US20220111256A1 - Weight Machine Sensor - Google Patents
Weight Machine Sensor Download PDFInfo
- Publication number
- US20220111256A1 US20220111256A1 US17/645,436 US202117645436A US2022111256A1 US 20220111256 A1 US20220111256 A1 US 20220111256A1 US 202117645436 A US202117645436 A US 202117645436A US 2022111256 A1 US2022111256 A1 US 2022111256A1
- Authority
- US
- United States
- Prior art keywords
- sensor
- rotation
- pulley
- data
- weight
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Abandoned
Links
- 230000033001 locomotion Effects 0.000 claims abstract description 26
- 230000003287 optical effect Effects 0.000 claims description 9
- 230000005355 Hall effect Effects 0.000 claims description 3
- 235000014676 Phragmites communis Nutrition 0.000 claims description 3
- 238000004891 communication Methods 0.000 description 16
- 238000000034 method Methods 0.000 description 9
- 230000006399 behavior Effects 0.000 description 7
- 230000000694 effects Effects 0.000 description 7
- 230000008569 process Effects 0.000 description 6
- 238000005516 engineering process Methods 0.000 description 5
- 230000015654 memory Effects 0.000 description 5
- 230000005540 biological transmission Effects 0.000 description 4
- 238000001514 detection method Methods 0.000 description 4
- ZLGYJAIAVPVCNF-UHFFFAOYSA-N 1,2,4-trichloro-5-(3,5-dichlorophenyl)benzene Chemical compound ClC1=CC(Cl)=CC(C=2C(=CC(Cl)=C(Cl)C=2)Cl)=C1 ZLGYJAIAVPVCNF-UHFFFAOYSA-N 0.000 description 3
- 238000003306 harvesting Methods 0.000 description 3
- 238000013459 approach Methods 0.000 description 2
- 230000009286 beneficial effect Effects 0.000 description 2
- 230000008859 change Effects 0.000 description 2
- 238000004590 computer program Methods 0.000 description 2
- 239000011888 foil Substances 0.000 description 2
- 230000007246 mechanism Effects 0.000 description 2
- 238000012544 monitoring process Methods 0.000 description 2
- 240000005020 Acaciella glauca Species 0.000 description 1
- RYGMFSIKBFXOCR-UHFFFAOYSA-N Copper Chemical compound [Cu] RYGMFSIKBFXOCR-UHFFFAOYSA-N 0.000 description 1
- 230000003321 amplification Effects 0.000 description 1
- 230000003466 anti-cipated effect Effects 0.000 description 1
- 238000004422 calculation algorithm Methods 0.000 description 1
- 238000004364 calculation method Methods 0.000 description 1
- 238000011161 development Methods 0.000 description 1
- 230000018109 developmental process Effects 0.000 description 1
- 230000005611 electricity Effects 0.000 description 1
- 230000005674 electromagnetic induction Effects 0.000 description 1
- 230000001815 facial effect Effects 0.000 description 1
- 239000000835 fiber Substances 0.000 description 1
- 230000006870 function Effects 0.000 description 1
- 230000003993 interaction Effects 0.000 description 1
- 230000002452 interceptive effect Effects 0.000 description 1
- 238000007726 management method Methods 0.000 description 1
- 238000004519 manufacturing process Methods 0.000 description 1
- 239000000463 material Substances 0.000 description 1
- 238000005259 measurement Methods 0.000 description 1
- 239000002184 metal Substances 0.000 description 1
- 229910052751 metal Inorganic materials 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 210000003205 muscle Anatomy 0.000 description 1
- 238000003199 nucleic acid amplification method Methods 0.000 description 1
- 230000002093 peripheral effect Effects 0.000 description 1
- 230000002085 persistent effect Effects 0.000 description 1
- 230000010399 physical interaction Effects 0.000 description 1
- 238000000554 physical therapy Methods 0.000 description 1
- 238000012545 processing Methods 0.000 description 1
- 230000035755 proliferation Effects 0.000 description 1
- 235000003499 redwood Nutrition 0.000 description 1
- 230000004044 response Effects 0.000 description 1
- 210000001525 retina Anatomy 0.000 description 1
- 230000000630 rising effect Effects 0.000 description 1
- 125000006850 spacer group Chemical group 0.000 description 1
- 239000010409 thin film Substances 0.000 description 1
- 238000012549 training Methods 0.000 description 1
- 230000000007 visual effect Effects 0.000 description 1
Images
Classifications
-
- A—HUMAN NECESSITIES
- A63—SPORTS; GAMES; AMUSEMENTS
- A63B—APPARATUS FOR PHYSICAL TRAINING, GYMNASTICS, SWIMMING, CLIMBING, OR FENCING; BALL GAMES; TRAINING EQUIPMENT
- A63B24/00—Electric or electronic controls for exercising apparatus of preceding groups; Controlling or monitoring of exercises, sportive games, training or athletic performances
- A63B24/0062—Monitoring athletic performances, e.g. for determining the work of a user on an exercise apparatus, the completed jogging or cycling distance
-
- A—HUMAN NECESSITIES
- A63—SPORTS; GAMES; AMUSEMENTS
- A63B—APPARATUS FOR PHYSICAL TRAINING, GYMNASTICS, SWIMMING, CLIMBING, OR FENCING; BALL GAMES; TRAINING EQUIPMENT
- A63B21/00—Exercising apparatus for developing or strengthening the muscles or joints of the body by working against a counterforce, with or without measuring devices
- A63B21/06—User-manipulated weights
- A63B21/062—User-manipulated weights including guide for vertical or non-vertical weights or array of weights to move against gravity forces
- A63B21/0626—User-manipulated weights including guide for vertical or non-vertical weights or array of weights to move against gravity forces with substantially vertical guiding means
- A63B21/0628—User-manipulated weights including guide for vertical or non-vertical weights or array of weights to move against gravity forces with substantially vertical guiding means for vertical array of weights
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/22—Ergometry; Measuring muscular strength or the force of a muscular blow
- A61B5/224—Measuring muscular strength
-
- A—HUMAN NECESSITIES
- A63—SPORTS; GAMES; AMUSEMENTS
- A63B—APPARATUS FOR PHYSICAL TRAINING, GYMNASTICS, SWIMMING, CLIMBING, OR FENCING; BALL GAMES; TRAINING EQUIPMENT
- A63B24/00—Electric or electronic controls for exercising apparatus of preceding groups; Controlling or monitoring of exercises, sportive games, training or athletic performances
- A63B24/0075—Means for generating exercise programs or schemes, e.g. computerized virtual trainer, e.g. using expert databases
-
- A—HUMAN NECESSITIES
- A63—SPORTS; GAMES; AMUSEMENTS
- A63B—APPARATUS FOR PHYSICAL TRAINING, GYMNASTICS, SWIMMING, CLIMBING, OR FENCING; BALL GAMES; TRAINING EQUIPMENT
- A63B71/00—Games or sports accessories not covered in groups A63B1/00 - A63B69/00
- A63B71/06—Indicating or scoring devices for games or players, or for other sports activities
- A63B71/0619—Displays, user interfaces and indicating devices, specially adapted for sport equipment, e.g. display mounted on treadmills
- A63B71/0622—Visual, audio or audio-visual systems for entertaining, instructing or motivating the user
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B2503/00—Evaluating a particular growth phase or type of persons or animals
- A61B2503/10—Athletes
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/117—Identification of persons
- A61B5/1171—Identification of persons based on the shapes or appearances of their bodies or parts thereof
- A61B5/1176—Recognition of faces
-
- A—HUMAN NECESSITIES
- A63—SPORTS; GAMES; AMUSEMENTS
- A63B—APPARATUS FOR PHYSICAL TRAINING, GYMNASTICS, SWIMMING, CLIMBING, OR FENCING; BALL GAMES; TRAINING EQUIPMENT
- A63B24/00—Electric or electronic controls for exercising apparatus of preceding groups; Controlling or monitoring of exercises, sportive games, training or athletic performances
- A63B24/0062—Monitoring athletic performances, e.g. for determining the work of a user on an exercise apparatus, the completed jogging or cycling distance
- A63B2024/0065—Evaluating the fitness, e.g. fitness level or fitness index
-
- A—HUMAN NECESSITIES
- A63—SPORTS; GAMES; AMUSEMENTS
- A63B—APPARATUS FOR PHYSICAL TRAINING, GYMNASTICS, SWIMMING, CLIMBING, OR FENCING; BALL GAMES; TRAINING EQUIPMENT
- A63B2220/00—Measuring of physical parameters relating to sporting activity
- A63B2220/50—Force related parameters
- A63B2220/51—Force
-
- A—HUMAN NECESSITIES
- A63—SPORTS; GAMES; AMUSEMENTS
- A63B—APPARATUS FOR PHYSICAL TRAINING, GYMNASTICS, SWIMMING, CLIMBING, OR FENCING; BALL GAMES; TRAINING EQUIPMENT
- A63B2220/00—Measuring of physical parameters relating to sporting activity
- A63B2220/80—Special sensors, transducers or devices therefor
- A63B2220/805—Optical or opto-electronic sensors
-
- A—HUMAN NECESSITIES
- A63—SPORTS; GAMES; AMUSEMENTS
- A63B—APPARATUS FOR PHYSICAL TRAINING, GYMNASTICS, SWIMMING, CLIMBING, OR FENCING; BALL GAMES; TRAINING EQUIPMENT
- A63B2220/00—Measuring of physical parameters relating to sporting activity
- A63B2220/80—Special sensors, transducers or devices therefor
- A63B2220/807—Photo cameras
-
- A—HUMAN NECESSITIES
- A63—SPORTS; GAMES; AMUSEMENTS
- A63B—APPARATUS FOR PHYSICAL TRAINING, GYMNASTICS, SWIMMING, CLIMBING, OR FENCING; BALL GAMES; TRAINING EQUIPMENT
- A63B2220/00—Measuring of physical parameters relating to sporting activity
- A63B2220/80—Special sensors, transducers or devices therefor
- A63B2220/83—Special sensors, transducers or devices therefor characterised by the position of the sensor
- A63B2220/833—Sensors arranged on the exercise apparatus or sports implement
-
- A—HUMAN NECESSITIES
- A63—SPORTS; GAMES; AMUSEMENTS
- A63B—APPARATUS FOR PHYSICAL TRAINING, GYMNASTICS, SWIMMING, CLIMBING, OR FENCING; BALL GAMES; TRAINING EQUIPMENT
- A63B2220/00—Measuring of physical parameters relating to sporting activity
- A63B2220/80—Special sensors, transducers or devices therefor
- A63B2220/89—Field sensors, e.g. radar systems
-
- A—HUMAN NECESSITIES
- A63—SPORTS; GAMES; AMUSEMENTS
- A63B—APPARATUS FOR PHYSICAL TRAINING, GYMNASTICS, SWIMMING, CLIMBING, OR FENCING; BALL GAMES; TRAINING EQUIPMENT
- A63B2225/00—Miscellaneous features of sport apparatus, devices or equipment
- A63B2225/15—Miscellaneous features of sport apparatus, devices or equipment with identification means that can be read by electronic means
-
- A—HUMAN NECESSITIES
- A63—SPORTS; GAMES; AMUSEMENTS
- A63B—APPARATUS FOR PHYSICAL TRAINING, GYMNASTICS, SWIMMING, CLIMBING, OR FENCING; BALL GAMES; TRAINING EQUIPMENT
- A63B2225/00—Miscellaneous features of sport apparatus, devices or equipment
- A63B2225/20—Miscellaneous features of sport apparatus, devices or equipment with means for remote communication, e.g. internet or the like
-
- A—HUMAN NECESSITIES
- A63—SPORTS; GAMES; AMUSEMENTS
- A63B—APPARATUS FOR PHYSICAL TRAINING, GYMNASTICS, SWIMMING, CLIMBING, OR FENCING; BALL GAMES; TRAINING EQUIPMENT
- A63B2225/00—Miscellaneous features of sport apparatus, devices or equipment
- A63B2225/50—Wireless data transmission, e.g. by radio transmitters or telemetry
- A63B2225/52—Wireless data transmission, e.g. by radio transmitters or telemetry modulated by measured values
-
- A—HUMAN NECESSITIES
- A63—SPORTS; GAMES; AMUSEMENTS
- A63B—APPARATUS FOR PHYSICAL TRAINING, GYMNASTICS, SWIMMING, CLIMBING, OR FENCING; BALL GAMES; TRAINING EQUIPMENT
- A63B2225/00—Miscellaneous features of sport apparatus, devices or equipment
- A63B2225/50—Wireless data transmission, e.g. by radio transmitters or telemetry
- A63B2225/54—Transponders, e.g. RFID
-
- A—HUMAN NECESSITIES
- A63—SPORTS; GAMES; AMUSEMENTS
- A63B—APPARATUS FOR PHYSICAL TRAINING, GYMNASTICS, SWIMMING, CLIMBING, OR FENCING; BALL GAMES; TRAINING EQUIPMENT
- A63B2230/00—Measuring physiological parameters of the user
- A63B2230/75—Measuring physiological parameters of the user calorie expenditure
Definitions
- FIG. 1 shows a configuration of the weight machine sensor that can be attached to a variety of weight machines.
- FIG. 2 illustrates an exploded view of the device shown in FIG. 1 .
- FIG. 3 shows a cross-sectional side view of the device shown in FIG. 1 .
- FIG. 4 shows the device in FIG. 1 incorporated into the frame of a weight machine.
- FIG. 5 shows the configuration of FIG. 4 from a side view illustrating how the tension in the cable of the weight machine translates into force exerted onto the pulley.
- FIG. 6 shows a configuration of the weight machine sensor in which the pulley is in line with the force sensor.
- FIG. 7 shows a configuration of the weight machine sensor in which the base mounts directly to the moving stack of weights.
- FIG. 8 shows a configuration of the weight machine sensor featuring an “E type” load cell as the force sensor.
- FIG. 9 shows a configuration of the weight machine sensor featuring a button type load cell as the force sensor.
- FIG. 10 shows a configuration of the weight machine sensor featuring a load pin load cell integrated into the shaft of the pulley as the force sensor.
- FIG. 11 shows a configuration of the weight machine sensor featuring componentry to facilitate kinetic charging of a battery.
- FIG. 12 shows a configuration of the weight machine sensor featuring a solar panel for charging of a battery.
- FIG. 13 shows a configuration of the weight machine sensor featuring a plurality of position sensors for detecting the weight setting on an exercise machine as well as the motion behavior of those weights during an exercise.
- Weight machines typically allow users to set his/her training resistance by isolating some fraction of a stack of weights using a pin, lever, or some other mechanism.
- the mechanical configuration of the machine is such that when the user moves in the intended fashion the weights that were isolated move in accordance with the movement of the body, thereby providing resistance to the desired muscle group or groups that is proportional to the weight setting selected by the user.
- Translating motion of the body into the rising and falling of the weight stack is achieved by using a cable or belt and a series of one or more pulleys to redirect the tension such that it resists the movement.
- Using a stack of weights is the most common form of resistance for these machines, sometimes referred to as “selectorized” machines, but resistance can be provided in other ways. For example, resistance can be provided by flexing one or more beams, or by an electromechanical device such as a motor or dynamo.
- One solution for recording fitness activity on an exercise machine involves a weight machine sensor that can detect repetitions performed on the exercise machine, especially one that requires a user to tension a cable to provide resistance.
- An example of this sensor is a device that can detect the weight lifted—or force exerted—by the user and the number of repetitions performed on the exercise equipment.
- the device includes a force sensor programmed to output a force signal representing a force applied to a cable associated with the piece of exercise equipment.
- the weight machine sensor further includes a rotation sensor to determine from the rotation of the pulley, providing information about the exercise being performed. Rotation of the pulley can be used to measure the physical movement of the stack of weights, but alternatively a position sensor or rangefinder can also be used to achieve the same result.
- the weight machine sensor further includes a processor programmed to receive the force signal and rotation signals and determine, from these signals, exercise data including an amount of weight lifted and a number of repetitions performed.
- the exercise data can be transmitted to and viewed by the user of the exercise equipment.
- the exercise data may be transmitted to a remote server.
- the user can view the exercise data by accessing the data stored on the remote server via, e.g., a computer such as a smartphone, tablet computer, a desktop computer, a laptop computer, or the like.
- the elements shown may take many different forms and include multiple and/or alternate components and facilities.
- the example components illustrated are not intended to be limiting. Indeed, additional or alternative components and/or implementations may be used. Further, the elements shown are not necessarily drawn to scale unless explicitly stated as such.
- FIG. 1 shows one basic form of the weight machine sensor 100 which features a base 102 , a pulley 104 , and a cover 106 to protect the enclosed electronic components.
- a rotation sensor 108 extends through the cover 106 to measure rotation of the pulley 104 as a way to calculate exercise data.
- Rotation data can be translated into position data for the weight stack 134 and therefore also velocity of the weight stack 134 , range of motion, and repetitions.
- This position or rotation signal is combined with information about the tension in the cable other metrics such as work output, power output, and calories burned can also be calculated.
- the rotation sensor 108 shown in the figure is an optical sensor that interacts with features or marks on the pulley 104 to infer information about the amount of rotation and direction of rotation of the pulley 104 .
- Some rotation sensors work by reflecting light off of a surface and observing the pattern of reflected light, while others feature a light emitting source opposed from a light detector that observes the pattern of light passed through a series of slots, protrusions, or other feature on a rotating wheel.
- This rotation sensor might also feature multiple sensors that, when used simultaneously, can help determine the direction of rotation from the pattern observed when comparing the two signals.
- Magnets can also be embedded in the pulley or other rotating feature allowing for hall effect or reed sensors to determine rotation information from the resulting magnetic interaction signal.
- Optical or magnetic rotation sensors do not require direct physical contact with the pulley and therefore do not cause friction nor will they wear out mechanically.
- a potentiometer or other absolute position sensor could also be used because the pulley 104 is limited to a specific number of revolutions depending upon the diameter of the pulley and range of travel of the weight stack 134 .
- the weight machine sensor 100 shown in FIG. 1 is modular in nature such that it can be placed at various locations and on various makes and models of weight machines without significant re-engineering.
- the compactness of the device and simple hole-mounts 103 featured in the base 102 serve to make the sensor more universally implementable with some simple additional mounting brackets, shims, and/or fasteners.
- the device could therefore be used to retrofit existing lines of equipment or could be directly integrated into the machines as they are being manufactured.
- FIG. 2 shows an exploded view of the example device shown in FIG. 1 with the cover 106 removed to reveal some of the internal components. Removal of the screws 122 allows for accessing or servicing the internal components.
- a shoulder bolt 110 connects the pulley 104 to a force sensor 114 with a bushing 112 utilized to fill the difference between the inner diameter of the bearing in the pulley 104 and the outer diameter of the shoulder bolt 110 .
- the force sensor is then rigidly fixed to the base 102 with a bolt 116 .
- the example force sensor 114 shown here features a strain gauge (e.g., a metal foil gauge) fixed directly to a rigid beam that is deflected when a load is applied.
- a strain gauge e.g., a metal foil gauge
- the force sensor features a cantilevered body designed to deflect an amount proportional to the force applied
- the force may be measured by the strain gauge, which may include a metallic foil with an electrical resistance that changes based on the amount of deflection.
- the change in resistance may be amplified via, e.g., a Wheatstone bridge circuit or other type of amplification circuit.
- the force exerted onto the force sensor 114 via the pulley 104 may be measured via a piezo-resistive force sensor, a pressure transducer, a thin film pressure sensor, or any other force-measuring sensor could be employed.
- a spacer 118 is included to control the position of the pulley 104 relative to the force sensor 114 .
- a printed circuit board (PCB′ 120 contains the microprocessor 121 as well as peripheral integrated circuitry for processing the signals received from the force sensor 114 and rotation sensor 108 . Additionally, the PCB 120 includes a wireless communication device 123 (e.g., a wireless transmitter) for transmitting the data that is recorded by the sensors.
- the PCB also includes a wire connector 125 such as a barrel connector for providing and receiving wired data transmission, power, or both data transmission and power simultaneously.
- FIG. 3 shows a side view of the weight machine sensor 100 shown in FIG. 1 with the cover 106 and associated screws 122 removed.
- This figure more clearly illustrates how the pulley 104 is connected to a force sensor 114 which in this example configuration utilizes strain gauges applied to a beam cantilevered from the base 102 .
- An example of the direction of force 124 is shown with an arrow, but the force sensor 114 can be configured to measure force applied in any direction. For example, if a cable is routed such that it contacts the top of the pulley 104 the direction of force will be downward, while if the cable is routed such that it contacts the bottom of the pulley 104 the direction of force will be upward.
- FIG. 4 shows a perspective view of the weight machine sensor 100 affixed to the rigid frame 126 of the exercise machine.
- the sensor 100 may be associated with (e.g., identify or otherwise distinguish) the user performing the exercise. This association may facilitate workout tracking and progress monitoring over time as well as administer more sophisticated automated coaching programs which would be unique to each user.
- a short range communication device 127 implemented via an antenna, circuits, chips, and possibly other electronic components could be integrated into the sensor system. Examples of the short range communication device 127 may include a near field communication (NFC) or radio frequency identification (RIM) check-in electronic (hardware) module.
- NFC near field communication
- RIM radio frequency identification
- Most fitness trackers, wearables, smart phones, and smart watches include NFC or RFD readable chips which could be used to check the user in to the exercise machine.
- a dedicated monitor 130 on the exercise machine allows real-time data and coaching feedback 131 to be displayed to the user. The data could be transmitted from the weight machine sensor 100 to the monitor wirelessly or physically wired via the wire connector 125 included on the PCB 120 .
- the coaching feedback 131 displayed on the screen could include time-series data such as force, power, repetition count, calories burned, position, or total work output for that set. It could also include scatter plots that do not include time on one of the axes but rather a combination of two of the coaching metrics. For example, a graph showing power on one axis and position on the other axis could be useful. Or repetition count on one axis and total work on another axis as another example. But any combination of metrics provided by the sensor could be configured to suit the needs of the coaching paradigm, trainer, or exerciser. These metrics could be displayed on the dedicated monitor 130 or a remote device 190 (see FIG. 1 ), such as a mobile phone, smartwatch, or wearable activity tracker, or to a remote server 195 (see FIG. 1 ), such as a cloud-based server or a server associated with a particular facility (e.g., a gym).
- a remote device 190 see FIG. 1
- a remote server 195 see FIG. 1
- a bracket may allow the base 102 to be rigidly mounted to the frame 126 such that any force transferred from the cable 128 to the pulley 104 is thereby detected by the force sensor 114 . If the cable 128 were to pass by the pulley 104 without being rerouted such that it remained a straight line, there could be sufficient friction to rotate the pulley 104 and therefore record motion and position data via the rotation sensor 108 . To record data regarding the amount of weight lifted, however, the tension in the cable 128 should also be measured. For this reason, the pulley 104 should actively reroute the cable 128 by some angle. The force applied by the cable 128 to the pulley 104 can then be measured by the force sensor 114 to deduce the tension in the cable and therefore the amount of resistance experienced by the user.
- FIG. 5 shows a side view of the configuration shown in FIG. 4 .
- This angle makes the resultant force 124 applied to the pulley 104 by the cable 128 more apparent. Rerouting the cable 128 by a small angle will result in a force 124 that is small relative to the tension in the cable. Rerouting the cable 128 by a large angle, conversely, will result in a relatively higher force 124 .
- Translating the force measurement to weight values can be achieved by calibrating the device as the relationship is in most cases a basic linear fit. For the weight machine sensor to measure adequate information about the exercise being performed, it measures two basic details of the activity: the amount of weight being lifted and the motion behavior of the weight stack 134 .
- the force sensor incorporated into the base and pulley assembly allows the sensor to deduce the weight being lifted, but there are more ways to measure the motion behavior of the weight stack 134 .
- One configuration presented earlier features a rotation sensor on the pulley.
- Another approach is to use an optical position sensor 144 that is mounted to the frame 126 of the weight machine and oriented toward the weight stack 134 to measure its position.
- the position sensor 144 could include an infrared sensor, a lidar sensor, an ultrasonic sensor, or any other form of position detection.
- the position sensor 144 in a position where it is fixed relative to the sensor is most convenient, but the same results could be achieved by mounting the position sensor 144 such that it moves relative to the weight stack 134 and measures position relative to a fixed object such as the frame 126 .
- the examples just cited feature an optical way to “watch” the behavior of the weight stack 134 without any physical interaction, but a string wrapped around a rotary encoder that extends from the weight stack 134 could also be used as a way to measure the motion behavior.
- Another way to deduce the weight setting used by the user would be to connect the weight selector pin to the aforementioned string.
- the length of the string when it is in its selector location could indicate the weight resistance chosen by the user.
- a single rotatory encoder could be used to determine both the weight setting selected by the user and the motion behavior of the weight stack 134 .
- FIG. 6 shows a configuration of the weight machine sensor in which the pulley 104 is in line with the force sensor 114 , rather than cantilevered off the side as shown in the configuration represented in FIG. 1 .
- FIG. 7A shows a configuration of the weight machine sensor in which the base 102 has a bracket for containing the pulley 104 , and the base 102 mounts directly to a weight selector tube 132 which in turn raises the stack of weights 134 .
- a portion of the bracket is removed such that force exerted onto the pulley 104 by the cable 128 is transferred, at least in part, through the force sensor 114 attached to the base 102 .
- the example shown here features an “S type” load cell as the force sensor but other configurations or force sensor types could be employed.
- FIG. 7B shows an alternate view of the configuration shown in FIG.
- the weight machine sensor 100 could include a rotation sensor 108 , a motion sensor, or both. Because the device is moving, an accelerometer could be used as a motion sensor, although position sensors such as infrared (IR), ultrasonic, or lidar, for example, could also be used.
- IR infrared
- ultrasonic ultrasonic
- lidar lidar
- the pulley 104 might be lifted by the cable 128 on the left side causing clockwise motion, lifted by the right side causing counter-clockwise motion, or lifted by both sides simultaneously to allow for raising the weights with little or no rotation of the pulley 104 .
- rotation data and motion data for this example application.
- FIG. 8 shows a configuration of the weight machine sensor featuring an “E type” load cell as the force sensor.
- the force sensor 114 could be positioned to measure force transferred between the base 102 and the fixed, rigid frame 126 of the weight machine.
- the force sensor 114 could be positioned to measure force transferred between the base 102 and the weight selector tube 132 .
- the weight machine sensor 100 could be positioned such that it is stationary or it could be positioned such that it moves in accordance with movement of the weights or other resistance source.
- FIG. 9 shows a variation of the weight machine sensor 100 shown in FIG. 8 but features a button type load cell as the force sensor rather than an “E type” load cell.
- FIG. 10 shows a configuration of the weight machine sensor 100 featuring a load pin load cell integrated into the shaft of the pulley as the force sensor 114 .
- FIG. 11 shows an exploded view of the same weight machine sensor 100 shown in FIG. 2 , but with some additional kinetic charger components to facilitate kinetic charging of a battery that powers the device.
- the kinetic charger components include electrical coils 136 fixed to the base 102 and positioned in such a way that an electrical current is generated when the plurality of magnets 138 rotate.
- the magnets 138 are mounted in a fashion such that rotation of the pulley 104 causes rotation of the magnets 138 and therefore the production of an electrical current through the coils 136 .
- the circuitry could be set up such that the resulting torque applied to the pulley from electromagnetic induction will be experienced only when the weights are being lowered to not add any additional resistance when the weights are being lifted. In this case, electricity would also only be generated when the weights are being lowered.
- One possible rotation sensor 108 technology features rotating magnets and a hall-effect or reed sensor to deduce rotational position and rotational direction data.
- the rotation sensor 108 could be situated such that the magnets 138 used for kinetic charging could also be used for rotation detection.
- FIG. 12 illustrates another possible way to harvest energy featuring a solar panel 140 to charge a battery 142 that runs the electronics on the weight machine sensor 100 .
- a solar panel 140 or photovoltaic cell of some form, could provide the power required to run the device.
- the weight machine sensor 100 operates in a “low-power” or “sleep” mode for extended periods of time and will “wake up” and transmit data only when in use. A wake sensor allows for this functionality. Given these usage patterns the solar panel 140 need not be able to provide the maximum power requirement such as when the device is awake and transmitting data wirelessly, but rather merely provide the average power requirement.
- the presence of a battery 142 allows for a buffer to store the harvested energy to be delivered whenever the device demands.
- the battery would also be included in the configuration shown in FIG. 11 featuring kinetic energy harvesting and could also be included in any of the other configurations described herein.
- FIG. 13 demonstrates a configuration of the weight machine sensor 100 wherein a plurality of optical position sensors 144 can be arranged in a manner to allow detection of the amount of weight resistance chosen from the weight stack 134 as well as the motion behavior of the weight stack 134 .
- the position sensors 144 could include an infrared sensor, a lidar sensor, an ultrasonic sensor, or any other form of position detection or combination thereof.
- a position sensor 144 arranged on the frame 126 of the machine facing downward, for example, could view the motion of the weight stack 134 while position sensors 144 arranged adjacent to the weight stack, possibly horizontally angled, could view the weight stack 134 from a different angle and thereby be used by the microprocessor 121 to infer the weight setting.
- the algorithms implemented on the microprocessor 121 could calculate the thickness of the material being moved and therefore determine the weight setting and therefore the exercise data produced by other configurations of the weight machine sensor.
- the combination of the force sensor 114 and rotation sensor 108 data (or position sensor 144 data), which the microprocessor 121 is programmed to determine from the force signal output by the force sensor and the motion signal output by the rotation sensor, respectively, allows for calculation of many exercise metrics (referred to as “exercise data”) that allow the exerciser to monitor the progress of his/her physical fitness and automate the delivery of coaching feedback 131 .
- exercise data many exercise metrics
- the user's strength, force, power, work output, calorie expenditure, repetition count, and weight resistance settings can all be tracked and compared to historical performance.
- the microprocessor 121 may be programmed to calculate strength, force, power, work output, calorie expenditure, and weight resistance setting from the force signal output by the force sensor, the motion signal output by the position/rotation sensor, or both.
- the metrics also allow for engagement with an interactive community whose members could be in close proximity or geographically dispersed. For example, the metrics could be displayed on a leaderboard with real time comparisons of the group of participants, or the participants could be exercising in a home gym environment with a similar leaderboard monitoring and comparing everyone's progress.
- the workouts that are part of this described experience could be self-guided, loaded on an “on-demand” basis, or streamed live onto the user's television, mobile device, or wearable fitness tracker.
- the wireless communication device 123 may be implemented via an antenna, circuits, chips, or other electronic components configured or programmed to facilitate wireless communication.
- the wireless communication device may be programmed to transmit the data collected by the force sensor, rotation sensor, or both via a telecommunication protocol such as Bluetooth®, Bluetooth Low Energy®, etc., to a remote device 190 (see FIG. 1 ) such as a mobile phone, smartwatch, or wearable activity tracker, or to a remote server 195 (see FIG. 1 ), such as a cloud-based server or a server associated with a particular facility (e.g., a gym).
- Wireless communication could be the only way to communicate the exercise data or it could be secondary to data transmission via a wired connection such as with an ethernet cable.
- remote device 190 and remote server 195 may be physically near the exercise tracker 100 (i.e., the remote server 195 may be in communication with the exercise tracker 100 , the remote device 190 , or both, via a local network connection).
- the remote device 190 or remote server 195 may be physically “remote” but still in signal communication with the exercise tracker 100 (e.g., the remote server 195 may be cloud-based).
- the data may be transmitted from the weight machine sensor 100 to the remote device 190 or the remote server 195 (see FIG. 1 ) via a Wi-Fi network connection.
- the wireless communication device may be programmed to periodically transmit the collected data to the remote device or remote server, or transmit the data as it is collected.
- the wireless communication device may be programmed to transmit the data to the remote device or the remote server 195 at specific times, such as when all repetitions have been performed or when a workout is complete.
- the wireless communication device may determine that all repetitions have been performed based on the force sensor signal or that the workout is complete in response to a user input provided to the exercise machine input or remote device 195 .
- the computing systems and/or devices described may employ any of a number of computer operating systems, including, but by no means limited to, versions and/or varieties of the Microsoft Windows® operating system, the Unix operating system (e.g., the Solaris® operating system distributed by Oracle Corporation of Redwood Shores, Calif.), the AIX UNIX operating system distributed by International Business Machines of Armonk, N.Y., the Linux operating system, the Mac OSX, macOS, and iOS operating systems distributed by Apple Inc. of Cupertino, Calif., the BlackBerry OS distributed by Blackberry, Ltd. of Waterloo, Canada, and the Android operating system developed by Google, Inc. and the Open Handset Alliance.
- Examples of computing devices include, without limitation, a computer workstation, a server, a desktop, notebook, laptop, or handheld computer, or some other computing system and/or device.
- Computing devices generally include computer-executable instructions, where the instructions may be executable by one or more computing devices such as those listed above.
- Computer-executable instructions may be compiled or interpreted from computer programs created using a variety of programming languages and/or technologies, including, without limitation, and either alone or in combination, JavaTM, C, C++, Visual Basic, Java Script, Perl, etc. Some of these applications may be compiled and executed on a virtual machine, such as the Java Virtual Machine, the Dalvik virtual machine, or the like.
- a processor e.g., a microprocessor
- receives instructions e.g., from a memory, a computer-readable medium, etc., and executes these instructions, thereby performing one or more processes, including one or more of the processes described herein.
- Such instructions and other data may be stored and transmitted using a variety of computer-readable media.
- a computer-readable medium includes any non-transitory (e.g., tangible) medium that participates in providing data (e.g., instructions) that may be read by a computer (e.g., by a processor of a computer).
- a medium may take many forms, including, but not limited to, non-volatile media and volatile media.
- Non-volatile media may include, for example, optical or magnetic disks and other persistent memory.
- Volatile media may include, for example, dynamic random access memory (DRAM), which typically constitutes a main memory.
- Such instructions may be transmitted by one or more transmission media, including coaxial cables, copper wire and fiber optics, including the wires that comprise a system bus coupled to a processor of a computer.
- Computer-readable media include, for example, a floppy disk, a flexible disk, hard disk, magnetic tape, any other magnetic medium, a CD-ROM, DVD, any other optical medium, punch cards, paper tape, any other physical medium with patterns of holes, a RAM, a PROM, an EPROM, a FLASH-EEPROM, any other memory chip or cartridge, or any other medium from which a computer can read.
- Databases, data repositories or other data stores described herein may include various kinds of mechanisms for storing, accessing, and retrieving various kinds of data, including a hierarchical database, a set of files in a file system, an application database in a proprietary format, a relational database management system (RDBMS), etc.
- Each such data store is generally included within a computing device employing a computer operating system such as one of those mentioned above, and are accessed via a network in any one or more of a variety of manners.
- a file system may be accessible from a computer operating system, and may include files stored in various formats.
- An RDBMS generally employs the Structured Query Language (SQL) in addition to a language for creating, storing, editing, and executing stored procedures, such as the PL/SQL language mentioned above.
- SQL Structured Query Language
- system elements may be implemented as computer-readable instructions (e.g., software) on one or more computing devices (e.g., servers, personal computers, etc.), stored on computer readable media associated therewith (e.g., disks, memories, etc.).
- a computer program product may comprise such instructions stored on computer readable media for carrying out the functions described herein.
Landscapes
- Health & Medical Sciences (AREA)
- General Health & Medical Sciences (AREA)
- Physical Education & Sports Medicine (AREA)
- Life Sciences & Earth Sciences (AREA)
- Engineering & Computer Science (AREA)
- Biophysics (AREA)
- Human Computer Interaction (AREA)
- Medical Informatics (AREA)
- Veterinary Medicine (AREA)
- Multimedia (AREA)
- Orthopedic Medicine & Surgery (AREA)
- Physics & Mathematics (AREA)
- Pathology (AREA)
- Biomedical Technology (AREA)
- Heart & Thoracic Surgery (AREA)
- Public Health (AREA)
- Molecular Biology (AREA)
- Surgery (AREA)
- Animal Behavior & Ethology (AREA)
- Databases & Information Systems (AREA)
- Software Systems (AREA)
- Arrangements For Transmission Of Measured Signals (AREA)
- Measurement Of The Respiration, Hearing Ability, Form, And Blood Characteristics Of Living Organisms (AREA)
Abstract
A weight machine sensor includes a force sensor, a position sensor, and a processor. The force sensor is programmed to output a force signal representing a force applied to a pulley-disposed on a cable incorporated into exercise equipment having a stack of weights. The position sensor is programmed to detect motion of the stack of weights and output a position signal representing the motion detected. The processor is programmed to receive the force signal and the rotation signal and determine, from the force signal and the position signal, exercise data including an amount of exercise resistance and a number of repetitions performed.
Description
- This application claims priority to provisional patent application No. 62/514,941 titled “SENSOR EQUIPPED EXERCISE MACHINE PULLEY” filed on Jun. 4, 2017, the contents of which are hereby incorporated by reference in their entirety.
- The advent of fitness trackers coupled with the increasing ease with which digital data can be wirelessly recorded has led to a proliferation of technologies that allow users to track and gain insights from their exercise activities.
-
FIG. 1 shows a configuration of the weight machine sensor that can be attached to a variety of weight machines. -
FIG. 2 illustrates an exploded view of the device shown inFIG. 1 . -
FIG. 3 shows a cross-sectional side view of the device shown inFIG. 1 . -
FIG. 4 shows the device inFIG. 1 incorporated into the frame of a weight machine. -
FIG. 5 shows the configuration ofFIG. 4 from a side view illustrating how the tension in the cable of the weight machine translates into force exerted onto the pulley. -
FIG. 6 shows a configuration of the weight machine sensor in which the pulley is in line with the force sensor. -
FIG. 7 shows a configuration of the weight machine sensor in which the base mounts directly to the moving stack of weights. -
FIG. 8 shows a configuration of the weight machine sensor featuring an “E type” load cell as the force sensor. -
FIG. 9 shows a configuration of the weight machine sensor featuring a button type load cell as the force sensor. -
FIG. 10 shows a configuration of the weight machine sensor featuring a load pin load cell integrated into the shaft of the pulley as the force sensor. -
FIG. 11 shows a configuration of the weight machine sensor featuring componentry to facilitate kinetic charging of a battery. -
FIG. 12 shows a configuration of the weight machine sensor featuring a solar panel for charging of a battery. -
FIG. 13 shows a configuration of the weight machine sensor featuring a plurality of position sensors for detecting the weight setting on an exercise machine as well as the motion behavior of those weights during an exercise. - Despite the increased interest in digitizing and recording users' fitness activity, currently-available products do not accurately capture the activity performed on weight machines commonly found in home gyms, commercial gyms, corporate wellness facilities, or physical therapy centers. Thus, a device which can integrate this significant aspect of physical fitness into the expanding ecosystem of fitness trackers would be beneficial.
- Weight machines typically allow users to set his/her training resistance by isolating some fraction of a stack of weights using a pin, lever, or some other mechanism. The mechanical configuration of the machine is such that when the user moves in the intended fashion the weights that were isolated move in accordance with the movement of the body, thereby providing resistance to the desired muscle group or groups that is proportional to the weight setting selected by the user. Translating motion of the body into the rising and falling of the weight stack is achieved by using a cable or belt and a series of one or more pulleys to redirect the tension such that it resists the movement. Using a stack of weights is the most common form of resistance for these machines, sometimes referred to as “selectorized” machines, but resistance can be provided in other ways. For example, resistance can be provided by flexing one or more beams, or by an electromechanical device such as a motor or dynamo.
- One solution for recording fitness activity on an exercise machine involves a weight machine sensor that can detect repetitions performed on the exercise machine, especially one that requires a user to tension a cable to provide resistance. An example of this sensor is a device that can detect the weight lifted—or force exerted—by the user and the number of repetitions performed on the exercise equipment. The device includes a force sensor programmed to output a force signal representing a force applied to a cable associated with the piece of exercise equipment. The weight machine sensor further includes a rotation sensor to determine from the rotation of the pulley, providing information about the exercise being performed. Rotation of the pulley can be used to measure the physical movement of the stack of weights, but alternatively a position sensor or rangefinder can also be used to achieve the same result. The weight machine sensor further includes a processor programmed to receive the force signal and rotation signals and determine, from these signals, exercise data including an amount of weight lifted and a number of repetitions performed.
- The exercise data can be transmitted to and viewed by the user of the exercise equipment. In some instances, the exercise data may be transmitted to a remote server. The user can view the exercise data by accessing the data stored on the remote server via, e.g., a computer such as a smartphone, tablet computer, a desktop computer, a laptop computer, or the like.
- The elements shown may take many different forms and include multiple and/or alternate components and facilities. The example components illustrated are not intended to be limiting. Indeed, additional or alternative components and/or implementations may be used. Further, the elements shown are not necessarily drawn to scale unless explicitly stated as such.
-
FIG. 1 shows one basic form of theweight machine sensor 100 which features abase 102, apulley 104, and acover 106 to protect the enclosed electronic components. In this implementation, arotation sensor 108 extends through thecover 106 to measure rotation of thepulley 104 as a way to calculate exercise data. Rotation data can be translated into position data for theweight stack 134 and therefore also velocity of theweight stack 134, range of motion, and repetitions. When this position or rotation signal is combined with information about the tension in the cable other metrics such as work output, power output, and calories burned can also be calculated. Therotation sensor 108 shown in the figure is an optical sensor that interacts with features or marks on thepulley 104 to infer information about the amount of rotation and direction of rotation of thepulley 104. - Some rotation sensors, or rotary encoders, work by reflecting light off of a surface and observing the pattern of reflected light, while others feature a light emitting source opposed from a light detector that observes the pattern of light passed through a series of slots, protrusions, or other feature on a rotating wheel. This rotation sensor might also feature multiple sensors that, when used simultaneously, can help determine the direction of rotation from the pattern observed when comparing the two signals. Magnets can also be embedded in the pulley or other rotating feature allowing for hall effect or reed sensors to determine rotation information from the resulting magnetic interaction signal. Optical or magnetic rotation sensors do not require direct physical contact with the pulley and therefore do not cause friction nor will they wear out mechanically. These are examples of incremental rotation sensors that only measure the relative change in angular position. A potentiometer or other absolute position sensor could also be used because the
pulley 104 is limited to a specific number of revolutions depending upon the diameter of the pulley and range of travel of theweight stack 134. - The
weight machine sensor 100 shown inFIG. 1 is modular in nature such that it can be placed at various locations and on various makes and models of weight machines without significant re-engineering. The compactness of the device and simple hole-mounts 103 featured in thebase 102 serve to make the sensor more universally implementable with some simple additional mounting brackets, shims, and/or fasteners. The device could therefore be used to retrofit existing lines of equipment or could be directly integrated into the machines as they are being manufactured. -
FIG. 2 shows an exploded view of the example device shown inFIG. 1 with thecover 106 removed to reveal some of the internal components. Removal of thescrews 122 allows for accessing or servicing the internal components. Ashoulder bolt 110 connects thepulley 104 to aforce sensor 114 with abushing 112 utilized to fill the difference between the inner diameter of the bearing in thepulley 104 and the outer diameter of theshoulder bolt 110. The force sensor is then rigidly fixed to thebase 102 with abolt 116. Theexample force sensor 114 shown here features a strain gauge (e.g., a metal foil gauge) fixed directly to a rigid beam that is deflected when a load is applied. Since the force sensor features a cantilevered body designed to deflect an amount proportional to the force applied, the force may be measured by the strain gauge, which may include a metallic foil with an electrical resistance that changes based on the amount of deflection. The change in resistance may be amplified via, e.g., a Wheatstone bridge circuit or other type of amplification circuit. In a different approach, the force exerted onto theforce sensor 114 via thepulley 104 may be measured via a piezo-resistive force sensor, a pressure transducer, a thin film pressure sensor, or any other force-measuring sensor could be employed. - A
spacer 118 is included to control the position of thepulley 104 relative to theforce sensor 114. A printed circuit board (PCB′ 120 contains themicroprocessor 121 as well as peripheral integrated circuitry for processing the signals received from theforce sensor 114 androtation sensor 108. Additionally, the PCB 120 includes a wireless communication device 123 (e.g., a wireless transmitter) for transmitting the data that is recorded by the sensors. The PCB also includes awire connector 125 such as a barrel connector for providing and receiving wired data transmission, power, or both data transmission and power simultaneously. -
FIG. 3 shows a side view of theweight machine sensor 100 shown inFIG. 1 with thecover 106 and associatedscrews 122 removed. This figure more clearly illustrates how thepulley 104 is connected to aforce sensor 114 which in this example configuration utilizes strain gauges applied to a beam cantilevered from thebase 102. An example of the direction offorce 124 is shown with an arrow, but theforce sensor 114 can be configured to measure force applied in any direction. For example, if a cable is routed such that it contacts the top of thepulley 104 the direction of force will be downward, while if the cable is routed such that it contacts the bottom of thepulley 104 the direction of force will be upward. -
FIG. 4 shows a perspective view of theweight machine sensor 100 affixed to therigid frame 126 of the exercise machine. Thesensor 100 may be associated with (e.g., identify or otherwise distinguish) the user performing the exercise. This association may facilitate workout tracking and progress monitoring over time as well as administer more sophisticated automated coaching programs which would be unique to each user. A shortrange communication device 127, implemented via an antenna, circuits, chips, and possibly other electronic components could be integrated into the sensor system. Examples of the shortrange communication device 127 may include a near field communication (NFC) or radio frequency identification (RIM) check-in electronic (hardware) module. Most fitness trackers, wearables, smart phones, and smart watches include NFC or RFD readable chips which could be used to check the user in to the exercise machine. Members of commercial gyms are also commonly issued keychain fobs, bracelets, or other ways to identify themselves when they check in to the gym that could also be used to check in to the individual exercise machine stations using the shortrange communication device 127. Anoptical camera 129 coupled with facial recognition functionality could also be used to scan the individual's face as a way to identify which user is at the machine. A retina scanners or fingerprint scanner could similarly provide the ability for the user to be identified without requiring him or her to wear or carry an NFC/RFID equipped item. Adedicated monitor 130 on the exercise machine allows real-time data andcoaching feedback 131 to be displayed to the user. The data could be transmitted from theweight machine sensor 100 to the monitor wirelessly or physically wired via thewire connector 125 included on thePCB 120. Thecoaching feedback 131 displayed on the screen could include time-series data such as force, power, repetition count, calories burned, position, or total work output for that set. It could also include scatter plots that do not include time on one of the axes but rather a combination of two of the coaching metrics. For example, a graph showing power on one axis and position on the other axis could be useful. Or repetition count on one axis and total work on another axis as another example. But any combination of metrics provided by the sensor could be configured to suit the needs of the coaching paradigm, trainer, or exerciser. These metrics could be displayed on thededicated monitor 130 or a remote device 190 (seeFIG. 1 ), such as a mobile phone, smartwatch, or wearable activity tracker, or to a remote server 195 (seeFIG. 1 ), such as a cloud-based server or a server associated with a particular facility (e.g., a gym). - A bracket may allow the base 102 to be rigidly mounted to the
frame 126 such that any force transferred from thecable 128 to thepulley 104 is thereby detected by theforce sensor 114. If thecable 128 were to pass by thepulley 104 without being rerouted such that it remained a straight line, there could be sufficient friction to rotate thepulley 104 and therefore record motion and position data via therotation sensor 108. To record data regarding the amount of weight lifted, however, the tension in thecable 128 should also be measured. For this reason, thepulley 104 should actively reroute thecable 128 by some angle. The force applied by thecable 128 to thepulley 104 can then be measured by theforce sensor 114 to deduce the tension in the cable and therefore the amount of resistance experienced by the user. -
FIG. 5 shows a side view of the configuration shown inFIG. 4 . This angle makes theresultant force 124 applied to thepulley 104 by thecable 128 more apparent. Rerouting thecable 128 by a small angle will result in aforce 124 that is small relative to the tension in the cable. Rerouting thecable 128 by a large angle, conversely, will result in a relativelyhigher force 124. Translating the force measurement to weight values can be achieved by calibrating the device as the relationship is in most cases a basic linear fit. For the weight machine sensor to measure adequate information about the exercise being performed, it measures two basic details of the activity: the amount of weight being lifted and the motion behavior of theweight stack 134. The force sensor incorporated into the base and pulley assembly allows the sensor to deduce the weight being lifted, but there are more ways to measure the motion behavior of theweight stack 134. One configuration presented earlier features a rotation sensor on the pulley. Another approach is to use anoptical position sensor 144 that is mounted to theframe 126 of the weight machine and oriented toward theweight stack 134 to measure its position. Theposition sensor 144 could include an infrared sensor, a lidar sensor, an ultrasonic sensor, or any other form of position detection. Mounting theposition sensor 144 in a position where it is fixed relative to the sensor is most convenient, but the same results could be achieved by mounting theposition sensor 144 such that it moves relative to theweight stack 134 and measures position relative to a fixed object such as theframe 126. The examples just cited feature an optical way to “watch” the behavior of theweight stack 134 without any physical interaction, but a string wrapped around a rotary encoder that extends from theweight stack 134 could also be used as a way to measure the motion behavior. Another way to deduce the weight setting used by the user would be to connect the weight selector pin to the aforementioned string. Because the weight setting selection locations typically begin with the lightest weight settings near the top of theweight stack 134 and the heaviest weight setting at the bottom, the length of the string when it is in its selector location could indicate the weight resistance chosen by the user. In this example, a single rotatory encoder could be used to determine both the weight setting selected by the user and the motion behavior of theweight stack 134. -
FIG. 6 shows a configuration of the weight machine sensor in which thepulley 104 is in line with theforce sensor 114, rather than cantilevered off the side as shown in the configuration represented inFIG. 1 . -
FIG. 7A shows a configuration of the weight machine sensor in which thebase 102 has a bracket for containing thepulley 104, and the base 102 mounts directly to aweight selector tube 132 which in turn raises the stack ofweights 134. In this configuration, a portion of the bracket is removed such that force exerted onto thepulley 104 by thecable 128 is transferred, at least in part, through theforce sensor 114 attached to thebase 102. The example shown here features an “S type” load cell as the force sensor but other configurations or force sensor types could be employed.FIG. 7B shows an alternate view of the configuration shown inFIG. 7A but with thepulley 104 andcable 128 removed to illustrate the portion of the base 102 that is removed so that the force experienced by the user from the movement of theweight stack 134 is transferred through theforce sensor 114. In this example featuring just oneforce sensor 114, only about half of the force will be measured, but two force sensors could be used on both halves of the bracket orbase 102 such that the total force applied to thepulley 104 is measured. This configuration of theweight machine sensor 100 could include arotation sensor 108, a motion sensor, or both. Because the device is moving, an accelerometer could be used as a motion sensor, although position sensors such as infrared (IR), ultrasonic, or lidar, for example, could also be used. In some scenarios such as a multi-gym environment where multiple exercise types can be conducted at the same station, thepulley 104 might be lifted by thecable 128 on the left side causing clockwise motion, lifted by the right side causing counter-clockwise motion, or lifted by both sides simultaneously to allow for raising the weights with little or no rotation of thepulley 104. To detect exercise types and gather more data about the exercises being performed it would therefore be beneficial include both rotation data and motion data for this example application. -
FIG. 8 shows a configuration of the weight machine sensor featuring an “E type” load cell as the force sensor. In this sample configuration, theforce sensor 114 could be positioned to measure force transferred between the base 102 and the fixed,rigid frame 126 of the weight machine. Alternatively, theforce sensor 114 could be positioned to measure force transferred between the base 102 and theweight selector tube 132. In other words, theweight machine sensor 100 could be positioned such that it is stationary or it could be positioned such that it moves in accordance with movement of the weights or other resistance source. -
FIG. 9 shows a variation of theweight machine sensor 100 shown inFIG. 8 but features a button type load cell as the force sensor rather than an “E type” load cell. -
FIG. 10 shows a configuration of theweight machine sensor 100 featuring a load pin load cell integrated into the shaft of the pulley as theforce sensor 114. - In commercial gym environments it can be difficult or cumbersome to route power cables to the weight machines, so harvesting energy as a way to power the electronics on the
PCB 120,microprocessor 120, andwireless communication device 123 would eliminate the need to plug the device in or replace batteries.FIG. 11 shows an exploded view of the sameweight machine sensor 100 shown inFIG. 2 , but with some additional kinetic charger components to facilitate kinetic charging of a battery that powers the device. In this sample configuration, the kinetic charger components includeelectrical coils 136 fixed to thebase 102 and positioned in such a way that an electrical current is generated when the plurality ofmagnets 138 rotate. Themagnets 138 are mounted in a fashion such that rotation of thepulley 104 causes rotation of themagnets 138 and therefore the production of an electrical current through thecoils 136. The circuitry could be set up such that the resulting torque applied to the pulley from electromagnetic induction will be experienced only when the weights are being lowered to not add any additional resistance when the weights are being lifted. In this case, electricity would also only be generated when the weights are being lowered. Onepossible rotation sensor 108 technology features rotating magnets and a hall-effect or reed sensor to deduce rotational position and rotational direction data. Therotation sensor 108 could be situated such that themagnets 138 used for kinetic charging could also be used for rotation detection. -
FIG. 12 illustrates another possible way to harvest energy featuring asolar panel 140 to charge abattery 142 that runs the electronics on theweight machine sensor 100. Whether the gym is outdoors or indoors, the presence of some form of lighting means that asolar panel 140, or photovoltaic cell of some form, could provide the power required to run the device. Theweight machine sensor 100 operates in a “low-power” or “sleep” mode for extended periods of time and will “wake up” and transmit data only when in use. A wake sensor allows for this functionality. Given these usage patterns thesolar panel 140 need not be able to provide the maximum power requirement such as when the device is awake and transmitting data wirelessly, but rather merely provide the average power requirement. The presence of abattery 142 allows for a buffer to store the harvested energy to be delivered whenever the device demands. The battery would also be included in the configuration shown inFIG. 11 featuring kinetic energy harvesting and could also be included in any of the other configurations described herein. -
FIG. 13 demonstrates a configuration of theweight machine sensor 100 wherein a plurality ofoptical position sensors 144 can be arranged in a manner to allow detection of the amount of weight resistance chosen from theweight stack 134 as well as the motion behavior of theweight stack 134. Theposition sensors 144 could include an infrared sensor, a lidar sensor, an ultrasonic sensor, or any other form of position detection or combination thereof. Aposition sensor 144 arranged on theframe 126 of the machine facing downward, for example, could view the motion of theweight stack 134 whileposition sensors 144 arranged adjacent to the weight stack, possibly horizontally angled, could view theweight stack 134 from a different angle and thereby be used by themicroprocessor 121 to infer the weight setting. By overlaying data from thevarious position sensors 144 the algorithms implemented on themicroprocessor 121 could calculate the thickness of the material being moved and therefore determine the weight setting and therefore the exercise data produced by other configurations of the weight machine sensor. - The combination of the
force sensor 114 androtation sensor 108 data (orposition sensor 144 data), which themicroprocessor 121 is programmed to determine from the force signal output by the force sensor and the motion signal output by the rotation sensor, respectively, allows for calculation of many exercise metrics (referred to as “exercise data”) that allow the exerciser to monitor the progress of his/her physical fitness and automate the delivery ofcoaching feedback 131. For example, the user's strength, force, power, work output, calorie expenditure, repetition count, and weight resistance settings can all be tracked and compared to historical performance. That is, themicroprocessor 121 may be programmed to calculate strength, force, power, work output, calorie expenditure, and weight resistance setting from the force signal output by the force sensor, the motion signal output by the position/rotation sensor, or both. The metrics also allow for engagement with an interactive community whose members could be in close proximity or geographically dispersed. For example, the metrics could be displayed on a leaderboard with real time comparisons of the group of participants, or the participants could be exercising in a home gym environment with a similar leaderboard monitoring and comparing everyone's progress. The workouts that are part of this described experience could be self-guided, loaded on an “on-demand” basis, or streamed live onto the user's television, mobile device, or wearable fitness tracker. - The
wireless communication device 123 may be implemented via an antenna, circuits, chips, or other electronic components configured or programmed to facilitate wireless communication. For instance, the wireless communication device may be programmed to transmit the data collected by the force sensor, rotation sensor, or both via a telecommunication protocol such as Bluetooth®, Bluetooth Low Energy®, etc., to a remote device 190 (seeFIG. 1 ) such as a mobile phone, smartwatch, or wearable activity tracker, or to a remote server 195 (seeFIG. 1 ), such as a cloud-based server or a server associated with a particular facility (e.g., a gym). Wireless communication could be the only way to communicate the exercise data or it could be secondary to data transmission via a wired connection such as with an ethernet cable. Multiple formats of wireless communication could also be used in combination to allow simultaneous streaming of data to aremote device 190 and aremote server 195, for example. The term “server” refers to a computer having a processor and memory. The term “remote” when used in the context of the remote device and remote server may refer to the spatial relationship of the remote device, the remote server, or both, relative to the exercise tracker. Therefore, although referred to as “remote,” theremote device 190 andremote server 195 may be physically near the exercise tracker 100 (i.e., theremote server 195 may be in communication with theexercise tracker 100, theremote device 190, or both, via a local network connection). Alternatively, theremote device 190 orremote server 195, or both, may be physically “remote” but still in signal communication with the exercise tracker 100 (e.g., theremote server 195 may be cloud-based). Accordingly, in some implementations, the data may be transmitted from theweight machine sensor 100 to theremote device 190 or the remote server 195 (seeFIG. 1 ) via a Wi-Fi network connection. The wireless communication device may be programmed to periodically transmit the collected data to the remote device or remote server, or transmit the data as it is collected. Alternatively, the wireless communication device may be programmed to transmit the data to the remote device or theremote server 195 at specific times, such as when all repetitions have been performed or when a workout is complete. The wireless communication device may determine that all repetitions have been performed based on the force sensor signal or that the workout is complete in response to a user input provided to the exercise machine input orremote device 195. - In general, the computing systems and/or devices described may employ any of a number of computer operating systems, including, but by no means limited to, versions and/or varieties of the Microsoft Windows® operating system, the Unix operating system (e.g., the Solaris® operating system distributed by Oracle Corporation of Redwood Shores, Calif.), the AIX UNIX operating system distributed by International Business Machines of Armonk, N.Y., the Linux operating system, the Mac OSX, macOS, and iOS operating systems distributed by Apple Inc. of Cupertino, Calif., the BlackBerry OS distributed by Blackberry, Ltd. of Waterloo, Canada, and the Android operating system developed by Google, Inc. and the Open Handset Alliance. Examples of computing devices include, without limitation, a computer workstation, a server, a desktop, notebook, laptop, or handheld computer, or some other computing system and/or device.
- Computing devices generally include computer-executable instructions, where the instructions may be executable by one or more computing devices such as those listed above. Computer-executable instructions may be compiled or interpreted from computer programs created using a variety of programming languages and/or technologies, including, without limitation, and either alone or in combination, Java™, C, C++, Visual Basic, Java Script, Perl, etc. Some of these applications may be compiled and executed on a virtual machine, such as the Java Virtual Machine, the Dalvik virtual machine, or the like. In general, a processor (e.g., a microprocessor) receives instructions, e.g., from a memory, a computer-readable medium, etc., and executes these instructions, thereby performing one or more processes, including one or more of the processes described herein. Such instructions and other data may be stored and transmitted using a variety of computer-readable media.
- A computer-readable medium (also referred to as a processor-readable medium) includes any non-transitory (e.g., tangible) medium that participates in providing data (e.g., instructions) that may be read by a computer (e.g., by a processor of a computer). Such a medium may take many forms, including, but not limited to, non-volatile media and volatile media. Non-volatile media may include, for example, optical or magnetic disks and other persistent memory. Volatile media may include, for example, dynamic random access memory (DRAM), which typically constitutes a main memory. Such instructions may be transmitted by one or more transmission media, including coaxial cables, copper wire and fiber optics, including the wires that comprise a system bus coupled to a processor of a computer. Common forms of computer-readable media include, for example, a floppy disk, a flexible disk, hard disk, magnetic tape, any other magnetic medium, a CD-ROM, DVD, any other optical medium, punch cards, paper tape, any other physical medium with patterns of holes, a RAM, a PROM, an EPROM, a FLASH-EEPROM, any other memory chip or cartridge, or any other medium from which a computer can read.
- Databases, data repositories or other data stores described herein may include various kinds of mechanisms for storing, accessing, and retrieving various kinds of data, including a hierarchical database, a set of files in a file system, an application database in a proprietary format, a relational database management system (RDBMS), etc. Each such data store is generally included within a computing device employing a computer operating system such as one of those mentioned above, and are accessed via a network in any one or more of a variety of manners. A file system may be accessible from a computer operating system, and may include files stored in various formats. An RDBMS generally employs the Structured Query Language (SQL) in addition to a language for creating, storing, editing, and executing stored procedures, such as the PL/SQL language mentioned above.
- In some examples, system elements may be implemented as computer-readable instructions (e.g., software) on one or more computing devices (e.g., servers, personal computers, etc.), stored on computer readable media associated therewith (e.g., disks, memories, etc.). A computer program product may comprise such instructions stored on computer readable media for carrying out the functions described herein.
- With regard to the processes, systems, methods, heuristics, etc. described herein, it should be understood that, although the steps of such processes, etc. have been described as occurring according to a certain ordered sequence, such processes could be practiced with the described steps performed in an order other than the order described herein. It further should be understood that certain steps could be performed simultaneously, that other steps could be added, or that certain steps described herein could be omitted. In other words, the descriptions of processes herein are provided for the purpose of illustrating certain embodiments, and should in no way be construed so as to limit the claims.
- Accordingly, it is to be understood that the above description is intended to be illustrative and not restrictive. Many embodiments and applications other than the examples provided would be apparent upon reading the above description. The scope should be determined, not with reference to the above description, but should instead be determined with reference to the appended claims, along with the full scope of equivalents to which such claims are entitled. It is anticipated and intended that future developments will occur in the technologies discussed herein, and that the disclosed systems and methods will be incorporated into such future embodiments. In sum, it should be understood that the application is capable of modification and variation.
- All terms used in the claims are intended to be given their ordinary meanings as understood by those knowledgeable in the technologies described herein unless an explicit indication to the contrary is made herein. In particular, use of the singular articles such as “a,” “the,” “said,” etc. should be read to recite one or more of the indicated elements unless a claim recites an explicit limitation to the contrary.
Claims (18)
1-20. (canceled)
21. A weight machine sensor comprising:
a force sensor programmed to output a force signal representing a force applied to a pulley disposed on a cable incorporated into exercise equipment;
at least one rotation sensor programmed to collect rotation data representing rotation of the pulley; and
a processor programmed to determine force data from the force signal and further determine position data from the rotation data, wherein the position data represents a position of a weight stack, and wherein the processor is programmed to determine an amount of exercise resistance based at least in part on the force data and a number of repetitions performed based at least in part on the rotation data.
22. The weight machine sensor of claim 21 , wherein the rotation data collected by the at least one rotation sensor represents at least one of a direction of rotation of the pulley and a magnitude of rotation of the pulley.
23. The weight machine sensor of claim 22 , wherein the processor is configured to compare rotation data output by the at least one rotation sensor and determine at least one of the direction of rotation of the pulley and magnitude of rotation of the pulley from the rotation data.
23. The weight machine sensor of claim 21 , wherein the rotation sensor includes an optical sensor configured to visually detect features of the pulley.
24. The weight machine sensor of claim 23 , wherein the rotation sensor includes a rotary encoder.
25. The weight machine sensor of claim 24 , further comprising a light source configured to illuminate the pulley, and wherein the rotary encoder is configured to output rotation data based at least in part on an observed pattern of light.
26. The weight machine sensor of claim 24 , wherein the pulley includes a plurality of slots and wherein the rotary encoder is configured to collect rotation data based at least in part on light shining through the plurality of slots as the pulley is rotated.
27. The weight machine sensor of claim 24 , wherein the pulley includes a plurality of protrusions and wherein the rotary encoder is configured to collect rotation data based at least in part on light reflected by the plurality of protrusions as the pulley is rotated.
28. The weight machine sensor of claim 21 , wherein the processor is programmed to determine a velocity of the weight stack based at least in part on the rotation data.
29. The weight machine sensor of claim 21 , wherein the processor is programmed to determine a range of motion of the weight stack.
30. A weight machine sensor comprising:
a force sensor programmed to output a force signal representing a force applied to a pulley disposed on a cable incorporated into exercise equipment having a weight stack;
at least one magnet disposed on the pulley;
at least one magnetic sensor configured to output rotation data representing rotation of the pulley, wherein the magnetic sensor is configured to detect rotation of the pulley based at least in part on a magnetic field generated by at least one magnet; and
a processor programmed to determine force data from the force signal and further determine position data from the rotation data, wherein the position data represents a position of the weight stack, and wherein the processor is programmed to determine an amount of exercise resistance based at least in part on the force data and a number of repetitions performed based at least in part on the rotation data.
31. The weight machine sensor of claim 30 , wherein the processor is programmed to determine a velocity of the weight stack based at least in part on the rotation data.
32. The weight machine sensor of claim 30 , wherein the processor is programmed to determine a range of motion of the weight stack.
33. The weight machine sensor of claim 30 , wherein the at least one magnetic sensor includes at least one Reed switch.
34. The weight machine sensor of claim 30 , wherein the at least one magnetic sensor includes at least one Hall Effect sensor.
35. The weight machine sensor of claim 30 , wherein the rotation data collected by the at least one magnetic sensor represents at least one of a direction of rotation of the pulley and a magnitude of rotation of the pulley.
36. The weight machine sensor of claim 35 , wherein the processor is configured to compare rotation data output by the at least one magnetic sensor and determine at least one of the direction of rotation of the pulley and the magnitude of rotation of the pulley from the rotation data.
Priority Applications (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
US17/645,436 US20220111256A1 (en) | 2017-06-04 | 2021-12-21 | Weight Machine Sensor |
Applications Claiming Priority (3)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
US201762514941P | 2017-06-04 | 2017-06-04 | |
US15/997,200 US11235201B2 (en) | 2017-06-04 | 2018-06-04 | Weight machine sensor |
US17/645,436 US20220111256A1 (en) | 2017-06-04 | 2021-12-21 | Weight Machine Sensor |
Related Parent Applications (1)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
US15/997,200 Continuation US11235201B2 (en) | 2017-06-04 | 2018-06-04 | Weight machine sensor |
Publications (1)
Publication Number | Publication Date |
---|---|
US20220111256A1 true US20220111256A1 (en) | 2022-04-14 |
Family
ID=64458574
Family Applications (2)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
US15/997,200 Active 2039-07-13 US11235201B2 (en) | 2017-06-04 | 2018-06-04 | Weight machine sensor |
US17/645,436 Abandoned US20220111256A1 (en) | 2017-06-04 | 2021-12-21 | Weight Machine Sensor |
Family Applications Before (1)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
US15/997,200 Active 2039-07-13 US11235201B2 (en) | 2017-06-04 | 2018-06-04 | Weight machine sensor |
Country Status (1)
Country | Link |
---|---|
US (2) | US11235201B2 (en) |
Families Citing this family (12)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US11351420B2 (en) * | 2015-02-23 | 2022-06-07 | Smartweights, Inc. | Method and system for virtual fitness training and tracking devices |
US10610733B2 (en) * | 2017-03-03 | 2020-04-07 | uBody, Inc. | Smart weight-lifting pin |
US11235201B2 (en) * | 2017-06-04 | 2022-02-01 | Shapelog, Inc. | Weight machine sensor |
US20210402256A1 (en) * | 2020-06-30 | 2021-12-30 | Paul David Huch | Training system |
US11117018B2 (en) * | 2018-09-05 | 2021-09-14 | Vadim MALIS | System for measuring, monitoring and displaying physical parameters of exercises on selectorized fitness machines |
US20210077849A1 (en) * | 2019-09-13 | 2021-03-18 | Vertimax, Llc | Smart pulley |
EP3812013B1 (en) * | 2019-10-25 | 2024-05-08 | Lumos Holdings US Acquisition Co. | Predictive maintenance of exercise machines with time-of-flight sensors |
US11759691B2 (en) * | 2019-11-14 | 2023-09-19 | Destro Machines LLC | Tethered resistance swim training apparatus with smart pulley |
US11883717B2 (en) * | 2020-01-21 | 2024-01-30 | Claudio Ploumis, Inc. | Weightlifting machine and method of use |
WO2021173888A1 (en) * | 2020-02-26 | 2021-09-02 | Texas Tech University System | Dynamo torque analyzer |
IT202100013442A1 (en) * | 2021-05-24 | 2022-11-24 | Labogym Srl | ACCESSORY FOR GYM MACHINE |
AT526418B1 (en) * | 2022-09-20 | 2024-03-15 | Klaushofer Thomas | CABLE PULLEY UNIT FOR A TRAINING DEVICE |
Citations (3)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US20060035768A1 (en) * | 2004-08-11 | 2006-02-16 | Kowallis Rodney C | Repetition sensor in exercise equipment |
US20150126332A1 (en) * | 2004-05-10 | 2015-05-07 | Koko Fitness, Inc. | Exercising apparatus |
US20170319905A1 (en) * | 2016-05-06 | 2017-11-09 | Christopher S. O'CONNOR | Dynamically adaptive weight lifting apparatus |
Family Cites Families (30)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US4919418A (en) * | 1988-01-27 | 1990-04-24 | Miller Jan W | Computerized drive mechanism for exercise, physical therapy and rehabilitation |
US5151071A (en) * | 1990-10-05 | 1992-09-29 | Baltimore Therapeutic Equipment Co. | Isoinertial lifting device |
US5655997A (en) * | 1994-07-07 | 1997-08-12 | Integrated Fitness Corporation | Fitness feedback system for weight stack machines |
US6358188B1 (en) * | 1998-02-26 | 2002-03-19 | Gym-In Ltd. | Exercise tracking system |
US8636631B2 (en) * | 2002-08-15 | 2014-01-28 | Alan L Carlson | Arrangements for exercising via semispherical motion |
US7651442B2 (en) * | 2002-08-15 | 2010-01-26 | Alan Carlson | Universal system for monitoring and controlling exercise parameters |
US20060293151A1 (en) * | 2005-06-27 | 2006-12-28 | Rast Rodger H | Apparatus and method for static resistance training |
US20100197462A1 (en) * | 2005-09-07 | 2010-08-05 | Bvp Holding, Inc. | 3-d, interactive exercise analysis, gaming, and physical therapy system |
US20070213183A1 (en) * | 2006-03-08 | 2007-09-13 | Menektchiev Alexandre K | Sensor arrays for exercise equipment and methods to operate the same |
US7785232B2 (en) * | 2006-11-27 | 2010-08-31 | Cole Neil M | Training system and method |
US8069737B2 (en) * | 2007-07-10 | 2011-12-06 | MYTRAK Health System, Inc. | Force sensing system for a tensioned flexible member |
TW201034715A (en) * | 2009-03-18 | 2010-10-01 | Joong Chenn Industry Co Ltd | Fitness equipment |
CN201464091U (en) | 2009-06-18 | 2010-05-12 | 罗毅 | Acting force measuring device for exercise equipment |
TW201130539A (en) * | 2010-03-11 | 2011-09-16 | Joong Chenn Industry Co Ltd | Exercise device with resistance inspection function |
US20120004076A1 (en) * | 2010-06-30 | 2012-01-05 | Fenster Mrako A | Apparatus for Counting Repetitions of an Exercise Device |
US8529408B2 (en) * | 2010-10-19 | 2013-09-10 | Edward J. Bell | Weight-lifting exercise machine |
US20130310221A1 (en) * | 2012-05-18 | 2013-11-21 | Precor Incorporated | Exercise metric graphical code generation |
US10383784B2 (en) * | 2013-07-30 | 2019-08-20 | Northeastern University | Gait training system and methods |
US20150209609A1 (en) * | 2014-01-26 | 2015-07-30 | Strength Companion, LLC | Systems and methods for determining selected exercise resistance |
US9669261B2 (en) * | 2014-05-21 | 2017-06-06 | IncludeFitness, Inc. | Fitness systems and methods thereof |
US9616292B2 (en) * | 2015-01-09 | 2017-04-11 | Nolan Orfield | Exercise tracker |
US9409053B1 (en) * | 2015-07-13 | 2016-08-09 | Bml Productions, Inc. | Exercise data collection system |
GB2541725B (en) * | 2015-08-28 | 2018-01-03 | Flak Ltd | Weights system |
US10675497B2 (en) * | 2015-09-18 | 2020-06-09 | Jaquish Biomedical Corporation | Devices for exercise apparatuses |
US10004972B2 (en) * | 2015-12-07 | 2018-06-26 | Calgym Group Holdings Pty. Ltd. | Stationary strength training equipmment with lockable bilateral user interface |
WO2017160903A1 (en) * | 2016-03-16 | 2017-09-21 | Drexel University | Portable load testing device |
US20170282013A1 (en) * | 2016-03-29 | 2017-10-05 | Trevor Adam Paulsen | Force Measuring Exercise Device |
EP3522998A4 (en) | 2016-10-10 | 2020-05-27 | IncludeHealth, Inc. | Exercise apparatus with sensors and methods thereof |
US11235201B2 (en) * | 2017-06-04 | 2022-02-01 | Shapelog, Inc. | Weight machine sensor |
US9814920B1 (en) * | 2017-07-05 | 2017-11-14 | Jensen Franz Monterrey | Exercise apparatus to enhance muscle recruitment of a user through isometric and plyometric movements |
-
2018
- 2018-06-04 US US15/997,200 patent/US11235201B2/en active Active
-
2021
- 2021-12-21 US US17/645,436 patent/US20220111256A1/en not_active Abandoned
Patent Citations (3)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US20150126332A1 (en) * | 2004-05-10 | 2015-05-07 | Koko Fitness, Inc. | Exercising apparatus |
US20060035768A1 (en) * | 2004-08-11 | 2006-02-16 | Kowallis Rodney C | Repetition sensor in exercise equipment |
US20170319905A1 (en) * | 2016-05-06 | 2017-11-09 | Christopher S. O'CONNOR | Dynamically adaptive weight lifting apparatus |
Also Published As
Publication number | Publication date |
---|---|
US11235201B2 (en) | 2022-02-01 |
US20180345080A1 (en) | 2018-12-06 |
Similar Documents
Publication | Publication Date | Title |
---|---|---|
US20220111256A1 (en) | Weight Machine Sensor | |
US10307641B2 (en) | Exercise tracker | |
US20210128971A1 (en) | Sensor equipped resistance training grip | |
US11338169B2 (en) | Strength training apparatus | |
US9381399B2 (en) | Exercise recordation method and system | |
US9550091B2 (en) | System and method for capturing exercise data | |
US7931563B2 (en) | Virtual trainer system and method | |
US9468793B2 (en) | System for monitoring fitness performance | |
US20180064992A1 (en) | Multi-Functional Weight Rack and Exercise Monitoring System for Tracking Exercise Movements | |
US8905855B2 (en) | System and method for utilizing motion capture data | |
EP3406083B1 (en) | Determining weight and repetions in a gym machine with no mechanical impact | |
WO2013034987A2 (en) | Sensor device and system for fitness equipment | |
US20180250553A1 (en) | Smart weight-lifting pin | |
US20160151672A1 (en) | Recommending an exercise activity for a user | |
US11117018B2 (en) | System for measuring, monitoring and displaying physical parameters of exercises on selectorized fitness machines | |
US20230191197A1 (en) | Smart glove | |
CN113874947A (en) | System and method for monitoring or evaluating physical fitness from different exercise devices and activity trackers | |
KR20150089485A (en) | system and method for measuring physical exercise and feedback for fitness equipments using mobile device | |
WO2018033909A1 (en) | An apparatus for measuring and tracking progress of a person's movements during physical exercise | |
Patch et al. | An exercise Data Logging system for retrofitting gym equipment | |
WO2023085951A1 (en) | Weight stack sensor system, fitness tracking system and method for fitness tracking | |
GB2483115A (en) | An athletic performance measurement device for measuring a load and the number of repetitions | |
KR20190099556A (en) | Weight machine and method for providing exercise feedback service | |
CN210845232U (en) | Motion data acquisition device of apparatus | |
KR20240009594A (en) | Tension measurement and transmission device of exercise equipment, Method thereof, and Exercise load measurement system of exercise equipment |
Legal Events
Date | Code | Title | Description |
---|---|---|---|
AS | Assignment |
Owner name: SHAPELOG, INC., MICHIGAN Free format text: ASSIGNMENT OF ASSIGNORS INTEREST;ASSIGNORS:RALEIGH, JESSE;ORFIELD, NOLAN;MUTH, ANDREW;AND OTHERS;REEL/FRAME:058452/0040 Effective date: 20180604 |
|
STPP | Information on status: patent application and granting procedure in general |
Free format text: DOCKETED NEW CASE - READY FOR EXAMINATION |
|
STPP | Information on status: patent application and granting procedure in general |
Free format text: NON FINAL ACTION MAILED |
|
STCB | Information on status: application discontinuation |
Free format text: ABANDONED -- FAILURE TO RESPOND TO AN OFFICE ACTION |