Exercise systems and methods of use

Abstract

Various exercise devices and methods of use are disclosed herein. In one example, an exercise device includes a first platform and a second platform. The first platform includes one or more feet configured to interface with and remain static with a support surface. The second platform includes one or more wheels configured to roll on the support surface. An elastic coupling is arranged between the first platform and the second platform, and the elastic coupling is configured to transition from a relaxed condition to a tensioned condition as the second platform is advanced away from the first platform. A sensor is coupled to the exercise system and is configured to detect exercise data.

Description

EXERCISE SYSTEMS AND METHODS OF USE CROSS-REFERENCE TO RELATED APPLICATIONS

[0001] The present application is a non-provisional application claiming priority to U.S. Provisional Patent Application No.63 / 502,854, filed May 17, 2023, the contents of which are hereby incorporated by reference. BACKGROUND

[0002] Physical exercise can provide several benefits for improving a person’s quality of life. For instance, regular physical exercise can help in maintaining a healthy weight, lowering risk of disease, improving mood or self-esteem, boosting energy, and promoting better sleep.

[0003] Example types of physical exercise are Pilates and Lagree, which include performing controlled movements designed to improve flexibility, build strength, and develop control and endurance in the entire body. Pilates and Lagree exercises are often performed with the aid of exercise devices, including exercise devices known as ‘reformers.’ SUMMARY

[0004] The systems and methods disclosed herein provide improvements to exercise systems and their methods of use. In particular, the example exercise devices of the present disclosure can be less costly, smaller in size (e.g., smaller profile, footprint, weight, etc.), and collapsible for easy transport. Further, the exercise systems and methods include sensors to detect exercise data and transmit the exercise data to a computing device to provide real-time feedback to a user during a workout.

[0005] In an example embodiment, an exercise system includes a first platform, a second platform having one or more wheels, and an elastic coupling arranged between the first platform and the second platform, the elastic coupling being configured to transition from a relaxed condition to a tensioned condition as the second platform is advanced away from the first platform. The exercise system further includes a sensor coupled to the exercise system and configured to detect exercise data.

[0006] In another example embodiment, method of exercising using an exercise device is disclosed. An example exercise device includes (i) a first platform, (ii) a second platform, (iii) an elastic coupling configured to couple the first platform to the second platform, and (iv) a sensor coupled to the exercise device. The method includes advancing the second platform away from the first platform, thereby causing the elastic coupling to transition from a relaxed ^condition to a tensioned condition. The method further includes detecting exercise data via the sensor. The method additionally includes transmitting the detected exercise data to a computing device.

[0007] In a further example embodiment, an exercise system includes an exercise device and a computing device. The exercise device includes a first platform, a second platform having one or more wheels, an elastic coupling arranged between the first platform and the second platform, the elastic coupling being configured to transition from a relaxed condition to a tensioned condition as the second platform is advanced away from the first platform, and a sensor coupled to the exercise system and configured to detect exercise data. The computing device includes a processor and a non-transitory computer-readable storage medium, having stored thereon program instructions that, upon execution by the processor, cause performance of a set of operations. The set of operations includes receiving detected exercise data from the sensor and outputting the exercise data for display via a graphical user interface. BRIEF DESCRIPTION OF THE FIGURES

[0008] FIG.1 illustrates a computing device, according to an example embodiment.

[0009] FIG. 2 illustrates a user using an exercise device, according to an example embodiment.

[0010] FIG. 3 illustrates a platform of the exercise device of FIG. 1, according to an example embodiment.

[0011] FIG. 4A illustrates the exercise device of FIG. 1, according to an example embodiment.

[0012] FIG. 4B illustrates a bottom of the exercise device of FIG. 1, according to an example embodiment.

[0013] FIG. 5 illustrates a graphical user interface (GUI), according to an example embodiment.

[0014] FIG.6 illustrates another GUI, according to an example embodiment.

[0015] FIG.7 illustrates another GUI, according to an example embodiment.

[0016] FIG.8 illustrates another GUI, according to an example embodiment.

[0017] FIG. 9 is a flow chart of a method of exercising, according to an example embodiment. ^DETAILED DESCRIPTION I. Overview

[0018] Example exercise devices as well as methods of use are described herein. Any example embodiment or feature described herein is not necessarily to be construed as preferred or advantageous over other embodiments or features. The example embodiments described herein are not meant to be limiting. It will be readily understood that certain aspects of the disclosed methods can be arranged and combined in a wide variety of different configurations, all of which are contemplated herein. II. Example Architecture

[0019] Figure 1 is a simplified block diagram of an example computing device 100. The computing device 100 can be configured to perform and / or can perform one or more acts and / or functions, such as those described in this disclosure. The computing device 100 can include various components, such as a processor 102, a data storage unit 104, a communication interface 106, sensor 108 and / or a user interface 110. Each of these components can be connected to each other via a connection mechanism 112.

[0020] In this disclosure, the term ‘connection mechanism’ means a mechanism that facilitates communication between two or more components, devices, systems, or other entities. A connection mechanism can be a relatively simple mechanism, such as a cable or system bus, or a relatively complex mechanism, such as a packet-based communication network (e.g., the Internet). In some instances, a connection mechanism can include a non- tangible medium (e.g., in the case where the connection is wireless).

[0021] The processor 102 can include a general-purpose processor (e.g., a microprocessor) and / or a special-purpose processor (e.g., a digital signal processor (DSP)). The processor 102 can execute program instructions included in the data storage unit 104 as discussed below.

[0022] The data storage unit 104 can include one or more volatile, non-volatile, removable, and / or non-removable storage components, such as magnetic, optical, and / or flash storage, and / or can be integrated in whole or in part with the processor 102. Further, the data storage unit 104 can take the form of a non-transitory computer-readable storage medium, having stored thereon program instructions (e.g., compiled or non-compiled program logic and / or machine code) that, upon execution by the processor 102, cause the computing device 100 to perform one or more acts and / or functions, such as those described in this disclosure. These program instructions can define, and / or be part of, a discrete software application. In some instances, the computing device 100 can execute program instructions in response to ^receiving an input, such as an input received via the communication interface 106 and / or the user interface 110. The data storage unit 104 can also store other types of data, such as those types described in this disclosure.

[0023] The communication interface 106 can allow the computing device 100 to connect with and / or communicate with another entity according to one or more protocols. In one example, the communication interface 106 can be a wired interface, such as an Ethernet interface. In another example, the communication interface 106 can be a wireless interface, such as a cellular or WIFI interface. In this disclosure, a connection can be a direct connection or an indirect connection, the latter being a connection that passes through and / or traverses one or more entities, such as a router, switcher, or other network device. Likewise, in this disclosure, a transmission can be a direct transmission or an indirect transmission.

[0024] The sensor 108 can include sensors now known or later developed, including but not limited to weight detection sensors, weight distribution sensors (e.g., coupled to the first platform and / or the second platform of the exercise system), a load cell sensor (e.g., cou- pled to the elastic coupling of the exercise system), a sound detection sensor, a motion sensor, a thermal imaging sensor, a humidity sensor, a capacitance sensor (e.g., a sensor to detect con- tact from one or more hands or feet of the user), a temperature sensor, an oxygen sensor, a carbon monoxide sensor, a proximity sensor (e.g., a Bluetooth sensor and / or communication protocol to determine the proximity of one platform to another and / or a wearable mobile com- puting device that is associated with the user and / or the computing device), a location sensor (e.g., a GPS sensor), sensors that measure: (i) heart rate, (ii) body mass index (BMI), (iii) mus- cle rate, (iv) body fat percentage, (v) subcutaneous fat percentage, (vi) visceral fat percentage, (vii) fat-free body weight, (viii) body water rate, (ix) skeletal muscle rate, (x) muscle mass, (xi) bone mass, (xii) protein level, (xiii) basal metabolic rate (BMR), (xiv) heart index, and / or (xv) body age, and / or a combination of these sensors, among other possibilities.

[0025] The user interface 110 can include hardware and / or software components that facilitate interaction between the computing device 100 and a user of the computing device 100, if applicable. As such, the user interface 110 can include input components such as a keyboard, a keypad, a mouse, a touch sensitive panel, and / or a microphone, and / or output components such as a display device (which, for example, can be combined with a touch sensitive panel), a sound speaker, and / or a haptic feedback system.

[0026] The computing device 100 can take various forms, such as a workstation terminal, a desktop computer, a laptop, a tablet, a mobile phone, and / or a mobile computing device. ^III. Example Systems

[0027] FIG.2 illustrates an example of a user using the exercise system 200 to perform an exercise. The exercise system 200 includes a first platform 202, a second platform 204, an elastic coupling 206, and a sensor 216. The elastic coupling 206 is arranged at least partially between the first platform 202 and the second platform 204 and couples the first platform 202 to the second platform 204. As used herein, ‘elastic’ refers to the capability of a material to substantially resume its original shape after being stretched, deformed, compressed, or expanded. As such, an elastic material may be placed under tension, thereby inducing resistance against movement. Accordingly, it should be understood that the elastic coupling 206 may be a variety of different materials. The elastic coupling 206 as shown includes four elastic bands, but in other examples the elastic coupling 206 may include additional or fewer bands or other types of elastic coupling. For instance, the elastic coupling 206 may include any number of elastic bands, cords, straps, links, ropes, chains, or any other elastic mechanism for coupling the first platform 202 to the second platform 204. In practice, a user can use the exercise system 200 without the elastic coupling 206 between the first platform 202 and the second platform.

[0028] Additionally, elastic couplings 206 may have one or more different resistance strengths. For instance a low strength elastic band can have a resistance level range from 5 lbs- 15 lbs. A medium strength elastic band can have a resist level range from 25 lbs-50 lbs. And a high strength elastic band can have a resistance level range from 45 lbs-110 lbs. In practice a user can use any combination of elastic bands to achieve a desired resistance of the elastic coupling 206. For example, the user can couple one low strength elastic band, two medium strength resistance bands, and one high strength elastic band to the first platform 202 and the second platform 204 to achieve the desired resistance of the elastic coupling 206 for a given exercise. In examples, the elastic coupling 206 can include an indication of the strength of the resistance, for example labels and / or color-coded bands.

[0029] As shown, the user may place their first foot on the first platform 202, place their second foot on the second platform 204, and perform a leg lunge exercise or a leg split exercise in order to advance the second platform 204 away from the first platform 202. In another example, the user may place their shoulder(s) or upper back on the first platform 202, place their foot on the second platform 204, and perform a pelvic lift exercise in order to advance the second platform 204 away from the first platform 202. In yet another example, the user may place their knee on the first platform 202, place their hand on the second platform 204, and advance the second platform 204 away from the first platform 202 by moving their ^hand away from their knee. In still another example, the user may place their foot on the first platform 202, place their hand on the second platform 204, and advance the second platform 204 away from the first platform 202 by moving their hand away from their foot. Other examples are possible as well. Further, in the above examples, where an example includes placing a body part on the first platform 202, the example could alternatively include placing the body part on the second platform 204 and vice versa.

[0030] Additionally, when advancing the second platform 204 away from the first platform 202, the second platform 204 may be moved in a variety of directions. For instance, the second platform 204 may be advanced along a longitudinal axis that extends lengthwise between the first and second platforms. Alternatively or additionally, the second platform 204 may be advanced along a lateral axis that is orthogonal to the longitudinal axis (e.g., side to side). Further, the second platform 204 may be advanced away from the first platform 202 in a diagonal or oblique direction. Other examples are possible as well.

[0031] A tension of the elastic coupling 206 may vary based on a position of the first platform 202 relative to the second platform 204. For instance, the elastic coupling 206 may be in a relaxed condition when no external forces are applied to the first platform 202 or the second platform 204, and the elastic coupling 206 may transition to a tensioned condition as the second platform 204 is advanced away from the first platform 202. As used herein, ‘relaxed condition’ refers to a relaxed, un-tensioned condition of the elastic coupling 206 when the first platform 202 and the second platform 204 are not being forced away from one another, and ‘tensioned condition’ refers to a condition of the elastic coupling 206 when the first platform 202 and the second platform 204 are advanced away from each other, thereby increasing a tension or resistance of the elastic coupling 206.

[0032] In practice, a user may use the device 100 to exercise by exerting a force on the second platform 204 to advance the second platform 204 away from the first platform 202, or vice versa. As the user advances the second platform 204 away from the first platform 202, the elastic coupling 206 enters a tensioned condition in which the elastic coupling 206 resists further advancement of the second platform 204 away from the first platform 202. Accordingly, the user must exert additional force to continue to advance the second platform 204. After advancing the second platform 204 away from the first platform 202 by a desired distance, the user may reduce the amount of force applied to the second platform 204, allowing a tensile force of the elastic coupling 206 to pull the second platform 204 back toward the first platform 202. In order to prevent the second platform 204 from rapidly jerking back toward the first platform 202, the user may continue to apply a force that partially resists the tensile ^force of the elastic coupling 206, causing the second platform 204 to smoothly retreat back toward the first platform 202. In this manner, the user exerts energy when advancing the second platform 204 away from the first platform 202 and also when allowing the second platform 204 to retreat back toward the first platform 202. Because there are numerous different ways in which the user can move the second platform 204 relative to the first platform 202, there are numerous different exercises that can be performed using the exercise system 200.

[0033] In order to facilitate the above example exercises or other exercises, the exercise system 200 may be arranged on a support surface 214. The support surface 214 could be any surface that supports the exercise system 200, including but not limited to, a floor surface, a ground surface, or the like, that the exercise system 200 may be placed against in use.

[0034] In practice, the first platform 202 may be configured to remain static when in contact with the support surface 214, while the second platform 204 may be configured to be moveable when in contact with the support surface 214. For instance, a bottom side of the first platform 202 may include one or more feet 208, and a bottom side of the second platform 204 may include one or more wheels 210. In such an arrangement, the feet 208 of the first platform 202 may be configured to grip the support surface 214, and the wheels 210 of the second platform 204 may be configured to roll across the support surface 214.

[0035] Because the support surface 214 may take various forms (e.g., a hardwood, tile, linoleum, or carpeted floor surface), the feet 208 of the first platform 202 may include or be composed of various materials for interfacing with different types of support surface 214. For instance, in order to remain static when in contact with the support surface 214, the feet 208 of the first platform 202 may include or be composed of a material having a high coefficient of friction (e.g., greater than 0.5) relative to both hard and soft floor surfaces. Such a material could include various types of rubber or other high-friction polymers. Other examples are possible as well.

[0036] Further, because many of the exercises described above involve the user standing on one or both of the first platform 202 and second platform 204, the first and second platforms may each include a textured surface 212 for interfacing with a foot or shoe of the user. The textured surface 212 may be configured to grip the foot or shoe of the user so that the user does not slip off of the exercise system 200 when exercising. As such, the textured surface 212 may include a number of ridges or other protruding elements to increase the friction of the textured surface 212. Further, the textured surface may include or be composed of a material that has a high coefficient of friction (e.g., greater than 0.5) when interfacing with ^shoe soles and / or feet. Such a material could include various types of rubber or other high- friction polymers.

[0037] In example embodiments, the exercise system 200 the first platform 202 and / or second platform 204 can be height adjustable. For instance, the exercise system 200 can further include one or more stackable blocks which can be detachably coupled to a top side of the first platform 202 or the second platform 204. The stackable blocks allow a user to perform different exercises and / or modified versions of exercises. For instance, a user can perform a modified plank hold by coupling the stackable block on top of the first platform 202. Many other examples are possible.

[0038] In some examples, the exercise system 200 may facilitate other exercises in addition to those described above. For example, the exercise system 200 may be configured to interface with one or more elastic bands for performing various elastic band exercises.

[0039] FIG.3 illustrates the exercise system 200 interfacing with a resistance band 220. As shown, the first platform 202 includes an interface, depicted as a pair of slots 222, for receiving the resistance band 220. Additionally or alternatively, in some example embodiments, the second platform 204 may include slots 222 for receiving the resistance band 220, as well. In example implementations, the resistance band 220 may include additional bands, different length bands, or other types of couplings. For instance, the resistance band 220 may include any number of elastic bands, cords, straps, links, ropes, chains, or any other elastic mechanism for coupling to the first platform 202 and / or the second platform 204. Further, in some examples, the resistance band 220 includes handles. Additionally or alternatively, the resistance band 220 can include a soft loop, for example, for a user to loop around their foot.

[0040] The slots 222 may be located on lateral sides 224 of the first platform 202 between a bottom side and top side of the first platform 202. In this manner, the resistance band 220 can be wrapped around the bottom side of the first platform 202 and fed up through the slots 222 on the lateral sides 224 of the first platform so that the ends or handles of the resistance band 220 are accessible by a user standing on the top side of the first platform 202. As shown, the slots 222 are located proximate to the centers of the lateral sides 224 of the first platform 202. However, other configurations are possible as well. For instance, the slots 222 may be located on the lateral sides 224 closer to a front side 308 or a rear side 310 of the first platform 202.

[0041] The slots 222 may have a diameter approximately equal to, or slightly larger than, a diameter of the resistance band 220 so that the resistance band 220 may fit snugly in ^the slots 222. Further, the slots 222 may have openings that are slightly thinner than the diameter of the resistance band 220. In this manner, the slot openings may be wide enough to allow a user to squeeze the band into the slots 222 due to the elasticity of the resistance band 302, and the slot openings may be sufficiently narrow to help prevent the resistance band 302 from sliding out of the slots 304 during use.

[0042] Once the resistance band 220 is attached to the exercise system 200, for example using the slots 222, the user can perform a variety of resistance band exercises. For instance, the user can stand on the first platform 202, grabbing the resistance band 220 with one or both hands, and perform various resistance band exercises, such as biceps curls, triceps extensions, overhead presses, forward / lateral raises, upright rows, or the like. In some examples, the user may perform the resistance band exercises in parallel with the exercises described above that involve moving the second platform 204 relative to the first platform 202. For instance, the user may sit on the first platform 202, grabbing the resistance band 220 with one or both hands and placing the user’s feet on the second platform 204. The user can then perform various resistance band arm and / or back exercises while using the user’s legs and feet to advance the second platform 204 away from the first platform. Alternatively, the user may sit on the second platform 204, placing the user’s feet on the first platform 202 while grabbing the resistance band 220 with one or both hands. The user can then perform various resistance band exercises while advancing the second platform 204 away from the first platform 202 by extending the user’s legs and pushing off of the first platform 202. Other examples are possible as well. IV. Detection and Collection of Exercise Data

[0043] Referring to FIGs. 3A-3B, various views of the first platform 202, second platform 204, and elastic coupling 206 are shown. FIG. 3A shows a perspective view of the first platform 202, second platform 204, and elastic coupling 206 and FIG.3B shows a bottom view of the the same. As noted above, in example embodiments, the exercise system 200 includes one or more sensors 216 to collect exercise data and transmit the collected exercise data to a computing device, such as computing device 100. In some examples, the exercise system 200 includes a computing device. In other examples, the sensor 216 communicates, via a wired or wireless connection, with an external computing device, such as a user’s phone or tablet. Exercise data can include measurements of external forces on the exercise system 200, such as work, torque, tension strength, and / or weight distribution, for example. Additionally or alternatively, exercise data can include biometric data. In examples, exercise data can include, but is not limited to (i) number of repetitions; (ii) speed of movements; (iii) length of movements; and (iv) time of exercise. The exercise system 200 can then provide ^feedback to a user during or after an exercise session, for example, by way of a graphical user interface (GUI). In some examples, the exercise system 200 includes a GUI (for example, on the first platform 202) to provide such feedback to the user. Additionally or alternatively, the exercise system 200 can transmit collected exercise data to a user device which includes a GUI, such as a workstation terminal, a desktop computer, a laptop, a tablet, a mobile phone, and / or a mobile computing device to provide such feedback to the user.

[0044] Many different types and combinations of sensors can be utilized to collect exercise data. Further, sensors 216 can located on or in various components throughout the exercise system 200. For instance, the elastic coupling 206 can include or be coupled to one or more load cells to measure the tension force on the elastic coupling 206. As the user advances the second platform 204 away from the first platform 202, the load cell can measure the tension on the elastic coupling 206 to determine the work done by the user. In examples, the load cell can also measure torque to determine a directional component to the elastic coupling 206. The load cell can transmit the detected data to a computing device.

[0045] Similarly, in examples including resistance bands 220, as shown in FIG.3, the resistance bands can include or be coupled to one or more load cells. As a user performs various exercises with the resistance band 220, such as biceps curls, triceps extensions, overhead presses, forward / lateral raises, upright rows, or the like, the load cell can measure the tension on the resistance band 220 to determine the work done by the user. In examples, the load cell can also measure torque to determine a directional component to the resistance band 220 as well. The load cell can transmit the detected data to a computing device.

[0046] In another example, the first platform 202, second platform 204, and / or the elastic coupling 206 can include radio-frequency identification (RFID) sensors to determine external forces on the exercise system 200. For instance, RFID sensors can be used to determine the distance between the first platform 202 and the second platform 204. The distance can then be correlated with the resistance level of the elastic coupling 206 to determine the external force on the first platform 202 or second platform 204, for example, as a user advances the first platform 202 away from the second platform 204. In examples, the first platform 202 and second platform 204 can each have an RFID sensor. In another example, a first end of the elastic coupling 206 can have a first RFID sensor and the second end of the elastic coupling 206 can have a second RFID sensor. In yet another example, the resistance band 220 can include an RFID sensor at one or both ends of the band. Many examples of the placement of the RFID sensors are possible. ^

[0047] Further, an RFID sensors can be used to determine or identify the resistance level of the elastic coupling 206. In examples where the elastic coupling 206 includes a plurality of elastic bands, each elastic band can include an RFID sensor indicating the resistance level of each band. For instance, a low strength elastic band can include a RFID sensor including an identifier that the resistance range of that elastic band is between 5 lbs-15 lbs and a medium strength elastic band can include a RFID sensor including an identifier that the resistance range of that elastic band is between 25 lbs-50 lbs.

[0048] Additionally or alternatively, the RFID sensors can be used to determine the number of elastic bands making up the elastic coupling 206 which are coupled to the first platform 202 and / or second platform 204. For instance, for a given exercise the user can use one elastic band as the elastic coupling 206. For another exercise, the user may use three elastic bands for the elastic coupling 206. In examples, each of the elastic bands can include an RFID sensor so that the exercise system 200 can determine how many elastic bands are coupled the first platform 202 and / or second platform 204 at any given time. Accordingly, the exercise system 200 and / or computing device 100 can determine that resistance level of the elastic coupling 206 at any given time. For instance, the exercise system 200 can determine that one low level resistance band and two high level resistance bands are coupled to the first platform 202 and the second platform 204 to determine the total resistance of the elastic coupling 206.

[0049] Once the distance between and resistance level are determined, the exercise system 200 can determine one or more additional kinetic and / or static metrics associated with the exercises, including the work (force x distance) done by the user based on the determined distance and the resistance range of the elastic coupling 206. The RFID sensors can also transmit the collect data to the computing device 100.

[0050] Additionally or alternatively, the first platform 202 and / or second platform 204 can include weight distribution sensors. In practice, the weight distribution sensors can determine a user’s balance during a workout. The weight distribution sensor can transmit the detected data to a computing device.

[0051] In some example embodiments, the exercise system 200 can include a sensor to determine a user’s body composition metrics such as heart rate, body mass index (BMI), muscle rate, body fat percentage, subcutaneous fat percentage, visceral fat percentage, fat-free body weight, body water rate, skeletal muscle rate, muscle mass, bone mass, protein, basal metabolic rate (BMR), heart index, body age, etc. The biometric sensor can transmit the detected data to a computing device. ^

[0052] Many different types and combinations of sensors can be utilized to detect and transmit exercise data in addition to the example embodiments disclosed herein. V. Exercise Data Feedback

[0053] As noted above, the sensor 216 of the exercise system 200 can transmit detected exercise data to a computing device. This computing device is configured to determine exercise metrics based on the collected exercise data and output these exercise metrics for display on a GUI to provide feedback to a user during or after an exercise session. For instance, in practice, the exercise system 200 can transmit exercise data to a user device such as a workstation terminal, a desktop computer, a laptop, a tablet, a mobile phone, and / or a mobile computing device. The sensor 216 of the exercise system 200 can communicate with the computing device by way of a wired or wireless connection.

[0054] In example implementations, an application (e.g., a smartphone application) associated with the exercise system 200 can be downloaded onto and / or accessed from the user device. The application can include stored workout programs and guides. Each workout program can include a target output force, such as tension force exerted on the elastic coupling 206, with respect to time. In examples, the user may select a workout program . In examples, the application may sort or suggest different workout programs based on type (e.g., core- focused, arms and back, whole body, etc.), time, and / or difficulty level (e.g., beginner, intermediate, expert). Additionally or alternatively, the application can include a series of related workout programs (e.g., ‘10 Day Core Challenge’).

[0055] FIG.5 illustrates an example GUI 500 for the application. In practice, the user can select a workout program available in the application. The GUI shows a solid line 502 indicating the target output force based on the selected workout program, where force is represented on the vertical axis and time is represented on the horizontal axis. The dotted line 504 tracks the user’s force exerted over time, for example at the elastic coupling 206 based on the exercise data collected and transmitted by the sensor 216, as compared to the selected workout program with a vertical line 506 indicating current time. The GUI 500 can also indicate the type of exercise 508 for the user to perform at a given time, for example, a ‘Lateral Squat’. FIG.5 illustrates a snapshot of a point-in-time during a workout program. In practice, the GUI may ‘travel’ to the right along the horizontal axis with time during the workout program.

[0056] The GUI 500 may also provide instructions for changing exercises throughout the workout. For example, the GUI can indicate a new or difference exercise and provide ^instructions such as ‘SWITCH LEGS’, ‘SWITCH SIDES’, ‘REST’, ‘INCREASE RESISTANCE STRENGTH’, etc., in accordance with the selected workout program. Additionally, the GUI can include suggested resistance levels for the elastic coupling 206 and / or the resistance bands 220 for each exercise based on the selected workout program and / or type of exercise. For instance, the GUI can display text such as ‘TWO LIGHT BANDS’, ‘FOUR HEAVY BANDS’, etc. Further, in some examples the GUI may provide additional workout options, such as ‘PAUSE’, ‘START’, ‘FINISH’, etc., which may available and / or selectable throughout the workout program. These example instructions can be utilized with any of the example GUIs described herein.

[0057] FIG. 6 illustrates another example GUI 600 for the application. As described above, in practice, the user can select a workout program available in the application. The GUI 600 shows a solid line 602 indicating the target output force based on the selected workout program, where force is represented on the vertical axis and time is represented on the horizontal axis. The dotted line 604 tracks the user’s force exerted over time, based on the exercise data collected and transmitted by the sensor 216, as compared to the selected workout program with a vertical line 606 indicating current time. The GUI 600 can also indicate the type of exercise 608 for the user to perform at a given time, for example, ‘Split Squat Pulses’. The GUI may ‘travel’ along the horizontal axis with time during the workout program.

[0058] FIG. 7 illustrates another example GUI 700 for the application. The GUI 700 provides a split screen for performing two exercises at once, displaying the forces exerted over time from both the elastic coupling 206 and resistance bands 220, simultaneously. When the selected workout program includes two exercises to be performed at once, the GUI 700 shows a first solid line 702 indicating the target output force for the first exercise based on the selected workout program, where force is represented on the vertical axis and time is represented on the horizontal axis. In this example, the first exercise, an ‘Overhead Press’ which is done using the resistance bands 220. The GUI also shows a second solid line 710 indicating the target output force for the second exercise. In this example, the second exercise, a ‘Split Squat (Left)’ is done using the first platform 202, second platform 204, and elastic coupling 206. The first dotted line 704 tracks the user’s force exerted over time for the first exercise, based on the exercise data collected and transmitted by the sensors 216, as compared to the first exercise of the selected workout program with a vertical line 706 indicating current time. The second dotted line 712 tracks the user’s force exerted over time for the first exercise, based on the exercise data collected and transmitted by the sensors 216, as compared to the second exercise ^of the selected workout program. The GUI may ‘travel’ to the right along the horizontal axis with time during the workout program.

[0059] FIG.8 illustrates another example GUI 800 for the application. In this example, the GUI 800 shows a circle 802, where the radius 804 of the circle represents desired force exerted for the given exercise based on the selected workout program. The current time, or time passed, is represented by line 806. As time passes, line 806 travels in a clockwise direction around the circle 802, similar to the hands of a clock. The dotted line 808 tracks the user’s force exerted over time, based on the exercise data collected and transmitted by the sensor 216, as compared to the selected workout program. The GUI 800 can also indicate the type of exercise 810 for the user to perform at a given time, for example, ‘Plank Hold’.

[0060] In some example implementations, the user does not need to select a particular workout program. The user can instead select a ‘Freestyle’ or ‘Open’ workout option or select a start button on the exercise system 200 or in the application to begin a workout. The exercise system 200 can then begin collecting and transmitting exercise data to the computing device 100 during the duration of the workout. The user can provide an indication, for example via a button on the exercise system 200 and / or the application GUI, to finish the workout. During or after the workout, the GUI can display the detected exercise data.

[0061] In example implementations where the sensor 216 include a weight distribution sensor, the GUI can display an indication of the user’s balance metrics. For instance, the GUI can display a heat map or pressure map based on where a user is positioned and how stable the user is.

[0062] In example implementations, the application and / or exercise system 200 can make real-time recommendations during a workout, for example, to (i) suggest body positioning changes, (ii) movement, pace, and / or speed changes, and / or (iii) movement dimension changes. In this case the application can include a machine-learning component which utilizes the measured exercise data and to evaluate and determine recommendations for improvements in real-time, during the exercise. Modification recommendations can be based on a selected workout program, pre-programmed guides for each movement type, and / or based on the program’s learning of the user’s strengths and weaknesses as the user undergoes the exercise during one session or over time. The pre-programmed guides can also use machine learning over time to combine the user’s information (height, weight, age, sex, exercise goals, etc.) with the data being collected during the exercise, to then make recommendations in real- time, as well as after the exercise for future implementation (i.e., subsequent workouts). ^

[0063] In example implementations, the application and / or exercise system 200 can combine the user’s exercise data and metrics with pre-set data information to make exercise recommendations based on goals or detected weaknesses. In some examples, the application and / or exercise system 200 can utilize machine learning to determine and provide such recommendations. Recommendations can include movement or body positioning changes that provide different results for different body parts or muscle groups. For example, certain positions may strengthen the abdomen, but a change in position strengthens the quadriceps, and another change in position increases flexibility of hip flexors. Recommendations can be tailored to facilitate meeting the goals of the user. For example, goals can include improving balance, increasing flexibility, getting faster, improving certain aspects of an athlete that wants to improve a specific area of their sport, improving a specific function of a user that is rehabilitating, etc. Recommendations can also include general improvement recommendations based on user’s progress and provide associated metrics for improvement over time. The recommendations can also involve gamification, for example, to reach milestones and advance levels, among other uses.

[0064] In example implementations, the application can incorporate user’s music playlist. For instance, the user can create a music playlist in the application. Additionally or alternatively, the application can import a user’s playlist from another source, such as a streaming service (e.g., Spotify®, Apple Music®, Pandora®, etc.). In some example, the application can play the user’s selected music playlist during a selected workout program. Additionally or alternatively, the application can suggest or create a workout program based on the selected music playlist. For example, the application can determine characteristics of the songs on the user’s music playlist, such as genre, artist, average beats per minute, length of songs, etc. The application can then suggest or create a workout program based on the determined characteristics. For example, the application may suggest a more difficult workout program if the user’s music playlist includes electronic dance music and an easier workout program if the user’s music playlist includes classical music. In an example, if the user’s music playlist includes songs by the band LYON$, the application can select or suggest or create a moderate workout program based on characteristics of the songs (e.g., tempo, song length, mood, intensity, etc.).

[0065] When the user completes or finishes a workout, the application may provide a summary of the user’s workout and / or exercise metrics. In examples, the summary can include exercise metrics such as total work done, total time under tension, calories burned, balance ^metrics, average heart rate, etc. The application can also track a user’s progress over time, such as total number of workouts and ‘personal best’ metrics, for example.

[0066] Further, in some examples, a user can set goals via the application. The application can then recommend or select workouts for the user based on the user’s goals.

[0067] In some examples, the application can train a machine learning model using the user’s exercise data and metrics to generate exercise recommendations based on goals or detected weaknesses and / or playlist recommendations. In these examples, user’s data can be encrypted so that the data used to train the machine learning model is user agnostic to maintain data privacy. The machine learning model may be trained using training data that shares similar user information and preferences (e.g., height, weight, age, sex, exercise goals, playlist selection, etc.) to generate recommendations suitable to the user.

[0068] The machine learning model may include an artificial neural network, a support vector machine, a regression tree, an ensemble of regression trees, or some other machine learning model architecture or combination of architectures.

[0069] In some examples, the machine learning model of the application may be adjusted based on training such that if the user responds positively to a generated recommendation, the machine learning model is reinforced and if the user responds negatively to the generated recommendation, the machine learning model is modified. In some examples, modifying the machine learning model includes increasing or decreasing a weight of a factor within the neural network of the machine learning model. In other examples, modifying the machine learning model includes adding or subtracting rules during the training of the machine learning model.

[0070] In examples, the application can have a social networking component allowing a user to connect with other users of the application. In examples, the user can opt to share exercise data and metrics with other users of the application. The application can provide users with general information collected from the general population of users, such as a rating for a particular workout program or guide. The application can provide options of connecting with and searching for other users. Further, the application can allow users to interact and compete with one another.

[0071] In some example implementations, the application can match or suggest matching users that may have similarities (e.g., goals, exercise progress, location-based, social media connections, sports preferences, music preferences, etc.). The application can utilize machine learning or other techniques to make such suggestions. In examples, the application can match or suggest matching new users starting and / or suggest a beginner’s program that ^facilitates the users improving together by reaching certain levels and / or milestones. The application can also connect people and have them exercise “together” via the exercise data and metrics. VI. Example Methods

[0072] FIG. 9 is a flow chart of a method of exercising, according to an example embodiment. The method may be carried out using any of the exercise devices disclosed herein, each of which include a first platform, a second platform, an elastic coupling that couples the first platform to the second platform, and a sensor coupled to the exercise system. At block 902, the method involves advancing the second platform away from the first platform, thereby causing the elastic coupling to transition from a relaxed condition to a tensioned condition. In line with the discussion above, the second platform may be advanced away from the first platform in a variety of ways. For instance, a user may place a first body part of the user on the first platform, place a second body part of the user on the second platform, and advance the second body part away from the first body part, thereby advancing the second platform away from the first platform.

[0073] Additionally, when advancing the second platform away from the first platform, the second platform may be moved in a variety of directions. For instance, the second platform may be advanced along a longitudinal axis that extends lengthwise between the first and second platforms. Alternatively or additionally, the second platform may be advanced along a lateral axis that is orthogonal to the longitudinal axis (e.g., side to side). Further, the second platform may be advanced away from the first platform in a diagonal or oblique direction. Other examples are possible as well.

[0074] At block 904, the method involves detecting exercise data via a sensor. In line with the discussion above, detecting exercise data via the sensor can involve detect external forces on the exercise device such as work, torque, tension, and / or weight distribution . Detecting exercise data can also include determining a distance between the first platform and the second platform and / or the speed of the change in distance. Additionally or alternatively, the sensor can detect biometric data such as heart rate, body mass index (BMI), muscle rate, body fat percentage, subcutaneous fat percentage, visceral fat percentage, fat-free body weight, body water rate, skeletal muscle rate, muscle mass, bone mass, protein, basal metabolic rate (BMR), heart index, or body age.

[0075] At block 906, the method involves transmitting the detected exercise data to a computing device. In line with the discussion above, transmitting the detected exercise data to ^a computing device can additionally include displaying the detected exercise data on a graphical user interface. VII. Alternative Embodiments

[0076] In some examples, any of the exercise devices described herein may further include one or more pads coupled to one or more surfaces of the first and second platforms. The pads may be arranged to provide cushioning when a user advances the platforms away from one another using their body.

[0077] In some examples, any of the exercise devices described herein may further include a frame for guiding the movement of the second platform along the longitudinal axis and / or another desired direction or axis. The frame may couple to one or more side surfaces of the second platform via a sliding track mechanism, for instance, such that advancing the second platform away from the first platform may involve sliding the second platform along the sliding track mechanism. The frame may be telescopic and may include a hinge arranged between the first and second platforms such that the frame may collapse on itself and fold up to increase portability of the exercise device when not in use. VIII. Conclusion

[0078] The above detailed description describes various features and functions of the disclosed exercise devices and methods of use with reference to the accompanying figures. While various aspects and embodiments have been disclosed herein, other aspects and embodiments will be apparent to those skilled in the art. The various aspects and embodiments disclosed herein are for purposes of illustration and are not intended to be limiting, with the true scope being indicated by the following claims. ^

Claims

CLAIMS What is claimed is:

1. An exercise system comprising: a first platform; a second platform having one or more wheels; and an elastic coupling arranged between the first platform and the second platform, the elastic coupling being configured to transition from a relaxed condition to a tensioned condition as the second platform is advanced away from the first platform; and a sensor coupled to the exercise system and configured to detect exercise data.

2. The exercise system of claim 1, wherein the sensor is communicably coupled to a computing device.

3. The exercise system of claim 2, wherein the computing device is configured to output the exercise data for display on a graphical user interface.

4. The exercise system of claim 1, wherein the sensor comprises a load cell coupled to the elastic coupling.

5. The exercise system of claim 1, wherein the sensor comprises a weight distribution sensor coupled to the first platform or the second platform.

6. The exercise system of claim 1, wherein the sensor comprises radio-frequency identification. 7.^ The exercise system of claim 1, wherein the sensor is configured to detect at least one of: (i) heart rate; (ii) body mass index (BMI); (iii) muscle rate; (iv) body fat percentage; (v) subcutaneous fat percentage; (vi) visceral fat percentage; (vii) fat-free body weight; (viii) body water rate; (ix) skeletal muscle rate; (x) muscle mass; (xi) bone mass; (xii) protein level; (xiii) basal metabolic rate (BMR); (xiv) heart index; and (xv) body age. ^8.^ The exercise system of claim 1, wherein the exercise data comprises at least one external force exerted on the exercise system, including; (i) weight; (ii) torque; (iii) time under tension; and (iv) weight distribution.

9. The exercise system of claim 1, wherein the exercise data comprises at least one of: (i) number of repetitions; (ii) speed of movements; (iii) length of movements; and (iv) time of exercise.

10. The exercise system of claim 1, wherein the sensor is a first sensor coupled to the elastic coupling and the exercise data is first exercise data, and the exercise system further comprises: a resistance band coupled to a lateral side of the first platform or a lateral side of the second platform; and a second sensor coupled to the resistance band and configured to collect second exercise data. 11.^ The exercise system of claim 1, wherein the elastic coupling comprises one or more elastic bands, and the sensor is configured to detect at least one of: (i) a number of elastic bands; and (ii) a resistance level of the one or more elastic bands. 12.^ A method of exercising using an exercise device that includes: (i) a first platform, (ii) a second platform, (iii) an elastic coupling configured to couple the first platform to the second platform, and (iv) a sensor coupled to the exercise device, the method comprising: advancing the second platform away from the first platform, thereby causing the elastic coupling to transition from a relaxed condition to a tensioned condition; and detecting exercise data via the sensor; and transmitting the detected exercise data to a computing device.

13. The method of claim 12, wherein the computing device comprises a graphical user interface and the exercise data comprises a measured force on the elastic coupling, the method further comprising: displaying a workout program via the graphical user interface, wherein the workout program comprises a target output force with respect to time; and displaying the measured force with respect to time via the graphical user interface. ^14. The method of claim 12, wherein detecting exercise metrics via the sensor further comprises: determining a tension force exerted on the elastic coupling.

15. The method of claim 12, wherein detecting exercise metrics via the sensor further comprises: determining a distance between the first platform and the second platform.

16. The method of claim 12, wherein the elastic coupling comprises one or more elastic bands, and wherein detecting exercise metrics via the sensor further comprises: determining a number of elastic bands coupled to the first platform or the second platform.

17. The method of claim 12, wherein detecting exercise metrics via the sensor further comprises: detecting at least one of: (i) heart rate; (ii) body mass index (BMI); (iii) muscle rate; (iv) body fat percentage; (v) subcutaneous fat percentage; (vi) visceral fat percentage; (vii) fat- free body weight; (viii) body water rate; (ix) skeletal muscle rate; (x) muscle mass; (xi) bone mass; (xii) protein level; (xiii) basal metabolic rate (BMR); (xiv) heart index; and (xv) body age.

18. An exercise system comprising: an exercise device comprising: a first platform; a second platform having one or more wheels; and an elastic coupling arranged between the first platform and the second platform, the elastic coupling being configured to transition from a relaxed condition to a tensioned condition as the second platform is advanced away from the first platform; and a sensor coupled to the exercise system and configured to detect exercise data; and a computing device comprising: a processor; and ^a non-transitory computer-readable storage medium, having stored thereon program instructions that, upon execution by the processor, cause performance of a set of operations comprising: receiving detected exercise data from the sensor; and outputting the exercise data for display via a graphical user interface.

19. The exercise system of claim 18, wherein the exercise data includes a measured force on the elastic coupling, wherein the set of operations further comprises: displaying a workout program via the graphical user interface, wherein the workout program comprises a target output force with respect to time; and displaying the measured force with respect to time via the graphical user interface.

20. The exercise system of claim 18, wherein the exercise data comprises a resistance strength of the elastic coupling and a distance between the first platform and the second platform.

21. The exercise system of claim 18, wherein the exercise data comprises at least one of: (i) heart rate; (ii) body mass index (BMI); (iii) muscle rate; (iv) body fat percentage; (v) subcutaneous fat percentage; (vi) visceral fat percentage; (vii) fat-free body weight; (viii) body water rate; (ix) skeletal muscle rate; (x) muscle mass; (xi) bone mass; (xii) protein level; (xiii) basal metabolic rate (BMR); (xiv) heart index; and (xv) body age. ^

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