US20080146366A1

US20080146366A1 - Motion monitor

Info

Publication number: US20080146366A1
Application number: US11/985,142
Authority: US
Inventors: Edward Miesak
Original assignee: Individual
Current assignee: Individual
Priority date: 2006-12-13
Filing date: 2007-11-13
Publication date: 2008-06-19

Abstract

A method for evaluating the motion of a moveable object relative to a reference object includes locating the reference object within a three-dimensional coordinate system having first, second, and third positional coordinates such that the position of the reference object is characterized by respective values of first, second, and third positional coordinates. A mechanism is provided having a plurality of visual indicators. A sensor is configured to detect the position of the moveable object within the three-dimensional coordinate system substantially apart from any dynamic property inherent in the movement of the moveable object. An acceptable minimal number of sampling events is determined and providing a sensor having sufficient response rate as to be capable of determining respective positions of the moveable object as the moveable object moves relative to the reference object such that the number of the respective positions exceeds the acceptable minimal number for any maximum velocity of the moveable object manually achievable by the user.

Description

CROSS-REFERENCE TO RELATED APPLICATIONS

This application claims be the benefit of U.S. Provisional App. No. 60/857,125, filed Nov. 7, 2006, and U.S. Provisional App. No. 60/874,320, filed Dec. 13, 2006.

BACKGROUND OF THE INVENTION

The present invention obtains movement information about the movement of a mechanical device.
In many cases it is desirable to obtain movement information about the motion of a golf club head in order to be able to properly modify its swing.
The foregoing and other objectives, features, and advantages of the invention will be more readily understood upon consideration of the following detailed description of the invention, taken in conjunction with the accompanying drawings.

BRIEF DESCRIPTION OF THE SEVERAL VIEWS OF THE DRAWINGS

FIG. 1 illustrates a six dimensional coordinate system.

FIG. 2 illustrates movement through a sensor detection range.

FIG. 3 illustrates a typical sensor output.

FIG. 4 illustrates constant distance movement within a sensor detection range.

FIG. 5 illustrates two overlapping sensor ranges.

FIG. 6 illustrates three overlapping sensor ranges.

FIG. 7 illustrates a golf swing monitor.

DETAILED DESCRIPTION OF PREFERRED EMBODIMENT

A data acquisition system (DAQ) may be used to capture the vector movement (magnitude and direction) of an object traversing a complex path in three dimensions and extract the constituent movements into a six dimensional coordinate space (or other number of dimensions). A golf club swing is used as an illustrative example of a complex mechanical movement. A three dimensional (3D) Cartesian coordinate axes (X, Y, Z) is shown in FIG. 1. The golf club head swings primarily along the direction of the Z axis. The Y axis is in the vertical direction representing the height of the club above the ground, and the X axis represents the side-to-side (S2S) position of the club. The origin of the axes is centered on the golf ball, i.e. the center of the ball is located at the intersection of the X, Y, and Z axes. Each axis has a linear and rotational movement associated with it. Linear movements are measured along each axis while rotational movements are measured about each axis. The three axes times the two movements (linear, rotational) produces the six dimensional measurement space described above.
Complex mechanical movement can be decomposed into a set of orthogonal (independent) component (constituent) movements. The original movement can be reconstructed from these component movements by adding them back together into a “superposition.” The data acquisition system (DAQ) may capture and decompose a complex mechanical movement into orthogonal linear and rotational components. The coordinate axes system used here is a three dimensional Cartesian coordinate system (three orthogonal axes X, Y, Z). Any valid coordinate system may be used with this application, i.e., cylindrical, spherical, etc.
Movement along any one axis of a Cartesian coordinate system is independent of the other two axes. In other words, a movement directly along the X axis for example, is not visible on the Y or Z axes. This is advantageous to a user who needs to investigate individual components of a complex movement. For example, this could be applied to the area of analyzing a golf club swing. A golf club, during normal use, travels through a three dimensional space in a highly complex manner, i.e. it has many linear and rotational components along multiple axes. Decomposing such a complex movement into basic constituents (i.e., head rotation about the vertical axis, head velocity along the direction of the swing, etc.) greatly simplifies the task of improving the complete golf club swing because the user can isolate a component of the swing giving him/her trouble and work on it.
Every movement (linear, rotational) is described by three related quantities, position, velocity, acceleration (PVA). Each of these can be represented mathematically in the time domain as x(t) (position), v(t) (velocity), and a(t) (acceleration.) They are related through the definitions,
$v (t) = \frac{\partial x}{\partial t},$
$a (t) = \frac{\partial v}{\partial t} .$
Each of these quantities (PVA) can be positive, zero, or negative. Because they are mathematically related to each other, measuring one can produce the other two.
A complicated vector movement of an object traveling through a three dimensional space can be described by providing values for each of the 6D coordinate space components of the object's movement. The total number of components required to produce a complete description is three linear axes (X, Y, Z) plus three rotational axes (X, Y, Z) times three quantities (PVA) or eighteen.
The data acquisition system (DAQ) are designed specifically to allow accurate movement decomposition. The sensors should have the capability of producing data rich enough in content from which the software can extract the 6D components. These two pieces of the DAQ (hardware, software) should be designed together in order to function well.
For purposes of explanation here the complex mechanical movement being captured, recorded, and deconstructed, will be produced by a golf club during normal play or practice. The system tracks the movement of a mechanical object through space with respect to time. The movement is recorded then dissected into six dimension (6D) parameters (described above) in order to provide a deep understanding of the complex movement for the user.
Sensors are used to track the complex movement of an object. In order for this system to function properly there are minimum requirements on the sensors. They need to be able to respond fast enough to capture much of the high frequency component of the movement. They also should be able to capture the low frequency component, typically a stationary position. The output of a sensor should depend only on the distance of the object from the sensor and not on the speed of the object moving past the sensor. This characteristic allows the system to measure speed and distance independently.
Referring to FIG. 2, an object traveling through the range of a sensor, shown as a hemisphere, will produce a signal dependent on the distance to the sensor. When the object first enters the sensor range a weak signal is produced. As the object continues to travel towards the sensor the signal strength continues to increase. At the point where the object is closest to the sensor the signal reaches its maximum value. As the object travels away from the sensor the signal strength decreases. The signal returns to zero when the object leaves the range of the sensor.
In order to create an accurate temporal snapshot of the movement of an object through the sensor detection range some technique of data collection with memory should be employed. A micro-controller (μC) can be used to create such a picture in time. A μC having all the necessary components to collect and store sensor data may be used. A technique of adapting the sensor output signal to a μC input is utilized. For instance, many sensors have analog outputs. A μC having an analog to digital converter (ADC) is easily found. Simple electronic interface circuitry insures that the sensor output signal is compatible with the μC input circuit. The μC can be programmed to collect and store sensor signals at known time intervals. All the sensor signals are stored such that the time of occurrence of each signal is known. The sensor signals can be read-out in correct order to create an accurate temporal picture of the sensor signal.
Referring to FIG. 3, as an example, the graph illustrates an actual sensor output of a mechanical object traveling on a straight line path through the sensor detection range. More than 200 samples of the sensor output were collected and stored during the object's travel. The samples are treated as a single quantity because they all reside in a single file. This file is available to be processed by the μC at some later time.
Typically the sensors are sampled many times in rapid succession. These samples are then assembled to create a virtually continuous picture in time of the sensor signal. This provides the necessary accuracy and richness of information that allows more than one quantity to be extracted from each sensor, i.e., peak amplitude, average amplitude, pulse width, etc., during post-processing.
A single sensor can typically discern only the distance to an object, not the path taken. For instance, if an object travels at a constant distance from the sensor within its sensing range the sensor will produce a constant signal. Referring to FIG. 4, as an example, a sensor is illustrated with a circular path (broken line) above it at a constant distance from it. If an object is anywhere on this line either stationary or traveling at a constant or varying speed, the output signal from the sensor will always be the same value. The sensor can only detect distance. Since the distance is constant the signal is also constant. This is an ambiguous situation. The position, velocity, and acceleration (PVA) of the object are unknown.
A top-down view of the sensor detection range is a circle with the sensor at the center. The only information that can be determined when an object is sensed inside this circle is the distance from the sensor. Adding a second sensor provides additional information which can be used to reduce the PVA ambiguity. The two sensors are placed so that their detection ranges overlap each other. If the two sensors are placed in the same plane, a top-down view of their sensing range would be two over lapped circles, as is shown in FIG. 5.
The single cross-hatched area between the two sensors (Sn1, Sn2) is where the two detection ranges overlap. If the object being tracked is in this area additional information about its PVA can be obtained by comparing the output signals from Sn1 and Sn2. The PVA of the object along the direction of the line B-B within the single cross-hatched area can be determined. A third sensor is added in order to remove the PVA ambiguity along the direction of the line A-A. The optimum location for this third sensor would be directly on the line A-A though it could also reside else where (as long as it's not on the line B-B).
Referring to FIG. 6, an illustration of using three sensors is shown. The layout begins with the two sensor configuration shown above then adds a third sensor (Sn3) on the line A-A. This allows a triangulation of the signals in order to determine the object PVA within the double cross-hatched area. Using three sensors may be adequate for one application but not for another. Each application is analyzed in order to determine the optimum sensor quantity, placement, and software deconstruction semantics. This places responsibility on the designer to create a sensor layout and software design together that will work for a particular application. A special application would be a golf swing monitor.
When used to monitor the movement of a golf club head during a swing one preferred embodiment places the sensors in the immediate vicinity of the golf ball. This could be due to a limited sensor detection range. This motion (swing) monitor would also contain a display for the user. FIG. 7 shows one embodiment of a swing monitor. In the illustration the display area is denoted by the recessed area around the golf ball. The sensors reside under the golf ball. The swing monitor is placed on the ground with the display facing the user. The user places a golf ball on it in a pre-determined location then hits the ball in a normal fashion. A golf ball tee may or may not be used with the swing monitor. The display on the surface shows properties of the swing that resulted in the vicinity of the ball.
The motion monitor would be battery operated and completely self sufficient, i.e. it would not need to be interfaced to a laptop or desktop computer in order to operate. The μC on board the system is capable of providing all the functions necessary for the system to operate. The small size and self-sufficiency allows this motion monitor to be highly portable and very useful in almost any location.
One type of sensor that could be used with a swing monitor is a Hall effect magnetic sensor. This type of sensor has the sensor properties stated above, i.e.:
a. High frequency response.
b. Zero frequency response.
c. Output signal depends only on the distance to the magnet, not velocity.
This sensor should include a magnet to be attached to or installed inside of the golf club head.
Some types of magnetic sensors will only operate when the magnet is moving, (i.e., they will not sense a stationary magnet) these can be called dynamic sensors. These sensors typically contain a loop of wire or an induction coil. These sensors are typically sensitive to two parameters simultaneously, proximity and velocity. A single reading by one of these sensors will be the result of both the velocity of the magnet and the distance of the magnet to the sensor. This type of sensor would not be optimum for a golf swing monitor.
The sensors chosen for the swing monitor of this example will operate with non-moving magnets, i.e. they will sense a stationary magnet as well as a moving magnet. These can be referred to as base-band sensors. These sensors are not sensitive to the magnet velocity as it passes the sensor, only proximity. These two properties are useful because they allow a minimum number of sensors to detect a maximum number of movement properties. For instance, when the user is “addressing the ball” the club is not swinging, it is being placed in a stationary position behind the golf ball prior to the swing. Base-band sensors will be able to acquire the static position/orientation of the golf club in this instance whereas dynamic sensors will not. When a swing is made the base-band sensors will also be able to record the moving club.
Magnetic sensors are not the only type that will work with this motion monitor. Any sensor that possesses the above described characteristics and has an acceptable range of detection can be made to work. But not every sensor is easy to work with, or has to optimum price range, or power requirements, or size.
The sensors in this example motion monitor lie underneath the golf ball in a flat plane. The position of each sensor is defined by the size and strength of the magnet on the moving object (in this case a golf club.) There is an optimum position for each sensor depending on which parameter is being sensed. In order to simultaneously collect as many of the 6D parameters as possible, compromises have to be made on the positions of all the sensors together. Deconstructing software is then appropriately designed.
The micro-controller (μC) portion of the DAQ will collect all the sensor information, store it, and process it. Processing involves extracting 6D components of the complex movement for display. The μC can also drive (control) the display.
Sensor signal acquisition occurs through continuous sampling over time. Each sensor signal is recorded and stored in an array long enough to contain all the vital characteristics of the movement. A single array contains a continuous picture of the sensor signal in time. After the movement has been recorded it is processed to extract the basic components making it up. These 6D components are displayed for the user to see. The movement components are often more valuable to the user than the complex motion itself.
The terms and expressions which have been employed in the foregoing specification are used therein as terms of description and not of limitation, and there is no intention, in the use of such terms and expressions, of excluding equivalents of the features shown and described or portions thereof, it being recognized that the scope of the invention is defined and limited only by the claims which follow.

Claims

1. A method for evaluating the motion of a moveable object relative to a reference object comprising:

(a) locating said reference object within a three-dimensional coordinate system having first, second, and third positional coordinates such that the position of said reference object is characterized by respective values of said first, second, and third positional coordinates;

(b) providing a mechanism having a plurality of visual indicators;

(c) providing a sensor configured to detect the position of said moveable object within said three-dimensional coordinate system substantially apart from any dynamic property inherent in the movement of said moveable object;

(d) determining an acceptable minimal number of sampling events and providing a sensor having sufficient response rate as to be capable of determining respective positions of said moveable object as said moveable object moves relative to said reference object such that the number of said respective positions exceeds said acceptable minimal number for any maximum velocity of said moveable object manually achievable by said user.

2. The method of claim 1 wherein said moveable object is the head portion of a golf club.

3. The method of claim 1 wherein said reference object is a golf ball.

4. The method of claim 1 wherein said offset and said array of said first one of said indicators are linear.

5. The method of claim 1 wherein said dynamic property is an angle of approach based on the angle between an axis of intended trajectory of said reference object and an axis of motion of said moveable object as said moveable object closely approaches said reference object as evaluated with each said axis being projected onto a common plane within said three dimensional coordinate system.

6. The method of claim 1 wherein said sensor detects high frequency movements.

7. The method of claim 1 wherein said sensor detects low frequency movements.

8. The method of claim 1 wherein said sensor detects zero frequency movements.

9. The method of claim 1 wherein said sensor proves an output that is independent of object speed.

10. The method of claim 1 wherein said sensors are positioned related to one another to detect multi-dimensional movements.

11. The method of claim 1 wherein said multi-dimensional movements are orthogonal.

12. The method of claim 1 wherein said movements are linear orthogonal.

13. The method of claim 1 wherein said movements are rotational orthogonal.

14. The method of claim 1 wherein said movements include nine orthogonal linear components and nine orthogonal rotational components.