Biomechanics and Medicine in Swimming XI

BiomechanicsandmedicineinswimmingXi
Preliminary Results of a “Multi-2D” Kinematic
Analysis of “Straight- vs. Bent-arm” Freestyle
Swimming, Using High-Speed Videography.
Prins, J.h., Murata, n.M., & Allen, J. s. III.
University of Hawaii. U.S.A.
Synchronized, high-speed digital cameras were used for underwater
videotaping of swimmers, each of whom were required to perform a
series of trials with both bent-arm and straight-arm pull patterns. The
resulting video footage was digitized and processed using “Multi 2-D”
motion capture software. Results demonstrated (1.) The advantages of
using high-speed videography for quantifying swimming stroke mechanics.
(2) The resulting data provided insight into the relationship
between the varying degrees of elbow-bend during the pull cycle, and
fluctuations in linear hip and wrist velocities.
Key words: Freestyle stroke mechanics; high-speed videography;
motion analysis;.
IntroductIon
The accessibility of high-speed digital cameras, coupled with the ability
to synchronize the video output from multiple cameras, has made it
possible to analyze swimmers in more detail. Motion analysis software
makes possible the kinematic analysis of the resulting video footage.
One area of interest is the perceived outcomes between a “bent-arm” vs.
“straight-arm” underwater pull in Freestyle (Front-Crawl) swimming.
Following the success of a select number of Olympic finalists who have
used a straight-arm Freestyle arm recovery, there is now a question of
whether a straight-arm recovery, coupled with a similarly straight-arm
underwater pull leads to the generation of increased propulsive forces.
The purpose of this paper is to describe the preliminary results of a kinematic
analysis of the straight-arm vs. bent-arm underwater pull, using
selected variables of these two types of pull patterns.
Methods
Four members (age= 19.4 +/- 0.8 yr; height 183 cms +/- 6.2 cms) of the
Men’s University of Hawaii “Division I” Intercollegiate swimming team
participated in this pilot study. Each swimmer was filmed for a total of
6 trials, during 3 of which they were instructed to maintain their natural
bent elbow position (B.A.), followed by 3 trials using a straight-arm
(S.A.) underwater pull. Subjects were asked to swim at a pace as close
as possible to their best 200 meter swimming time.
Two high-speed digital cameras (Basler Model A602f ), installed in
custom housings, were mounted to rigid frames which themselves were
anchored to the pool deck. The cameras were placed at a depth of 0.3
meters, each at right angles to each other for frontal and lateral viewing.
The cameras were controlled via dual cabling from a desktop
computer located on the pool deck. One cable was assigned for
camera control via Firewire (IEEE 1394), the second cable was
used for camera frame synchronization. Frame rate was set at 100
frames/second.
Rotational joint segments were identified using a series of light
emitting diodes (LED’s) housed in waterproof housings. The LED’s
were taped to the body and were powered by a battery pack attached to a
belt worn by the swimmer at the waist. Calibration was conducted using
a 4-point frame (1m x 1m), located in the plane of motion.
Motion analysis software (Vicon Motus, Denver, CO), was used for
video capture, data analysis, and generating reports. The software includes
a “Multi 2-D” (M2-D) feature, which enables multiple cameras
to be synchronized. Each sequence was digitized using a combination
of auto-tracking and manual modes.
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Biomechanics and Medicine in Swimming XI Chapter 2 Biomechanics b
Rotational joint segments were identified using a series of light emitting diodes
(LED’s) housed in waterproof housings. The LED’s were taped to the body and were
powered by a battery pack attached to a belt worn by the swimmer at the waist.
Calibration was conducted using a 4-point frame (1m x 1m), located in the plane of
results
motion.
Motion analysis software (Vicon Motus, Denver, CO), was used for video capture,
Following data analysis, video and generating capture reports. and digitizing, The software the includes following a “Multi variables 2-D” (M2-D) were
measured feature, which using enables the Motus multiple cameras software: to be (1) synchronized. Degree of Each elbow-bend; sequence was (2)
digitized using a combination of auto-tracking and manual modes.
Linear velocities of the hip in the saggital plane (X –axis); (3) Linear
velocities RESULTS: of the wrist in the saggital (X), Vertical (Y), & the Resultant
Following video capture and digitizing, the following variables were measured using
(R), the directions; Motus software: (4) (1) Angular Degree of velocities elbow-bend; of the (2) Linear wrist velocities as measured of the hip from in the the
shoulder. saggital plane A composite (X –axis); (3) of Linear the data velocities is presented of the wrist in Table the saggital 1. (X), Vertical
(Y), & the Resultant (R), directions; (4) Angular velocities of the wrist as measured
from the shoulder. A composite of the data is presented in Table 1.
Table 1. Data shows Degree of Elbow Bend, Linear Hip and Wrist Ve-
Table 1. Data shows Degree of Elbow Bend, Linear Hip and Wrist Velocities &
locities & Angular Wrist Velocities as a function of Elbow Positions.
Angular Wrist Velocities as a function of Elbow Position.
Degree of
Elbow Bend
Hip – Linear
Velocity (LHV)
Wrist - Linear
Velocities
103
Wrist - Angular
Velocities
(degrees/sec)
301.9 to 398.3
(degrees) - X-axis (m/sec) (LWV) - (m/sec)
Natural Bent- Range 121 to 1.41 to 1.92 X – 1.41 to 2.31
Arm Pull 134
Y – 1.36 to 2.72
R - 1.70 to 2.73
Straight-Arm Range 160 to 1.52 to 2.02 X – 1.78 to 2.52 123.7 to 186.4
Pull
178
Y – 1.36 to 2.52
R - 1.70 to 2.53
DISCUSSION:
The study focused on two areas of interest: First, was the adoption of high-speed video
technology coupled with motion analysis software to capture and analyze the
underwater pull patterns of swimmers. The second area of interest was the possible
interaction between the degree of elbow bend during the underwater pull, and linear
changes in wrist and hip velocities in the primary plane of motion.
The decision to use the “Multi 2-D” (M2-D) feature incorporated into the software
was made because it provided a means of monitoring selected kinematic parameters,
specifically the potential changes in hip velocity as a function of underwater elbow
flexion. In spite of the inherent limitations of 2D vs. 3D analyses, the M2-D feature
was designed with gait analysis in mind, i.e. placing the cameras at right angles to each
other, making it ideally suited for observing swimming stroke mechanics. The second
innovation, i.e. designing and implementing a system of waterproof LED’s that were
taped to the swimmer’s joint segments, proved invaluable for digitizing the resulting
footage.
With respect to the ability to film at higher frame rates, the results were
immediately apparent. Past experience using cameras that were limited to standard
frame rates (30 fps or 60 fields/sec) consistently produced blurring of the hands,
particularly at the end of the pull, the phase referred to as the “follow-through”. As
dIscussIon
The study focused on two areas of interest: First, was the adoption of
high-speed video technology coupled with motion analysis software to
capture and analyze the underwater pull patterns of swimmers. The
second area of interest was the possible interaction between the degree
of elbow bend during the underwater pull, and linear changes in wrist
and hip velocities in the primary plane of motion.
The decision to use the “Multi 2-D” (M2-D) feature incorporated
into the software was made because it provided a means of monitoring
selected kinematic parameters, specifically the potential changes in hip
velocity as a function of underwater elbow flexion. In spite of the inherent
limitations of 2D vs. 3D analyses, the M2-D feature was designed
with gait analysis in mind, i.e. placing the cameras at right angles to each
other, making it ideally suited for observing swimming stroke mechanics.
The second innovation, i.e. designing and implementing a system
of waterproof LED’s that were taped to the swimmer’s joint segments,
proved invaluable for digitizing the resulting footage.
With respect to the ability to film at higher frame rates, the results
were immediately apparent. Past experience using cameras that were
limited to standard frame rates (30 fps or 60 fields/sec) consistently produced
blurring of the hands, particularly at the end of the pull, the phase
referred to as the “follow-through”. As anticipated, these distortions are
amplified with the caliber of swimmer being filmed. By increasing the
frame-rate to 100 fps, there was a significant change in the image quality,
which allowed the automatic digitizing feature incorporated in the
software to work function effectively.
After the resulting data was filtered and processed, two primary observations
emerged. The major observation was the manner in which the
linear hip velocity (LHV) changed over the duration of the underwater
pull cycle. Figure 1 is a sample report that combines the lateral synchronized
video frame with two graphs that plot LHV and LWV in the plane
of motion as a function of “time. “ The vertical line in the two graphs is
a feature of the software, which allows the synchronization of each video
frame with the respective time intervals on the selected graphs.
Figure 1. Synchronized video frame combined with linear variations in
“hip & wrist velocity”, each plotted as a function of “time”.