Biomedical Engineering Reference
In-Depth Information
Expanding Euler's equations of motion (Eqs. (4.44)-(4.46)),
M
Ax
0
þð
r
1
F
A
Þ
x
0
þð
r
2
F
g
Þ
x
0
þ
T
gx
0
¼
I
x
0
x
0
a
x
0
þð
I
z
0
z
0
I
y
0
y
0
Þ
o
y
0
o
z
0
M
Ay
0
þð
r
1
F
A
Þ
y
0
þð
r
2
F
g
Þ
y
0
þ
T
gy
0
¼
I
y
0
y
0
a
y
0
þð
I
x
0
x
0
I
z
0
z
0
Þ
o
z
0
o
x
0
M
Az
0
þð
r
1
F
A
Þ
z
0
þð
r
2
F
g
Þ
z
0
þ
T
gz
0
¼
I
z
0
z
0
a
z
0
þð
I
y
0
y
0
I
x
0
x
0
Þ
o
x
0
o
y
0
represents the
x
0
component of
r
1
represents the
x
0
com-
where
ð
r
1
F
A
Þ
x
0
F
A
,
ð
r
2
F
g
Þ
x
0
ponent of
r
2
F
g
, and so forth.
Substitution of the required values and arithmetic reduction yields
50
i
0
þ
9
j
0
16
k
0
Nm
M
A
0
¼
1
:
15
:
1
:
which can be transformed back into fixed lab coordinates,
M
A
037
k
Nm
By combining the ankle moment with the ankle angular velocity, the instantaneous ankle
power may be computed as
M
A
¼
2
:
54
i
þ
15
:
9
j
0
:
v
¼ð
2
:
54
i
þ
15
:
9
j
0
:
037
k
Nm
Þð
0
:
000759
i
þ
1
:
47
j
þ
0
:
0106
k
rad
=
s
Þ
ankle
¼
23
:
3 Watts
or
16
k
0
Nm
140
k
0
rad
50
i
0
þ
9
j
0
0946
i
0
þ
46
j
0
M
A
0
v
ankle
0
¼ð
1
:
15
:
1
:
Þð
0
:
1
:
0
:
=
s
Þ
3 Watts
which is thought to represent a quantitative measure of the ankle's contribution to propulsion.
¼
23
:
4.6.4 Clinical Gait Interpretation
The information and data provided for treatment decision making in clinical gait analy-
sis include not only the quantitative variables described previously—3-D kinematics such
as angular displacement of the torso, pelvis, hip, knee and ankle/foot, and 3-D kinetics,
such as moments and power of the hip, knee, and ankle—but the following as well:
Clinical examination measures
Biplanar video recordings of the patient walking
Stride and temporal gait data such as step length and walking speed
Electromyographic (EMG) recordings of selected lower extremity muscles
Generally, the interpretation of gait data involves the identification of abnormalities, the
determination of the causes of the apparent deviations, and the recommendation of treat-
ment alternatives. As each additional piece of data is incorporated, a coherent picture of
the patient's walking ability is developed by correlating corroborating data sets and resolv-
ing apparent contradictions in the information. Experience allows the team to distinguish a
gait anomaly that presents the difficulty for the patient from a gait compensatory mecha-
nism that aids the patient in circumventing the gait impediment to some degree.
To illustrate aspects of this process, consider the data presented in Figures 4.31-4.33,
which were measured from a 9-year-old girl with cerebral palsy spastic diplegia. Cerebral
