any of a plurality of touch sensitivity technologies, including but not limited to capacitive, resistive, infrared and surface acoustic wave technologies, as well as other proximity sensor arrays or other elements for determining one or more points of contact with touch surface <NUM>. Touch surface <NUM> can include, for example, a touch screen or the digital crown of a smart watch. I/O subsystem <NUM> can include a haptic engine or device for providing haptic feedback (e.g., vibration) in response to commands from processor <NUM>. In an embodiment, touch surface <NUM> can be a pressure-sensitive surface.

Other input controller(s) <NUM> can be coupled to other input/control devices <NUM>, such as one or more buttons, rocker switches, thumb-wheel, infrared port and USB port The one or more buttons (not shown) can include an up/down button for volume control of speaker <NUM> and/or microphone <NUM>. Touch surface <NUM> or other controllers <NUM> (e.g., a button) can include, or be coupled to, fingerprint identification circuitry for use with a fingerprint authentication application to authenticate a user based on their fingerprint(s).

In one implementation, a pressing of the button for a first duration may disengage a lock of the touch surface <NUM>; and a pressing of the button for a second duration that is longer than the first duration may turn power to the mobile device on or off. The user may be able to customize a functionality of one or more of the buttons. The touch surface <NUM> can, for example, also be used to implement virtual or soft buttons.

In some implementations, the mobile device can present recorded audio and/or video files, such as MP3, AAC and MPEG files. In some implementations, the mobile device can include the functionality of an MP3 player. Other input/output and control devices can also be used.

Memory interface <NUM> can be coupled to memory <NUM>. Memory <NUM> can include high-speed random access memory and/or non-volatile memory, such as one or more magnetic disk storage devices, one or more optical storage devices and/or flash memory (e.g., NAND, NOR). Memory <NUM> can store operating system <NUM>, such as the iOS operating system developed by Apple Inc. of Cupertino, California. Operating system <NUM> may include instructions for handling basic system services and for performing hardware dependent tasks. In some implementations, operating system <NUM> can include a kernel (e.g., UNIX kernel).

Memory <NUM> may also store communication instructions <NUM> to facilitate communicating with one or more additional devices, one or more computers and/or one or more servers, such as, for example, instructions for implementing a software stack for wired or wireless communications with other devices. Memory <NUM> may include graphical user interface instructions <NUM> to facilitate graphic user interface processing; sensor processing instructions <NUM> to facilitate sensor-related processing and functions; phone instructions <NUM> to facilitate phone-related processes and functions; electronic messaging instructions <NUM> to facilitate electronic-messaging related processes and functions; web browsing instructions <NUM> to facilitate web browsing-related processes and functions; media processing instructions <NUM> to facilitate media processing-related processes and functions; <iNSS/Location instructions <NUM> to facilitate generic GNSS and location-related processes and instructions; and heart rate instructions <NUM> to facilitate hear rate measurements. Memory <NUM> further includes activity application instructions for performing the features and processes described in reference to <FIG>.

Each of the above identified instructions and applications can correspond to a set of instructions for performing one or more functions described above. These instructions need not be implemented as separate software programs, procedures, or modules. Memory <NUM> can include additional instructions or fewer instructions. Furthermore, various functions of the mobile device may be implemented in hardware and/or in software, including in one or more signal processing and/or application specific integrated circuits.

The described features can be implemented advantageously in one or more computer programs that are executable on a programmable system including at least one programmable processor coupled to receive data and instructions from, and to transmit data and instructions to, a data storage system, at least one input device, and at least one output device. A computer program is a set of instructions that can be used, directly or indirectly, in a computer to perform a certain activity or bring about a certain result. A computer program can be written in any form of programming language (e.g., SWIFT, Objective-C, C#, Java), including compiled or interpreted languages, and it can be deployed in any form, including as a stand-alone program or as a module, component, subroutine, a browser-based web application, or other unit suitable for use in a computing environment.

Conversely, various features that are described in the context of a single embodiment can also be implemented in multiple embodiments separately or in any suitable sub combination. Moreover, although features may be described above as acting in certain combinations and even initially claimed as such, one or more features from a claimed combination can in some cases be excised from the combination, and the claimed combination may be directed to a sub combination or variation of a sub combination.

As described above, some aspects of the subject matter of this specification include gathering and use of data available from various sources to improve services a mobile device can provide to a user. The present disclosure contemplates that in some instances, this gathered data may identify a particular location or an address based on device usage. Such personal information data can include location-based data, addresses, subscriber account identifiers, or other identifying information.

The present disclosure further contemplates that the entities responsible for the collection, analysis, disclosure, transfer, storage, or other use of such personal information data will comply with well-established privacy policies and/or privacy practices. For example, personal information from users should be collected for legitimate and reasonable uses of the entity and not shared or sold outside of those legitimate uses. Further, such collection should occur only after receiving the informed consent of the users. Additionally, such entities would take any needed steps for safeguarding and securing access to such personal information data and ensuring that others with access to the personal information data adhere to their privacy policies and procedures.

In the case of advertisement delivery services, the present disclosure also contemplates embodiments in which users selectively block the use of, or access to, personal information data. That is, the present disclosure contemplates that hardware and/or software elements can be provided to prevent or block access to such personal information data. For example, in the case of advertisement delivery services, the present technology can be configured to allow users to select to "opt in'' or "opt out" of participation in the collection of personal information data during registration for services.

Claim 1:
A method comprising:
establishing, by a processor of a wearable computer, a wireless communication connection with a fitness machine;
obtaining, by the processor, machine data from the fitness machine, the machine data specifying a type of the fitness machine and comprising fitness metrics;
determining, by the processor, a workout session according to the machine data;
initiating the workout session on the wearable computer;
during the workout session:
obtaining, by the processor, a metabolic equivalent of tasks based at least in part on the machine data comprising the type of fitness machine and the fitness metrics;
obtaining, from a sensor of the wearable computer, physiological data of a user of the fitness machine;
determining, by the processor, fitness data for the user based at least in part on a combination of the physiological data and the metabolic equivalent of tasks, wherein the fitness data includes calories burned by the user.