Biomedical Engineering Reference
In-Depth Information
was combined with an aviation grade, extremely light and compact antenna that was
mounted onto a short pole fixed to a frame inside a backpack. Data were output at 5Hz
with a typical accuracy between 2 and 10 cm depending on environmental conditions
(tree cover, reflections etc). For additional measures about movements of the trunk
we used a 6-axis IMU (Crossbow Technology, IMU300), with measurement ranges
of
6m/s
2
and
100
◦
/
s. The measuring unit was rigidly fixed to the bottom of
the GPS antenna frame and logged data at 185Hz. To measure the head we used a
custom-built 3-axis IMU (ADXL202 and ADXRS150, logging at 1028Hz) that was
mounted on a head brace worn by the participants (total weight of less than 150g).
A strobe signal was used to align the data streams in post-processing. All devices
plus data loggers and battery packs were fit in the backpack (just under 9kg).
A task was designed that would induce the normal variability in walking behav-
ior without imposing a stereotypical walking pattern. Fourteen participants walked
through a residential area while searching for 30 predefined objects (e.g., street signs,
statues) using a map of the area. The locations of the objects were indicated on the
map by flags and participants were asked to note the time when they reached the loca-
tion of an object. They were instructed to optimize the order in which they visited
the targets such that they would visit the largest number of objects within one hour.
Using recordings of the 3D position of the trunk, a wide range of walking parameters
were computed including, step length (SL), step frequency (SF), and their ratio, also
known as the walk ratio (WR). This ratio has been found to be invariant within a
range of walking speeds [
48
,
90
], and has been linked to optimal energy expenditure
[
56
,
115
]. Evidence of invariance in WR has been reported for walking at manipu-
lated speeds along a 100m straight athletic track [
107
] and a 400m oval track [
108
],
but never under free walking conditions. We also measured walking speed during
straight and curved walking trajectories and starting and stopping behavior. Walking
speed was calculated as the difference between consecutive positions of the trunk
position in the horizontal (GPS) frame. Table
6.1
presents some individual and mean
basic gait parameters computed from the GPS data. For a complete description of
results please refer to [
97
].
Results demonstrated that when people walked on a straight path, the average
walking speed was 1.53m/s. This value is very similar to field survey data [
41
,
65
].
Perhaps not surprisingly, walking speed decreased when people walked on a curved
path. The magnitude of the decrease depended on both the radius and angle of the turn
taken. For turn angle, walking speed decreased linearly with angle. Thus, it changed
from 1.32 m/s at 45
◦
angles to around 1m/s at complete turnarounds (i.e., 180
◦
).
These values are in strong agreement with those observed in a controlled experiment
conducted in a fully-tracked indoor lab space [
98
]. As for turn radius, walking speed
was seemingly constant for turns with radii
±
19
.
±
≥
10m (1.49m/s) and for turns with radii
≤
5m (1.1m/s), while in between these radii values, walking speed changed in a
fairly linear fashion.
Consistent with previous literature [
90
,
107
] we found that WR was relatively
invariant with respect to walking speed. After correcting for participant height (see
[
90
]), we found that most of the adjusted values of WR were close to 0.4m/steps/s.
There were some outliers at slower walking speeds (i.e., below 1m/s), which is again
