KR20230113305A - Breathing feedback for improved athletic performance - Google Patents

Abstract

Systems and methods executed by a processor of user equipment to ensure that a user receives scheduled notifications are disclosed. Various embodiments may include determining a current exercise being performed by a user, determining a target breathing pattern appropriate for a current exercise being performed by a user, and performing a user's current exercise while performing a current exercise based on inputs from a breathing sensor. monitoring the current breathing pattern of the user, determining differences between the user's current breathing pattern and the target breathing pattern appropriate for the current exercise performed by the user, and the user's current breathing pattern and the target breathing pattern appropriate for the current exercise performed by the user. and providing the user with information about the determined differences between the current breathing patterns.

Description

Breathing feedback for improved athletic performance

[0001] Proper breathing can help reduce stress, control emotions, improve alertness, and maximize the benefits of exercise by increasing oxygenated blood flow to the heart. This helps prevent injury (such as hernias or spikes in blood pressure) and improves exercise efficiency, allowing people to exercise more comfortably for longer periods of time. Newbies to exercise want to learn how to exercise appropriately and most effectively for their individual ability level, but often the cost of a personal trainer leaves them out or they are too intimidated to go to the gym. Besides learning the exercises themselves, learning the proper breathing techniques for those exercises can be difficult. Intermediate and expert exercisers may also use handwritten notes or fitness tracking applications to track their progress, but these tracking techniques do not provide feedback during exercise. Although some exercisers use wearable heart rate monitors, heart rate measurements may not provide necessary information about whether the exerciser is performing the exercise properly and may not be useful for non-aerobic exercises such as yoga. Even cameras or motion sensors that monitor user movements do not provide user feedback designed to help improve breathing during a wide range of exercises. Proper breathing patterns can include targeting a breath-movement cadence (e.g., 2 steps versus 1 breath while running), and (e.g., thoracic movement in all directions versus shallow chest breaths). You can practice breathing deeply from the diaphragm). Breathing easily from the diaphragm is also generally a good indicator of proper muscle shape.

[0002] Various aspects include methods executed by a processor of user equipment and computing devices implementing the methods to provide information regarding a user's breathing patterns during exercise. Various aspects include determining a current exercise being performed by a user, determining a target breathing pattern appropriate for a current exercise being performed by a user, performing a current exercise of a user while performing a current exercise based on inputs from a breathing sensor. monitoring the breathing pattern, determining differences between the user's current breathing pattern and the target breathing pattern appropriate for the current exercise performed by the user, and the user's current breathing pattern and the target breathing pattern appropriate for the current exercise performed by the user. and providing the user with information about the determined differences between the patterns.

[0003] Some aspects may include receiving sensor input from an athletic sensor that provides information about user body movements, and determining a current workout is based on the sensor input received from the athletic sensor. In some aspects, the target breathing pattern is based on received sensor input from an athletic sensor indicating how the user is moving during exercise. Some aspects may include receiving sensor input from an athletic sensor that provides athletic information about a current exercise, the athletic sensor associated with athletic equipment being used by a user to perform a current exercise.

[0004] Some aspects may include receiving user body movement information from an athletic sensor indicating which of the first portion and the second portion of an exercise the user is currently performing. In some aspects, the target breathing pattern may include a first breathing pattern associated with a first portion of the current workout, and a second breathing pattern that is different from the first breathing pattern and is associated with a second portion of the current workout, and may inform the user Determining the differences between the user's current breathing pattern and the target breathing pattern appropriate for the current exercise performed by determining differences between the user's current breathing pattern, and the information provided to the user may include a target breathing pattern appropriate for the first and second portions of the current workout and during the first and second portions of the current workout. of the user's current breathing pattern.

[0005] Some aspects may include receiving manual user input regarding at least one of a current workout or a target breathing pattern, and determining the target breathing pattern is further based on the received manual user input. Some aspects may include receiving contextual information indicating a context in which a user is currently performing an exercise, and determining a target breathing pattern is further based on the received contextual information. In some aspects, the target breathing pattern may be based on at least one of the user's body type, fitness goals, or level of experience performing the current exercise.

[0006] Some aspects may include determining another target breathing pattern for a user to achieve in response to a current breathing pattern exceeding a normal breathing pattern threshold, and providing the user with additional information regarding the other target breathing pattern. . Some aspects may include, in response to a determination by the user that a current exercise is being performed, activating a breathing sensor configured to monitor a current breathing pattern of the user while performing a current exercise. In some aspects, determining the differences between the user's current breathing pattern and a target breathing pattern appropriate for a current exercise performed by the user may change the user's current breathing pattern to the user's previously determined breathing rate when the user performed the current exercise. , rhythm, or quality.

[0007] Some aspects may include activating an additional sensor in response to the user's current breathing pattern exceeding a normal breathing pattern threshold. Some aspects may include determining, apart from breathing, a first range of body movements by the user due to the determined current movement, wherein the user's current breathing pattern is attributable to breathing and is equal to the first range of body movement. Associated with a second range of body movement by the user, which is distinct.

[0008] In some aspects, the user's current breathing pattern includes at least one of a rate, rhythm or quality of breathing movement. In some aspects, providing the user with information about the determined differences includes notifying the user via at least one of a visual, audible or tactile alert. In some aspects, the current exercise is determined based on exercise equipment being used by the user, and information regarding the determined differences between the user's current breathing pattern and a target breathing pattern appropriate for the current exercise being performed by the user is the exercise equipment Provided to users through feedback from

[0009] Additional aspects include a user equipment device comprising a processor configured with processor executable instructions to perform the operations of any of the methods outlined above. Additional aspects include a non-transitory processor-readable storage medium having stored thereon processor-executable software instructions configured to cause a processor to perform the operations of any of the methods summarized above. Additional aspects include a processing device configured to perform the operations of any of the methods outlined above and for use in a computing device.

[0010] The accompanying drawings, incorporated herein and forming a part thereof, illustrate exemplary embodiments and, together with the general description given above and the detailed description given below, serve to explain features of various embodiments.
[0011] FIG. 1A is a schematic diagram illustrating user equipment working in conjunction with wearables to provide information regarding a user's breathing patterns during a resistance training workout, in accordance with various embodiments.
[0012] FIG. 1B is a schematic diagram illustrating user equipment working in conjunction with wearables to provide information regarding breathing patterns of a user performing yoga postures, in accordance with various embodiments.
1C is a schematic diagram illustrating user equipment working with wearables to provide information regarding breathing patterns of a user running on a treadmill, in accordance with various embodiments.
1D is a schematic diagram illustrating user equipment working in conjunction with wearables to provide information about a user's breathing patterns via a computerized exercise bike, in accordance with various embodiments.
[0015] FIG. 2 is a block diagram illustrating components of an example system of packages for use in a computing device, in accordance with various embodiments.
[0016] FIG. 3 is a component block diagram of an example system configured to be executed by a processor of user equipment to ensure that a user receives scheduled notifications.
[0017] FIG. 4a, 4b, 4c, 4d, 4e, 4f, 4g, 4h, 4i, and/or 4j is executed by a processor of a user equipment, according to various embodiments. Process flow diagrams of example methods for providing information about a user's breathing patterns are shown.
5 is a component block diagram of a networked computing device suitable for use in various embodiments.
6 is a component block diagram of a wireless computing device suitable for use in various embodiments.
7 is a component block diagram of an example of smart glasses suitable for use in various embodiments.

[0021] Various aspects will be described in detail with reference to the accompanying drawings. Wherever possible, the same reference numbers will be used throughout the drawings to indicate the same or like parts. References made to specific examples and embodiments are for purposes of illustration and are not intended to limit the scope of the various aspects or claims.

[0022] Various embodiments provide methods executed by a processor of user equipment to provide information regarding a user's breathing patterns during exercise. Various embodiments include determining a current exercise being performed by a user, determining a target breathing pattern appropriate for the current exercise, and monitoring the user's current breathing pattern while performing the current exercise based on inputs from a breathing sensor. This may include deciding Additionally, differences between the user's current breathing pattern and the target breathing pattern may be determined, and information regarding the determined differences may be provided to the user.

[0023] As used herein, the term “breathing pattern” refers to the respiratory rate, depth, timing and consistency of a user's breaths. While exercising, the user may strive to achieve a target breathing pattern configured to provide greater benefits to the user. To achieve a target breathing pattern, the user may attempt to better control the body movements involved in the exercise, or may attempt to directly alter their breathing to make their current breathing pattern match the target breathing pattern. there is.

[0024] As used herein, the term "computing device" means an electronic device having at least a processor, communication systems, and memory consisting of a contact database. Also, as used herein, the term “user equipment” refers to a particular computing device through which a user can receive notifications. Computing devices, including user equipment, include cellular telephones, smartphones, portable computing devices, personal or mobile multimedia players, laptop computers, tablet computers, 2-in-1 laptop/table computers , smartbooks, ultrabooks, palmtop computers, wireless e-mail receivers, multimedia internet enabled cellular phones, smart watches, smart glasses, wearable devices including smart contact lenses, augmented/virtual reality devices , entertainment devices (eg, wireless gaming controls, music and video players, satellite radios, etc.), and similar electronic devices including memory, wireless communication components, and a programmable processor. can do. In various embodiments, computing devices may be configured with memory and/or storage. Additionally, computing devices referred to in various example embodiments may be coupled to network transceiver(s) and antenna(s) configured to communicate with wired or wireless communication capabilities, such as wireless communication networks, implementing the various embodiments. may include these.

[0025] As used herein, the term "smart" in relation to a device includes a processor for autonomous operation, for collection and/or processing of data, and/or in relation to various embodiments herein. means a device that can be programmed to perform all or some of the described operations. Examples include smart phones, smart glasses, smart contact lenses, smart watches, smart rings, smart necklaces, smart cups, smart-straws, smart appliances, and the like.

[0026] The term “system on chip” (SOC) is used herein to refer to a single integrated circuit (IC) chip that includes multiple resources and/or processors integrated on a single substrate. A single SOC may contain circuitry for digital, analog, mixed signal and radio frequency functions. A single SOC may also include any number of general purpose and/or special processors (digital signal processors, modem processors, video processors, etc.), memory blocks (e.g. ROM, RAM, flash, etc.) and resources (e.g. timers, voltage regulators, oscillators, etc.). SOCs may also include software for controlling integrated resources and processors, as well as for controlling peripheral devices.

[0027] The term “system in a package” (SIP) refers to a single module or package that includes multiple resources, computing units, cores and/or processors on two or more IC chips, substrates or SOCs. can be used herein to For example, a SIP may include a single substrate on which multiple IC chips or semiconductor dies are stacked in a vertical configuration. Similarly, a SIP may include one or more multi-chip modules (MCMs) in which multiple ICs or semiconductor dies are packaged in an integrated substrate. A SIP may also include multiple independent SOCs coupled together via high-speed communication circuitry and packaged in close proximity, such as on a single motherboard or in a single wireless device. The proximity of SOCs enables high-speed communications and sharing of memory and resources.

[0028] Various embodiments may use one or more of the various sensors to detect user activity associated with one or more workouts, as well as breathing patterns of the user during the detected activity. In particular, sensors may include one or more adhesive patches, smart clothing, inertial measurement units, sensor-equipped wearable computing devices (also referred to herein as "wearables"), sensor-equipped athletic equipment, or other sensors or sensor computing devices. Included in the devices can measure activity associated with movement and/or breathing patterns. Wearables may include smart glasses, earpieces, other head worn devices, necklaces, chest straps, watches, bracelets, other wrist worn devices and/or smart rings. Input from one or more sensors may be used to automatically monitor the user's current breathing pattern and determine a target breathing pattern based on detected current movement performed by the user. Additionally, information regarding the determined differences between the user's current breathing pattern and the target breathing pattern appropriate for the current exercise may be provided to the user.

[0029] 1A-1D illustrate several environments 100, 101, 102, 103 in which user 5 is exercising, but feedback regarding user 5's breathing as user 5 engages in exercise. ), various sensors are used to provide 1A and 1B , users 5 and 6 have user equipment 110 nearby, which user equipment 110 communicates via wireless network 190 to remote computing devices (eg, server 195). and via wireless connections 50 (e.g., Wi-Fi, Bluetooth, cellular, etc.), by a wireless local area network router (not shown) or cellular network base station, such as a Wi-Fi wireless router. can be supported 1C and 1D , users 7 and 8 are on exercise equipment 160 and 170, which similarly make wireless connections to server 195 via wireless network 190. 50 (e.g., Wi-Fi, Bluetooth, cellular, etc.) and may be supported by a wireless local area network router (not shown) or cellular network base station, such as a Wi-Fi wireless router. .

[0030] 1A shows a target breathing pattern suitable for exercise and a current breathing of a user 5 by various sensors such as adhesive patch sensors 120, smart glasses 130, and/or smart watch 140, according to various embodiments. Illustrates environment 100 in which user 5 performs barbell bench presses (ie, exercise) while taking measurements that are processed by user equipment 110 to determine differences between patterns. Alternatively or additionally, adhesive patch sensors 120, smart glasses 130 and/or smart watch 140 may be stand-alone processing units having a display or other user interface (to provide feedback to the user) and , a processor configured to determine differences between a current breathing pattern of the user 5 and a target breathing pattern appropriate for the exercise using the measurements, according to various embodiments.

[0031] To perform a conventional barbell bench press, user 5 lies on a bench 90 while holding a bar 92 supporting weights 94. The user 5 then raises the bar 92 holding the weights 94 from a first position A near the user's chest to a second position B while extending the arms away from the chest. The user 5 then lowers the bar 92 bearing the weights 94 back to the chest and repeats the exercise for a number of repetitions. The amount of weights 94 (ie, how much they weigh collectively) is chosen to limit the number of repetitions the user 5 can perform before becoming fatigued. Since conventional bench press equipment does not include sensors, various embodiments provide a computing device, such as user equipment 110, configured to provide information regarding breathing patterns of user 5 during exercise and additional equipment having sensors. use. The illustrated user equipment 110 is in the form of a cellular telephone (ie, smart phone), but other types of computing devices (eg, tablets, personal computers, exercise machines, wearables, smart appliances, etc.) may be used. can

[0032] Adhesive patch sensors 120 may be worn by user 5 directly on the skin over one or more major muscles used for locomotion (eg, chest, shoulders, neck and/or triceps). The adhesive patch sensors 120 can detect blood flow, electrical activity, perspiration, movement of underlying muscles, and the like, operate without a battery (ie, passive), or powered by near-field communications (NFC). It may be supplied or may contain an onboard battery. Additionally, via NFC or an onboard transceiver, adhesive patch sensors 120 may communicate with user equipment 110 or other computing device via wireless connections 50 (eg, Wi-Fi, Bluetooth, cellular, etc.). can Adhesive patch sensors 120 may include one or more processors configured to implement methods of various embodiments described herein. In some embodiments, adhesive patch sensors 120 may provide one or more user interfaces by providing feedback to user 5 via a speaker and/or a haptic feedback device. Adhesive patch sensors 120 may operate as stand-alone devices or may operate in conjunction with other computing devices including user equipment 110, other wearables, and/or athletic equipment.

[0033] The smart glasses 130 are in the form of a wearable that may include a built-in camera as well as a heads-up display or augmented reality features on or near the front lenses. Like other sensor devices that provide information to user equipment 110 , smart glasses 130 may include a processor or control unit configured to collect information from onboard sensors, such as a camera having field of view 137 . . The camera may be used to capture images of athletic equipment and/or movements performed by a user to identify which exercise is being performed and/or which part of an exercise is being performed. For example, for a bar 92 in the field of view 137, the images collected by the camera show when the user is moving the bar 92 from position A to position B (concentric movement) or when the user moves the bar ( 92) from position B to position A (eccentric movement). The smart glasses 130 may include electromyography (eg, in the arms of the frame), microphone, thermometer and/or internal sensors, such as an inertial measurement unit (IMU), proximity/motion sensor, light sensor, lidar, gas sensors and the like. EMG can detect muscle movements associated with exercise. The microphones can detect breathing patterns from the mouth and/or nose. The thermometer may register the user's temperature and/or the ambient temperature around the user 5 , which may provide contextual information related to determining a target breathing pattern for the user. The smart glasses 130 support wireless technologies such as Bluetooth or Wi-Fi, such as a wireless connection 50 (eg, wireless communication) to the user equipment 110 and/or other sensors (eg, 120, 140). link) to enable communications. Additionally, smart glasses 130 may control or retrieve data from other sensors (eg, 120, 140) and/or remote computing devices 110, 195. In some embodiments, smart glasses 130 may function as one or more user interfaces, providing feedback to user 5 via an augmented reality or heads-up display, a speaker, and/or a haptic feedback device. Smart glasses 130 may include one or more processors configured to implement the methods of various embodiments described herein. The smart glasses 130 may operate as a stand-alone device or operate in conjunction with other computing devices, including user equipment 110, other wearables, and/or athletic equipment.

[0034] The smart watch 140 includes an array of sensors, such as an electrical heart sensor to take ECG readings, an optical heart sensor to measure heart rate, a photoplethysmogram (PPG) sensor to estimate breathing rate (e.g., detect changes in blood volume), It is a form of wearable that may include an accelerometer and/or gyroscope to track movement and rotation, a barometric altimeter to measure altitude, and an ambient light sensor to control the brightness of the display. Smart watch 140 collects information from on-board sensors and supports wireless technologies such as Bluetooth or Wi-Fi, such as wireless connection to user equipment 110 and/or other sensors (eg, 120, 130). and a processor or control unit configured to enable communications via 50 . Smart watch 140 may provide feedback to user 5 via a display, speaker, and/or haptic feedback device, and thus may function as a user interface. Additionally, smart watch 140 may control or retrieve data from other sensors (eg, 120, 130) and/or remote computing devices 110, 195. In some embodiments, smart watch 140 may operate with a mobile operating system to provide feedback to user 5 via a watch-face display, vibrations and/or sound. Smart watch 140 may include one or more processors configured to implement methods of various embodiments described herein. The smart watch 140 may operate as a stand-alone device or may operate in conjunction with other computing devices including user equipment 110, other wearables, and/or exercise equipment.

[0035] In various embodiments, a processor of user equipment 110, wearables, or other computing device is configured by user 5, such as through input received from sensors within one or more of wearables 120, 130, 140. You can determine the current exercise being performed. Based on the determined exercise, the processor may further determine a target breathing pattern appropriate for the current exercise being performed by user 5 . The target breathing pattern may be based on at least one of the user's body type, health goals, or level of experience performing the current exercise. Additionally, additional input received from sensors within one or more of wearables 120 , 130 , 140 may be used by the processor to monitor the user's current breathing pattern while performing a current exercise. The target breathing pattern may be based on received sensor inputs from one or more athletic sensors indicating how the user is moving during a current workout. The user's current breathing pattern may include at least one of rate, rhythm or quality of breathing movement. For example, inputs received from the sensors may be used to distinguish diaphragmatic breathing from chest breathing or vice versa. Similarly, different exercises may require different breathing patterns. For example, running, cycling, and swimming can be performed more efficiently while maintaining a constant cadence or stroke rate, which can be detected from sensor inputs. Also, some exercises, such as swimming, can be more efficient if exhaling or inhaling is performed at a specific part of the stroke, which can similarly be detected from sensor inputs. The processor may then determine differences between the target breathing pattern and the user's current breathing pattern. Accordingly, the processor may provide information about the determined differences between the target breathing pattern and the current breathing pattern to the user 5 . For example, user equipment 110 may provide feedback to user 5 via display 115, such as an alert that may read “Steady Your Breath,” or may use a speaker of user equipment 110 to provide feedback. It may be configured to provide audible feedback 116 , such as “Steady your breath,” “Breathe from your belly,” automated speech outputs, personalized messages, and/or other messages.

[0036] In some embodiments, the processor also or additionally receives sensor input from an athletic sensor, such as from athletic equipment being used during exercise (e.g., treadmill, bicycle, rower, elliptical, etc.) , can provide information about the user's body movements useful for determining the current movement. For example, video images (e.g. captured by smart glasses 130) of what user 5 is doing and/or other sensor input that detects movements, sounds, vibrations or muscle activity. By analyzing these, the processor of user equipment 110 can monitor the current breathing pattern of user 5 as well as determine the current exercise being performed by the user (eg, barbell bench presses, running, cycling, swimming, etc.). there is.

[0037] In some embodiments, the processor may receive user body movement information from an athletic sensor indicating how the user is moving during exercise. Additionally or alternatively, the processor may receive user body movement information from the athletic sensor indicating which part of the first or second part of the exercise the user is currently performing. Adhesive patch sensors 120 that may be placed, for example, on the skin near specific training muscles (i.e., primary muscles used in a specific exercise) or other wearables such as a smart watch 140. ) may provide input to the processor that is used to determine what movement is being performed, as well as specific body movements being performed and/or specific parts of the movement being performed. Additionally, sensors placed on the diaphragm may be used to monitor the user's current breathing pattern during exercise, including certain parts of the exercise. The processor may correlate the measured diaphragm movements associated with the current breathing patterns to muscle movements associated with the individual portions of the movement. Using yoga as an example, the target breathing pattern is to exhale while further stretching into a pose (i.e., the first part of the current exercise), then inhale as you release that pose (i.e., the first part of the current exercise). Part 2) may be involved. In this way, the determined target breathing pattern may include a first breathing pattern associated with a first portion of the current workout, and a second breathing pattern different from the first breathing pattern and associated with a second portion of the current workout. As another example, in resistance training, a first portion of an exercise may involve lifting a weight (ie, a pushing force) that must be performed while exhaling, while a second portion of the exercise is performed while holding one's breath. It may involve holding the weight in a raised position, which should be performed while inhaling, immediately prior to the lowering movement being performed. During a running, swimming or cycling workout, different parts of the movements may involve different parts of breathing.

[0038] Additionally, the processor may determine differences between target breathing patterns appropriate for the respective first and second portions of the current workout and the user's current breathing patterns during the respective first and second portions of the current workout. . Further, the processor transmits information including differences between target breathing patterns appropriate for the first and second parts of the current exercise and the user's current breathing patterns during the first and second parts of the current exercise to the user 5. can be provided to

[0039] In some embodiments, in response to determining that a current exercise is being performed by user 5, the processor may activate a breathing sensor (ie, a sensor configured to measure a current breathing pattern or aspects of a current breathing pattern). there is. For example, the processor may activate one or more sensors in smart glasses 130 configured to measure current breathing patterns. In this way, the breathing sensor does not need to be continuously active (which can conserve power), but once activated, can be configured to monitor the user's current breathing pattern while performing the current exercise.

[0040] The user equipment 110, adhesive patch sensors 120, smart glasses 130 and/or smart watch 140 may include other or additional sensors, such as camera, microphone, IMU, clocks, electromyograms, gas sensors , pressure sensors, proximity/motion sensors, light sensors, and thermometers. Although three wearables 120, 130, and 140 are illustrated in FIG. 1A, various embodiments may include fewer or more wearables and/or computing devices of one or more different types not shown in environment 100. number of wearables and/or remote computing devices.

[0041] User equipment 110 may provide a measure of what exercise is being performed, conventional functions applied in determining a target breathing pattern or current breathing pattern, such as how long movements or portions of a breathing pattern last. A clock/timer may be used, which may indicate which exercise is being performed, which part of the exercise is being performed, and/or the user's current breathing pattern.

[0042] 1B shows that smart watch 140, chest strap sensor 150, and camera 117 of user equipment 110 measure the current breathing pattern of user 6, as well as current movement (i.e., in the illustrated example). Illustrates an example 101 in which the user 6 is performing yoga (ie, exercise) while providing information useful for determining a current yoga pose. Using this information, the user equipment 110 may determine differences between the measured breathing pattern and the target breathing pattern appropriate for the current yoga pose according to various embodiments.

[0043] According to various embodiments, a processor of user equipment or other computing device may provide information to a user that may assist the user in properly adjusting each movement and breathing patterns of an exercise. In some embodiments, user equipment 110 may provide information to the user regarding the determined differences between the current breathing pattern and the target breathing pattern. Information may be provided to the user 6 via at least one of visual, audible or tactile alerts. In FIG. 1B , user equipment 110 is emitting verbal commands (ie, audible feedback 116 ) directing user 6 to “Steady Your Breath”. This type of command can help remind the user to relax and coordinate her breathing with each movement.

[0044] According to various embodiments, existing wrist worn sensors such as smart watch 140 can be improved in a number of ways to increase their value for various workouts. A smart watch 140 or other wrist worn sensor may be used for power measurements and/or respiration tracking. Power measurements can measure muscle exertion levels, such as during a difficult isometric yoga pose that requires the user to maintain a static contraction of the muscles without significant movement of the joints. Additionally, using one wrist-worn sensor for each arm would greatly improve the accuracy for detecting the type of exercise as well as the number of repetitions compared to using only a single wrist-worn sensor for one of the user's two arms. can

[0045] The smart watch 140 and the chest strap sensor 150 may each include a control unit 131, which controls various circuits and devices used to control operations of the control unit 131. can include In the example illustrated in FIG. 1B , the control unit 131 includes a processor 132 , a memory 133 , an input module 134 and an output module 135 . Additionally, control unit 131 may be coupled to a transceiver 138 and one or more sensors 139 for transmitting and/or receiving wireless communications. In some embodiments, like smart watch 140, chest strap sensor 150 is a speaker and/or haptic feedback device that can be on smart watch 140, chest strap sensor 150, or both. By providing feedback to the user 6 through, one or more user interfaces may be provided.

[0046] 1C shows various sensors, such as those of a treadmill 160 (ie, exercise equipment) that include a chest strap sensor 150 and a camera (shown as camera imaging angle 167), according to various embodiments. Environment 102 in which user 7 runs (i.e., performs an exercise) on treadmill 160, providing information useful in determining differences between a target breathing pattern appropriate for exercise and user 7's current breathing pattern. exemplify

[0047] Treadmill 160 similarly has processor 132, memory 133, input module 134, and output module 135 capable of rendering feedback information on display 165 of treadmill 160. A control unit 131 may be included. Additionally, control unit 131 may be coupled to a transceiver 138 and one or more sensors 139 for transmitting and/or receiving wireless communications. Treadmill 160 may provide feedback to user 7 via a display, speaker, and/or haptic feedback device (eg, a vibrator on or in handholds), thereby providing one or more user interfaces. can provide them.

[0048] In some embodiments, sensor-equipped exercise equipment may include a treadmill, elliptical machine, exercise cycle, and/or rowing machine. In this way, the processor can receive sensor input from the athletic sensor that provides athletic information about the current exercise, the athletic sensor associated with the exercise equipment being used by the user to perform the current exercise.

[0049] 1D shows the current breathing pattern of user 6 and the target breathing pattern appropriate for the exercise by various sensors of exercise bike 170 including a camera (shown as camera imaging angle 167), according to various embodiments. Illustrates environment 103 where user 8 is riding exercise bike 170 (ie, performing exercise), providing information useful for determining differences between the two.

[0050] Exercise bike 170 similarly has a control unit ( 131) may be included. Additionally, control unit 131 may be coupled to a transceiver 138 and one or more sensors 139 for transmitting and/or receiving wireless communications. Exercise bike 170 may provide feedback to user 8 via a display, speaker, and/or haptic feedback device (eg, a vibrator on or within handlebars), whereby one or more User interfaces can be provided.

[0051] Various embodiments are directed to various types of user equipment, computing devices and control in different devices using multiple uniprocessor and multiprocessor computer systems, including system-on-chip (SOC) or system in a package (SIP). 2 is a computing device, such as a user equipment (eg, 110) and/or one or more of wearables (eg, 130, 150, 170, etc.), implementing various embodiments. Illustrates an exemplary computing system or SIP 200 architecture that may be used.

[0052] Referring to FIGS. 1A-2 , the illustrated example SIP 200 includes two SOCs 202 and 204 , a clock 206 , a voltage regulator 208 and a radio transceiver 266 . In some embodiments, the first SOC 202 is a CPU (CPU) of the wireless device that executes instructions by performing arithmetic, logic, control and input/output (I/O) operations specified by the instructions of software application programs. It acts as a central processing unit. In some embodiments, second SOC 204 can operate as a specialized processing unit. For example, the second SOC 204 may operate as a specialized 5G processing unit responsible for managing high volume, high speed (eg, 5 Gbps, etc.) and/or very high frequency short-wavelength (eg, 28 GHz mmWave spectrum, etc.) communications. can

[0053] The first SOC 202 includes a digital signal processor (DSP) 210, a modem processor 212, a graphics processor 214, an application processor 216, and one or more auxiliary processors 218 connected to one or more of the processors. ) (e.g., vector coprocessor), memory 220, custom circuit 222, system components and resources 224, interconnect/bus module 226, one or more sensors 230 (e.g., thermal sensors, motion sensors, proximity sensors, multimeters, etc.), a thermal management unit 232 and a thermal power envelope (TPE) component 234 . The second SOC 204 includes a 5G modem processor 252, a power management unit 254, an interconnect/bus module 264, a plurality of mmWave transceivers 256, a memory 258 and various additional processors 260 ), such as an application processor, a packet processor, and the like.

[0054] Each processor 210, 212, 214, 216, 218, 252, 260 may include one or more cores, and each processor/core may perform operations independent of the other processors/cores. For example, the first SOC 202 may include a processor running a first type of operating system (eg, FreeBSD, LINUX, OS X, etc.) and a processor running a second type of operating system (eg, MICROSOFT WINDOWS 10). can include Additionally, any or all of the processors 210, 212, 214, 216, 218, 252, 260 may be part of a processor cluster architecture (eg, synchronous processor cluster architecture, asynchronous or heterogeneous processor cluster architecture, etc.) can be included

[0055] The first SOC 202 and the second SOC 204 provide encoded audio and video signals for managing sensor data, analog-to-digital conversions, wireless data transmissions, and for decoding data packets and rendering in a web browser. It may include various system components, resources, and custom circuitry to perform other specialized operations such as processing. For example, the system components and resources 224 of the first SOC 202 may include power amplifiers, voltage regulators, oscillators, phase locked loops, peripheral bridges, data controllers, memory controllers, system controllers, access ports, timers, and other similar components used to support processors and software clients running on the wireless device. System components and resources 224 and/or custom circuitry 222 may also include circuitry for interfacing with peripheral devices such as cameras, electronic displays, wireless communication devices, external memory chips, and the like.

[0056] The first SOC 202 and the second SOC 204 may communicate via an interconnect/bus module 250 . The various processors (210, 212, 214, 216, 218) interconnect/bus module 226 via one or more memory elements 220, system components and resources 224, custom circuitry 222 and may be interconnected to the thermal management unit 232 . Similarly, processor 252 may be interconnected via interconnect/bus module 264 to power management unit 254, mmWave transceivers 256, memory 258 and various additional processors 260. . The interconnect/bus module 226, 250, 264 may include an array of reconfigurable logic gates and/or may implement a bus architecture (eg, CoreConnect, AMBA, etc.). Communications may be provided by advanced interconnections, such as high performance networks-on chip (NoCs).

[0057] First SOC 202 and/or second SOC 204 may further include (not illustrated) an input/output module for communicating with resources external to the SOC, such as clock 206 and voltage regulator 208. can Resources external to the SOC (eg, clock 206, voltage regulator 208) may be shared by two or more of the internal SOC processors/cores.

[0058] In addition to the exemplary SIP 200 discussed above, various embodiments may be implemented on a wide variety of computing systems that may include a single processor, multiple processors, multicore processors, or any combination thereof. there is.

[0059] In some embodiments, wearables (eg, 130 , 130 ) where only one SOC (eg, 132 , 202 ) is configured to provide sensor information to higher performance user equipment, such as a smartphone (eg, UE 110 ). , 150, 170, etc.) can be used in lower performance computing devices. In such embodiments, the communication capabilities of the wearable (eg, 130, 150, 170, etc.) may be limited to a short-range communication link such as Bluetooth or Wi-Fi, in which case the 5G-capable SOC 204 is the wearable's processing system. may not be included in

[0060] As used herein, the terms "component," "system," "unit," "module" and the like refer to hardware, firmware, a combination of hardware and software, software, or Includes computer-related entities such as (but not limited to) running software. For example, a component may be (but is not limited to) a process, processor, object, executable, thread of execution, program, and/or computer that runs on a processor. By way of example, both an application running on a communication device and a communication device may be referred to as a component. One or more components can reside within a process and/or thread of execution and a component can be localized on one processor or core and/or distributed between two or more processors or cores. Additionally, these components can execute from various non-transitory computer readable media having various instructions and/or data structures stored thereon. Components may communicate via local and/or remote processes, function or procedure calls, electronic signals, data packets, memory reads/writes, and other known computer, processor and/or process related communication methods. .

[0061] 3 is a component block diagram illustrating a system 300 configured to provide information about a user's breathing patterns executed by a processor of a computing device in accordance with various embodiments. Referring to FIGS. 1A-3 , system 300 may include user equipment 110 , via local wireless connection 50 (eg, Wi-Fi, Bluetooth, Ant, etc.) or other NFC communication techniques. It may be configured to communicate with one or more remote device(s) 315 (eg, 120, 130, 140, 150, 160, 170 in FIGS. 1A-1D) or other computing devices. User equipment 110 may also be configured to communicate with external resources 320 (eg, server 195) via a wireless connection 50 to a wireless network 190, such as a cellular wireless communications network.

[0062] User equipment 110 may include electronic storage 325 , one or more processors 330 , a radio transceiver 266 and other components. User equipment 110 may include communication lines or ports to enable exchange of information with a network and/or other computing platforms. The example of user equipment 110 in FIG. 3 is not intended to be limiting. User equipment 110 may include a plurality of hardware, software and/or firmware components that operate in concert to provide the functionality attributed to user equipment 110 herein.

[0063] Electronic storage 325 may include non-transitory storage media that electronically store information. Electronic storage media of the electronic storage 325 may include system storage and/or a port (eg, universal serial bus (USB) port) that is integrally (ie substantially non-removable) with the user equipment 110 . , a FireWire port, etc.) or removable storage that is removably connectable to the user equipment 110 through a drive (eg, a disk drive, etc.). Electronic storage 325 includes optically readable storage media (eg, optical disks, etc.), magnetically readable storage media (eg, magnetic tape, magnetic hard drive, floppy drive, etc.), charge-based storage media (eg, EEPROM, RAM, etc.), solid state storage media (eg, flash drive, etc.), and/or other electronically readable storage media. Electronic storage 325 may include one or more virtual storage resources (eg, cloud storage, virtual private network, and/or other virtual storage resources). Electronic storage 325 may include software algorithms, information determined by processor(s) 330, information received from user equipment 110, information received from remote platform(s) 304, and/or user equipment ( 110) may store other information that enables it to function as described herein.

[0064] Processor(s) 330 may include one or more processors (eg, 210, 212, 214, 216, 218, 252, 260) that may be configured to provide information processing capabilities in user equipment 110. . Accordingly, processor(s) 330 may be digital processors, analog processors, digital circuitry designed to process information, analog circuitry designed to process information, state machines, and/or among other mechanisms for processing information electronically. may contain one or more. Although processor(s) 330 are shown as a single entity in FIG. 3 , this is for illustrative purposes only. In some embodiments, processor(s) 330 may include a plurality of processing units. These processing units may be physically located within the same device, or processor(s) 330 may represent the processing functionality of a plurality of devices operating in concert.

[0065] User equipment 110 may be configured by machine readable instructions 335 that may include one or more instruction modules. Instruction modules may include computer program modules. In particular, the command modules include sensor/passive input receiving module 340, context information receiving module 345, body motion analysis module 350, current motion determination module 355, target breathing pattern determination module 360, sensor activation module 365, current breathing pattern monitoring module 370, normal breathing pattern determination module 375, breathing pattern difference determination module 380, user information transmission module 385, and/or one or more of other command modules. can include

[0066] The sensor/passive input receiving module 340 may be configured to detect user equipment (eg 110 ) and/or remote computing devices 315 in the vicinity of user equipment 110 (eg smart glasses 130 , smart watch 140 , chest One or more sensors (e.g., adhesive patch sensors 120, smart glasses 130, smart watch 140, chest strap sensor) communicating information to strap sensor 150, athletic equipment 160, 170, etc. 150, exercise equipment 160, 170, etc.). The processor may then determine a current exercise being performed by the user and/or a target breathing pattern appropriate for the current exercise being performed by the user based on the received sensor inputs. The sensors may detect a user performing particular types of actions associated with one or more particular exercises and/or may detect the user's current breathing patterns. As a non-limiting example, sensor information may come from cameras, lidar, light sensors, microphones, IMUs, electromyograms, pressure sensors, and/or proximity/motion sensors. Cameras and lidar may detect movements associated with a specific workout and/or equipment and/or accessories associated with a specific workout. The microphones can detect current breathing patterns. IMUs can detect movements associated with a particular workout. EMGs may detect muscle movements and/or activation associated with a particular movement as well as muscle movements associated with the current breathing pattern.

[0067] Additionally, sensor/passive input receiving module 340 may be configured to receive manual inputs from a user or other operator regarding at least one of a current exercise or a target breathing pattern. For example, a user may manually enter or select an indication of which exercise is being performed. Similarly, the user can manually enter or select a desired target breathing pattern. In this way, a current exercise and/or target breathing pattern may be determined based on the passive input received.

[0068] The processor(s) 330 of the user equipment may receive sensor information directly from onboard sensors and/or use available wireless connections 50 (e.g., Wi-Fi) to obtain sensor information from remote sensors. , Bluetooth, cellular, etc.) may use one or more transceivers (eg, 256, 266). Additionally, sensor/passive input receiving module 340 may be configured to determine whether a detected communication link is available to a wearable or other remote computing device.

[0069] The contextual information receiving module 345 may be configured to receive contextual information indicating the context in which the user is currently performing an exercise in order to consider the total information available about the environment and/or conditions in which the user is exercising. there is. The determined target breathing pattern may then be further based on the received contextual information. For example, a thermometer may indicate that the user is exercising in an extremely cold or hot environment. Similarly, a thermometer can be used to determine the user's body temperature, and if the body temperature is too high, it can ensure selection of a lower target breathing pattern to reduce the intensity of the current exercise, which will help the user cool down. can Additionally, contextual information may include information about the environment (eg, humidity, barometric pressure), time of day, or information about the user's activity levels or wellness that may affect target breathing pattern decisions. can Still further, contextual information includes information from user inputs or other sources, such as the user's age, gender, gender, weight, current experience exercising or at least performing a workout, and/or the user's current health conditions. can do. In some embodiments, the received contextual information may indicate a context in which the user is currently performing an exercise. Thus, the determined target breathing pattern may be further based on the received contextual information.

[0070] As non-limiting examples, camera(s) and/or lidar(s) can collect imaging identifying lighting conditions or other elements of the surrounding environment, thermometers can detect ambient temperature, and microphones can Sounds (eg, current breathing patterns, coughing, sneezing, etc.) may be collected, and electromyograms may collect indications of muscle movements (eg, associated with exercises). Accordingly, contextual information may be received from sensors that provide information to user equipment (eg, 110) and/or local computing devices within the vicinity of user equipment 110.

[0071] To determine contextual information, the contextual information receiving module 345 may also be stored in a memory (eg, 220, 258, 325) or a remote system (eg, 315) using a transceiver (eg, 256, 266) and related components. ) or from a remote source, such as external resources (eg, 320), the database containing one or more data records. A processor of the user equipment may access the data records and compare previously stored information about the sensor data with data received from the sensors to determine what the received sensor indications represent. For example, a lookup table may provide information used to determine an appropriate target breathing pattern corresponding to current temperature, pressure and/or humidity conditions.

[0072] The body movement analysis module 350 may be configured to determine the degree, type and/or rate of a body movement being performed by the user based on sensor or passive inputs received from the sensor/passive input receiving module 340. there is. The user's body movement may help to detect not only which exercise the user is performing, but more specifically, which part of the exercise the user is performing. Many exercises have multiple parts, each with distinct movements that can be associated with different breathing patterns. In this way, the received user body movement information may indicate which part of the exercise the user is currently performing. Additionally, the user's body movements may directly provide information about the user's current breathing patterns. Periodic movement of the user's chest, abdomen and/or nostrils may generally be correlated with the rate at which the user breathes or the depth of those breaths. Additionally, the manner in which the user is breathing may be determined based on some sensor inputs, such as whether the user is breathing diaphragmatically or breathing through the chest.

[0073] Additionally, the analysis of the user's body motion determines which parts of the user's body motion can be attributed to the current motion determined separately from breathing and which parts of the user's body motion is attributed to breathing apart from movements associated with the current motion. You can decide if you can. For example, when a user runs, jumps, or performs other movements that are a natural part of a given workout, the user's chest may move up and down, but these athletic movements do not follow the inhalation of the user's chest, which is a natural part of breathing. movements or exhalation movements. By storing historical respiration measurement data, the user's typical chest movements for the determined workout may be known by body movement analysis module 350 . Accordingly, body motion analysis module 350 may compare the user's current chest movements to such typical chest movements to identify inappropriate or abnormal breathing patterns.

[0074] Users will generally benefit when feedback regarding proper form and breathing is provided during exercise. Proper forms for yoga, for example, include not only muscle activity, but especially body alignment and breathing, which require consistent practice to achieve. Similarly, analysis of body movements by body movement analysis module 350 may, for example, provide the user with feedback to assist the user in performing an exercise using only the muscles that need to be burned during the completion of a repetition of the exercise. can help ensure that you are performing strength training exercises in a safe and effective manner. Tracking the user's progress toward optimal alignment over time can be used to increase/maintain the user's motivation to continue practicing on a regular basis. Performing exercises in an improper form can sometimes make the exercise easier than it should or cause injury to the user. Body alignment may be determined by body motion analysis module 350 as part of body motion analysis. Additionally, if muscles that should not be engaged with a certain intensity are being used, the user will benefit from the body movement analysis module 350 providing real-time feedback on how to improve form for more effective and safe movements. As a non-limiting example, the camera(s) and/or lidar(s) may collect imaging identifying body movement, and/or EMGs may be analyzed by the body movement analysis module 350 ( For example, it may collect indications of muscle movements (associated with movements).

[0075] Still further, power during lifting exercises can be measured using IMUs or wearable cameras, such as in smart glasses (e.g., 130), to measure the relative speed of a lift over a single repetition, set, or workout so that the body motion analysis module ( 350) can be determined. The speed of the concentric portion of the lift can be used by the body motion analysis module 350 as a measure of power, and can be used for tracking as well as guidance (in combination with heart rate data) on when to increase weight or repetitions. Similarly, body motion analysis can be used by body motion analysis module 350 to reduce the weight the user (eg, 5) is using for a workout if the power measurements indicate that the weight is too high. Lower power may indicate that the user is over-trained and needs increased rest between workouts or sets. Power measurements by body movement analysis module 350 can be presented aurally to the user after each repetition, allowing the user to apply that information to guide their own performance during exercise.

[0076] By way of non-limiting example, body motion information may be obtained from sensors that provide information to user equipment (eg, 110) and/or local computing devices within the vicinity of user equipment (eg, adhesive patch sensors 120, smart Glasses 130, smart watch 140, chest strap sensor 150, exercise equipment 160, 170, etc.) may be received by body motion analysis module 350. The body motion analysis module 350 may also be stored in local memory (eg, 220, 258, 325) or a remote system (eg, 315) using a transceiver (eg, 256, 266) and related components, or external resources (eg, , 320) may analyze body movement information by accessing a database containing one or more data records from a remote source.

[0077] The current exercise determination module 355 may be configured to determine a current exercise being performed by the user. In some embodiments, the current workout may be determined based on a determination from body motion analysis module 350 . In some other embodiments, the current workout may be determined by the current workout determination module 355 based on manual user input. In some embodiments, a current workout may be determined by current workout determination module 355 based on input from workout equipment (eg, 160, 170) dedicated to a particular type of workout. In some embodiments, the current workout may be determined by current workout determination module 355 based on a combination of body motion analysis, manual user input, and/or input from exercise equipment or sensors.

[0078] Determination of the current motion is more reliable after initial calibration of the current motion determination module 355 to identify the motion. Accordingly, the user may be prompted to enter, describe, select, and/or perform a particular exercise during calibration of the current exercise determination module 355 . The user equipment may process the information received from the various sensors and correlate or calibrate the information to the displayed movement during its initial calibration. The sensor data collected during the initial calibration can be used by the current workout determination module 355 to automatically identify that workout when performed again later by the user. For example, a processor of user equipment may record and/or analyze sensor data received while a user performs a particular exercise, and correlate various sensor readings to that exercise. The calibration process can enable the processor to later correlate similar sensor data with the displayed workout. Once the calibration process is complete, the results can be stored in memory in the form of look-up tables, and the processor can use the look-up tables to determine which movement is being performed.

[0079] Alternatively or additionally, in response to the processor's subsequent detection of a recognized movement from the calibration process, if extended sensor readings associated with that movement are identified by the user, they may be used to more accurately identify the movement at a later time. there is. The processor may alternatively maintain a rolling average of sensor readings associated with the exercise and prompt the user when the rolling average changes beyond a threshold. The stimulus may ask the user to confirm a calculated guess (ie, estimate) about the exercise being performed to obtain feedback and provide additional corrections for generating updates to previously determined sensor readings associated with the exercise. there is. Various embodiments may apply machine learning to determine updates that may occur from time to time and identify user habits or tendencies regarding specific exercises at specific times of the day or specific days of the week, which exercise This can be useful in determining if this is done. The processor may correlate the contextual information with the determined update. For example, situations where the user had a temperature, sweated more than usual, was unusually active, or exercised on a hot or very cold day could be correlated with an update determined when similar situations occur in the future. .

[0080] Initial calibration of the current motion determination module 355 may require the user to wear one or more additional sensors that may not be needed to subsequently detect that motion. By using multiple types of sensors during initial calibration, the processor can subsequently identify motion when the user is wearing fewer than all such sensors. In this way, the user can give up wearing all the corrective sensors every time he or she performs an exercise.

[0081] As a non-limiting example, the processor(s) 330 of the user equipment may determine the current exercise being performed by the user using active and/or passive calibration techniques. Manual entry of an indication of an exercise being performed may be helpful for later identification of that exercise, particularly during the initial calibration process. However, automatic detection of the current workout by the sensors may also or alternatively be used in the initial calibration process to determine criteria parameters that identify the workout when performed by a particular user. Additionally, the criteria parameters may include contextual factors that may affect detection of motion, such as temperature, environment, time of day, or activity levels of the user, age, gender, weight or health conditions (eg diabetes). information can be taken into account.

[0082] To determine the current workout, current workout determination module 355 may receive information from sensors and/or access a database containing one or more data records. Records may be stored in local memory (e.g. 220, 258, 325) or from a remote source such as a remote system (e.g. 315) or external resources (e.g. 320) using a transceiver (e.g. 256, 266) and related components. can be received from Sensors may similarly be part of user equipment, or may be received from a remote source, such as a remote system (eg 315) or external resources (eg 320) using a transceiver (eg 256, 266) and related components. .

[0083] The target breathing pattern determination module 360 may be configured to determine a target breathing pattern appropriate for the current exercise being performed by the user. For example, a lookup table may provide information used to determine an appropriate target breathing pattern corresponding to a current exercise being performed by the user. The determined target breathing pattern may include a first breathing pattern associated with a first portion of the current workout, and a second breathing pattern that is different from the first breathing pattern and associated with a second portion of the current workout. In some embodiments, more than two different breathing patterns may be associated with exercise. In some embodiments, the target breathing pattern may be based on sensor input received from an athletic sensor indicating how the user is moving during exercise. In some embodiments, the target breathing pattern may be determined based on the context (eg, contextual information) of the exercise being performed (eg, obtained by the contextual information receiving module 345). Further, in some embodiments, the target breathing pattern may be based on information provided by the user via a user interface, such as the user's body type, health goals, and/or level of experience performing the current exercise.

[0084] Additionally, the processor may receive input from the user indicating that an update is required for the target breathing pattern. For example, after providing the user with information about the determined target breathing pattern, the user may feel that the suggested target breathing pattern is too difficult, not difficult enough, or needs to be changed. In response to receiving user input indicating that the user wishes to change the target breathing pattern, the processor may recalculate the target breathing pattern, possibly with additional input from the user.

[0085] Alternatively, after receiving input from the sensor indicating that the user's current breathing pattern or other biometric reading of the user has exceeded a threshold, the processor may determine and present to the user a new target breathing pattern that may be safer for the user. there is. For example, a dangerous breathing threshold is when a user is breathing at a breathing rate of less than 12 or greater than 25 breaths per minute for very light exercise, or at higher relative rates for other exercises that require more exertion. it may be when Conditions that can alter a user's normal breathing rate include asthma, anxiety, pneumonia, congestive cardiac arrest, lung disease, use of drugs, or drug overdose.

[0086] As a non-limiting example, processor(s) 330 of user equipment 110 may determine a target breathing pattern by accessing a database containing one or more data records, such as a lookup table. Records may be stored in local memory (e.g. 220, 258, 325) or from a remote source such as a remote system (e.g. 315) or external resources (e.g. 320) using a transceiver (e.g. 256, 266) and related components. can be received from Records may be maintained on user equipment or received from a remote source, such as a remote system (eg 315) or external resources (eg 320) using a transceiver (eg 256, 266) and related components.

[0087] Sensor activation module 365 may be configured to activate one or more specific sensors in response to specific conditions. In some embodiments, a breathing sensor configured to determine the user's current breathing pattern may be activated in response to the processor determining that the user is performing an exercise. Due to the nature of the movement, additional sensors may be required. Alternatively, additional sensors may be needed so that the respiration sensors can remain inactive (ie, when the user is not exercising) as much as possible. In some embodiments, an additional sensor may be activated in response to the user's current breathing pattern meeting a predetermined threshold. For example, if the user's breathing pattern goes below a low threshold or above a high threshold, the processor can activate an additional sensor to confirm the detected low/high breathing pattern. In some embodiments, a biometric sensor configured to measure vital signs of a user may be activated in response to the user's current breathing pattern meeting a predetermined threshold (eg, a low or high breathing threshold).

[0088] By way of non-limiting example, a further activated sensor may be one or more sensors within user equipment 110 and/or sensors within one or more remote device(s) 315 (e.g., 120 130 in FIGS. 1A-1D , 140, 150, 160, 170).

[0089] Current breathing pattern monitoring module 370 may be configured to monitor the user's current breathing pattern while performing a current exercise based on inputs from the breathing sensor. A respiration sensor may be any one or more sensors configured to detect characteristics of a user's breathing, such as rate, depth, timing and consistency of the user's breaths. In some embodiments, the current breathing pattern may be monitored by regular or continuous measurements obtained from body motion analysis module 350 . In some embodiments, the current breathing pattern may be determined based on input from exercise equipment (e.g., 160, 170) or other sensors (e.g., 120, 130, 140, 150) dedicated to a particular type of exercise. . In some embodiments, the current breathing pattern may be determined based on a combination of body motion analysis and/or input from athletic equipment or other sensors.

[0090] Various embodiments include devices that can be configured to more accurately measure and track a user's breathing pattern by developing, maintaining and using baseline breathing patterns for the individual under different conditions. For example, controlled breathing pattern measurements can be made and recorded on an individual, possibly through a calibration or learning process under different circumstances (eg, changed temperature, time of day, type of activity, etc.); Here the user generally breathes for a predetermined period of time and the sensors calculate one or more breathing patterns, such as the rate, rhythm and/or quality of the breaths. Such controlled breathing measurements use the active participation and input of the user, and are therefore referred to herein as “active baselining”. Active baseline setting can be particularly useful for initially determining a user's regular breathing patterns. Active baseline setting can also help identify conditions in which a user's breathing is irregular, or can be an early warning of a developing health problem. For example, excessive breathing by a user after only low levels of physical activity could be a sign of a breathing or heart problem.

[0091] Rather than using a predetermined reference breathing pattern, a processor implementing various embodiments may compare the user's currently detected breathing pattern to a target breathing pattern without considering the reference breathing pattern. Further, once the processor receives confidence that the sensor readings (eg, from redundant sensors) accurately measure current breathing patterns, the processor can then determine the measured breathing pattern without the user passively or actively inputting information about it. can be used to determine, verify and/or update baseline breathing patterns, which is referred to herein as “passive baselining”. Manual baseline setting can be useful in situations where sensors can reliably measure and determine a user's current breathing pattern. In this way, once an active baseline is established for a user, passive baseline setting can provide for continuous calibration or refinement of the baseline to more accurately estimate the user's breathing pattern.

[0092] As a non-limiting example, the user's current breathing pattern may be monitored and determined from the body motion analysis module 350 . In addition, the current breathing pattern can be detected by sensors providing information to user equipment (eg, 110) and/or local computing devices (eg, adhesive patch sensors 120, smart glasses 130) within the vicinity of user equipment 110. , smart watch 140, chest strap sensor 150, exercise equipment 160, 170, etc.).

[0093] The current breathing pattern monitoring module 370 may also be stored in a local memory (eg 220, 258, 325) or a remote system (eg 315) using a transceiver (eg 256, 266) and related components or external resources ( The breathing pattern information may be received by accessing a database containing one or more data records from a remote source, eg, 320). Additionally, the current breathing pattern monitoring module 370 may store the determined value(s) of the user's current breathing pattern using a local memory (eg, 220, 258, 325) or a transceiver (eg, 256, 266) and related components. It may be stored in memory of a remote source, such as a remote system (eg 315) or external resources (eg 320).

[0094] Normal breathing pattern determination module 375 may be configured to determine when the user's current breathing pattern may be within a normal range for the user. Breathing patterns outside the normal range (ie, abnormal breathing patterns) may be hazardous to the user's health and/or may require initiation of additional actions by the processor. Detection of abnormal breathing patterns may trigger additional information provided to the user, such as additional encouragement or additional commands regarding breathing or motor movements. Breathing patterns that are more than slightly abnormal can be a sign of a health risk to the user. For example, the processor may indicate that the user is breathing at a breathing rate of less than 12 or greater than 25 breaths per minute for very light exercise or at higher relative rates for other exercises requiring more exertion. inputs can be received. Similarly, sudden spikes in the frequency of breathing patterns or irregular breathing patterns may be considered abnormal or even dangerous to the user. Devices implementing some embodiments may continuously monitor and facilitate normal breathing appropriate for the user and the current activity (eg, a particular exercise) or recommend different cadences or other changes in breathing or movements associated with the exercise, thereby preventing the user from breathing at risk. It can be configured to attempt to prevent the pattern from developing.

[0095] As a non-limiting example, processor(s) 330 of user equipment 110 may generate one or more data records, such as a lookup table, indicating that certain breathing patterns or individual parameters of breathing patterns are dangerous to this particular user. By accessing the database including, it is possible to determine when the user's current breathing pattern can be considered normal. Records may be stored in local memory (e.g. 220, 258, 325) or from a remote source such as a remote system (e.g. 315) or external resources (e.g. 320) using a transceiver (e.g. 256, 266) and related components. can be received from Records may be maintained on user equipment or received from a remote source, such as a remote system (eg 315) or external resources (eg 320) using a transceiver (eg 256, 266) and related components.

[0096] The breathing pattern difference determination module 380 may be configured to determine differences between the target breathing pattern determined by the target breathing pattern determination module 360 and the user's current breathing pattern determined by the current breathing pattern monitoring module 370. . In some embodiments, determining the differences between the user's current breathing pattern and a target breathing pattern appropriate for a current exercise performed by the user may change the user's current breathing pattern to a determined number of breaths when the user previously performed the current exercise. Comparing respiratory rate, rhythm and/or quality. In some embodiments, determining differences between a target breathing pattern appropriate for a current exercise performed by the user and a current breathing pattern of the user is determining differences between a target breathing pattern appropriate for the first and second portions of the current exercise and a second portion of the current exercise. determining differences between the user's current breathing pattern during the first portion and the second portion.

[0097] As a non-limiting example, processor(s) 330 of the user equipment may calculate the differences determined by breathing pattern difference determination module 380 . Differences may be reflected in different respiratory rates, rhythm or quality of breaths. Additionally, the user equipment's processor(s) 330 may use one or more transceivers to transmit the determined differences to the remote computing device (e.g., 120, 130, 140) along with instructions on what to do with the information. (e.g. 256, 266) can be used.

[0098] The user information transmission module 385, as determined by the breathing pattern difference determination module 380, transmits information about the determined differences between the user's current breathing pattern and the target breathing pattern suitable for the current exercise performed by the user to the user. It can be configured to provide In some embodiments, the information provided to the user will include differences between a target breathing pattern appropriate for the first and second portions of the current workout and the user's current breathing pattern during the first and second portions of the current workout. can In some embodiments, additional information regarding another target breathing pattern determined in response to the current breathing pattern exceeding the normal breathing threshold may be provided to the user.

[0099] The information provided to the user regarding the determined differences between the target and current breathing patterns may include an actual measure of the rate, volume and/or stability of the user's breathing relative to the target breathing pattern. The provided information may be conveyed to the user via a display (eg 115) on the user equipment (eg 110). Alternatively or additionally, the provided information may be transmitted to a remote source, such as a remote system (eg 315) or external resources (eg 320) using a transceiver (eg 256, 266) and related components. For example, the processor may generate text or render an image on a display of the user equipment to provide an alert message regarding the user's breathing patterns during exercise. In particular, the warning message may speak to the user to stabilize the user's breathing, to remind the user to synchronize the user's breathing with certain athletic movements, or to remind the user not to hold the user's breath. Alternatively, the processor may transmit information to the remote computing device that is configured to cause the remote computing device to perform a notification function on behalf of the user equipment.

[0100] In addition to providing users with feedback on how or when to perform parts of the exercise, the system may provide a score on how often the users' breathing matches designated movements of the exercise. Alternatively, the system may provide a score for how closely the user matches the target breathing pattern. Feedback may be provided after the exercise is complete or as a reminder to breathe how and/or when to breathe or during a session. Similarly, for weight training, the feedback provided can measure whether the user is breathing in on the eccentric portion of the lift and exhaling on the concentric portion of the lift, and provide appropriate feedback.

[0101] After receiving input from the sensor indicating that the user's current breathing pattern or other biometric reading of the user has exceeded a threshold, the display and/or audio output from the system is used to determine a more appropriate target breathing pattern (e.g., running (e.g., change the number of steps between breaths) or cycling (eg, change the number of pedal revolutions per minute). If the user complies with the suggested change in movement pattern, but the user's breathing pattern continues to exceed or exceeds the threshold for a predetermined percentage (eg, 80%) of the time, the system may alert the user to a potential problem. may be advised to rest and/or rest.

[0102] As a non-limiting example, processor(s) 330 of user equipment 110 may use a display (eg, 115 ) and/or a speaker to report determined breathing pattern differences to the user. Additionally, the processor(s) 330 of the user equipment 110 may perform the determined breathing pattern difference, along with instructions regarding how, when and/or under what circumstances the remote computing device notification functions to the user may occur. One or more transceivers (eg, 256, 266) may be used to transmit data to a remote computing device (eg, 120, 130, 140).

[0103] Remote computing device 315 may include one or more processors configured to execute computer program modules similar to those of machine readable instructions 335 described above. By way of non-limiting example, in addition to the wearable devices described above (e.g., 120, 130, 140, 150), remote computing devices may include smart rings, smart appliances, desktop computers, laptop computers, handheld computers, tablet computing platforms , netbooks, other smartphones, gaming consoles, and/or other computing devices.

[0104] External resources 320 may include remote servers that store lookup tables in a database (or a backup copy of a lookup database), sources of information external to system 300, external entities participating in system 300, and/or other resources may be included. In some embodiments, some or all of the functionality attributed herein to external resources 320 may be provided by resources included in system 300 .

[0105] Processor(s) 330 may be configured to execute modules 340, 345, 350, 355, 360, 365, 370, 375, 380 and/or 385, and/or other modules. The processor(s) 330 may include software; hardware; firmware; any combination of software, hardware and/or firmware; and/or other mechanisms for configuring the processing capabilities on processor(s) 330 so that modules 340, 345, 350, 355, 360, 365, 370, 375, 380 and/or 385 and/or It can be configured to run other modules. As used herein, the term "module" can refer to any component or set of components that performs a function attributed to the module. It may include one or more physical processors, processor readable instructions, circuitry, hardware, storage media or any other components during execution of the processor readable instructions.

[0106] The description of the functionality provided by the different modules 340, 345, 350, 355, 360, 365, 370, 375, 380 and/or 385 described below is for illustration purposes, and modules 340, 345 , 350, 355, 360, 365, 370, 375, 380 and/or 385) may provide more or less functionality than described and are not intended to be limiting. For example, one or more of the modules 340, 345, 350, 355, 360, 365, 370, 375, 380, and/or 385 may be eliminated, and some or all of the functionality of the modules 340, 345, 350, 355, 360, 365, 370, 375, 380 and/or 385). As another example, processor(s) 330 may include some or all of the following functionality attributable to one of modules 340, 345, 350, 355, 360, 365, 370, 375, 380 and/or 385. may be configured to execute one or more additional modules capable of performing

[0107] 4A illustrates a method 400 that may be executed by a processor of user equipment and/or one or more other computing devices that provides breathing feedback for improved activity performance, in accordance with various embodiments. 4B, 4C, 4D, 4E, 4F, 4G, 4H and/or 4I are methods 401, 402, 403 that may be performed as part of method 400 in some embodiments. , 404, 405, 406, 407, 408, 409). The operations of methods 400, 401, 402, 403, 404, 405, 406, 407, 408, 409 are intended to be exemplary. In some embodiments, methods 400, 401, 402, 403, 404, 405, 406, 407, 408, 409 may be performed with one or more additional operations not described and/or without one or more of the operations discussed. can be achieved In addition, the operations of methods 400, 401, 402, 403, 404, 405, 406, 407, 408, 409 are shown in FIGS. 4A, 4B, 4C, 4D, 4E, 4F, 4G, The order shown in FIGS. 4H, 4I and 4J and described below is not intended to be limiting.

[0108] Referring to Figures 1A-1J, methods 400, 401, 402, 403, 404, 405, 406, 407, 408, 409 are processor executable instructions stored on a non-transitory processor readable storage medium. One or more processors (eg, of user equipment (eg, 110) and/or one or more other computing devices, including configured wearables (eg, 130, 140, 150) and/or athletic equipment (eg, 160, 170) , 132, 202, 204, 210, 212, 214, 216, 218, 252, 260, 330). The one or more processors may include one or more devices configured through hardware, firmware and/or software that may be specifically designed for the execution of one or more of the operations of the methods.

[0109] 4A illustrates a method 400 that enables a processor of user equipment to provide information about a user's breathing patterns during exercise, in accordance with one or more embodiments.

[0110] At block 420, the processor of the user equipment may perform operations including determining a current exercise being performed by the user. To make a decision at block 420, the processor may use a body motion analysis module (eg, 350) and/or a current motion determination module (eg, 355). Also, at block 420, the processor may use external resources (eg, 315) or stored in local memory (eg, 220, 258) or remote systems (eg, 256, 266) and related components using the transceiver (eg, 256, 266). 320) to access a database containing one or more data records from a remote source. The database may provide information about known workouts as well as movements associated with those workouts. The means for performing the operations of block 420 may be a remote system (eg 315) coupled to a memory (eg 220, 258, 325) or using a transceiver (eg 256, 266) and related components or an external resource. (eg, 132, 202, 204, 210, 212, 214, 216, 218, 252, 260, 330) from a remote source, such as (eg, 320).

[0111] At block 422, the processor of the user equipment may perform actions including determining a target breathing pattern appropriate for the current exercise being performed by the user. To perform the operations of block 422, the processor can use a target breathing pattern determination module (eg, 360). Further, at block 422, the processor may use external resources (e.g., 315) or stored in local memory (e.g., 220, 258) or remote systems (e.g., 256, 266) and related components. 320) to access a database containing one or more data records from a remote source. The database may provide information about target breathing patterns as well as exercises associated with those target breathing patterns. The means for performing the operations of block 422 may be a remote system (eg 315) coupled to a memory (eg 220, 258, 325) or using a transceiver (eg 256, 266) and related components or an external resource. (eg, 132, 202, 204, 210, 212, 214, 216, 218, 252, 260, 330) from a remote source, such as (eg, 320).

[0112] At block 424, the processor of the user equipment may perform an action that includes monitoring the user's current breathing pattern while performing the current exercise based on the inputs from the breathing sensor. To perform the operations of block 424, the processor can use a current breathing pattern monitoring module (eg, 370). Further, at block 424, the processor may include user equipment (e.g., 110), devices having sensors (e.g., 120, 130, 140, 150) and/or athletic equipment (e.g., 160, 170). Input about the user's current breathing pattern may be received from the sensors. Means for performing the operations of block 424 may include a processor (e.g., 132, 202, 204, 210, 212, 214, 216, 218, 252, 260, 330) coupled to a memory (e.g., 220, 258, 325). ) and sensors (eg, 110, 120, 130, 140, 150, 160, 170). Other means for performing the operations of block 424 may include a remote source such as a remote system (eg 315) or external resources (eg 320) using the transceiver (eg 256, 266) and related components. can

[0113] At block 426, the processor of the user equipment may perform an operation that includes determining differences between the user's current breathing pattern and a target breathing pattern appropriate for a current exercise performed by the user. To perform the operations of block 426, the processor can use a breathing pattern difference determination module (eg, 380). Also, at block 426, the processor may use external resources (e.g., 315) or stored in local memory (e.g., 220, 258) or remote systems (e.g., 256, 266) and related components. 320) to access a database containing one or more data records from a remote source. The database may provide information regarding target breathing patterns, current breathing patterns, and/or other breathing patterns, as well as exercises associated with those breathing patterns. The means for performing the operations of block 426 may be a remote system (eg 315) coupled to a memory (eg 220, 258, 325) or using a transceiver (eg 256, 266) and related components or an external resource. (eg, 132, 202, 204, 210, 212, 214, 216, 218, 252, 260, 330) from a remote source, such as (eg, 320).

[0114] At block 428, the processor of the user equipment may perform an action that includes providing the user with information regarding the determined differences between the user's current breathing pattern and a target breathing pattern appropriate for a current exercise performed by the user. . To perform the operations of block 428, the processor can use a user information delivery module (eg, 385). Further, at block 428, the processor may cause a display (eg, 115) to show information regarding the determined differences between the user's current breathing pattern and a target breathing pattern appropriate for the current exercise being performed by the user. Information about the determined differences may take the form of a message to the user (eg, "Steady Your Breath"). Additionally or alternatively, the processor may, at block 428 , initiate an audible alert, flash or flash a light, and/or generate a vibration to alert the user. Additionally or alternatively, the processor may instruct the remote computing device to display an indication of the determined differences in (current versus target) breathing patterns. Means for performing the operations of block 428 may be coupled to a display (eg 115), a speaker, a vibration device, a memory (eg 220, 258, 325) or a transceiver (eg 256, 266) and related components. processor (e.g., 132, 202, 204, 210, 212, 214, 216, 218, 252, 260, 330) from a remote source, such as a remote system (e.g., 315) or external resources (e.g., 320) using can include

[0115] Providing information about the difference between the user's current breathing pattern and the target breathing pattern can help the user achieve the target breathing pattern and obtain additional benefits from the current exercise. For example, if the processor reminds the user to steady the user's breathing, the user can maximize the benefits of the exercise he is performing if he complies.

[0116] The operations of method 400 may be repeated, for example, if the current workout changes or the user's current breathing pattern changes.

[0117] 4B illustrates a method 401 by which a processor may provide information regarding a user's breathing patterns during exercise. At block 430, the processor may receive sensor input from the athletic sensor that provides information about user body movements, and the current movement determined at block 420 may be based on the sensor input received from the athletic sensor. . For example, the processor may, from motion sensor inputs received from the smart watch 140, move from a first position near the user's chest with the arms extended away from the chest (see position A in FIG. 1A ) to a second position (see position A in FIG. The movement of the user's arms or hands to the position B of FIG. 1A) may be recognized. This body movement information enables the processor to determine that the user is performing barbell bench presses (as shown in FIG. 1A ). Similarly, images of bar 92 and weights 94 from camera images received from smart glasses (eg, 130) may reinforce a conclusion by the processor that the user is performing barbell bench presses. Similarly, the processor may recognize yoga movements/poses from camera images received from a camera of the user equipment (eg, 110) and thus determine that the user is performing yoga (as shown in FIG. 1B). . As another example, a processor receiving sensor inputs from an athletic sensor may recognize a rate and/or type of movement in one or more parts of the body associated with a particular exercise. In this way, the rate/range of cycling movements and/or their cadence, running movements and/or their strides, or the rate/range of swimming movements and/or their strokes can be determined. In some embodiments, the target breathing pattern (eg, determined at block 422 ) may be based on sensor input received from an athletic sensor indicating how the user is moving during exercise.

[0118] To perform the operations of block 430, the processor may use the sensor/passive input receiving module 340. Means for performing the operations of block 430 may be a remote source such as a remote system (e.g. 315) or external resources (e.g. 320) using a transceiver (e.g. 256, 266) and related components and memory (e.g. , 220, 258, 325) coupled to the processor (eg, 132, 202, 204, 210, 212, 214, 216, 218, 252, 260, 330).

[0119] Following the actions of block 430, the processor may perform the actions of block 420 of method 400 as described.

[0120] 4C illustrates a method 402 by which a processor may provide information regarding a user's breathing patterns during exercise. At block 432, the processor may receive sensor input from an athletic sensor that provides athletic information regarding a current exercise, the athletic sensor associated with exercise equipment being used by the user to perform the current exercise. For example, a processor may recognize a user running on a treadmill from a message received from a treadmill (eg, 160) that is in close proximity, indicating that the user is running on the treadmill. Alternatively, the processor may receive camera images received from a camera included in the treadmill (eg, 160) and accordingly determine that the user is running. As another example, the processor may recognize a user exercising on a stationary bicycle from a wireless communication link (eg, 50) between a user equipment (eg, 110) and a stationary bicycle (eg, 170). Based on the wireless communication link, the processor may determine that the user is riding a stationary bicycle. Alternatively, the processor may receive camera images from a camera included in a stationary bicycle (eg, 170 ) and thus determine that the user is riding a bicycle.

[0121] To perform the operations of block 432, the processor may use the sensor/passive input receiving module 340. Means for performing the operations of block 430 may be a remote source such as a remote system (e.g. 315) or external resources (e.g. 320) using a transceiver (e.g. 256, 266) and related components and memory (e.g. , 220, 258, 325) coupled to the processor (eg, 132, 202, 204, 210, 212, 214, 216, 218, 252, 260, 330).

[0122] Following the actions of block 432, the processor may perform the actions of block 420 of method 400 as described.

[0123] 4D illustrates a method 403 by which a processor may provide information regarding a user's breathing patterns during exercise. At block 434, the processor may receive sensor input from an athletic sensor that provides athletic information regarding the current exercise, the athletic sensor associated with exercise equipment being used by the user to perform the current exercise. For example, the processor can recognize from camera images received from smart glasses 130 or motion sensor and gyroscope inputs received from smart watch 140 as users perform different parts of an exercise. While the entire workout is barbell bench presses, one portion of the workout may involve the user pushing a barbell away from their chest (eg, from position A to position B in FIG. 1A ). The second part of the workout may involve the user lowering the barbell from an elevated position to a lower position (eg, from position B to position A in FIG. 1A ). This body movement information may enable the processor to associate different breathing patterns with different parts of the movement.

[0124] To perform the operations of block 434, the processor may use the sensor/passive input receiving module 340. Means for performing the operations of block 430 may be a remote source such as a remote system (e.g. 315) or external resources (e.g. 320) using a transceiver (e.g. 256, 266) and related components and memory (e.g. , 220, 258, 325) coupled to the processor (eg, 132, 202, 204, 210, 212, 214, 216, 218, 252, 260, 330).

[0125] Following the actions of block 434, the processor may perform the actions of block 420 of method 400 as described.

[0126] 4E illustrates a method 404 by which a processor may provide information regarding a user's breathing patterns during exercise. At block 436, the processor may receive manual user input regarding at least one of a current workout or a target breathing pattern, and determining the target breathing pattern is further based on the received manual user input. For example, the processor may receive manual input on a treadmill (eg, 160) or exercise bike (eg, 170) indicating what exercise the user is performing. Alternatively, the processor may use user equipment (e.g., 110 ) or a manual input input to a wearable such as a smart watch (eg, 140).

[0127] To perform the operations of block 436, the processor may use the sensor/passive input receiving module 340. Means for performing the operations of block 430 may be a remote source such as a remote system (e.g. 315) or external resources (e.g. 320) using a transceiver (e.g. 256, 266) and related components and memory (e.g. , 220, 258, 325) coupled to the processor (eg, 132, 202, 204, 210, 212, 214, 216, 218, 252, 260, 330).

[0128] Following the actions of block 434, the processor may perform the actions of block 420 of method 400 as described.

[0129] 4F illustrates a method 405 that enables a processor of user equipment to receive contextual information that can be used to select a target breathing pattern, in accordance with some embodiments.

[0130] At block 438, following the actions of block 420, the processor of the user equipment may perform actions including receiving context information indicating a context in which the user is currently performing an exercise, Determining the breathing pattern is further based on the received contextual information. For example, the processor may receive a sensor input indicating that the user's body temperature is high, from a thermometer in the user's smart watch (eg, 140). In this way, the processor may select a low target breathing pattern to give the user's body a chance to recover from the heat. Alternatively, the processor may send information providing profile and/or biometric information about the user (eg, the user's body type, fitness goals, level of experience with the current exercise, age, gender, weight, etc.) to the user equipment. (eg, 110), which can be used to select an appropriate target breathing pattern for a particular workout. To perform the operations of block 438, the processor can use context information receiving module 345. Means for performing the operations of block 438 may be a remote system (eg 315) coupled to a memory (eg 220, 258, 325) or using a transceiver (eg 256, 266) and related components or an external resource. (eg, 132, 202, 204, 210, 212, 214, 216, 218, 252, 260, 330) from a remote source, such as (eg, 320).

[0131] By way of non-limiting example, contextual information may include user equipment (eg 110 ) and/or local computing devices within the vicinity of user equipment 110 (eg smart glasses 130 , smart watch 140 , chest strap sensor 150 ), etc.) may be received from sensors that provide information. Contextual information may also be stored in local memory (e.g., 220, 258, 325) or from a remote source, such as a remote system (e.g., 315) or external resources (e.g., 256, 266) and related components. 320) by accessing a database containing one or more data records.

[0132] Following the actions of block 438, the processor may perform the actions of block 422 of method 400 as described.

[0133] 4G illustrates a method 406 by which the processor may determine another target breathing pattern for the user when the user's current breathing pattern is not within the normal range.

[0134] At decision block 440, following the actions at block 424, the processor of the user equipment may perform actions that include determining whether the current breathing pattern exceeds a normal breathing pattern threshold. For any given person, normal breathing patterns may change, and individual parameters of that person's breathing patterns, such as the rate, rhythm or quality of breathing movement, may also change. Accordingly, one or more thresholds representing typical ranges for one or more of such parameters may be set. If these thresholds are exceeded, additional actions by the processor, such as activating one or more additional sensors, determining another target breathing pattern for the user, or additional information that may help the user correct the breathing pattern It can be designed to trigger an action presented to the user. For each parameter individual thresholds can be set that can trigger additional actions. In this way, any one of the user's breathing rate, rhythm or quality of breathing movement may trigger the system to perform additional actions. Additionally, the system can be configured to combine the thresholds for each parameter that are lower than the individual thresholds to determine whether to perform additional actions when one or more of those parameters are exceeded. For example, additional actions may be triggered if both of the user's combined rate and rhythm threshold are exceeded, even if the higher individual rate and rhythm thresholds are not exceeded. When a user's breathing rate is too high or too low, it can be an indication of a life-threatening health problem. The normal breathing pattern threshold may be a predetermined upper and/or lower limit of breaths per minute. Similarly, abnormally shallow breaths (eg, 25% shallower than normal for a user) may reflect the development of a dangerous health condition. Thus, a predetermined limit on the shallowness of the user's current breathing pattern may be used as the normal breathing pattern threshold. To make a decision at decision block 440, the processor may use a normal breathing pattern determination module (eg, 375). Further, at decision block 440, the processor may use external resources (e.g., 315) or stored in local memory (e.g., 220, 258) or remote systems (e.g., 256, 266) and related components. , 320) to access a database containing one or more data records from a remote source. The database may provide information regarding breathing pattern thresholds, exceeding which may be considered abnormal or dangerous to the user. The means for performing the operations of block 420 may be a remote system (eg 315) coupled to a memory (eg 220, 258, 325) or using a transceiver (eg 256, 266) and related components or an external resource. (eg, 132, 202, 204, 210, 212, 214, 216, 218, 252, 260, 330) from a remote source, such as (eg, 320).

[0135] In response to a determination that the user's current breathing pattern does not exceed the normal breathing pattern threshold (ie, decision block 440 =“No”), the processor may perform the operations of block 426 .

[0136] In response to a determination that the user's current breathing pattern exceeds the normal breathing pattern threshold (ie, decision block 440 = "yes"), the processor determines at block 442 another target breathing pattern for the user to achieve. operations can be performed, including To make the determination at block 442, the processor may use a target breathing pattern determination module (eg, 360). Further, at block 442, the processor may use external resources (e.g., 315) or stored in local memory (e.g., 220, 258) or remote systems (e.g., 256, 266) and related components. 320) to access a database containing one or more data records from a remote source. The database may provide information about target breathing patterns as well as exercises associated with those target breathing patterns. Means for performing the operations of block 442 may be a remote system (eg 315) coupled to a memory (eg 220, 258, 325) or using a transceiver (eg 256, 266) and related components or an external resource. (eg, 132, 202, 204, 210, 212, 214, 216, 218, 252, 260, 330) from a remote source, such as (eg, 320).

[0137] Following the actions of block 442, the processor may perform the actions of block 424 of method 400 as described.

[0138] 4H illustrates a method 407 that enables a processor of user equipment to activate a sensor to measure and/or verify a user's current breathing pattern, in accordance with some embodiments.

[0139] At block 444, following the actions at block 420, the processor of the user equipment, in response to determining that a current exercise is being performed by the user, determines the user's current breathing pattern while performing the current exercise. You can perform actions that include activating a respiration sensor configured to monitor. A user may be wearing a chest strap (eg, 150) configured to detect chest movements associated with breathing but operating in a dormant mode until awakened by a signal from user equipment (eg, 110). Thus, in response to the processor of the user equipment determining that the user is exercising, the processor may signal the chest strip to wake from sleep mode.

[0140] To perform the operations of block 444, the processor can use sensor activation module 365. The means for performing the operations of block 444 may be a remote system (eg 315) coupled to a memory (eg 220, 258, 325) or using a transceiver (eg 256, 266) and related components or an external resource. (eg, 132, 202, 204, 210, 212, 214, 216, 218, 252, 260, 330) from a remote source, such as (eg, 320).

[0141] Following the actions of block 444, the processor may perform the actions of block 422 of method 400 as described.

[0142] 4I illustrates a method 408 that enables a processor of user equipment to activate an additional sensor, in accordance with some embodiments.

[0143] At block 446, in response to a determination that the current breathing pattern of the user exceeds the normal breathing pattern threshold (ie, decision block 440 = "yes"), the processor of the user equipment includes activating an additional sensor. actions can be performed. The additional sensor may be another respiration sensor for redundant and/or more accurate measurements. For example, if one breathing sensor (eg, exercise equipment sensor) is already providing inputs regarding the current breathing pattern, in response to determining that the user's current breathing pattern exceeds a normal breathing pattern threshold (eg, , on the wearable) a second respiration sensor may be activated. Alternatively, the additional sensor may be a biometric sensor for measuring vital signs of the user. In this way, in response to determining that the user's current breathing pattern exceeds the normal breathing pattern threshold, a biometric sensor such as a heart rate monitor may be activated to ensure that the level of exercise does not pose a risk to the user.

[0144] Alternatively, subsequent to the actions at block 444, the user equipment's processor may perform actions that include activating an additional sensor. For example, in response to the processor determining that the user is performing a high-intensity exercise (eg, at block 420), in addition to activating a respiration sensor at block 444, the processor at block 446 may activate a heart rate monitor or other biometric sensor to alert the user if the user's heart rate or other vital signs become too high during exercise. As a further example, in response to determining that a currently active breathing sensor is insufficient or most suitable for measuring the user's breathing patterns, the processor may activate an additional sensor at block 446 .

[0145] To perform the operations of block 446, the processor can use sensor activation module 365. Means for performing the operations of block 446 may be a remote system (eg 315) coupled to a memory (eg 220, 258, 325) or using a transceiver (eg 256, 266) and related components or an external resource. (eg, 132, 202, 204, 210, 212, 214, 216, 218, 252, 260, 330) from a remote source, such as (eg, 320).

[0146] Following the actions of block 446, the processor may perform the actions of block 422 of method 400 as described.

[0147] 4J illustrates a method 409 that allows a processor of user equipment to distinguish between body movements associated with a current workout and body movements associated only with breathing, in accordance with some embodiments.

[0148] At block 448, subsequent to the operations at block 424, the processor at the user equipment includes determining a first range of body movements by the user due to the determined current movement apart from respiration. and the user's current breathing pattern is associated with a second range of body movement by the user that is attributable to breathing and separate from the first range of body movement. For example, when performing a barbell bench press exercise (see FIG. 1A ), the user's chest rises and falls slightly while moving the barbell between a lowered position (eg, position A) and an elevated position (eg, position B). and this chest movement may be associated with a first range of body movements by the user resulting from a current movement determined separately from breathing. Additionally, the user's chest may rise and fall as part of the normal breathing process, and this chest movement may be attributable to breathing and may be distinct from a first range of body movement.

[0149] To perform the operations at block 448 , the processor may use body motion analysis module 350 and current breathing pattern monitoring module 370 . Means for performing the operations of block 448 may be a remote system (eg 315) coupled to a memory (eg 220, 258, 325) or using a transceiver (eg 256, 266) and related components or an external resource. (eg, 132, 202, 204, 210, 212, 214, 216, 218, 252, 260, 330) from a remote source, such as (eg, 320).

[0150] Following the actions of block 448, the processor may perform the actions of block 426 of method 400 as described.

[0151] Various embodiments (including but not limited to those discussed above with reference to FIGS. 1A-4J ) may be implemented on various computing devices, an example of which is illustrated in FIG. 5 in the form of a server. Referring to FIGS. 1A-5 , a networked computing device 500 may include a processor 501 coupled to volatile memory 502 and a large-capacity non-volatile memory, such as a disk drive 503 . The network computing device 500 may also include a peripheral memory access device, such as a floppy disk drive, compact disc (CD) or digital video disc (DVD) drive 506 coupled to the processor 501 . Network computing device 500 also includes network access ports 504 coupled to processor 501 for establishing data connections with a network, such as the Internet and/or local area network coupled to other system computers and servers. (or interface). Network computing device 500 may include one or more antennas 507 for transmitting and receiving electromagnetic radiation that may be coupled to a wireless communication link. Network computing device 500 may include additional access ports for coupling to peripherals, external memory or other devices, such as USB, Firewire, Thunderbolt, and the like.

[0152] Various embodiments (including but not limited to those discussed above with reference to FIGS. 1A-4J) may be implemented on a variety of computing devices, an example of which is illustrated in FIG. 6 in the form of a mobile computing device. . Referring to FIGS. 1A-6 , a mobile computing device 600 is coupled to a first SoC (eg, a 5G capable SoC) to a second SoC 204 (eg, a 5G capable SoC) such as D2D links established in dedicated ITS 5.9 GHz spectrum communications. 202) (eg, SoC-CPU). The first SOC 202 and/or the second SOC 204 may be coupled to internal memories 325 and 625 , display 115 and speaker 614 . Additionally, the mobile computing device 600 may include one or more wireless transceivers 266 coupled to the one or more processors of the first SOC 202 and/or the second SOC 204 (eg, a wireless data link and/or or one or more antennas 604 for transmitting and receiving electromagnetic radiation, which may be connected to a cellular transceiver, etc.). Mobile computing devices 600 may also include menu selection buttons or rocker switches 620 for receiving user inputs.

[0153] The mobile computing devices 600 further digitize sound received from the microphone into data packets suitable for wireless transmission and decode the received sound data packets to produce analog signals that are provided to a speaker to produce sound. An encoding/decoding (CODEC) circuit 610 may be included. In addition, one or more of the processors of the first SOC 202 and/or the second SOC 204, the wireless transceiver 266, and the CODEC circuit 610 includes a digital signal processor (DSP) circuit (not shown separately). can include

[0154] Various embodiments (including the embodiments discussed above with reference to FIGS. 1A-4J ) may be implemented on various wearable devices, an example of which is illustrated in FIG. 7 in the form of smart glasses 130 . Referring to FIGS. 1A-7 , smart glasses 130 may operate like conventional glasses, but with heads-up display or augmented reality features on or near lenses 731 and a built-in camera. 735 and can operate using advanced computer features and sensors. Like any eyeglasses, smart glasses may include a frame 702 coupled to temples 704 that fit alongside the wearer's head and behind the ears. Frame 702 holds lenses 731 in place in front of the wearer's eyes when nose pads 706 on bridge 708 are placed on the wearer's nose.

[0155] In some embodiments, smart glasses 130 may be built into one or both temples 704 of frame 702 and configured to project images onto optical lenses 731 . an image rendering device 714 (eg, an image projector). In some embodiments, image rendering device 714 may include a light-emitting diode (LED) module, light tunnel, homogenizing lens, optical display, fold mirror, or other components that are well known projectors or head mounted displays. there is. In some embodiments (eg, those in which image rendering device 714 is included or not used), optical lenses 731 can be or include see-through or partially see-through electronic displays. can In some embodiments, optical lenses 731 include image generating elements, such as see-through Organic Light-Emitting Diode (OLED) display elements or liquid crystal on silicon (LCOS) display elements. In some embodiments, optical lenses 731 may include independent left and right eye display elements. In some embodiments, optical lenses 731 may include or act as a light guide for directing light from the display elements to the wearer's eyes.

[0156] The smart glasses 130 acquire information about external conditions and wearer actions that may be useful in detecting images, sounds, muscle movements, and other phenomena that may be useful in determining an exercise being performed. It may include a number of external sensors that may be configured to. In some embodiments, smart glasses 130 may include a camera 735 configured to image objects in front of the wearer into still images or a video stream, which may be used by another computing device (e.g., a mobile device ( 600)). In some embodiments, smart glasses 130 may include a microphone 710 positioned and configured to record sounds in the vicinity of the wearer. In some embodiments, multiple microphones are placed at different locations on the frame 702, such as temples 704 near the chin, to record sounds emanating from the wearer, such as jaw movements, breathing sounds, and the like. It can be positioned at the distal end of. In some embodiments, the smart glasses 130 are mounted on one or both temples 704 , such as near the temples or over the ears, and the nerves and muscles in the chin and temple region of the wearer are mounted. may include one or more electromyograms 716 configured to measure electrical activity. In some embodiments, smart glasses 130 may include pressure sensors configured to sense facial movements, such as nose pads 706 . In some embodiments, the smart glasses 130 may include other sensors for collecting information related to the user's conditions, which may be useful in determining the user's lung condition, oxygen levels, and/or the user's breathing pattern. eg, a thermometer, heart rate monitor, body temperature sensor, pulse oximeter, etc.).

[0157] Processing system 712 may include processing and communications SOC 202, which may include one or more processors (eg, 132, 202, 204, 210, 212, 214, 216, 218), among which processors One or more may consist of processor executable instructions to perform the operations of various embodiments. Processing and communications SOC 202 may include one or more internal sensors 720, internal memory 722, and one or more wireless data links to establish a wireless data link with an external computing device (eg, mobile device 600), such as via a Bluetooth link. Communication circuitry 724 coupled to antenna 726 may be coupled. Processing and communications SOC 202 also controls and receives data from camera 735, microphone(s) 710, one or more EMGs 716, and other sensors positioned on frame 702. may be coupled to sensor interface circuitry 728 configured to.

[0158] Internal sensors 720 may include an IMU including electronic gyroscopes, accelerometers, and a magnetic compass configured to measure movements and orientation of the wearer's head. Internal sensors 720 may further include a magnetometer, altimeter, odometer and atmospheric pressure sensor, as well as other sensors useful for determining orientation and movements of smart glasses 130 . Such sensors may, in various embodiments, be useful for detecting head movements associated with consuming liquids as described.

[0159] Processing system 712 may further include a power source, such as a rechargeable battery 730 coupled to SOC 202 as well as external sensors on frame 702 .

[0160] Processors implementing various embodiments may be any programmable microprocessor, microcomputer or multiplexer that can be configured by software instructions (applications) to perform various functions, including those of various aspects described herein. It may be a processor chip or chips. In some communication devices, multiple processors may be provided, such as one processor dedicated to wireless communication functions and one processor dedicated to running other applications. Typically, software applications may be stored in internal memory before they are accessed and loaded into the processor. A processor may include internal memory sufficient to store application software instructions.

[0161] As used in this application, the terms "component," "module," "system," and the like refer to hardware, firmware, a combination of hardware and software, software, or running software that is configured to perform specific operations or functions. It is intended to include such (but not limited to) computer-related entities. For example, a component can be (but is not limited to) a process, processor, object, executable file, thread of execution, program, and/or computer that runs on a processor. By way of example, both an application running on a processor of a communication device and a communication device may be referred to as a component. One or more components can reside within a process and/or thread of execution and a component can be localized on one processor or core and/or distributed between two or more processors or cores. Additionally, these components can execute from various non-transitory computer readable media having various instructions and/or data structures stored thereon. Components may communicate via local and/or remote processes, function or procedure calls, electronic signals, data packets, memory reads/writes and other known network, computer, processor and/or process related communication methods. can

[0162] A number of different cellular and mobile communication services and standards are available or contemplated in the future, all of which may implement and benefit from various aspects. Such services and standards include, for example, third generation partnership project (3GPP), long term evolution (LTE) systems, 3rd generation wireless mobile communication technology (3G), 4th generation wireless mobile communication technology (4G), 5th generation wireless mobile communication technology. Technology (5G), global system for mobile communications (GSM), universal mobile telecommunications system (UMTS), 3GSM, general packet radio service (GPRS), code division multiple access (CDMA) systems (e.g. cdmaOne, CDMA1020TM), EDGE , advanced mobile phone system (AMPS), digital AMPS (IS-136/TDMA), evolution-data optimized (EV-DO), digital enhanced cordless telecommunications (DECT), Worldwide Interoperability for Microwave Access (WiMAX), wireless local (WLAN) area network), WPA, Wi-Fi Protected Access I & II (WPA2), integrated digital enhanced network (iden), C-V2X, V2V, V2P, V2I and V2N. Each of these technologies involves the transmission and reception of, for example, voice, data, signaling and/or content messages. Any references to terminology and/or technical details relating to a particular telecommunications standard or technology are for illustrative purposes only and do not limit the scope of the claims to a particular telecommunications system or technology unless specifically recited in claim language. It should be understood that it is not intended to be.

[0163] Implementation examples are described in the following paragraphs. While some of the following implementation examples are described in terms of example methods, additional example implementations include: Exemplary methods discussed in ; the example methods discussed in the following paragraphs implemented by a computing device that includes means for performing the functions of the example methods; and the example methods discussed in the following paragraphs embodied as a non-transitory processor-readable storage medium having stored thereon processor-executable instructions configured to cause a processor of a computing device to perform operations of the example methods.

[0164] Example 1. A method executed by a processor of user equipment to provide information regarding breathing patterns of a user during exercise includes: determining a current exercise being performed by a user; determining a target breathing pattern appropriate for a current exercise performed by the user; monitoring a user's current breathing pattern while performing a current exercise based on inputs from the breathing sensor; determining differences between a target breathing pattern appropriate for a current exercise performed by the user and a current breathing pattern of the user; and providing the user with information about the determined differences between the user's current breathing pattern and a target breathing pattern appropriate for the current exercise performed by the user.

[0165] Example 2. The method of example 1 further includes receiving sensor input from the athletic sensor that provides information about user body movements, wherein determining the current exercise is based on the sensor input received from the athletic sensor. .

[0166] Example 3. The method of example 2, the target breathing pattern is based on sensor input received from the motion sensor indicating how the user is moving during the exercise.

[0167] Example 4. The method of any one of Examples 1-3 further comprising receiving sensor input from an athletic sensor that provides athletic information relating to a current exercise, wherein the athletic sensor is configured by a user to perform the current exercise. Associated with the exercise equipment being used.

[0168] Example 5. The method of any one of Examples 1-4 includes receiving user body movement information from an athletic sensor indicating which part of a first or second part of a current exercise the user is currently performing. further comprising, wherein the target breathing pattern includes a first breathing pattern associated with a first portion of the current workout, and a second breathing pattern different from the first breathing pattern and associated with a second portion of the current workout; Determining differences between a target breathing pattern appropriate for a current exercise performed by the user and a current breathing pattern of the user may include: a current breathing pattern of the user during a first portion and a second portion of the current workout and a first portion and a second portion of the current workout; determining differences between target breathing patterns appropriate for the second portion; and providing information to the user may include providing the user with information about differences between a target breathing pattern appropriate for the first and second parts of the current exercise and a current breathing pattern of the user during the first and second parts of the current exercise. It includes the step of providing

[0169] Example 6. The method of any one of Examples 1-5 further comprising receiving a passive user input regarding at least one of a current exercise or a target breathing pattern, wherein determining the target breathing pattern is performed by the received passive user input. Further based on the input.

[0170] Example 7. The method of any one of Examples 1-6 further includes receiving contextual information indicating a context in which the user is currently performing an exercise, wherein determining a target breathing pattern comprises receiving contextual information additionally based on

[0171] Example 8. The method of any one of Examples 1-7, wherein the target breathing pattern is based at least in part on at least one of the user's body type, fitness goals, or level of experience performing the current exercise.

[0172] Example 9. The method of any one of Examples 1-8 includes determining another target breathing pattern to be achieved by the user in response to the current breathing pattern exceeding a normal breathing pattern threshold; and providing additional information about other target breathing patterns to the user.

[0173] Example 10. The method of any one of Examples 1-9, in response to determining by the user that a current exercise is being performed, activating a respiration sensor configured to monitor a current breathing pattern of the user while performing a current exercise. Include more steps.

[0174] Example 11. The method of any one of Examples 1-10, wherein determining differences between a target breathing pattern appropriate for a current exercise performed by the user and a current breathing pattern of the user may include: comparing the user's current breathing pattern with at least one of the user's previously determined breathing rate, rhythm or quality.

[0175] Example 12. The method of any one of Examples 1-11 further includes activating an additional sensor in response to the user's current breathing pattern exceeding a normal breathing pattern threshold.

[0176] Example 13. The method of any one of Examples 1-12 further comprising determining a first range of body movements by the user due to the determined current movement apart from breathing, wherein the user's current breathing pattern is respiration. and is associated with a second range of body movements by the user that is separate from the first range of body movements.

[0177] Example 14. The method of any one of Examples 1-13, wherein the user's current breathing pattern includes at least one of a rate, rhythm or quality of breathing movement.

[0178] Example 15. The method of any one of Examples 1-14, wherein providing the user with information regarding the determined differences includes notifying the user via at least one of a visual, audible, or tactile alert.

[0179] Example 16. The method of any one of Examples 1-15, wherein the current exercise is determined based on exercise equipment being used by the user, and a target breathing pattern appropriate for the current exercise being performed by the user and the user's current breathing pattern Information about the determined differences between the liver is provided to the user via feedback from the exercise equipment.

[0180] The various aspects illustrated and described are provided merely as examples to illustrate various features of the claims. However, features shown and described for any given aspect are not necessarily limited to the associated aspect and may be used or combined with other aspects shown and described. Additionally, the claims are not intended to be limited by any single exemplary aspect. For example, one or more of the operations of the methods may be replaced with or combined with one or more of the operations of the methods.

[0181] The above method descriptions and process flow diagrams are provided only as illustrative examples, and are not intended to require or imply that the actions in the various aspects must be performed in the order presented. As will be appreciated by one skilled in the art, the order of actions in the above aspects may be performed in any order. Words such as “after,” “then,” “next to,” and the like are not intended to limit the order of operations; These words are used to guide the reader through the description of the methods. Additionally, for example, any references to a singular number of claim elements should not be construed as limiting the element to the singular number.

[0182] The various illustrative logical blocks, modules, components, circuits, and algorithmic operations described in connection with the aspects disclosed herein may be implemented as electronic hardware, computer software, or combinations of both. To clearly illustrate this interchangeability of hardware and software, various illustrative components, blocks, modules, circuits, and operations have been described above generally in terms of their functionality. Whether this functionality is implemented in hardware or software depends on the particular application and the design constraints imposed on the overall system. Skilled artisans may implement the described functionality in varying ways for each particular application, but such aspect decisions should not be interpreted as causing a departure from the scope of the claims.

[0183] Hardware used to implement the various illustrative logics, logic blocks, modules, and circuits described in connection with the various aspects disclosed herein may include a general-purpose processor, digital DSP (DSP) designed to perform the functions described herein. signal processor), ASIC, field programmable gate array (FPGA) or other programmable logic device, discrete gate or transistor logic, discrete hardware components, or any combination thereof. A general purpose processor may be a microprocessor, but in the alternative the processor may be any conventional processor, controller, microcontroller or state machine. A processor may also be implemented as a combination of receiver smart objects, such as a combination of a DSP and a microprocessor, a plurality of microprocessors, one or more microprocessors in conjunction with a DSP core, or any other such configuration. Alternatively, some operations or methods may be performed by circuitry specific to a given function.

[0184] In one or more aspects, the described functions may be implemented in hardware, software, firmware, or any combination thereof. If implemented in software, these functions may be stored as one or more instructions or code on a non-transitory computer-readable storage medium or a non-transitory processor-readable storage medium. The operations of a method or algorithm disclosed herein may be embodied in a processor executable software module or processor executable instructions that may reside in a non-transitory computer readable or processor readable storage medium. A non-transitory computer readable or processor readable storage medium may be any storage medium that can be accessed by a computer or processor. By way of example and not limitation, such non-transitory computer readable or processor readable storage media may include RAM, ROM, EEPROM, FLASH memory, CD-ROM or other optical disk storage, magnetic disk storage or other magnetic storage smart objects, or It can include any other medium that can be used to store desired program code in the form of instructions or data structures and that can be accessed by a computer. Disk and disc as used herein include compact disc, laser disc, optical disc, digital versatile disc (DVD), floppy disk, and blu-ray. Includes a Blu-ray disc, where disks usually reproduce data magnetically, while discs reproduce data optically by means of lasers. Combinations of the above are also included within the scope of non-transitory computer-readable or processor-readable media. Additionally, the operations of a method or algorithm may be performed as one or any combination or set of codes and/or instructions on a non-transitory processor readable storage medium and/or computer readable storage medium that may be incorporated into a computer program product. can reside

[0185] The above description of the disclosed aspects is provided to enable any person skilled in the art to make or use the claims. Various modifications to these aspects will be readily apparent to those skilled in the art, and the generic principles defined herein may be applied to other aspects without departing from the scope of the claims. Therefore, this disclosure is not intended to be limited to the aspects shown herein but is to be accorded the widest scope consistent with the following claims and the principles and novel features disclosed herein.

Claims (30)

A method executed by a processor of user equipment to provide information about a user's breathing patterns during exercise, comprising:
determining a current exercise being performed by the user;
determining a target breathing pattern suitable for a current exercise performed by the user;
monitoring a current breathing pattern of the user while performing the current exercise based on inputs from a breathing sensor;
determining differences between a target breathing pattern appropriate for a current exercise performed by the user and a current breathing pattern of the user; and
Providing the user with information about the determined differences between a target breathing pattern appropriate for a current exercise performed by the user and a current breathing pattern of the user,
A method executed by a processor of a user equipment to provide information regarding a user's breathing patterns during exercise. According to claim 1,
receiving sensor input from the motion sensor that provides information about user body movements;
determining the current motion is based on sensor input received from the motion sensor;
A method executed by a processor of a user equipment to provide information regarding a user's breathing patterns during exercise. According to claim 2,
The target breathing pattern is based on sensor input received from the motion sensor indicating how the user is moving during the exercise.
A method executed by a processor of a user equipment to provide information regarding a user's breathing patterns during exercise. According to claim 1,
Further comprising receiving a sensor input providing exercise information about the current exercise from a motion sensor,
wherein the motion sensor is associated with exercise equipment used by the user to perform the current exercise;
A method executed by a processor of a user equipment to provide information regarding a user's breathing patterns during exercise. According to claim 1,
Receiving user body movement information indicating which part of the first part and the second part of the current exercise the user is currently performing from an exercise sensor,
the target breathing pattern comprises a first breathing pattern associated with a first portion of the current workout, and a second breathing pattern different from the first breathing pattern and associated with a second portion of the current workout;
Determining differences between a target breathing pattern suitable for a current exercise performed by the user and a current breathing pattern of the user may include a target breathing pattern suitable for a first part and a second part of the current exercise and a second part of the current exercise. determining differences between the user's current breathing pattern during the first portion and the second portion; and
The step of providing information to the user may include determining differences between a target breathing pattern appropriate for the first and second portions of the current workout and the user's current breathing pattern during the first and second portions of the current workout. Including providing information about the user to the user,
A method executed by a processor of a user equipment to provide information regarding a user's breathing patterns during exercise. According to claim 1,
Further comprising receiving a manual user input related to at least one of the current exercise or the target breathing pattern,
Determining the target breathing pattern is further based on the received manual user input,
A method executed by a processor of a user equipment to provide information regarding a user's breathing patterns during exercise. According to claim 1,
Receiving context information indicating a context in which the user is currently performing the exercise;
Determining the target breathing pattern is further based on the received context information,
A method executed by a processor of a user equipment to provide information regarding a user's breathing patterns during exercise. According to claim 1,
The target breathing pattern is based on at least one of the user's body type, health goals, or level of experience performing the current exercise.
A method executed by a processor of a user equipment to provide information regarding a user's breathing patterns during exercise. According to claim 1,
determining another target breathing pattern to be achieved by the user in response to the current breathing pattern exceeding a normal breathing pattern threshold; and
Further comprising providing the user with additional information about the other target breathing pattern,
A method executed by a processor of a user equipment to provide information regarding a user's breathing patterns during exercise. According to claim 1,
In response to determining that the current exercise is being performed by the user, activating a breathing sensor configured to monitor a current breathing pattern of the user while performing the current exercise.
A method executed by a processor of a user equipment to provide information regarding a user's breathing patterns during exercise. According to claim 1,
Determining differences between a target breathing pattern suitable for a current exercise performed by the user and a current breathing pattern of the user may include comparing the current breathing pattern of the user to a previous breathing pattern of the user when the user performed the current exercise. Comprising a step of comparing with at least one of the determined respiratory rate, rhythm or quality,
A method executed by a processor of a user equipment to provide information regarding a user's breathing patterns during exercise. According to claim 1,
Further comprising activating an additional sensor in response to the user's current breathing pattern exceeding a normal breathing pattern threshold.
A method executed by a processor of a user equipment to provide information regarding a user's breathing patterns during exercise. According to claim 1,
determining a first range of body movements by the user due to the determined current movement apart from respiration;
the user's current breathing pattern is associated with a second range of body movements by the user, which is attributable to breathing and separate from the first range of body movements;
A method executed by a processor of a user equipment to provide information regarding a user's breathing patterns during exercise. According to claim 1,
The user's current breathing pattern includes at least one of the rate, rhythm or quality of breathing movement.
A method executed by a processor of a user equipment to provide information regarding a user's breathing patterns during exercise. According to claim 1,
Wherein providing information about the determined differences to the user comprises notifying the user via at least one of a visual, audible or tactile alert.
A method executed by a processor of a user equipment to provide information regarding a user's breathing patterns during exercise. According to claim 1,
The current exercise is determined based on exercise equipment being used by the user, and information about the determined differences between a current breathing pattern of the user and a target breathing pattern appropriate for the current exercise being performed by the user is the exercise equipment Provided to the user through feedback from,
A method executed by a processor of a user equipment to provide information regarding a user's breathing patterns during exercise. As a user equipment (UE),
user interface; and
a processor coupled to the user interface;
The processor comprises processor executable instructions of:
determine a current exercise being performed by the user;
determine a target breathing pattern appropriate for a current exercise being performed by the user;
monitor the user's current breathing pattern while performing the current exercise based on inputs from a breathing sensor;
determine differences between a target breathing pattern appropriate for a current exercise performed by the user and a current breathing pattern of the user; and
Provide the user via the user interface with information regarding determined differences between a target breathing pattern appropriate for a current exercise performed by the user and a current breathing pattern of the user,
UE. According to claim 17,
The processor comprises processor executable instructions of:
receive sensor input from the motion sensor that provides information about user body movements; and
further configured to determine the current movement based on sensor input received from the movement sensor;
UE. According to claim 17,
The processor comprises processor executable instructions of:
further configured to receive sensor input from an athletic sensor providing athletic information about the current exercise;
wherein the motion sensor is associated with exercise equipment used by the user to perform the current exercise;
UE. According to claim 17,
the target breathing pattern for the current workout includes a first breathing pattern associated with a first portion of the current workout, and a second breathing pattern different from the first breathing pattern and associated with a second portion of the current workout; and
The processor comprises processor executable instructions of:
receiving user body movement information indicating which part of the first part or the second part of the current exercise the user is performing from an exercise sensor;
The user's current breathing pattern during the first and second portions of the current workout and the target breathing pattern appropriate for the first and second portions of the current workout are determined, thereby appropriate for the current exercise performed by the user. determine differences between a target breathing pattern and the user's current breathing pattern; and
Information about determined differences between a target breathing pattern appropriate for the first and second portions of the current exercise and the current breathing pattern of the user during the first and second parts of the current exercise is transmitted to the user interface through the user interface. further configured to provide to the user;
UE. According to claim 17,
The processor comprises processor executable instructions of:
receive manual user input regarding at least one of the current exercise or the target breathing pattern; and
Further configured to determine the target breathing pattern further based on the received manual user input.
UE. According to claim 17,
The processor comprises processor executable instructions of:
receive context information indicating a context in which the user is performing the current exercise; and
Further configured to determine the target breathing pattern further based on the received contextual information.
UE. According to claim 17,
The processor comprises processor executable instructions of:
determine another target breathing pattern for the user to achieve in response to the current breathing pattern exceeding a normal breathing pattern threshold; and
Further configured to provide the user with additional information regarding the other target breathing pattern.
UE. According to claim 17,
The processor comprises processor executable instructions of:
activate the respiration sensor in response to a determination that the current exercise is being performed by the user; and
Further configured to activate an additional sensor in response to the user's current breathing pattern exceeding a normal breathing pattern threshold.
UE. According to claim 17,
The processor comprises processor executable instructions of:
further configured to determine a first range of body movements by the user due to the determined current movement apart from breathing;
the user's current breathing pattern is associated with a second range of body movements by the user, which is attributable to breathing and separate from the first range of body movements;
UE. A non-transitory processor-readable storage medium having stored thereon processor-executable instructions configured to cause a processor of user equipment (UE) to provide information about breathing patterns of a user during exercise by performing operations, comprising:
The above actions are:
determining a current exercise being performed by the user;
determining a target breathing pattern suitable for a current exercise performed by the user;
monitoring a current breathing pattern of the user while performing the current exercise based on inputs from a breathing sensor;
determining differences between a target breathing pattern appropriate for a current exercise performed by the user and a current breathing pattern of the user; and
Providing the user with information about the determined differences between a target breathing pattern suitable for a current exercise performed by the user and a current breathing pattern of the user,
A non-transitory processor readable storage medium. 27. The method of claim 26,
The stored processor executable instructions cause the processor of the UE to:
configured to perform operations further comprising receiving sensor input from the motion sensor that provides information about user body movements;
The operation of determining the current motion is based on sensor input received from the motion sensor.
A non-transitory processor readable storage medium. 27. The method of claim 26,
The stored processor-executable instructions cause the processor of the UE to receive user body movement information indicating which part of the first part and the second part of the current exercise the user is currently performing from a motion sensor. configured to perform operations further comprising; and
The stored processor executable instructions cause the processor of the UE to:
the target breathing pattern comprises a first breathing pattern associated with a first portion of the current workout, and a second breathing pattern different from the first breathing pattern and associated with a second portion of the current workout;
An operation of determining differences between a target breathing pattern suitable for a current exercise performed by the user and a current breathing pattern of the user may include a target breathing pattern suitable for a first part and a second part of the current exercise and a second part of the current exercise. determining differences between the user's current breathing pattern during the first portion and the second portion; and
The operation of providing information to the user relates to differences between a target breathing pattern appropriate for the first and second portions of the current workout and the user's current breathing pattern during the first and second portions of the current workout. Including the operation of providing information to the user,
configured to perform operations;
A non-transitory processor-readable storage medium. 27. The method of claim 26,
The stored processor executable instructions cause the processor of the UE to:
receiving context information indicating a context in which the user is currently performing the exercise; and
And configured to perform operations further comprising determining the target breathing pattern further based on the received context information.
A non-transitory processor readable storage medium. As user equipment,
means for determining a current exercise being performed by a user;
means for determining a target breathing pattern appropriate for a current exercise being performed by the user;
means for monitoring a current breathing pattern of the user while performing the current exercise based on inputs from a breathing sensor;
means for determining differences between a target breathing pattern appropriate for a current exercise performed by the user and the user's current breathing pattern; and
Means for providing the user with information regarding the determined differences between the user's current breathing pattern and a target breathing pattern appropriate for a current exercise performed by the user.
user equipment.