The present invention relates generally to a fitness apparatus that can be used for professional and recreational training. The invention is, however, more particularly directed to an intelligent heavy bag system capable of stimulating and sensing impacts on the surface of the bag, and processing the magnitude, location, and time delay of those impacts to measure performance.
Mixed martial arts (MMA) has grown into a popular spectator sport over the last several years. Professional MMA fighters undergo rigorous training programs to improve and maintain their strength, conditioning, and technique. These training programs have become popular among fitness enthusiasts as well.
Martial arts training programs have proved to be an effective way to improve health and fitness. Many people see positive results from martial arts training, such as improved cardiovascular endurance, increased muscular strength and tone, as well as weight loss. It also helps users gain a sense of inner strength and emotional balance.
Martial arts are unique in working most of the main muscle groups at the same time. This is different from a workout at a normal gym, where different machines are needed for different muscle groups. Martial arts' particular combination of techniques and movements provides a full body workout in a single session.
Martial arts training sessions are typically complemented with various devices. One of the most common devices used in martial arts training is the heavy bag. The heavy bag resembles an opponent and is designed to be repeatedly punched and kicked. Traditional heavy bags and other training devices primarily lack the ability to provide performance tracking and feedback. As a result, multiple devices in the prior art have incorporated electronic components that enable them to capture and feedback performance data for any number of users.
In accordance with the invention, an intelligent heavy bag that can be used for both professional and recreational training at gyms, martial arts schools, and home is provided. In one embodiment, the intelligent bag comprises a central core assembly having an illumination system and impact sensor system. A layered body structure is disposed about the central core assembly, and is adapted to permit visible light to transmit through the layered body to the exterior of the heavy bag. The visible light defines lighting zones that indicate where and when a user should hit the surface of the heavy bag. The sensor system detects impact anywhere along the surface of the heavy bag.
In another aspect, the intelligent heavy bag includes a computational system with memory capability to store training sequences and performance data for multiple of users. The system can communicate with multiple external user interface devices for configuration, mode selection, data management, and real-time monitoring. Additionally, the system may be internet-ready, which allows locally stored data to be accessed and managed remotely. This internet connectivity can also be used for live peer-to-peer sessions, where two remote users can train against each other.
These and other aspects, features, and advantages of the present invention will become more readily apparent from the attached drawings and the detailed description of the exemplary embodiments, which follow.
Exemplary embodiments of the invention will hereinafter be described in conjunction with the appended drawings provided to illustrate and not to limit the invention, where like designations denote like elements, and in which:
The following detailed description is merely exemplary in nature and is not intended to limit the described embodiments or the application and uses of the described embodiments.
In one aspect, the intelligent heavy bag system is a customizable, modular system, which includes a body comprising a central core assembly to hold a core member disposed within the first and second layers. The central core assembly further includes a sensor system to sense and process impact upon the bag surface, and an illumination system to transmit visible light to an exterior of the heavy bag system. When illuminated, the visible lights define zones as an indicator for when and where to hit the heavy bag. Advantageously, the intelligent heavy bag system is capable of stimulating and sensing impacts upon the surface of the bag, and processing the magnitude, location, and time delay of those impacts to measure performance.
In one embodiment, as illustrated in
In one embodiment, a central core assembly 140 is configured to hold a core member 130 axially disposed within inner layer 120 and an outer layer 110 (best shown in
Core member 130 member defines an elongate tubular structure as shown in
The core member 130 is at least partially surrounded by inner layer 120
In an alternative embodiment as shown in
An illumination system locking bracket 181 supports one end of the illumination system to the upper lid as shown in
Outer layer 110 provides an external skin that surrounds inner layer 120. (
When the inner layer includes a plurality of holes 121 to permit light to transmit through the layer, translucent stumps 163 (
Referring back to
In another embodiment, central core assembly 140′ as shown in
Various other types of fasteners can be employed to secure the core member and inner and outer layers to the central core assembly, such as a plurality of fastening snaps, buttons, Velcro™ type hooks and loops, glue and the like.
As described above, the intelligent heavy bag can be configured to hang. In this aspect, the central core assembly may be configured to facilitate hanging from another structure. For example, the central core assembly 140 may include eye bolts 147 (
Users of traditional heavy bags sometimes manually introduce motion to the heavy bag in addition to the natural movements of the bag upon impact. The moving target resulting from the motion adds a level of difficulty. The intelligent heavy bag system 100 can be adapted to automatically induce motion by actuating chain 149 supporting the heavy bag to a ceiling or other structure. In one embodiment, the heavy bag system includes electromechanical actuators to actuate the chains to induce random or predetermined motions. The motion can also be generated based on the location and intention of the user. As a result, the bag can simulate offensive and evasive maneuvers.
The structural design of the intelligent heavy bag 100 can be intrinsically modular. Outer layer 110 and inner layer 120 may include different hardness that can easily be swapped during the manufacturing process. The weight of the heavy bag 100 can also be adjusted by attaching discs to the core of the bag. This modularity is highly desirable because some martial arts require heavy bags with different physical characteristics.
The intelligent heavy bag includes a sensor system capable of detecting impacts from a user upon the surface of the heavy bag. In one embodiment, the sensor system includes at least first and second impact sensors 150a, 150b disposed at opposing ends of the central core assembly bar 141, as shown in
In some embodiments, a high viscosity fluid is included within the housing, submerging sensors 150a, 150b. In such embodiments, the fluid provides a dynamic dampening proportional to the strength of the impact. The fluid also eliminates residual vibrations that produce unwanted noise.
As shown in
The placement of the first and second sensors at approximately opposite ends of the heavy bag system provides the capability to determine the vertical and/or angular location of an impact. The piezoelectric transducers inside each sensor capture the two horizontal components of an impact. These components are used to calculate the angular location and magnitude of an impact. In some embodiments, the piezoelectric transducers are arranged to flex upon impact. The signal generated by the piezoelectric transducers may be high output impedance and low power and thus may require amplification, compression and DC level conditioning to be processed by the microprocessor A/D converter.
The data is processed by a microprocessor that executes an impact detection algorithm to calculate the magnitude and location of the actual impacts anywhere on the surface of the bag. The impact detection algorithm comprises impact measurement, false impact exclusion, decompression, and calculation of the magnitude and position of the impact. Impact measurement includes ongoing monitoring of the sensor signals and processing only those portions of the signal that display the characteristics of an impact. These signals are further screened to exclude false impacts that may result from secondary oscillations. Decompression reverses the compression applied to the analog signal prior to conversion to digital. The magnitude and position of the impact may then be calculated.
In particular, the vector sum of the mechanical forces detected by piezoelectric transducers 151, 152 determines the direction from which the impact originated and its magnitude. The microprocessor receives output signals from each of the piezoelectric transducers of each of first and second impact sensors 150a, 150b. A scaling correction may be applied to each of the output signals in order to obtain a force measurement in preferred units. In other embodiments the scaling correction is a non-linear equation suitable for the response range of the particular piezoelectric transducer and compression algorithm. The angular direction of each piezoelectric transducer is known a priori, and in some embodiments, piezoelectric transducers 151, 152 are disposed at 90 degrees to each other and are each adapted to detect a force perpendicular to the axis of the core 141. The corrected force measurements and the known angular directions of the piezoelectric transducers are combined to form vectors v1 and v2. A vector sum v1+v2=f is computed to determine the direction and magnitude of the impact relative to the overall assembly. In some embodiments, the vectors calculated from the outputs of the piezoelectric transducers of each of first and second impact sensors 150a, 150b are averaged to determine the angular location of the impact.
Force vector f is computed for each of sensors 150a, 150b (f1 and f2). The ratio of the magnitudes of force vectors f1 and f2 is determined. Based on this ratio and the absolute magnitude of the vectors, the vertorial phase of each vector and the position of the center of gravity of the bag between impact sensor 150a, 150b, the position of the impact is determined along the vertical axis of the bag. In some embodiments, the absolute magnitudes of the vectors relative to the response range of the piezoelectric sensors are also considered. Different linear approximations of the nonlinear equation are used depending on the position of the impact to calculate the vertical location. These equations have various coefficients that are adjusted according to the physical properties of the bag.
As described, the heavy bag further includes an illumination system 162 (
When both the core member and inner layer include holes 131 and 121, the illumination elements 157 can be disposed in close proximity to holes 131 and holes 121 such that light is transmitted through both core member and inner layer. When core member or inner layer is formed from transparent or translucent material, the illumination elements have intensity capable of being visible exterior to the heavy bag system. In some embodiments, the illumination elements comprise a high intensity Light Emitting Diode (LED). In some embodiments, the illumination elements comprise a plurality of LEDs of different colors, that may be separately operated. In one embodiment, the illumination system is an internal LED matrix. The LEDs are high intensity RGB LEDs. In some embodiments, the illumination elements comprise a liquid crystal display (LCD) and a backlight.
Each of the illumination elements 157 are operatively connected to one or more printed circuit boards (PCB) 158. They may be connected to programmable elements assembled on a bus topology. In another implementation, all of the LEDs are connected to a common controller board (Star topology). The illumination elements form a plurality of lighting zones that can be actuated independently of each other. In other words, one or more of the plurality of lighting zones transmit light according to a predetermined or selective training module. In some embodiments, each of the PCBs is connected to a digital bus (not pictured) that runs along elongate member 159. In other embodiments, the PCBs 158 are omitted, and lighting control circuitry is integrated into integrated circuit 153. In one embodiment, for example, a light matrix controller sends a signal to the individual LED boards to light the illumination elements. These signals can be sent according to a stored sequence, or in response to a sensed impact upon the heavy bag.
The lighting zones can light up with different colors and/or different intensity. In some embodiments, PCB 158 is operable to separately illuminate one of several LEDs in illumination element 157. In some embodiments, PCB 158 is operable to receive a color code via a digital bus and illuminate a plurality of LEDs in proportion to the color components of the color code. For example, an RGB color code of 0xFF99CC would result in illumination of a red LED, green LED, and blue LED in the ratio of 255:153:204. In other embodiments, the PCB comprises display controller circuitry operable to control an LED display and the associated backlight.
In some embodiments, an embedded computational system is included in intelligent heavy bag system 100. The embedded computational system may be a general purpose computer, microprocessor/microcontroller, or may be an application specific integrated circuit, or field-programmable gate array. The embedded computation system is operably coupled to an output of each of impact sensors 150a, 150b. The embedded computation system is operably connected to each illumination element 157, either directly or through a digital bus and PCB 158. In some embodiments, the embedded computation system comprises a mass storage device encoding at least one training sequence comprising a plurality of timed indicators to activate at least one of illumination elements 157. The training sequence may be played back by the embedded computation system to illuminate illumination elements 157 according to the encoded sequence. In alternative embodiments, the functionality of the embedded computational system is provided by a computation system external to the heavy bag 100, but remaining operably coupled to an output of each of impact sensors via a wired or wireless connection.
In addition to using the lighting zones to instruct the user when and where to hit, after the user delivers an impact, the lighting zone(s) closest to the location of the impact can light up with a relevant color and intensity proportional to the strength of the impact. In other words, a color code and intensity can be used as feedback to the user of the detected performance. The color and intensity of the LEDs can be used to feedback performance to the user.
The magnitude, accuracy, as well as time delay between stimuli (lights) and response (impact) are used by the embedded computation system to measure performance. Hit accuracy can be measured by comparing the location of the illuminated lighting zone to the actual impact location as measured by sensors 150a, 150b, while the time delay is measured from the time the lighting zone is illuminated to the time that the impact is sensed.
The correlation between light stimuli and the data captured by the sensors can be processed by the computational system. The memory or non-transitory machine readable storage medium or mass storage device of the embedded computational system can store numerous training sequences as well as performance data collected for each of multiple users. In some embodiments, the embedded computational system is operable to record a training sequence through user interaction. In such embodiments, heavy bag system 100 comprises a learning mode switch. Upon activation of the learning mode switch, the embedded computational system begins recording impacts to the memory of the storage medium. In this mode, users impact the bag in multiple desired locations and then save the locations of the impacts into a new sequence.
In some embodiments, intelligent heavy bag system 100 includes wireless network interface 101. Wireless network connectivity may be provided through 802.11 (WiFi), Bluetooth, cellular data, or other wireless protocol known in the art. Wired connectivity may be provided by Ethernet or other wired protocols known in the art. The network interface may be connected to a LAN, a WAN or the Internet. In some embodiments, the embedded computational system comprises an embedded web server providing a web interface. In such embodiments, data recorded by the embedded computational system is accessible by a web browser of an external via wireless network interface 101. In some embodiments, the embedded computation system automatically and periodically uploads recorded data via wireless network interface 101 to a remote server. The remote server may be a remote web server, FTP server, cloud storage, or other data storage location known in the art. In some embodiments, the upload schedule and selected data may be determined by a user through the web interface. In some embodiments, a website is provided that allows users to track and share performance data as well as customize and share training sequences.
Desktops 102, notebooks 103, smart phones 104 and cell phones 105 can be used with a wireless connection 106 to communicate with the system 100 for configuration, mode selection, and data management. Additionally, a training session can be monitored by third parties (instructor, spectator, etc.) in real time using these client systems (see
As will be appreciated by one of skill in the art, the system of the present disclosure may be used in various network environments combining wireless and wired networks. In an exemplary deployment (
In another exemplary embodiment, a peer-to-peer mode (see
As used herein, the word “exemplary” or “illustrative” means “serving as an example, instance, or illustration.” Any implementation described herein as “exemplary” or “illustrative” is not necessarily to be construed as preferred or advantageous over other implementations. All of the implementations described below are exemplary implementations provided to enable persons skilled in the art to make or use the embodiments of the disclosure and are not intended to limit the scope of the disclosure, which is defined by the claims. For purposes of description herein, the terms “upper”, “lower”, “left”, “rear”, “right”, “front”, “vertical”, “horizontal”, and derivatives thereof shall relate to the invention as oriented in
While the preferred embodiments of the invention have been described above, it will be recognized and understood that various modifications can be made in the invention and the appended claims are intended to cover all such modifications which may fall within the spirit and scope of the invention.
This application claims priority to U.S. Provisional Patent Application Ser. No. 61/755,561 filed Jan. 23, 2013, the contents of which are incorporated herein by reference thereto.
Number | Date | Country | |
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61755561 | Jan 2013 | US |