Relation between kinematic analysis of wheelchair propulsion and wheelchair functional basketball classification


Crespo-Ruiz, B.M.; Del Ama-Espinosa, A.J.; Gil-Agudo, A.M.

Adapted Physical Activity Quarterly 28(2): 157-172

2011


The objective was to conduct a methodological pilot study to analyze wheelchair propulsion upper limb kinematics in standard competitive play considering the functional classification of each athlete. Ten basketball players with a functional classification ranging from 1 to 4 were included in the study. Four camcorders (Kinescan-IBV) and a treadmill for wheelchairs were used. Temporal parameters were analyzed and the upper limb kinematics was obtained using ISB recommendations. The value of the temporal parameters such as push phase duration, the ratio of push phase/recovery phase, contact, and propulsion angle seems to reduce as the functional classification increases. A methodological protocol has been developed that allows the analysis of kinematic characteristics of wheelchair propulsion in basketball players taking into account their functional classification.

Adapted
Physical
Activity
Quarterly,
2011,
28,
157-172
2011
Human
Kinetics,
Inc.
Relation
Between
Kinematic
Analysis
of
Wheelchair
Propulsion
and
Wheelchair
Functional
Basketball
Classification
Beatriz
M.
Crespo-Ruiz,
Antonio
J.
Del
Ama-Espinosa,
and
Angel
M.
Gil-Agudo
National
Hospital
for
Spinal
Cord
Injury,
Spain
The
objective
was
to
conduct
a
methodological
pilot
study
to
analyze
wheelchair
propulsion
upper
limb
kinematics
in
standard
competitive
play
considering
the
functional
classification
of
each
athlete.
Ten
basketball
players
with
a
functional
classification
ranging
from
1
to
4
were
included
in
the
study.
Four
camcorders
(Kinescan-IBV)
and
a
treadmill
for
wheelchairs
were
used.
Temporal
parameters
were
analyzed
and
the
upper
limb
kinematics
was
obtained
using
ISB
recom-
mendations.
The
value
of
the
temporal
parameters
such
as
push
phase
duration,
the
ratio
of
push
phase/recovery
phase,
contact,
and
propulsion
angle
seems
to
reduce
as
the
functional
classification
increases.
A
methodological
protocol
has
been
developed
that
allows
the
analysis
of
kinematic
characteristics
of
wheelchair
propulsion
in
basketball
players
taking
into
account
their
functional
classification.
One
of
the
most
crucial
issues
in
wheelchair
sports
is
the
functional
clas-
sification
that
allows
the
grouping
of
players
with
a
similar
level
of
functional
capacity
based
on
their
ability
of
perform
movements,
which
aims
to
eliminate
competitive
inequalities
due
to
the
greater
or
lesser
severity
of
the
impairment
of
different
athletes.
Wheelchair
basketball
is
probably
the
most
popular
disabled
sport.
According
to
estimates
of
the
IWBF
(International
Wheelchair
Basketball
Federation),
approximately
30,000
people
play
worldwide.
Wheelchair
basketball
has
one
of
the
best
developed
functional
classification
systems
in
disabled
sports
(IWBF,
2002).
The
current
player
classification
system
adopted
by
the
IWBF
was
used
for
the
first
time
in
international
competition
in
July
1984
at
the
VIIth
World
Paralympic
Games
in
Aylesbury,
UK
(Weiss,
&
Curtis,
1985).
Under
this
system,
players
are
tested
on
their
ability
to
play
the
game,
not
on
their
medical
disability.
The
wheelchair
basketball
functional
classification
is
based
on
players'
capacity
in
terms
of
playing
skills—pushing,
pivoting,
shooting,
rebounding,
dribbling,
passing,
and
catching
(IWBF,
2002).
Earlier
studies
have
tried
to
validate
the
wheelchair
basketball
classification
system
using
field
performance
analysis
in
elite
athletes
(Vanlandewijck,
Spaepen,
&
Lysens,
1995;
Vanlandewijck
et
al.,
2003).
Although
The
authors
are
with
the
Biomechanics
and
Technical
Aids
Department,
Hospital
Nacional
de
Para-
plejicos,
Toledo,
Spain.
157
158
Crespo-Ruiz,
Del
Ama-Espinosa,
and
Gil-Agudo
the
functional
classification
system
is
well
established,
it
would
be
interesting
to
further
explore
the
biomechanical
analysis
of
player
classes
to
support
the
clas-
sification
system
with
objective
data
on
how
playing
skills
are
performed.
The
initial
purpose
of
most
biomechanical
studies
in
wheelchair
sports
was
to
prevent
injuries
related
to
propulsion
(Bollinger,
Robertson,
Wolff,
&
Cooper,
1996;
Burham,
Chan,
Hazlett,
Laskin,
&
Steadward,
1994).
The
objective
of
preventing
sport
injuries
was
later
broadened
to
include
optimizing
athletic
performance
(Van-
landewijck,
Theisen,
&
Daly,
2001).
The
sports
performance
optimization
question
has
been
approached
from
the
perspectives
of
ergonomics
and
skill
proficiency.
In
earlier
studies,
biomechanical
analysis
techniques
have
been
used
to
compare
and
examine
the
propulsion
techniques
of
senior
male,
senior
female,
and
junior
male
athletes
and
to
determine
the
relationship
between
the
kinematic
variables
and
performance
in
an
800-m
race
(Goosey,
Fowler,
&
Campbell,
1997).
Kinematic
patterns
were
later
analyzed
for
a
range
of
wheelchair
propulsion
speeds
(6.0,
6.5,
and
7.0
m/s)
and
the
relation
between
wheelchair
propulsion
and
pushing
economy
was
examined
(Goosey
&
Campbell,
1998).
It
was
concluded
that
adaptations
to
speed
changes
occur
initially
by
decreasing
cycle
time
and
increasing
cycle
rate
and
later
by
increasing
elbow
flexion
(Goosey
et
al.,
1997).
As
indicated
above,
one
of
the
questions
that
require
quantitative
information
is
classification
systems.
Biomechanical
analysis
techniques
are
among
the
most
indicated
to
contribute
scientific
evidence
to
the
validation
of
different
methods
of
classification
(Gil-Agudo,
Del
Ama-Espinosa,
&
Crespo-Ruiz,
2010b).
Among
the
most
significant
examples
are
the
studies
by
Chow
et
al.
of
the
application
of
kinematic
analysis
techniques
to
the
movement
characteristics
of
wheelchair
field
events,
such
as
shot-putting
(Chow,
Chae,
&
Crawford,
2000)
and
javelin
throw,
performed
by
wheelchair
athletes
of
different
functional
classes
(Chow,
Kuenster,
&
Lim,
2003).
In
both
studies,
the
different
classes
are
described
and
characterized
using
kinematics
data.
In
wheelchair
basketball,
one
earlier
study
tried
to
describe
the
characteris-
tics
of
different
wheelchair
basketball
classes
in
biomechanical
terms
and
also
examined
physiologic
differences
(Vanlandewijck,
Spaepen,
&
Lysens,
1994).
The
user-related
parameter
was
the
force
applied
to
the
pushrim
at
different
speeds
on
a
wheelchair
ergometer.
The
authors
found
that
the
level
of
functional
disability
had
little
impact
on
the
isometric
and
dynamic
forces
applied
to
the
pushrim
in
class
II
and
BI
athletes
(ISMWSF
wheelchair
basketball
classification;
Vanlandewijck
et
al.,
1994);
however,
it
may
be
more
appropriate
to
analyze
the
key
movements
on
which
classifiers
focus
when
classifying
players.
The
definition
of
these
movements
makes
it
relatively
easy
to
introduce
biomechanical
analysis
techniques.
It
has
been
reported
the
need
for
further
study
to
determine
the
biomechanical
characteristics
of
wheelchair
basketball
shooting
so
that
comparisons
could
be
made
among
classes
and
individuals
(Malone,
Nielsen,
&
Steadward,
2000).
Still,
one
interesting
and
novel
use
of
biomechanics
in
wheelchair
basketball
is
in
the
analysis
of
player
classifications.
Despite
being
generally
accepted,
the
current
wheelchair
classification
system
is
based
on
the
observations
of
classifiers,
which
can
be
somewhat
subjective.
Objective
knowledge
of
the
characteristics
of
each
of
the
classes
is
needed.
In
this
field,
biomechanical
analysis
may
have
much
to
offer
(Gil-Agudo
et
al.,
2010b).
Little,
if
any,
quantitative
research
has
been
completed
to
date
on
the
mechanics
of
wheelchair
basketball
(Malone,
Gervais,
&
Steadward,
Wheelchair
Basketball
Classification
159
2002).
The
available
literature
tends
to
be
qualitative
in
nature,
based
on
coaches'
opinions
and
subjective
analyses;
however,
an
understanding
of
the
mechanism
of
the
movements
in
wheelchair
basketball
is
essential.
A
further
distinction
must
be
made
regarding
objective
differences
in
the
mechanics
of
movement
in
each
player
classification
group
(Malone
et
al.,
2002).
Up
to
date,
biomechanical
characteristics
of
manual
wheelchair
propulsion
in
wheelchair
basketball
players
have
not
been
studied
in
depth.
We
undertook
this
pilot
study
to
explore
the
characteristics
of
wheelchair
propulsion kinematics
among
wheelchair
basketball
players
with
different
levels
of
disability
by
kine-
matic
analysis
of
manual
wheelchair
propulsion.
The
objective
of
this
study
was
to
conduct
a
methodological
pilot
study
to
analyze
wheelchair
propulsion
upper
limb
kinematics
in
standard
competitive
play
considering
the
functional
classification
of
each
athlete.
Method
Participants
Ten
male
wheelchair
basketball
players
(age
26.9
±
6.6
years)
participated
in
this
study.
All
were
classified
by
European
IWBF
classifiers
and
were
considered
elite
players
because
they
had
participated
in
international
events.
According
to
current
classification
system
(IWBF,
2002),
the
results
of
the
sample
analyzed
were
the
fol-
lowing:
3
players
in
class
1,
3
in
class
2,
2
in
class
3,
and
2
in
class
4
(Table
1).
All
participants
signed
an
informed
consent
form
before
the
study
began.
Declaration
Table
1
Characteristics
of
Study
Subjects
in
a
Kinematic
Analysis
of
Player
Classifications
Participants
Functional
Class
Age
(Years)
Injury
Individual
Speed
Registered
(Km/h)
1 1
33
SCI
D4
Complete
11
2
1
39
SCI
D5
Complete
8.7
3
1
33
SCI
D5
Complete
9
4
2
19
SCI
D10
Complete
12.2
5
2
29
SCI
Ll
Complete
16.1
6
2
24
SCI
D9
Complete
11.1
7
3
25
Right
hip
disarticulation
15
8
3
19
SCI
D8
Incomplete
13.1
9
4
27
Double,
above—knee,
lower—limb
amputee
11.5
10
4
21
Congenital
lower—
limb
malformation
12.4
Third
metacarpal
joint
SeNenth
vertebra]
iere
icae
Technical
M
arke
rs
160
Crespo-Ruiz,
Del
Ama-Espinosa,
and
Gil-Agudo
of
Helsinki
guidelines
were
followed
in
every
case.
We
certify
that
all
applicable
institutional
and
government
regulations
concerning
the
ethical
use
of
human
volunteers
were
followed
during
the
course
of
our
research.
Instrumentation
Kinematics.
The
right
upper
limb
was
used
for
kinematic
analysis.
Reflective
markers
were
positioned
following
ISB
recommendations
(Wu
et
al.,
2005)
to
define
local
reference
systems
on
the
hand,
forearm,
and
arm
(Figure
1).
Twenty-
two
reflective
markers
were
positioned
on
the
following
bony
landmarks:
3
on
the
trunk
(C7
spinous
process,
right
acromio-clavicular
joint,
and
left
acromio-
clavicular
joint),
4
on
the
arm,
2
on
the
forearm,
3
on
the
hand,
4
on
the
wheel-
chair,
and
2
clusters
of
three
markers
each
on
the
upper
arm
and
on
the
lower
forearm
(Figure
1;
Gil-Agudo,
Del
Ama-Espinosa,
Perez-Rizo,
Perez-Nombela,
&
Rodriguez-Rodriguez,
2010a).
An
upper-limb
model
was
defined
following
ISB
recommendations
for
local
reference
systems
on
the
hand,
forearm,
and
arm.
The
axes
of
this
reference
system
have
been
described
in
detail
elsewhere
(Gil-Agudo,
Del
Ama-Espinosa,
Perez-Rizo,
Perez-Nombela,
&
Crespo-Ruiz,
2009).
Three-
dimensional
markers
positions
were
collected
at
50
Hz
with
four
camcorders,
and
the
video
recordings
were
digitalized
using
adequate
software
(Kinescan—IBV,
Institute
de
Biomecanica
de
Valencia, Valencia,
Spain).
Previously,
a
reference
system
was
calibrated
that
included
the
entire
surface
of
the
treadmill
and
sufficient
Lett
and
Right
ae
rom
kola
ic
u
I
ar
Joint
External
Epicondile
Ulnar
Styloid
Fifth
metacarpal
joint
sr
.40
Whec
I
axle
marker
Figure
1
Upper
limb
marker
placement:
3
on
the
trunk
(C7
spinous
process,
right
acro-
mioclavicular
joint,
and
left
acromioclavicular
joint),
4
on
the
arm,
2
on
the
forearm,
3
on
the
hand,
and
2
clusters
of
three
markers
each
on
the
upper
arm
and
on
the
lower
forearm.
Wheelchair
Basketball
Classification
161
height
to
allow
trunk
markers
to
be recorded.
Spatial
marker
coordinates
were
smoothed
out
using
a
mobile
means
procedure
(Gil-Agudo
et
al.,
2009).
Data
Compilation.
A
treadmill
of
suitable
dimensions
for
wheelchairs
was
used
to
simulate
realistic
propulsion
conditions
(Bonte
Zwolle
B.V.,
BO
Sys-
tems,
GTR-2.50).
Each
athlete
was
analyzed
in
the
usual
standard
competitive
play
for
the
player's
classification
with
regard
to
wheelchair
configuration
and
strapping
because
these
are
the
circumstances
in
which
the
player's
functional
class
is
valid.
Any
change
in
wheelchair
configuration
or
strapping
may
change
this
classification.
The
subject
then
was
instructed
to
propel
the
wheelchair
on
the
treadmill
at
a
comfortable
speed
for
a
two-minute
adaptation
period.
After
this
period,
a
1-s
static
video
capture
was
made
to
calibrate
the
marker
model.
Participants
propelled
their
wheelchair
during
a
1
min-test
on
the
treadmill
with
no
ramp.
The
treadmill
speed
for
each
player
was
the
mean
reached
previously
in
three
20-m
sprints
on
the
playing
court.
We
conducted
propulsion
trials
on
the
treadmill
with
a
safety
system.
A
spotter
at
the
front
of
the
treadmill
controlled
the
safety
tether.
Data
Simplification.
Data
were
collected
in
the
middle
20-s
interval
to
avoid
the
effect
of
acceleration
and
braking.
Five
cycles
(a
cycle
begins
when
the
hand
contact
the
handrim
and
lasts
until
it
returns
to
contact
again,
so
the
movement
includes
both
push
and
recovery
phase)
were
selected
from
the
20-s
data
recording
and
each
cycle
was
analyzed
separately
to
obtain
the
mean
value
of
the
5
cycles.
The
cycles
then
were
normalized
from
0%
to
100%
because
the
time
spent
in
each
cycle
varied
across
individuals
and
across
cycles.
Five
events
in
the
cycle
have
been
identified
for
systematizing
the
description
of
the
different
articular
events
(Davis
&
Growney,
1998).
Video
images
were
taken
into
account
to
identify
the
start/finish
of
the
push
phase.
Different
propulsion
events
and
angles
were
identified
using
a
marker
on
the
right
wheel
axis
and
a
marker
on
the
metacarpo-
phalangeal
joint
of
the
third
right
finger
(Davis
&
Growney,
1998).
The
angles
that
characterize
the
propulsion
cycle
(contact
angle,
release
angle,
and
propul-
sion
angle)
are
shown
in
Figure
2.
All
necessary
equations
and
calculations
were
processed
with
Matlab
(The
Mathworks
Inc,
Natick,
MA,
USA).
The
temporal
variables
and
upper
limb kinematics
were
analyzed
focusing
on
the
maximum
and
minimum
values
of
each
articular
movement
and
its
range
of
motion
(ROM).
Statistical
Analysis
For
each
variable,
descriptive
analyses
(mean
±
SD)
were
computed
for
each
class.
Analyses
were
made
with
SPSS
12.0
(SPSS
Inc.,
Chicago,
IL,
USA).
The
value
of
each
variable
is
presented
in
numerical
format
in
both
the
tables
and
graphs.
Due
to
the
small
group
size,
only
descriptive
analyses
have
been
made.
Results
The
individual
speed
registered
is
presented
in
Table
1.
The
descriptive
results
of
the
temporal
variables
are
listed
in
Table
2.
The
kinematic
variables
for
each
class
are
listed
for
the
shoulder,
elbow
and
wrist
(Table
3).
Results
were
not
compared
between
classes
due
to
the
small
number
of
participants
in
each
class.
A
visual
Propulsion
angle
Contact
angle
Release
t
u
lle
light
Figure
2
-
Description
of
biomechanical
wheelchair
propulsion
variables:
contact
angle,
release
angle
and
propulsion
angle.
Table
2
Biomechanical
Temporal
Parameters
of
Wheelchair
Propulsion
Temporal
Parameter
Class
1
Class
2
Class
3
Class
4
Speed
(Km/h)
10.97
±
1.97
11.30
±
2.33
12.10
±
1.05
13.43
±
2.46
Cadence
(strokes/s)
1.60
±
0.34
1.69
±
0.30
1.90
±
0.42
1.80
±
0.85
Duration
of
push
phase
(s)
0.21
±
0.03
0.15
±
0.05
0.14
±
0.02
0.09
±
0.02
Duration
of
recovery
phase
(s)
0.39
±
0.12
0.37
±
0.12
0.41
±
0.10
0.54
±
0.29
Push
phase/Recovery
phase
0.59
±
0.23
0.40
±
0.08
0.34
±
0.04
0.19
±
0.06
Contact
angle
(°)
119.12
±
2.71
107.27
±
14.09
101.72
±
0.93
81.40
±
6.76
Release
angle
(°)
19.96
±
15.28
13.95
±
4.17
7.84
±
4.05
20.16
±
14.23
Propulsion
angle
(°)
99.16
±
14.35
93.32
±
11.53
93.88
±
3.12
61.24
±
7.47
Note.
Statistical
Data
Group
Variables
(Mean
±
SD)
162
Table
3
Upper
Limb
Kinematics
Kinematic
Variables
Class
1
Class
2
Class
3
Class
4
Shoulder:
Maximum
elevation
-26.88
±
18.49
-26.03
±
3.04
-25.91
±
15.63
-26.49
±
15.63
Shoulder:
Minimum
elevation
-56.13
±
6.73
-67.73
±
3.88
-63.09
±
10.10
-69.07
±
4.77
Shoulder:
ROM
elevation
29.25
±
23.14
41.70
±
5.27
37.18
±
25.73
42.58
±
10.86
Shoulder:
Maximum
internal
rotation
40.60
±
8.61
22.37
±
28.54
24.53
±
34.62
63.34
±
25.86
Shoulder:
Minimum
internal
rotation
-65.41
±
23.95
-69.20
±
16.52
-90.68
±
29.48
-27.86
±
35.60
Shoulder:
ROM
internal
rotation
106.01
±
29.46
91.57
±
40.30
115.22
±
5.13
91.19
±
9.74
Shoulder:
Maximum
plane
of
elevation
51.01
±
13.62
60.37
±
5.22
60.20
±
3.38
13.37
±
65.68
Shoulder:
Minimum
plane
of
elevation
-46.08
±
11.60
-23.93
±
29.12
-24.52
±
12.49
-52.36
±
52.55
Shoulder:
ROM
plane
of
elevation
97.10
±
24.44
84.30
±
28.11
84.72
±
9.11
65.74
±
13.13
Elbow:
Maximum
flexion
95.34
±
12.90
100.52
±
2.79
98.52
±
0.89
94.20
±
4.59
Elbow:
Minimum
flexion
30.04
±
6.43
21.87
±
8.07
19.40
±
9.20
21.74
±
8.23
Elbow:
ROM
flexoextension
65.30
±
18.28
78.65
±
6.97
79.12
±
10.09
72.46
±
12.83
Elbow:
maximum
pronation
141.68
±
15.47
132.64
±
6.14
164.53
±
22.36
165.02
±
45.27
Elbow:
minimum
pronation
103.79
±
8.21
92.14
±
2.33
106.61
±
2.5
107.11
±
27.36
Elbow:
ROM
pronation
37.89
±
9.25
40.49
±
8.18
57.92
±
24.86
57.92
±
17.91
Wrist:
maximum
ulnar
deviation
20.16
±
0.91
26.19
±
3.17
22.41
±
1.01
29.42
±
7.74
Wrist:
maximum
radial
deviation
23.08
±
4.98
16.22
±
4.04
0.94
±
5.91
-7.64
±
11.94
Wrist:
ROM
ulnar-radial
4.64
±
2.01
9.98
±
3.65
21.46
±
4.9
37.06
±
19.69
Wrist:
maximum
flexion
29.77
±
13.3
12.31
±
14.92
5.44
±
12.91
-0.18
±
9.86
Wrist:
maximum
extension
17.55
±
9.36
34.06
±
6.61
32.62
±
4.23
25.98
±
6.97
Wrist:
ROM
flexo-extension
18.51
±
14.53
21.75
±
19.5
27.18
±
17.14 26.16
±
2.9
Note.
Group
Descriptive
statistics
(Mean
+
/
-
Standard
Deviation)
163
164
Crespo-Ruiz,
Del
Ama-Espinosa,
and
Gil-Agudo
inspection
of
Figure
3
suggests
that
temporal
parameters
such
as
push
phase
dura-
tion,
the
ratio
of
push
phase/recovery
phase,
and
contact
and
propulsion
angle
appears
to
be
reduced
while
the
class
increases
(Figure
3).
For
the
kinematic
parameters
the
same
tendency
for
ROM
values
of
the
shoulder
elevation
plane
was
observed
and
the
wrist
radial-ulnar
deviation
ROM
also
seems
to
increase
with
functional
classification
value
(Figure
4-6).
Discussion
This
study
was
a
pilot
study
to
assess
the
suitability
of
using
biomechanical
analysis
techniques
to
compare
and
define
functional
classifications
in
wheelchair
basketball.
The
decrease
in
several
temporal
parameters
with
functional
classification
was
observed,
such
as
push
phase
duration,
the
ratio
of
push
phase/recovery
phase,
and
contact
and
propulsion
angle.
These
observations
could
be
related
to
players
with
a
low
lesion
level;
the
hand
is
required
to
be
in
contact
less
time
with
the
pushrim
for
propulsion,
probably
due
to
a
stronger
impulse.
In
regard
to
the
upper
limb
kinematic
values,
the
tendency
for
an
increase
or
decrease
has
been
detected
in
several
parameters
such
as
ROM
values
of
the
shoulder
elevation
plane
and
the
wrist
radial-uhiar
deviation
ROM.
These
data
were
inspected
to
assess
the
relationship
with
functional
classes.
Furthermore,
given
the
importance
of
trunk
movement
in
the
functional
classification
of
wheelchair
basketball,
it
will
be
necessary
to
include
in
future
studies
a
biomechanical
model
that
includes
trunk
parameters
in
wheelchair
propulsion.
There
were
different
values
of
propulsion
velocity
and
wheelchair
configura-
tion
parameters
among
players,
which
conditioned
the
respective
starting
posi-
tion
and
execution
of
players.
Both
points
probably
had
an
impact
on
the
results.
However,
our
aim
was
to
work
with
the
current
functional
classification
system
so
each
player
was
examined
in
his
respective
standard
competitive
play.
The
stan-
dard
competitive
play
is
defined
by
the
player's
functional
capacity
and
physical
interaction
with
the
wheelchair,
which
is
conditioned
by
the
wheelchair
design
and
strapping.
Any
change
in
wheelchair
configuration
or
strapping
could
change
the
player's
assigned
class.
If
wheelchair
conditions
would
be
standardized,
we
would
have
been
analyzing
the
players
themselves
rather
than
their
functional
class,
which
is
the
product
of
player-wheelchair
interaction.
The
same
reasons
are
applicable
to
velocity.
According
to
the
current
classification
system,
the
player
is
asked
to
execute
a
sprint
at
maximum
speed
on
the
playing
floor,
because
each
player's
speed
depends
on
his
or
her
intrinsic
functional
capacity.
The
player
is
classified
during
propulsion
at
his
or
her
maximum
speed.
Therefore,
we
applied
the
same
criterion
and
treadmill
speed
was
determined
by
calculating
the
mean
of
three
previous
sprints
on
the
playing
floor.
We
are
aware
that
speed
is
a
variable
that
modifies
kinematic
findings,
but
if
all
players
would
perform
at
same
propulsion
velocity,
functional
differences
would
not
have
revealed.
Interest
in
the
biomechanical
analysis
of
manual
wheelchair
propulsion
has
increased
as
earlier
studies
have
reported
an
increasingly
older
population
of
people
with
spinal
cord
injury
(SCI)
and
a
high
incidence
of
upper
limb
pathology
(Gell-
man,
Sie,
&
Waters,
1988;
Sie,
Waters,
Adkins,
&
Gellman,
1992;
Silfverskold
&
Waters,
1991).
Biomechanical
analysis
of
wheelchair
propulsion
yields
pertinent
14000
12000
10000
saco
g
60.00
40.0)
2000
0
00
Daman
or
push
rhea.
Damian
of
recovny
phAs•
Ptah
plusealnovery
phut.
Class
1
Class
2
O
Class
3
MI
Class
4
Ribose
aN,I
,
Pr:Tuition
eagle
020
020
0.70
0.60
=0
50
Class
1
Class
2
0
Class
3
Class
4
040
020
020
0.10
0
Carlo.,
Class
1
Class
2
0
Class
3
Class
4
50
300
1
uu
150
81
100
050
00
Figure
3
Kinematics
parameters
and
wheelchair
basketball
player
classes
(Media
±SD).
165
aass
1
aass
2
aass
3
class
4
1Rn
a
,(11
,1
\
'non
of
wrist
60.00
-
50.00
40.00
30.00
a,
20.00
Maximum
ulnar
deviation
Maximum
radial
deviation
10.00
0.00
-10.00
-20.00
-
ROM
Wrist
flexion-extension
Class
1
Class
2
Class
3
IIII
Class
4
E
25.00
T
20.00
15.00
10.00
5.00
0.00
-5.00
-
Maximum
flexion
Maximum
extension
ROM
50.00
45.00
40.00
35.00
30.00
Figure
4
Wrist
spatial-temporal
parameters
and
wheelchair
basketball
player
classes
(Media
±
SD).
188
120.00
-
Elbow
flexion-extension
o
Class
1
o
Class
2
o
Class
3
Class
4
100.00
Maximum
flexion
Minimum
flexion
POI
80.00
h
60.00
a,
40.00
20.00
0.00
250.00
-
Forearm
pronatioil-supination
Class
1
7
Class
2
Class
3
Class
4
150.00
100.00
50.00
0.00
200.00
P1
nu
/3/
or
ati,
,
t1
IwIltarto
m
ROlvl
Figure
5
Elbow
spatial-temporal
parameters
and
wheelchair
basketball
player
classes
(Media
±
SD).
167
Internal-External
rotation
of
shoulder
Class
1
o
Class
2
Class
3
Class
4
150.00
-
100.00
5100
I
0.00
-50.00
-loom
-150.00
Minimum
interval
rotation
Maximum
entente]
rotation
Plane
of
elevation
of
shoulder
Class
1
Class
2
s
Class
3
s
Class
4
I
NrImi,..::n
Anne
of
elevation
Maximo:111)1one
of
elevation
1
ROM
EA
140.00
120.00
10000
80.00
woo
40.00
20
03
000
-2000
-40.00
60.00
-moo
Shoulder
elevation
Class
1
o
Class
2
Class
3
80.00
Class
4
60.00
40.00
20.00
Mesistun
elevation
Minirroin
elevation
0.00
ROM
a
-20.00
-40.00
-6000
-8000
Fi
gure
6
Shoulder
spatial-temporal
parameters
and
wheelchair
basketball
player
classes
(Media
±
SD).
188
Wheelchair
Basketball
Classification
169
information
for
identifying
the
factors
that
predispose
to
upper
limb
injuries
(Gil-
Agudo
et
al.,
2010a).
The
objective
of
our
work
was
to
initiate
a
methodological
pilot
study
to
analyze
wheelchair
propulsion
upper
limb
kinematics
in
standard
competitive
play
considering
the
functional
classification
of
each
athlete.
The
study
of
relevant
movements
during
wheelchair
propulsion
in
athletes could
be
related
to
the
prevention
of
upper
limb
injuries.
Wheelchair
propulsion
in
wheelchair
basketball
players
has
been
studied
ear-
lier
(Coutts,
1990).
The
differences
of
wheelchair
propulsion kinematics
between
basketball
and
track
athletes
on
a
wheelchair
ergometer
were
compared.
During
the
first
3
pushes,
basketball
players
had
a
higher
push
rim
velocity
throughout
effort
but
a
higher
wheelchair
velocity
only
at
the
end
of
the
first
push
(Coutts,
1990).
Another
key
point
in
wheelchair
basketball
classification
is
trunk
movement.
Curtis
et
al.
(1995)
described
a
methodology
for
the
kinematic
analysis
of
trunk
mobility
in
wheelchair
users.
This
study
provided
strong
evidence
that
a
chest
strap
increases
functional
reach
in
the
sagittal
plane,
but
functional
reach
does
not
appear
to
be
enhanced
by
a
thigh
strap
in
subjects
with
high
or
low
thoracic
paraplegia
(Curtis,
Kindlin,
Reich,
&
White,
1995).
It
could
be
related
to
strapping
in
wheelchair
basketball
players.
In
relation
to
biomechanical
wheelchair
basketball
analysis,
it
may
be
more
appropriate
to
analyze
the
key
movements
as
shooting
on
which
classifiers
focus
when
classifying
players
and
reproduce
the
standard
competitive
play
(wheelchair
configuration
and
strapping;
Nunome,
Doyo,
Sakurai,
Ikegmai,
&
Yabe,
2002).
Comparisons
between
studies
are
often
difficult
because
of
different
testing
procedures,
units
of
measurement,
equipment
employed,
and
characteristics
of
the
sample
studied
(Finley,
Rasch,
Keyser,
&
Rodgers,
2004).
In
this
study,
propulsion
analysis
was
carried
out
using
a
wheelchair placed
on
a
treadmill,
which
other
authors
have
characterized
as
the
ideal
mechanical
situation
(Richter,
Rodriguez,
Woods,
&Axelson,
2007).
Other
investigators
have
used
dynamometers
(DiGiovine,
Cooper,
&
Bollinger,
2001;
Kulig
et
al.,
1998;
Newsam
et
al.,
1999)
or
ergometers
(Niesing,
Eijskoot,
Kranse,
den
Ouden,
&
Storm,
1990).
Methodological
limitations
can
be
raised
to
the
current
study
because
each
player
used
his
own
adapted
wheelchair,
so
wheelchair
parameters
were
not
standardized.
Although
the
four
cameras
were
electronically
synchronized,
errors
may
have
resulted
from
the
limited
resolution
of
the
video
images.
Given
the
pilot
characteristic
of
this
work,
we
consider
that
all
the
variables
analyzed
have
the
potential
to
give
relevant
information.
Moreover,
some
additional
variables
should
and
will
be
considered:
variables
related
with
the
trunk
movement.
One
controversial
issue
may
derive
from
functional
classifications
being
defined
in
terms
of
playing
actions
and
being
made
during
actual
games,
whereas
biomechanical
analysis
is
conducted
in
the
experimental
laboratory
setting,
and
we
are
focusing
our
analysis
uniquely
on
linear
wheelchair
propulsion.
We
think
that
it
would
be
interesting
to
produce
a
better
classification
system
and
to
con-
tinue
this
study
with
a
larger
sample.
This
study
represents
just
an
example
about
how
to
introduce
biomechanical
techniques
to
assess
functional
classification
in
wheelchair
basketball.
Numerous
skills
are
not
studied
(e.g.,
shooting,
dribbling,
rebound,
and
manual
propulsion).
It
would
be
necessary
to
develop
a
new
set
up
to
analyze
those
skills.
One
of
our
aims
was
to
introduce
objective
assessment
in
the
current
classifica-
tion
system
but
in
some
way
we
maintained
this
subjectivity
in
our
data
analysis
170
Crespo-Ruiz,
Del
Ama-Espinosa,
and
Gil-Agudo
because
our
analysis
procedure
is
essentially
an
attempt
to
find
an
association
between
a
number
of
variables
and
the
functional
classification
level
produced
by
(subjective)
human
observers.
This
study
was
a
pilot
experiment
to
assess
the
suit-
ability
of
using
biomechanical
analysis
techniques
to
compare
and
define
functional
classifications
in
wheelchair
basketball
but
we
are
agreeing
that
is
necessary
to
defined
more
specific
key
movements.
Conclusion
Classification
systems
are
a
key
element
in
sports
for
athletes
with
disabilities,
especially
wheelchair
basketball.
Biomechanical
analysis
can
help
to
define
objec-
tively
propulsion
characteristics
for
each
wheelchair
basketball
functional
class.
The
present
study
is
a
pilot
experience
to
describe
a
methodology
to
analyze
upper
limb
kinematic
characteristics
of
wheelchair
propulsion
in
standard
competitive
play
(speed
and
wheelchair
configuration)
and
wheelchair
basketball
classification.
The
data
seems
to
be
related
when
temporal
parameters
are
inspected.
This
may
suggest
that
more
emphasis
should
be
placed
on
biomechanical
analysis
to
assess
functional
classification.
More
quantitative
data
are
needed
for
the
development
of
a
database
on
wheelchair
propulsion
characteristics
and
other
key
points
of
clas-
sification
(dribbling, braking,
rebounding,
etc.),
especially
in
the
play
situation.
Acknowledgment
This
work
was
part
of
a
project
financed
by
the
Consejeria
de
Sanidad
de
Castilla-La
Mancha,
which
does
not
have
any
commercial
interest
in
the
results
of
this
investigation
(Ref:
06006-00).
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